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Phase I
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2INNOVATE LLC
STTR Phase I: A novel wall-mounted gait assist system to reduce the risk of injuries on stairs and level surfaces
Contact
3622 WOODLAND DR
Metamora, MI 48455--9626
NSF Award
2304063 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a novel mechanical system which improves the safety of the elderly and disabled while walking on level surfaces and stairs. The novel, wall-mounted system will reduce the risks of injury by mechanically supporting individuals during ambulation, rehabilitation, and eventual in-home gait assistance. The system aims to reduce one of the top reasons for emergency room (ER) visits (nearly 3,000 ER visits in the United States each year) by preventing falls in the home. The solution may also be used in medical facilities to safely ambulate convalescent or acute care patients, especially on stairs. In addition to reducing direct patient injury risks, the technology improves economic and productivity measures by reducing the number of therapists/nurses, relatives, and support workers caring for people with disabilities or those at risk of falls.
This STTR Phase I project will demonstrate a novel, mechanical, wall-mounted gait assist that can safely reduce injuries and the risks of falling while walking across flat surfaces and stairs. A harness with an elastic-like tether, mobile trolley, and mechanical braking mechanism for maintaining patient safety will be completed. The individual is connected to a trolley travelling along a wall-side rail providing the variable forces needed to support a patient?s weight in order to minimize risks of injury. In the event of a fall, the trolley?s brake automatically activates, absorbing the shock with a vest/tether to prevent the user from falling to the floor. Following design engineering and prototype completion, a pilot proof of concept study will be conducted during Phase I to demonstrate the potential for patient use in safely walking without falling and causing injury.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
3FATES-XRAY, INC.
SBIR Phase I: Single-shot X-ray Phase-contrast Imaging Using Deep Learning Approaches
Contact
616 BRISTOL TER
Sunnyvale, CA 94087--1488
NSF Award
2321552 – SBIR Phase I
Award amount to date
$274,996
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project relates to the benefits of next-generation X-ray imaging systems. The proposed single-shot platform overcomes the current barriers to widespread commercialization of Differential Phase Contrast (DPC) X-ray imaging. If successful, the single-shot technology will enable the development and application of next generation X-ray imagers for detecting liquids, small explosives, and other security threats for aviation and business applications. Reducing false alarm rates at airports will increase customer satisfaction, improve security, and reduce cost. DPC imaging could also substantially increase the detection of food pests, thereby reducing food waste and saving billions of dollars. In another market, non-destructive testing could significantly improve the inspection of additive manufacturing products, reducing manufacturing time through fewer iterations and creating high-quality products. Medical DPC imagers would provide MRI (Magnetic Resonance Imaging)-like resolution and diagnostics at an order of magnitude lower cost than current MRI.
This Small Business Innovation Research Phase I project aims to develop a deep-learning approach to realize ?single-shot? X-ray phase-contrast imaging. To commercialize the technology, the deep-learning algorithm needs to identify more complicated real-world objects effectively and accurately. Deep-learning methods require thousands to millions of training samples to make a reliable model. However, no imaging library for this unique technology currently exists. The research and development plan initially incorporates the standard slow scanning method of X-ray phase-contrast imaging to obtain DPC tri-signature computed tomography (CT) images. The tri-signature CT images provide the basis for precise material characterization (e.g., absorption coefficients, indices of refraction, and scatter characteristics). Once the materials have been characterized, they form the basis for creating millions of numerical representations of real-world objects. These objects subsequently form the core for effectively and efficiently training deep-learning models without further experimentation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ABSTRACTIVE HEALTH, INC.
SBIR Phase I: A tool to automate a narrative patient summary of the medical chart for outpatient physicians
Contact
333 E 56 ST
New York, NY 10022--3760
NSF Award
2324507 – SBIR Phase I
Award amount to date
$274,991
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a machine learning-enabled medical record summarization tool designed to provide a narrative summary that can aid physicians in patient care. On average, physicians spend just 3 minutes reviewing a patient?s medical record, and during this time they must interpret unstructured Electronic Health Records (EHR) that can make it difficult for physicians to identify information essential to patient care and diagnosis. By targeting the rich clinical data embedded in unstructured clinical notes, the proposed tool could provide clinically relevant information and a contextual understanding of a patient?s medical history. If successful, the proposed solution will reduce the data burden placed on doctors, mitigate the risk of missing valuable information that could affect patient diagnosis or lead to costly medical errors, and maximize downstream effects on patient outcomes.
This Small Business Innovation Research (SBIR) Phase I project aims to leverage advances in natural language processing (NLP) to assist doctors by automating the process of electronic health record review. The underlying innovation is an extractive-abstractive pipeline that determines what content in the medical record is the most salient and should be summarized through a transformer (a machine learning model). This project aims to advance this summarization tool to more challenging use cases, primarily summarizing the outpatient record, a task made challenging by the large scope of the data, clinical redundancies, different data structures, and sources inherent to outpatient data, all of which need to be accounted for in model training and validation. Objectives include to 1) developing an outpatient summarization model and demonstrating the ability to produce summaries that semantically match reference text with a high level of fluency, 2) validating the utility of artificial intelligence (AI)-generated outpatient summaries to provide significant value to physicians, 3) evaluating the ability of AI-generated summaries that provide information relevant to future patient visit through ablation study, and 4) incorporating checks for bias in the existing model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ACATECHOL, INC.
SBIR Phase I: Anti-infective Foley catheters for long-term prevention of catheter-associated urinary tract infections
Contact
1396 POINSETTIA AVE
Vista, CA 92081--8504
NSF Award
2334168 – SBIR Phase I
Award amount to date
$274,982
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel anti-infective coating to mitigate catheter-associated urinary tract infections (CAUTIs). These infections often lead to severe complications, resulting in an estimated 13,000 annual deaths while incurring nearly $6.2 billion in direct and indirect U.S. healthcare system costs. The hybrid catheter technology aims to provide continuous protection against infections caused by biofilms, offering chronic antimicrobial and biofilm-repelling properties through a synergistic combination of biofilm-repelling and static antimicrobial surface moieties. The proposed catheter technology aims to demonstrate significant decreases in infection rates, improved catheter longevity, and broad-spectrum protection against pathogens to reduce the risks of infection associated with long-term catheter use, reducing the reliance of patients on antibiotics. The scope of this technology's application has broader potential beyond urinary catheters to include other catheter-based applications and acute in-hospital use medical devices. The overall technological objectives are to improve infection control practices and risk reduction for many common U.S. in-hospital procedures.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel device surface coating with enhanced anti-pathogen and biofilm resistance. The objective is to develop and validate in vitro an innovative catheter design that offers prolonged resistance to biofilm formation, superior to current single modality approaches. During this Phase 1 project, the anti-biofilm properties of zwitterionic moieties will be combined with the durable static microbicidal action of a Gemini-dicationic moieties into a single coating. Initial bench tests at the materials level demonstrate a significant reduction in biofilm formation superior to currently available methods. Invitro testing will be completed on the novel combined mode material to demonstrate reduced infection risks relative to existing antimicrobial Foley catheters. The proprietary material will then be integrated into manufacturing processes to prevent infection in catheter-use medical settings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADA TECH LLC
SBIR Phase I: Methods for Embedding User Data into 3D Generative AI Computer-aided-Design Models
Contact
65 PAMELA DR
Holliston, MA 01746--2055
NSF Award
2335491 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a novel Artificial-Intelligence-powered generative design solution that is able to address the needs of industrial and consumer-product manufacturers by exploiting the abundance of data (social media, usage, telemetry) currently available. The proposed framework will create new opportunities for American design and manufacturing firms to better align their products with rapidly evolving consumer needs while reducing the product development challenges that currently exist. It also enables faster cycle times for product development and the near-real-time inclusion of consumer sentiment into product design. The proposed computational methods will translate consumers? digital insight into new ways to increase the quality of the design concepts and the diversity of consumer perspectives incorporated into AI-generated design concepts, thereby enhancing the designers? ability to innovate socially aware, consumer-centric products. This project will foster the design of novel, effective, and efficient design models, augment designers? creativity, promote designer-AI co-creation and bias mitigation, and bridge the gap between consumer-needs discovery, Design for Excellence (DFX) engineering, and social impact. This has ramifications for nearly every industry and application.
This Small Business Innovation Research (SBIR) Phase I project will enable a generational leap in three-dimensional generative design capabilities by integrating qualitative and quantitative information into generative AI models for the efficient production of novel designs. The primary objective is to develop a testable demonstrator for fusing consumer data, data from the Internet of Things (IoT), and Design for Excellence (DFX) engineering specifications into 3D geometric data. The Phase I project will focus on exploring new methods for natural language processing, generative modeling, and data fusion models to integrate consumer data and technical requirements with IoT-based telemetric data, drawing inferences for product design, and building novel semi-supervised models to inject these data inputs into 3D CAD generative models. The project will determine how to directly connect consumer needs with functional performance and study the real-world effectiveness and efficiency gains from the generalizability of 3D generative design. The project will address several challenges of current generative design solutions, including the translation of qualitative and quantitative metadata into concepts, the control and iteration of automatically generated designs, and their seamless integration into manufacturing processes and workflows.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADDEN ENERGY INC
STTR Phase I: Advanced Lithium Metal Anodes for Solid-State Batteries
Contact
1432 MAIN ST
Waltham, MA 02451--1621
NSF Award
2335454 – STTR Phase I
Award amount to date
$274,990
Start / end date
04/01/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project enables high-performance and low-cost lithium metal anodes to be used in solid-state batteries. This solid-state battery technology, with fast charge and cycle lifetime, has been demonstrated using a lithium metal foil as the anode. However, lithium metal foil is a major cost driver and, thus, a commercial barrier. This research focuses on the development of pre-lithiation processes for 3-dimensional scaffolding materials to introduce a lithium source to the high-performance anode at a far cheaper cost than that of lithium metal foil. By removing the cost barrier to this solid-state battery platform, this project will enable the technology to expand the number of vehicle market segments that can electrify. This high-performance technology, combined with the underlying solid-state batteries, will address a $1 billion market for fast-charging electric vehicles that is rapidly growing.
The intellectual merit of this project is to determine the feasibility of using multiple alternative lithium sources in place of thick lithium metal foil in the anode of solid-state batteries. The research also seeks to develop an understanding of the kinetics and thermodynamics of the lithiation process in the solid-state battery. While high performing, thick lithium metal foil is a challenge to process with roll-to-roll manufacturing. This research and development will focus on methods to include lithium in the anode that are more easily combined with typical manufacturing processes. The team will investigate the fundamental kinetics and thermodynamics of each approach?s lithiation and de-lithiation process during cycling. By identifying alternative lithium sources with comparable kinetics to lithium metal foil, this project will develop a high-performance anode that greatly improves the manufacturability of the solid-state battery cells.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADIALANTE L.L.C.
SBIR Phase I: Novel development of a pediatric Magnetic Resonance Imaging (MRI) scanner
Contact
200 OAK ST SE
Minneapolis, MN 55455--2009
NSF Award
2323231 – SBIR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project focuses on the development of techniques that will facilitate the design and development of affordable, compact, and patient-friendly magnetic resonance imaging (MRI) systems. MRI systems are the preferred modality for a range of imaging types, notably pediatrics, due to their superior diagnostic capabilities, high resolution, and minimal side effects. However, traditional MRI experiences can be daunting for children due to the confined and noisy environment, often leading to alternatives such as the use of anesthesia for an MRI scan or the use of computerized tomography (CT), which exposes them to high levels of ionizing radiation. The objective of this project is to innovate novel techniques for developing a new generation of scanners, with a focus on creating child-friendly imaging experiences. These groundbreaking techniques have the potential to introduce new classes of MRI scanners, expand the imaging market, and democratize MRI systems to communities in need worldwide.
The intellectual merit of this project focuses on the development of B1 imaging approaches. While traditional MRI scanners rely on B0 gradient coils for spatial encoding, B1 coils have previously been shown to spatially encode, but they remain widely under-used and under-developed. The goal of this effort is to demonstrate the viability and expand upon the B1 imaging approach known as Frequency-modulated Rabi-Encoded Echoes (aka, FREE), specifically, frequency-encoded and phase-encoded FREE. FREE is unique from other B1 imaging approaches because of its high immunity to magnetic imperfections. FREE, unlike other approaches, can appropriately image in highly inhomogeneous (and inexpensive) magnets. A scanner built around FREE would take advantage of the cost savings that come with removing B0 gradient coils and from reducing the homogeneity of a magnet. An MRI scanner utilizing FREE would be more affordable, compact, and silent. This project will focus on demonstrating two- and three-dimensional imaging on a compact, affordable, and inhomogeneous 0.5 Tesla system, thereby demonstrating the capability of B1 imaging approaches.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AGIL THERAPEUTICS, INC.
SBIR Phase I: Treatment of Type 2 Diabetes through Cryoablation of the Duodenum
Contact
155 EASTWOOD DR
San Francisco, CA 94112--1227
NSF Award
2321818 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research Phase (SBIR) I project is a novel procedural treatment for the 5-10 million people in the U.S. with medical refractory Type 2 Diabetes. Current treatments require self-management of insulin injections and/or medication, frequent visits to specialists, and a controlled diet. Patients can fail to achieve optimal glycemic control due to the individual medication dosing requirements, safety, and tolerance limits. Poorly managed patients can suffer from adverse events including heart attack, stroke, nerve damage, blindness, and early death. This Duodenal Cryoablation system aims to provide an outpatient, minimally invasive procedure for controlled ablation of the duodenum utilizing a standard, cost-effective endoscopic approach. If successful, the novel therapy will decrease or eliminate insulin and/or medical therapies in patients suffering from medical refractory Type 2 Diabetes.
This SBIR Phase I project aims to develop a novel cryoablation system that delivers a highly controlled and targeted cryoablative agent for freezing the duodenum. The system is based on emerging evidence of duodenum remodeling upon ablation resulting in restoration of glucose control and regulation. The technical engineering milestones include managing high pressures of the cryogenic fluid within extreme dimensions including small luminal diameters and long length, within a unique and tortuous path. A key objective is to produce a system ensuring consistent cryogenic fluid delivery down a small diameter, insulated, long length lumen to a set of sprayers placed in the duodenum. A second objective is the development of a method of consistent cryogenic fluid distribution through the sprayers to the target tissue. The final objective is the development of bench methods and testing capabilities validating consistent cryogenic fluid delivery. The design will be tested in preclinical models and the harvested tissue evaluated via histopathological analysis for ablation efficacy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AGTEC INNOVATIONS INC
SBIR Phase I: Caged Urea as an Eco-friendly Nitrogen Fertilizer
Contact
1290 ALTAMEAD DR
Los Altos, CA 94024--5568
NSF Award
2233044 – SBIR Phase I
Award amount to date
$274,457
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the reduction in greenhouse gas emissions and water contamination due to nitrogen fertilizers. The project will also increase agricultural productivity at lower nitrogen application rates using a novel concept of urea trapped in molecular cages. Nitrogen fertilizers can be serious environmental pollutants. Available alternatives are either too expensive for general agricultural use or cause unwanted residue buildup and are, therefore, minimally used. Pollution from nitrogen fertilizers remains a serious concern globally. This project's impact is directed at three targets: (a) Farmer income: the proposed nitrogen fertilizer may increase crop yields by 5-10%, improve farm profits, and improve the income of 10% of the US population; (b) US economy: the technology may boost the US economy by global export of this fertilizer; and (c) Environment and health: the solution may reduce greenhouse gas emissions and water pollution from nitrogen fertilizer.
The project is aimed at the development of a novel fertilizer compound, where urea is trapped within a biodegradable molecular cage. The molecular cage is designed to bind urea within its structure to reduce its solubility and reduce pollutant production. Nitrogen is released from this cage only when the cage is dissolved by root secretions (such as organic acids). This technology is an intelligent release mechanism where an insoluble nutrient is released only on demand by the plant. The cage itself is constructed of plant nutrients therefore, when the plant dissolves the cage, it not only gets its nitrogen from urea but also consumes the cage because the cage is also food to the plant. To have a commercially successful product, the team will optimize the performance of the caged urea to meet agronomic and environmental targets and farmer acceptability. These goals will be accomplished by modulating the cage-link bridges to improve the trapping of urea, reducing volatilization by controlling the microenvironment modifiers, controlling emissions during production, and improving the physical properties for ease-of-farmer use. This project will help to develop caged- urea into an environmentally impactful, agronomically beneficial, marketable, consumer friendly, and manufacturable commodity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AI ACUITY
SBIR Phase I: Improved image compression targeting machine learning based detection algorithms
Contact
90 HULME CT APT 107
Stanford, CA 94305--7432
NSF Award
2233091 – SBIR Phase I
Award amount to date
$274,623
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in reducing the sizes of earth observation images, thereby saving millions of dollars on transmission, storage and processing costs. Storage and processing costs account for a large portion of costs for earth observation companies, reducing these costs will make earth observation imagery more accessible for a broader audience including companies performing climate and environment studies. The need for reduced image sizes also extends to video compression. Video calls, telepresence, telemedicine, remote work and metaverse all depend on the ability to stream video over limited or variable bandwidth connections. This technology will find ready applications in the area of high-efficiency video compression.
This SBIR Phase I project uses object detection algorithms to detect areas of importance in an image and utilizes that information to improve the efficiency of image compression. More specifically, the research will develop a compression network that maximizes the detection accuracy of a down-stream, machine learning-based object detector. In contrast, current compression algorithms do not interpret the images they are compressing and simply minimize a visual loss function that treats the entire image equally. The technology will produce images that can be stored in the standard image compression file formats including .png and .jpeg. This technology will enable fast compression and will explore modified compression architectures, quantization, pruning and parallelization using graphics processing units to reduce latency of compression.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AI-NEOTECH LLC
STTR Phase I: Patient-Specific System for Early Detection and Identification of Epileptic Seizures
Contact
11141 MINNEAPOLIS DR
Hollywood, FL 33026--4941
NSF Award
2322346 – STTR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to provide epileptic patients, and their caregivers a smart system that can predict seizures before they occur. There are more than 3 million adults and 1 million children in the US, and more than 50 million people worldwide, suffering from epilepsy. Repeated and unpredictable seizures significantly affect the quality of life of people suffering from epilepsy. These seizures remain the leading cause of economic, emotional, and physical injuries for people with epilepsy and their caregivers. Design, development, and integration of artificial intelligence (AI) models with instruments that detect abnormalities in brain waves like electroencephalogram (EEG) for real-time seizure prediction may bring improvements for these patients and their caregivers. This technology is poised to capture a portion of the rapidly growing $6 billion US market of AI healthcare solutions.
This Small Business Technology Transfer (STTR) Phase I project supports the development of a novel consumer product that works with caregivers to proactively mitigate the risk of seizure events in people with epilepsy. Current commercial solutions are mostly reactive, and support is available only after a seizure event. The company will fill this gap by developing, testing, integrating, and evaluating machine learning (ML) models - applied to EEG data - for epileptic seizure prediction. The scientific approach will leverage inherently heterogenous and complex edge technologies. Data connectivity with third party vendor EEG caps, microcontrollers, smart phones, and cloud services rely on many different operational technologies and communication standards. This research will overcome these challenges with hardware and software solutions that will integrate these services within an edge device to enable application portability and simplify deployment. Challenges such as inference on limited computational power and energy devices, and its effects on the accuracy/sensitivity of the predictions will be solved using robust cross-validation techniques, extensive testing, and benchmarking using community standards. The technical product of this research will advance caregiver knowledge and increase understanding of epileptic seizures as well as increase patient well-being.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALGOFACE INC
SBIR Phase I: Face Analyzer / Semantic Search
Contact
37204 NORTH TRANQUIL TRAIL
Carefree, AZ 85377--9633
NSF Award
2335287 – SBIR Phase I
Award amount to date
$274,996
Start / end date
03/01/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is significant as the company?s advanced Face Analysis AI technology will accelerate AI projects by 18-24 months. This innovative technology is poised to have a positive influence on various sectors such as retail and public safety, offering applications that go beyond facial recognition/identification. By focusing on collaborative human-AI facial tracking and analysis, this technology addresses ethical concerns and mitigates the risks and consequences of traditional facial recognition technologies. The project promotes diversity and inclusion in STEM fields by emphasizing a diverse team to combat bias and equity issues in technology development. The technology can contribute to national defense efforts by enabling efficient search for facial attributes of interest based on semantic queries. This aspect is particularly relevant in public safety scenarios with large crowds and high-security concerns. By reducing bias, improving accuracy, and addressing privacy and ethical concerns, the technology can have a lasting impact on the AI industry while advancing the welfare of the American public and supporting security efforts.
This Small Business Innovation Research (SBIR) Phase I project aims to create Face Analyzer/Semantic Search, an AI system bridging descriptive text and facial photos. Unlike conventional face recognition systems, which necessitate a probe photo for comparisons, the company's innovation seeks to eliminate this requirement. This approach offers benefits in terms of time, cost, and accuracy, challenging the conventional wisdom in the field. The project's initial challenge involves assembling diverse training datasets with labeled face photos and textual descriptions, establishing a scalable data pipeline to enhance accuracy and mitigate bias. The second challenge is assessing the accuracy of facial attribute classification models derived from text and images across various attributes, image types, sizes, and ambient conditions. The third challenge involves optimizing model size and computational efficiency for cost-effective deployment. The proposed solution entails constructing a comprehensive training image dataset, expanding computer vision capabilities, developing a natural language processing module, and implementing a matching system. Key milestones for product development include creating precise facial image indexing modules, enabling the extraction of facial attributes from textual descriptions, and efficiently deploying the system in the cloud. The innovation promises to streamline and enhance facial analysis, potentially reshaping the field of face AI.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALL-IN PEPPERS AND SPECIALTY PRODUCE LLC
SBIR Phase I: Developing an Indoor Method to Produce Morel Mushroom Fruiting Bodies
Contact
673 FOXTREE CIR APT 5
Burlington, WI 53105--1694
NSF Award
2325697 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project creates disability-friendly food production equipment for growing highly nutritious morel mushrooms. Creating equipment that is disability-friendly allows more work for an immensely underserved population and a greater employee base for farmers, who regularly need more employees than they can find. The project also focuses on farmers in both rural and urban food deserts, where nutritional needs aren?t being met. Leftover colonized agar media and fruiting bodies will be dehydrated and extracted into further nutritional supplementation. Morels and their mycelium are shown to be rich in nutrients and have many health benefits. Making the mushrooms easier for the general public to purchase consistently will improve the health and well-being of Americans. The higher supply of morel mushrooms will allow for their use in widespread nutritional supplements and a renaissance of mushroom cooking in the culinary world.
This project is based on a novel, self-contained method to grow fresh morel mushroom (M. esculenta) fruiting bodies on agar media using a single inoculation step. There are no existing commercial production methods that meet the market demand. The main supplier of fresh morels is through foraging, which is extremely labor intensive, ecologically destructive, and has a small window of procurement opportunity every year. This severely limits the availability of this incredibly nutritious and delicious food source. Two major technical hurdles must be overcome in order to bring this production method to market. The first hurdle is demonstrating microclimatic conditions for consistent production output. The project must identify a modified approach from the preliminary method in order to definitively determine appropriate microclimatic conditions. The second aim is to incorporate protective measures from adverse effects, such as the ongoing Trichoderma spp. epidemic which plagues mushroom farms worldwide. SBIR Phase I success will be measured by the ability to retain production output while producing morels with consistency of taste equal to or better than wild morels. Taste will be evaluated by a team of chefs who are experienced with their use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALTAY THERAPEUTICS, INC.
SBIR Phase I: Targeting the Root Cause of Ewing?s Sarcoma
Contact
733 INDUSTRIAL RD
San Carlos, CA 94070--3310
NSF Award
2233404 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to treat pediatric patients affected with Ewing?s Sarcoma by targeting the root cause of the disease. Using a novel approach, new therapeutics will be developed to specifically inhibit the protein that causes Ewing?s Sarcoma and thereby extend the lifespan of patient. The approach will enable understanding of the molecular underpinnings of this devastating disease. Importantly, findings from this study may be able to treat diseases driven by similar proteins, providing new medication for patients with few available treatment options. The successful outcome of the project would lead to the commercialization of the first-in-class
inhibitor to target the oncogenic fusion protein, EWS-FLI1, to treat Ewing?s Sarcoma. In addition, the technology could provide valuable data about drugging oncogenic proteins in other disesases such as prostate cancer and breast cancer.
This project will aid in characterizing potential therapies for Ewing?s Sarcoma. The goals include: (1) determining the toxicity profile of novel inhibitors across a panel of human cells, (2) measuring the drug specificity to the target protein, and (3) determining the efficacy of the lead molecule in mice. The data from this study will add to the understanding of drugging fusion proteins which are validated drivers of many diseases such as prostate cancer, breast cancer, and Ewing?s Sarcoma.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AMIE HEALTH INC.
SBIR Phase I: Artificial Intelligence (AI) chatbot providing flare-up support for patients with endometriosis
Contact
8 THE GRN
Dover, DE 19901--3618
NSF Award
2304436 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel chatbot that provides support to endometriosis patients. Endometriosis is a debilitating chronic pain disorder that impacts approximately one in ten women in the United States - resulting in significant loss of productivity, low quality of life, and greater than $80 billion annual economic burden. This artificial intelligence (AI) chatbot aims to conversationally educate users regarding clinically accepted paradigms of care and options during scenarios including painful endometriosis flare-ups. This project ultimately aims to improve patients' self-knowledge and quality of life, expand access to patients in rural communities to improve endometriosis patient recovery, and reduce the burden of the disease due to lack of knowledge or hesitancy for proper self-care.
This Small Business Innovation Research (SBIR) Phase I project will develop an on-demand endometriosis flare-up management chatbot using advanced Natural Language Processing (NLP) and Understanding (NLU). Many endometriosis patients experience pain or symptoms on a daily basis but symptoms can become unbearable during flare-ups, causing patients with little support to seek emergency room care. The conversational chatbot will be trained to answer user?s questions, guide them through pain-reducing exercises such as pelvic floor therapy, and provide direction to professional resources. This framework uses an internal Natural Language Understanding unit to create user intents, variable entities, conversation context, and conversation resuming slot filling. The technology incorporates emotional understanding and empathetic mirroring allowing the chatbot to have a natural freeform text conversation with the user to encourage them to freely express themselves and feel understood during moments of crisis. This chatbot will serve as a digital companion for patients, acting as both a supportive friend (listening and validating) and as a virtual coach (guiding the patient through exercises to alleviate symptoms). This technology project will design, develop and validate the chatbot in a limited patient pilot.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ANYGLABS, INC.
SBIR Phase I: Autonomous System for DNA Sequencing Prep in Space and Austere Environments
Contact
5770 OBERLIN DR
San Diego, CA 92121--1723
NSF Award
2344191 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to democratize access to advanced diagnostics tools by building an automated, miniaturized system for DNA extraction and preparation for sequencing for both in space and austere environments. This automated and miniaturized approach has the potential to contribute to a higher throughput acceleration of in-space R&D, manufacturing, and commercialization for biotechnology. DNA sequencing is used for various purposes in research and medicine ? for example, diagnosis and treatment of diseases, monitoring of pathogens in water supplies and food, and study of the effects of the environment on human, crop, and pet health. Yet nearly 50% of the world?s population has little or no access to such advanced diagnostics tools, and at least 2.2 billion people lacked safe drinking water in 2022. Even though there is high interest in genetic testing among individuals of low socioeconomic status, such tests are inaccessible due to cost or availability. The global DNA sequencing market size of $11B in 2022 is expected to grow to over $50B by 2032. This project is disrupting the status quo and addressing an unserved market by developing a small, portable, automated, high throughput, and cost-effective system for extracting DNA from a variety of biosamples to prepare them for next-generation sequencing. The in-space environment has the potential to leverage microgravity advantages for a wide range of biotechnology-based advances but is currently capacity and throughput-constrained. This project will further accelerate a high-throughput, faster iterative approach to in-space R&D to achieve more of the disruptive solutions possible from microgravity.
This SBIR Phase I project proposes a unique approach to technology development ? building the technology for space and microgravity, the most extreme environment. Currently, no such automated, miniaturized technology exists in space for DNA extraction and sample preparation. Space is a unique environment that can offer novel scientific insights. The availability of advanced tools in microgravity, such as the technology proposed in this project, will enable scientists to push the boundaries of knowledge across a variety of disciplines, from aging and longevity research to cancer medicines to stem cell expansion and organoid production in space. Furthermore, by solving for space ? an extreme, harsh environment with many constraints ? the technology will also solve for Earth?s austere environments and provide a high-caliber diagnostic system for populations in remote, underserved, under-resourced, and extreme environments, which includes military field operations for national defense and security. This technology is pushing the boundaries of scientific discovery in space and democratizing health and welfare on Earth. The first product is only the beginning of a series of products for portable advanced end-point-analysis tools. The platform technology will spin off subsequent devices that will eventually enable in-home or point-of-care diagnostics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
APPLIED IMPULSE INC.
SBIR Phase I: Repair, Weld, and Build Metallic Parts with Fill Impact Welding
Contact
2076 FAIRFAX RD
Columbus, OH 43221--4319
NSF Award
2322343 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project seeks to develop a welding technology that will improve the repair, joining, and additive manufacturing of metallic parts and features. First applications include material additions to repair gouges and mis-drilled holes during aircraft production and service, both of which represent significant financial opportunities. Repairs to the structural material are not currently permissible in a production environment due to adverse effects of currently available repair methods on base material properties, usually due to extreme temperatures. Aerostructure manufacturers have a strong incentive to minimize the weight of the aircraft structure, often at the significant financial and environmental expense of scrapping a whole panel. Maintenance, repair and overhaul often entails total replacement of damaged components with new ones as improper repairs of critical components can cause catastrophic harm. Replacement of parts is expensive and has long lead times due to high-value, low-volume nature of the aerospace industry. This project will develop an effective restoration method to repair of metallic components, while being agnostic to the material and part geometry. Reclamation of previously unrepairable parts made from materials such as titanium, nickel, and aluminum has a large positive environmental impact. Additionally, by broadly enabling solid-state joining, this technology will disrupt the welding industry, globally valued at $20 billion. The foundational technology platform, led in the US, will produce new jobs in science, technology and engineering fields while bolstering domestic manufacturing supply chains.
The innovation underpinning this project involves the sequential, tactical, and controlled deposition of metals using explosive welding. Explosive welding uses coin-sized metallic elements launched to speeds in the range of 300-1000m/s without explosives. While it is known that explosive welding can weld large plates together, the method is not suited to automation or conventional industrial settings. Impact welding will be developed as a fill-welding technique, much like a filler metal in conventional welding, and will use wrought sheet metal as feedstock. Here, electrically vaporized metallic foils will be used as the driver for the fill elements and the research will focus on whether those elements can be launched reproducibly to develop large bond areas and reproducible positioning. The ability to control element shape and orientation during flight and produce an interface that is fully welded are the most high-risk aspects of the technology. Mechanical testing, scanning electron microscopy, and inline process monitoring such as photonic Doppler velocimetry will be performed. This effort will develop a new process-structure-property loop, with the goal of producing parts that are better than those made with a competing technology such as cold spray as measured by total energy consumption, cost, and mechanical properties.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
APPLIED RESEARCH TEAM, INC.
SBIR Phase I: Radar Snow Retrieval
Contact
1750 WEWATTA ST
Denver, CO 80202--6696
NSF Award
2232761 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will develop transformative, machine-learning algorithms that will improve water management. Water management is critically important to the social well-being, food supply, and climate resiliency of the local population in the Western United States, yet water managers lack adequate snowpack depth and water content information necessary for the management, storage, and transfer of water for irrigation and consumption. Water deficits are made worse when snowpack depths are in error, potentially resulting in devastating damage to agricultural economies and vulnerable populations. The proposed technology will be able to scale from storm events to seasonal snowpack estimations and provide accurate mappings of snowpack depths and water equivalents for watershed areas needing water management.
This Small Business Innovation Research (SBIR) Phase I project develops algorithms for determining snowpack depth and water content. Snow retrieval algorithm development has not kept pace with the deployment of short wavelengths. C- and X-band radars are used as ?gap-filling? radars in mountainous valleys. Developing effective algorithms for detection of snow water equivalent is needed for these short wavelength radars. Artificial Intelligence/Machine Learning (AI/ML) and optimization algorithms are expected to improve estimation accuracy compared with point-scale (sensor) observations and across watershed areas relevant to water management. Physics-guided neural networks (PGNNs) can produce physically consistent results and generalize to out of sample scenarios. Application of a PGNN to snow retrievals is expected to perform better than purely data-driven or deterministic algorithms. Anticipated technical results will provide water managers with a cloud-based subscription service updated in real-time, using historical and current radar data to improve operational decision-making.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
APPLIED SENTIENCE INC.
SBIR Phase I: A Human-Aware Platform for Socially Collaborative Personal Artificial Intelligence (AI) Assistants
Contact
353 KEARNY ST
San Francisco, CA 94108--3226
NSF Award
2223224 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is enabling Artificial Intelligence (AI) assistants to become proactive, empowering them to provide better service to users. Currently, commercial AI assistants respond to user requests reactively. The technologies developed in this project would provide AI assistants with the situational awareness to understand users? lives and predict their needs. The technology will also enable social intelligence to take the initiative to support users in appropriate ways. This SBIR Phase I project will apply these technologies to a consumer product for assisting users with time management and meeting goals while establishing and strengthening healthy, desirable habits in their daily lives. Proactive personal AI assistants have the potential to improve productivity, convenience, and quality of life for every person, as well as to promote aging in place with greater independence and wellness. Fundamental scientific advancements will also enable a new generation of potential applications for AI assistants across sectors, fueling economic growth and creating jobs.
This project addresses two central technical challenges for enabling proactive AI assistants: contextual awareness of users and agent-initiated interaction. Contextual awareness includes the AI agent?s real-time understanding of current user state and activity, as well as a long-term understanding of past user habits. The project proposes to develop hybrid computational models combining machine learning of multimodal user observations from visual, acoustic, and geolocation data with probabilistic graphical models that perform long-term inference and prediction over historical user observations. A virtually-embodied AI agent will leverage these contextual awareness representations to conduct real-time, face-to-face collaborations with users. The project proposes to research and develop a dynamic scheduling approach to proactively enable the agent to communicate with users. These models will be integrated within a broader system that assists users with time management. This system will implement an end-to-end architecture for protecting user privacy while handling their data. The technical solution will be validated based on quantitative metrics related to utility and user acceptance by deploying the prototype in end users? homes over a multi-week period and conducting surveys about their subjective experience of the proactive AI assistants.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ARTIMATIC TECHNOLOGIES, INC.
SBIR Phase I: Artificial Intelligence for Automated Custom Avatar Creation
Contact
4190 TUCKERSHAM LN
Tucker, GA 30084--2233
NSF Award
2334192 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project will create a way for experienced animators to rapidly make high quality three-dimensional (3D) content, and for novices to create engaging 3D content without the need for years of technical training or powerful but expensive software. Engaging computer graphic content has revolutionized education, entertainment, medical, and virtual environments. This project will use artificial intelligence (AI) to unlock the full potential of 3D graphical content, a $17.21 billion annual market, by alleviating major bottlenecks in the workflow. While there are more than 62,000 animators currently employed in the United States, fewer than 10,000 work specifically at 3D animation studios, and a smaller proportion of them possess the skills for weight painting. Weight painting is a vital technique in 3D design that adds realism to characters, enabling them to move smoothly during animation. Compounding the difficulty, weight painting 3D models is a tedious task that can take an expert up to 2 days (or around 16 work hours) to manually complete one model. Smaller animation shops often do not have the expertise to perform this task at all and are unable to compete for bigger, more lucrative contracts. Furthermore, researchers and students at universities around the world are often unable to perform this weighting task, which reduces their ability to create animations for medical, athletic, and entertainment uses in augmented reality or virtual reality.
This Small Business Innovation Research (SBIR) Phase I project will utilize deep neural networks (DNN) to create 3D models from text input as well as a weight-painted rig from an industry-standard skeleton system and a 3D model mesh. The technology converts the mesh and skeleton into a format that can be processed by machine learning (ML) code, introducing a brand-new data structure. Additionally, the project will explore an adaptation of the COO (Coordinate List) matrix, a sparse matrix that performs effectively with neural networks but faces challenges when applied to machine learning tasks in 3D space where coordinate ordering is uncertain. The most difficult issues, such as weight painting and modeling, have been hampered by four specific limitations: 1. Lack of ground-truth, 2. Limited training data, 3. Lack of a-priori ML architecture, and 4. Lack of robustness and specificity for non-gaussian data. This project will make inroads into each of these areas by establishing a methodology for incorporating and transforming non-gaussian data for DNN analysis and will create a comprehensive data training set while establishing a domain specific ground-truth based on the canonical Turing test.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASIMICA LLC
SBIR Phase I: Boosting Industrial Bio-Fermentation with Microbial Stem Cells
Contact
1938 HARNEY ST STE 305
Laramie, WY 82072--3037
NSF Award
2222602 – SBIR Phase I
Award amount to date
$274,100
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to reimagine bio-manufacturing with a novel platform technology that could boost the yields of many products, including food additives, biomaterials precursors, biofuels, and pharmaceuticals. The technological advancement addresses a fundamental issue that limits conventional bio-fermentation, which is that producing cells suffer limited health and viability in exchange for higher yields. In this proposal, genetic tools will be used to divide the labor of cell reproduction and product synthesis into two different cell types, called stem cells and factory cells. As older factory cells become exhausted, productivity is maintained by new factory cells, which are born from the stem cell population. The approach may be particularly well suited to biofuels and other molecules that are difficult to produce in large quantities by conventional bio-fermentation because the product is toxic to the cells that make it. It could be applied toward increasing the profitability of existing bio-processes and also for bringing new products to market, which are currently too difficult to produce. In this project, the team seeks to demonstrate the benefits of producing a fuel (limonene) and a dairy enzyme (chymosin), as proof of its application in biofuel and agricultural sectors. Broad industrial implementation will advance bio-manufacturing toward the ?green? revolution, contributing to the development of cleaner industries and decreasing US and global reliance on fossil fuels.
This project aims to solve two major limitations of microbial fermentation processes: metabolic exhaustion and genetic drift. These are nearly universal problems in the industry. Highly producing cells can become inactive due to the lack of metabolic resources, cytotoxic effects of products, and mutations that break the biosynthetic pathway. In this project, Microbial Stem Cell Technology (MiST) uncouples growth and production by establishing a multicellular system. One cell type is dedicated to product synthesis (factory cells), while another (stem cells) is responsible for cell division and the generation of new factory cells. As older factory cells lose productivity, the bioreactor is continuously replenished with new factory cells, derived from the stem cell population. By maintaining an active factory cell population, MiST-supported cultures are expected to exhibit increased production longevity and higher overall yield than conventional bio-fermentations. This project aims to validate the technology in E. coli engineered to produce limonene, a precursor for biodiesel and other useful chemicals. In the factory cells, T7RNAP will drive high-level expression of a suite of biosynthetic enzymes. Since limonene has a cytotoxic effect on producing cells, MiST-supported factory cell replenishment is expected to increase productivity by more than 2-fold compared to the conventional limonene-producing strains.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASTRIA BIOSCIENCES, INC.
SBIR Phase I: A Blood Test to Detect Cerebral Aneurysms
Contact
1123 PINEWOOD DRIVE
Pittsburgh, PA 15234--1809
NSF Award
2335396 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is expected to advance the diagnosis and treatment of cerebral aneurysm (CA). CAs affect 2-5% of the population. Nearly 30,000 Americans each year suffer CA rupture without warning, resulting in approximately 50% mortality. CAs are largely asymptomatic, and therefore usually undetected until ruptured. By providing the first blood test able to detect and evaluate CAs, this project will enable monitoring at frequencies not possible today. The technology will also offer a dynamic rupture risk score that can be integrated into the patient care routine to better guide preoperative, invasive diagnosis and surgical interventions. Decreased testing costs enabled by this technology will promote more regular monitoring and early action, benefiting minorities and other groups with lower socioeconomic status who struggle to access preventative healthcare. Ultimately, this project has the potential to lead to improved patient outcomes and better quality of life for patients living with unruptured CAs and reductions in healthcare costs, as well as new insights into CA pathogenesis. The technology will bring peace of mind to those in high-risk groups and their families.
This Small Business Innovation Research (SBIR) Phase I project seeks to advance the first simple, whole blood-based diagnostic test to detect the presence and monitor the progression of a cerebral aneurysm (CA). The project will develop a dynamic rupture risk score as well as novel aneurysm subgroupings. Currently, CAs can only be diagnosed with cerebral imaging such as magnetic resonance imaging or computed tomography angiography. These approaches are not suited for regular screening due to prohibitively high costs and potential risks. This project will exploit the fact that aneurysms are dynamic and exhibit different cytokine signatures over time. With a carefully selected panel of cytokines and a proprietary model, these inflammatory signatures can be reliably differentiated in CA patients with unruptured and ruptured aneurysms. This project will generate a robust dataset of CA patient blood samples, with a focus on increasing sample representation from underserved populations. The dataset will be used to train a proprietary probabilistic equation to develop a risk of rupture metric. Data will be stratified using machine learning-based principal component analysis to create distinct aneurysm subgroups with key cytokines of interest. This analysis will open the door for precision-medicine molecular therapy against specific drivers of inflammation in those patients.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASTROFORGE, INC.
SBIR Phase I: Electromagnetic-ablative PGM Refining for In-situ Asteroid Mining
Contact
15261 CONNECTOR LN
Huntington Beach, CA 92649--1117
NSF Award
2327078 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This SBIR Phase I project will work to revolutionize the precious metal commodity market through asteroid mining. The company aims to identify and mine near-Earth asteroids containing Platinum Group Metals (PGMs), which are crucial components in various US industries such as automotive, electronics, medical devices, pharmaceuticals, renewable energy systems, and consumer goods. Currently, the United States relies heavily on non-US sources of PGMs and other critical minerals, most of which are outside the free world. AstroForge's technology will increase the economic competitiveness and national security of the US by providing a domestic source of these critical metals.
The SBIR Phase I project involves developing an ablative refining process for in-situ asteroid mining, using laser heating to process complex asteroid ore for separation and extraction of platinum group metals. This approach to developing a refinery in space is compatible with the mission goals and constraints, such as rapid extraction of PGMs to reduce radiation dose. The project also aims to address the environmental impact of traditional refining methods on Earth by creating a new system for refining metals in space that does not rely on chemical processes and their associated toxic waste production.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AUDIOT, INC.
STTR Phase I: Using Audio Analytics and Sensing to Enhance Broiler Chicken Welfare and Performance by Continuously Monitoring Bird Vocalizations
Contact
311 FERST DR NW STE L1334
Atlanta, GA 30318--5602
NSF Award
2335590 – STTR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project will be in enhancing the well-being of chickens on poultry farms and in equipping growers with effective tools to monitor bird conditions. As chicken is a widely consumed source of live-animal protein globally, there is a growing consumer preference for ethically raised animals. The project addresses this demand by fostering improved welfare practices in poultry farming. There are collaborative movements with major producers and institutional consumers to establish evidence-based welfare standards impacting entire supply chain. With a declining agricultural workforce in the United States, it is essential to have automated mechanisms to extend a farmer?s capabilities. This project will develop a smart monitoring system for the birds meeting these needs, resulting in improved bird welfare and amplification of the farmer?s capacity.
This Small Business Technology Transfer (STTR) Phase I project uses audio monitoring and machine listening to measure animal behavior. Since poultry operations differ significantly from farm to farm and over the life of the chicken as it grows from chick to a mature bird, the machine learning algorithms must adapt. The monitoring systems must be appliance-like in that they do not require expertise or any more than minimal involvement on the part of the farmer. This research will result in the advancement and productization of acoustic machine learning algorithms which search out unusual behaviors in the animals in their environment and provide early indications of distress, sickness, discomfort, and feed and water issues to the grower based on intelligent listening and inference. Acoustic approaches do not disturb the animals, are more robust than video for long-term deployment in dusty environments, and operate around the clock and in the dark. By providing early actionable insights to the grower, this technology can correct problems early, thereby improving not only the animal?s welfare, but their productivity as well. By deploying inexpensive microphones at multiple locations in a grow-out house, activities and problems can be localized, bringing precision livestock technology to flock-based animal management.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AVALANCHE ENERGY DESIGNS, INC.
SBIR Phase I: CHARACTERIZATOIN OF FUSION GAIN FACTOR Q FOR ORBITRON MICRO FUSION REACTOR
Contact
9100 E MARGINAL WAY S
Tukwila, WA 98108--4028
NSF Award
2303759 – SBIR Phase I
Award amount to date
$274,890
Start / end date
09/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Phase I Small Business Innovation Research (SBIR) project is to develop a small plasma confinement device called an orbitron, which could have applications to allow low cost, highly mobile fusion sources. Markets with the largest opportunity to benefit from small, carbon-free, micro-fusion reactors are the ?hard-to-decarbonize? industries like long haul trucking, maritime shipping, aviation, distributed energy, and also space power and propulsion. The development of a small clean energy fusion reactor would be a transformative technology for society. The proposed micro-fusion device may enable continuous clean energy production from readily available elements, without the use of long-term radioactive elements. This microfusion device is also expected to be orders of magnitude cheaper than larger scale fusion reactors, and will allow for iterative design and testing for optimization.
This SBIR Phase I project will result in the ability to achieve predictions of the fusion gain factor (Q) for orbitron-based micro-fusion reactors. Orbitron science combines aspects of electrostatic ion traps, like an Orbitrap, with high voltage microwave-type electron confinement in ?crossed-fields? like a Magnetron. The resulting plasma regime is novel and exhibits very high ion and electron energies, moderate densities, and long particle confinement times. Optimized fusion gain factor modelling will be achieved via systematic anchoring and validation of Particle-in-Cell (PIC) code via experimental measurements. Discrete experiments with small orbitron fusion reactors will be used to assess the various plasma loss mechanisms. These mechanisms include ionization between fuel ions and neutral background atoms, particle scattering collisions to the device walls and Bremsstrahlung X-ray radiation losses. Once these mechanisms are correlated with the PIC code, detailed assessments of the simulated fusion plasma will be made to determine the potential Q of a future small-scale fusion reactor for energy production. This gain in understanding will enable development of solutions to mitigate loss mechanisms in future prototypes to maximize Q for small net energy fusion devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AXILEA LLC
STTR Phase I: Metabolite-based Polymer-loaded Chimeric Antigen Receptor Expressing Metabolically-Fit Immune Cells for Immunotherapy
Contact
9010 S PRIEST DR
Tempe, AZ 85284--2818
NSF Award
2151586 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to improve cancer treatment. This project advances a new therapy that targets cancer cells and addresses their malignancies. Following the initial application of lymphomas, the results obtained herein can be applied to several types of cancer.
The proposed project will generate Chimeric Antigen Receptor (CAR)-based cell therapies to improve treatment for lymphomas. Currently, these therapies show negative effects, such as cytokine release syndrome and metabolic exhaustion upon reaching the tumor microenvironment. Furthermore, low nutrient availability for CAR cells in the tumor microenvironment decreases the efficacy. Therefore, strategies utilizing CAR therapy to help target the tumors and keep these cells sufficiently metabolically fit to perform their functions are beneficial. The main goal of this project is to test the feasibility of generating biomaterials that maintain activation of immune cells in resource-poor environments. This project will generate CAR-macrophages and test the ability of our biomaterials to maintain metabolic fitness in these cells. Technical activities include: (1) Generate human CAR macrophages using non-viral electroporation, (2) Show proof-of-concept that human CAR macrophages can survive in a resource-poor environment, and (3) Show proof-of-concept that mouse CAR macrophages do not induce toxicity in vivo in mice.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Afsartech Inc.
STTR Phase I: Innovative Expandable Dental Sealer
Contact
153 ORIENT WAY
Rutherford, NJ 07070--2115
NSF Award
2321456 – STTR Phase I
Award amount to date
$274,867
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is in developing a novel dental sealer technology for root canal treatments for endodontists and general dentists. The complex and inaccessible nature of the root canal system causes 65% of root canal fillings to fail. Expandable dental sealers used during root canal treatments provide an effective solution by filling the gaps in the canal space by preventing leakage, enabling clinicians to perform the procedure with greater ease and accuracy. This project?s commercial impact includes an addressable market of 22.3 million root canal treatments annually. The proposed innovation supports enhanced patient safety, reduced time at the dentists'/endodontists' office and decreased costs for patients, reduced risk of infection and retreatment, and advanced capabilities of clinicians through training.
This Small Business Technology Transfer (STTR) Phase I project will characterize the expansion and other properties of the patented elastomeric polyurethane sealer (EPS). The project will begin by generating a functionalized and optimized formula of the EPS using additive ingredients. The team will perform in vitro testing to evaluate the material?s physicochemical properties. Finally, the study will establish the in vivo histocompatibility of EPS using animal models and check its cytotoxicity, a key hurdle that must be overcome before clinical evaluation and Food and Drug Administration (FDA) registration. These studies will facilitate the development of an entirely new type of dental sealer.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Agile RF Systems LLC
SBIR Phase I: Multiple input multiple output (MIMO) radar processing module for significantly enhanced detection of severe weather and disaster management
Contact
4316 BEVERLY DR
Berthoud, CO 80513--7953
NSF Award
2313223 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project is to design novel technologies for accurate and fast weather updates for severe weather surveillance using small radars. The technology increases accuracy with faster update rates and also has advantages in terms of decreased power consumption, size, and weight. Small and large airports may benefit from higher accuracy wind shear detection phenomena enabled by the proposed radar processing. Equipped with better spatial resolution and faster updates, these radars and the phased array technology can provide information about rapidly evolving weather conditions in a timely manner to the airport staff and warn the pilots before storms or other adverse conditions affect the planes. Some of the potentially dangerous and short-lived weather conditions, such as wind shear in the airport area, can be detected with better spatial resolution and faster updates to warn the pilots to avoid specific routes. Municipalities can use these small radars for severe weather warnings and aid in rapid assessment of hail damage. By deploying small radar networks with data services, media will have access to real time events to share with the public and gain a more complete knowledge of weather phenomena.
This Small Business Innovation Research Phase I project will develop and demonstrate multiple input multiple output (MIMO) radar for significantly enhanced detection of severe weather events such as tornados, hail, and wind shear by small radars. During Phase I, algorithms will be developed, simulated, and implemented in the existing four channel software defined radar. These algorithms will first be evaluated by simulation to assess performance and optimize the multiple input and output parameters. The optimized parameters will be implemented and compared to data collections using the single input single output mode. The high-level system radar parameters of the portable weather radar developed by the team will be utilized. The optimized MIMO parameters will be implemented and the portable weather radar (PWR), or a very similar prototype, will be used to collect data in single input single output (SISO) mode and compared to data collections using the MIMO mode. The collected data will be post processed to quantify performance benefits of the MIMO collection mode. A variety of weather types will be encountered and analyzed during planned efforts to contrast and compare performance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Amplified Sciences, LLC
SBIR Phase I: Development of a SERS-based diagnostic platform for multiplexing ubiquitous inflammatory markers in cancer.
Contact
1281 WIN HENTSCHEL BLVD
West Lafayette, IN 47906--4331
NSF Award
2348543 – SBIR Phase I
Award amount to date
$274,750
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project stems from the fact that cancer causes approximately 10 million deaths yearly worldwide, and the economic burden on cancer patients in the United States alone is estimated to be around $21 billion/yr, excluding lost productivity. Over 600,000 people die from cancer in the United States each year, and cancer cases among the younger population are on the rise. Currently, only a handful of cancers, such as breast, colon, cervical, and prostate, have recommended early screening, and sadly, 70% of cancer deaths are caused by cancers without recommended screening. Early detection, coupled with accurate monitoring and surgery in appropriate cases, appears to be the ideal strategy to improve outcomes and quality of life and reduce healthcare costs. The availability of novel diagnostic technology for minimally invasive biomarker analysis using biofluids to accurately predict malignancy potential would greatly benefit patients and clinicians in the early diagnosis and management of deadly cancers. Development of the technology proposed herein would have a broad impact on the cancer diagnostic space in terms of accurate early detection and diagnosis, quality of life, mortality, and healthcare burden.
This Small Business Innovation Research (SBIR) Phase I project aims to develop multi-marker diagnostic assays to bridge a critical gap from biomarker discovery to diagnostic assay translation. This project leverages principles from synthetic chemistry, enzymology, spectroscopy, and engineering, leading to a novel biosensing platform that couples Surface-Enhanced Raman Spectroscopy (SERS) and a protease turnover assay to provide highly accurate methods for biomarker detection. This project will lead to developing next-generation sensors to meet the unique requirements for a multi-molecular protease activity assay from highly viscous, proteinaceous clinical samples and deliver a stackable assay workflow readily accessible to clinical laboratory staff with rapid turnaround. The technological hurdles that will be addressed during Phase I will include: 1) synthetic development of ultrasensitive SERS-active dyes and their conjugates with substrates of proteases associated with high-grade dysplasia in pancreatic cysts and other cancers, and 2) development and optimization of a multiplexed multi-protease turnover assay employing the aforementioned substrates using an automated-SERS detection platform with high-throughput capability for eventual commercialization in a CLIA lab setting. This technology has the potential to be transformative due to its multiplexing capability, high sensitivity and selectivity, cost-effectiveness, and reliable performance in complex biological fluids.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ArchDia LLC
SBIR Phase I: Value-Driven Design Debt Management for Contemporary Software Systems
Contact
173 VILLAGE DR
Cranberry Township, PA 16066--3349
NSF Award
2236824 – SBIR Phase I
Award amount to date
$274,894
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will design a value-driven design debt management system applicable to modern, distributed, dynamic software systems. This system will pinpoint and quantify design debt and recommend the most e?ective debt-reduction strategies. This system will also support risk analyses for managers and designers, helping them choose a strategy that prevents severe decay in product performance, and maximize product value, productivity, and quality.
This Small Business Innovation Research (SBIR) Phase I project provide a value-driven, design-debt management system that (1) discovers and empirically validates design debt in modern distributed and dynamically-typed software systems based on options theory, Conway's law, and design principles, leveraging a knowledge graph to capture and manage implicit, heterogeneous, and distributed entities and relations; (2) discovers the intrinsic and implicit relations among multiple design anti-patterns and creates an algorithm to prioritize and recommend the most effective debt-reduction strategies; and (3) bridges the gap between development and management, enabling a user to simulate refactoring outcomes and evaluate their economic implications by combining Monte Carlo simulation and Datar-Mathews option valuations, for each proposed refactoring strategy. The outcome of these research and development activities will lead to the first framework specialized for managing technical debt at the design and architecture level, rooted in financial and design theory, and applicable to modern distributed and dynamically typed software systems. This project has the potential to fundamentally change the management of software, supporting better informed, data driven decisions by focusing on their economic values.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BACTRIA PHARMACEUTICALS LLC
SBIR Phase I: Combating Multi-Drug Resistant Gram-negative Healthcare-Associated Infections
Contact
820 PEAKVIEW RD
Boulder, CO 80302--9472
NSF Award
2310453 – SBIR Phase I
Award amount to date
$274,937
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop therapeutic drugs that restore antibiotic sensitivity in bacteria that cause severe infections in patients that are hospitalized or receiving healthcare for another condition. Antibiotics are paramount to modern medicine. In addition to treating infections and controlling their spread, these drugs enable safe surgeris, facilitate childbirth, and provide treatments for diseases such as cancer. However, as microbes evolve and develop resistance, these life-saving drugs are losing effectiveness. Eleven potent and specific small molecules have been identified that restore antibiotic sensitivity in these bacteria. Bloodstream infections and ventilator-associated pneumonia caused by Gram-negative bacteria are two severe healthcare associated infections that despite current treatments cause significant excess mortality (150 deaths/1,000 patients), longer hospital stays, and incremental costs estimated at nearly $50,000 per patient. Developing therapeutics that restore the sensitivity of Multi-Drug Resistant (MDR) Gram-negative pathogens to commonly used, well tolerated antibiotics addresses a major unmet medical need and would be transformative for patients and physicians.
This project involves developing small molecules to restore the sensitivity of Multi-Drug Resistant (MDR) Gram-negative bacteria to commonly used, well tolerated antibiotics. The role of bacterial efflux pumps in MDR Gram-negative bacteria is well documented. These pumps are virulence determinants essential for infection, and by exporting antibiotics across the bacterial cell envelope they play a key role in antibiotic resistance. Eleven potent and specific small molecule inhibitors of bacterial efflux pumps (EPIs) have been identified. These EPIs are in early-stage lead optimization and this project involves three foundational assays: cryo-electron microscopy (cryo-EM), membrane permeability, and in vitro antibiotic combination assays, followed by in vitro characterization, safety pharmacology, and liability screening. Cryo-EM provides insight into the mechanism of action and binding of these EPIs to the efflux pump, enabling in-silico docking studies and the design of new analogs. Some prior EPI research failed due to membrane permeabilization, a property that can result in apparent in vitro efficacy. Cryo-EM data together with results from in vitro efficacy and membrane permeability assays allows early deselection of poor-quality compounds, focusing screening studies on the most promising EPIs. This project may provide insights into links between MDR, persister cells, and virulence in Gram-negative pathogens.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BANYU CARBON INC
SBIR Phase I: CAS: A light-based, energy-generating, carbon removal process
Contact
4000 MASON ROAD FLUKE HALL 304
Seattle, WA 98195--0001
NSF Award
2335596 – SBIR Phase I
Award amount to date
$274,094
Start / end date
01/15/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project includes reducing the amount of greenhouse gases in the atmosphere and sequestering them permanently or reusing them to make sustainable chemicals. The Intergovernmental Panel on Climate Change (IPCC), the world?s most authoritative body of climate scientists and policymakers, has declared that billions of tons of carbon dioxide must be removed from the atmosphere annually by 2050 to prevent global temperatures from exceeding 1.5°C above pre-industrial levels, avoiding the worst impacts of climate change. If successful, this research would provide a path to gigaton-scale carbon removal. The low energy requirements of the process could allow for deployment in locations distant from large energy infrastructure to bring the benefits and jobs of a new carbon removal industry to communities most affected by weather related events.
This project will commercialize a fundamentally new approach to carbon removal. The vast amount of carbon dioxide locked in seawater remains dissolved if it stays near neutral pH, but outgases spontaneously when acidified. This process uses a light-triggered reversible photoacid as a low-energy means to temporarily acidify seawater and drive out carbon dioxide, which can then be stored or used in industry. The proprietary photoacid at the heart of the process changes its structural conformation when exposed to visible light and releases a proton. The resulting increase in acidity upon illumination provides the proton driving force for carbon capture. Sunlight not absorbed by the photoacid can be used to generate electricity with embedded polysilicon solar cells. Two aspects of the system need to be improved for the process to be deployed at scale. The photoacid?s resistance to degradation needs to be increased or a simple and scalable process to recover the degraded photoacid needs to be demonstrated. In addition, the ion exchange membranes used in the initial lab prototype are expensive and need to be replaced with cheaper and higher flux membranes. If successful, these developments would lead to a scalable and affordable carbon removal process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BEEKEEPING 101 LLC
STTR Phase I: A Novel Biorational Approach to Curing Honey Bees
Contact
2990 POSSUM RUN RD
Mansfield, OH 44903--7555
NSF Award
2152247 – STTR Phase I
Award amount to date
$274,000
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to enhance honey bee health and hence crop production through the development of a biological treatment for Varroa destructor mite, the greatest single cause of honey bee decline. All honey bee colonies in the U.S. (>2.5 million) are infested with parasitic Varroa destructor mites which cause devastating colony loss due to the impact of the mite itself as well as the transfer of microbial diseases it carries. Currently, both commercial and hobbyist beekeepers must decide between losing a colony now to Varroa destructor infestation, or later to consequent pesticide effects. Bringing a safe and effective new biological-based product to the market will lower beekeeper?s annual spending as well as time and effort to keep their colonies alive by leaving honey bee colonies free from the devastating downstream effects of traditional pesticides. In addition, the solution paves the way for more biologicals to be developed and commercialized through the novel scientific approach and technological advancement proposed herein, essentially reducing the perceived risk.
The proposed project seeks to bring to market a novel, biorational, scientific approach in pesticide management of Varroa destructor mite infestation. This biorational pesticide is designed to target a little bug (the mite) that lives on a big bug (the honey bee) without harming the bee. No pesticide has previously taken the biorational approach described herein, thus a variety of experiments are necessary to optimize manufacturing and administration methods as well as provide proof of concept prior to bringing this product to market. The specific aims include: 1) the development of efficient and cost-effective mass production methods through empirical testing of varying growth conditions, 2) testing of various administration methods, including, but not limited to, liquid- and powder-based methods that are scalable and end-user friendly for three different groups of beekeepers (commercial, sideline, and hobbyist honey beekeepers), and 3) additional mode of action experiments to solidify the ?proof of concept? of the novel technological advancement, including an in-depth examination of the effect on honey bee heath. This technology will include developing administration methods suitable for warehouses containing hundreds of colonies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BEIROBOTICS LLC
SBIR Phase I: Unmanned Aerial Payload Systems for Live-line Access
Contact
1717 E CARY ST
Richmond, VA 23223-
NSF Award
2136680 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Phase I project is the potential use of Unmanned Aerial Systems (UAS) applications in performing inspections and repairs on a variety of live transmission equipment without the need for manned helicopter or bucket truck crews, reducing the time linemen are in harm?s way. The cost of transmission grid inspections and maintenance may decrease, leading to more frequent routine inspection and more timely and proactive inspections of infrastructure with potential for failure. Transmission grid operators may have a more resilient grids with lower losses thanks to increased and improved data from frequent inspections. The American people can potentially benefit from a more resilient grid with fewer outages and more consistent delivery of electricity. Fewer line losses conserve energy and reduce the amount of fossil fuels burned to generate electricity locally.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop Unmanned Aerial Systems (UAS) inspection capabilities enabling access to utility infrastructure unreachable and/or difficult to reach by current methods. Inspection, maintenance, repair, and auditing processes for electrical utility infrastructure are costly and hazardous to personnel. Current UAS-mounted payload technology has demonstrated initial success with inspecting connectors by approaching horizontally-arranged transmission conductor sets from above. Vertically-arranged conductors that cannot be approached from above represent a significant portion of transmission infrastructure. The project?s research seeks develop UAS payload system technology that delivers linemen?s tools to vertically-arranged, high voltage transmission infrastructure by approaching from the side and from below. To accomplish this research, new approach methods will be designed, engineered, constructed, and rigorously tested in de-energized and live environments to prove viability. Completing the research objectives of the project may establish commercial feasibility for the next generation of UAS payload technology in the electrical utility sector, paving the way for a safer and more efficient national electrical grid.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BETAFELD LLC
SBIR Phase I: CAS: Upcycling Farm-level Food Waste to Accelerate the Transition to a Circular Economy
Contact
245 FIRST STREET
Cambridge, MA 02142--1200
NSF Award
2335238 – SBIR Phase I
Award amount to date
$274,999
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project facilitates the upcycling of farm-level food waste using an innovative technological platform to connect farmers and buyers. Of the more than one hundred million tons of U.S. food waste generated yearly, an estimated twenty percent is comprised of fresh fruits and vegetables wasted at the farm level due to surplus or because the produce does not meet stringent aesthetic sales standards. This project connects farmers to additional buyers for whom aesthetics is not relevant, providing them with lower-cost materials and creating a circular supply chain. This reduction in food going to landfills will decrease methane emissions from landfills. Positive environmental impacts will also be discernible in the communities surrounding landfills through cleaner air, lessened water and soil contamination, and improved human health. As aesthetically imperfect and surplus fruits and vegetables enter the food supply chain, more affordable food will be available, combating food insecurity and promoting social fairness.
This SBIR Phase I project combines artificial intelligence and a powerful prescriptive analytics engine to build an innovative solution for mitigating farm-level food waste. The project?s primary innovation is creating a material valorization database for customers to access known and new alternative uses for food waste. Verification of saleable produce images will protect customer liability and improve material traceability. Novel custom decomposition optimization will account for produce aging, storage parameters, shipping schedules and consolidation, and transportation logistics to address farm-level supply chain challenges and optimize operations. Carbon-equivalent emissions reductions will also be available for each transaction. Beyond these features, obstacles such as service outages from high customer traffic and poor potential performance from neural networks will also be addressed. The project will address the complexity of large-scale transactions in optimizing farms, buyers, and operation logistics, providing a powerful, vital tool for achieving a circular economy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIODEVEK INC
SBIR Phase I: Sprayable hydrogel sealant for gastrointestinal wound protection
Contact
127 WESTERN AVE
Allston, MA 02134--1008
NSF Award
2335845 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 06/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project centers on improving wound closure methods in minimally invasive procedures, such as endoscopy and robotic surgery. By harnessing innovative hydrogel technology based on biocompatible, biodegradable polymers, this project aims to establish a resilient barrier over surgical wounds and perforations. This transformative approach, devoid of cumbersome metal clips, promises to avert delayed bleeding, perforations, infections, and post-procedural complications. Initially designed for the gastrointestinal tract, the technology caters to unmet clinical needs, extending to applications in cardiovascular and lung sealing. The societal impact is evident in improved patient outcomes and reduced healthcare costs, while the commercial potential includes widespread adoption of a superior wound closure solution.
This Small Business Innovation Research (SBIR) Phase I project focuses on the development of a versatile, sprayable sealant kit that delivers prolonged protection for gastrointestinal wounds. Employing multiple adhesion mechanisms, the technology ensures sustained adhesion across biological surfaces. Delivered via a catheter, it seamlessly integrates with commercial endoscopes and minimally invasive devices, optimizing surgical workflow. The project objectives involve the refinement of the adhesive formulation to meet gastrointestinal requirements and rigorous comparative testing. Anticipated technical outcomes encompass enhanced procedure efficiency, reduced complication rates, and improved wound healing, positioning this innovation as a transformative force in minimally invasive surgery.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOLATTICE, LLC
SBIR Phase I: Corneal Tissue Restoration with Engineered Tissue
Contact
3401 MARKET ST STE 200
Philadelphia, PA 19104--3358
NSF Award
2342532 – SBIR Phase I
Award amount to date
$274,416
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project includes reduces the financial burden of cornea blindness and advances the medical device manufacturing industry in the US. Vision loss costs communities in lost wages and medical expenses. In 2018, the combined cost for blindness and MSVI (moderate and severe vision impairment) was $55.51 billion in North America. By providing a treatment for cornea blindness equivalent to s donor cornea, this innovation would help restore the vision of patients affected by corneal blindness, improve their ability to contribute to society, and lower the burden on their caretakers. In addition, by contributing to the general process of tissue engineering, the engineered cornea will help foster research in the field of alternatives to donor tissues, which will contribute to the well-being of individuals in society as a whole. The development of engineered cornea would also help advance the position of the US in the cornea replacement material field and more generally in the engineered tissue research field and could result in growth opportunities in the medical device manufacturing industry, therefore increasing US competitiveness.
This Small Business Innovation Research (SBIR) Phase I project creates a novel acellular polymer membrane for use as a cornea substitute. The artificial cornea will differentiate itself from other artificial cornea options by offering a true alternative to donor cornea for full thickness cornea replacement (also known as penetrating keratoplasty). The artificial cornea will consist of a crosslinked polymer membrane that will provide biocompatibility with ocular tissues and suturability similar to a donor cornea. In addition, specific surface modifications will be added to the membrane to maintain its optical clarity, by preventing the adhesion of environmental and biological contaminants. These modifications will enable secure integration into the patient?s eye. The new materials will be aesthetically equivalent to existing donor cornea. By contrast to current artificial cornea options, the artificial cornea aims to provide a true replacement to donor cornea that can be used as a standard of care treatment for full thickness cornea replacement, without the risks generally associated with donor cornea tissue and without the need for refrigeration or complicated transport logistics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOSUPERIOR TECHNOLOGY, INC.
STTR Phase I: Bioengineering lung surfactant for the treatment of respiratory disease
Contact
1731 PENNY WAY
Los Altos, CA 94024--6234
NSF Award
2210373 – STTR Phase I
Award amount to date
$255,987
Start / end date
06/15/2022 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop a synthetic lung surfactant product for the potential treatment of serious respiratory illnesses in neonatal patients. Bronchopulmonary dysplasia affects 10,000-15,000 pre-term infants per year and has a high mortality rate. Exposure of immature lung tissue to air results in inflammation and damages lungs and airways. Decreasing bronchopulmonary dysplasia is anticipated to reduce the number of days infants spend in the hospital, the need for supplemental oxygen, and other burdens on the healthcare system. The average length of stay in the neonatal intensive care unit for an infant with bronchopulmonary dysplasia is currently 103 days.
This Small Business Technology Transfer (STTR) Phase I project may result in the formulation of synthetic proteins for a bioengineered lung surfactant that contains full-length critical phospholipids and anti-inflammatory agents. Currently, bioengineered pulmonary surfactants are not as effective as animal-derived pulmonary surfactants for the treatment of illnesses related to bronchopulmonary dysplasia such as neonatal respiratory distress syndrome. The synthesis of full-length, native surfactant proteins has yet to be achieved. This research seeks to synthesize proteins which may add significant viscoelasticity to the pulmonary surfactant. The protein will be combined with major surfactant phospholipids and anti-inflammatory therapeutics at defined ratios to potentially generate fully-synthetic pulmonary surfactant preparations with anti-inflammatory properties. These surfactant formulations will be screened in vitro and in vivo using a neonatal rat hyperoxia model of bronchopulmonary dysplasia.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOTRONIC INNOVATIONS LLC
SBIR Phase I: Path Planning for Multi-target Search and Localization in Co-Robotic Architectures
Contact
303 W FIR AVE
Flagstaff, AZ 86001--1385
NSF Award
2325364 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is a high-performance, drone-based, wildlife telemetry technology that is economical and easy to use. Its improved performance and significantly lower cost than existing competitive technologies will empower users with greater capability and lower the barrier to entry for field data collection. This technology will enable researchers to better understand the complex effects of geography, climate, interspecies competition, invasive species, and land use policy on animals and their habitats.
This project will enable a co-robotic system that employs an unmanned aerial vehicle (UAV) as an assistant wildlife tracker. By fusing data from the UAV and the knowledge and insights of the human tracker, the team will greatly increase the capability of these systems to track a larger number of animals, to increase the frequency of tracking campaigns, and to improve the ease of use. This research will develop and refine a new class of machine learning algorithms for wildlife localization. As the UAV platform executes its mission, the human tracker can monitor its progress and plans, and intervene at any time with commands to re-direct the UAV. The research plan tackles the key challenges in this problem domain, including safety of UAV operation and the possible effects of noise emissions. Based on the identification of key risks and mitigation strategies, the research plan executes multiple rapid iterations of a develop-simulate-deploy-test design process within a set of tasks that tackle increasingly complex localization scenarios.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BLOOM SURGICAL, INC.
SBIR Phase I: Optimization of a Novel Compliant Mechanisms-Based Laparoscope Cleaning Device
Contact
10472 EDINBURG DR.
Highland, UT 84003--9584
NSF Award
2213695 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel product for ensuring proper visualization through intraoperative scopes during laparoscopic procedures. Worldwide, 13 million laparoscopic surgeries are performed each year. Surgeons require proper visualization of the operating site which entails continually wiping the lens, reinserting the scope, relocating the surgical site, and then resuming the surgery. This difficulty in visualization results in the need to temporarily halt the operation and potentially lose critical focus of the surgical area in order to restore the surgical field of view. Surgeons repeat this process an average of six times per hour, accounting for nearly 1/3 of the operating time. This time delay results in an estimated loss of 336,000 hours of operating room procedure time and $1.25 billion in productivity losses in the United States alone each year.
This SBIR Phase 1 project will develop operating prototypes of a novel, flexible, micro-mechanical mechanism with multiple degrees of freedom. The device integrates flexible and conforming mechanisms with a wiping blade to enable real time wiping of surgical scopes and ports. This technology enables surgeons to quickly and intraoperatively re-enable laparoscope vision within the patient. The technical challenges of the project include the development of a computational engineering model that optimizes user control of off-axis stiffness, force response, and stress. The team will also need to ensure the solution has sufficient fatigue life and predictable mechanical response throughout the duration of the procedure. Computational engineering models will be used to design and develop several manufacturable prototypes, which will be tested and validated with several currently available laparoscopes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BRAVE VIRTUAL WORLDS, INC.
SBIR Phase I: Brave Virtual Worlds Human Movement Artificial Intelligence (AI) Engine and Biofeedback Loop
Contact
800 BRAZOS ST
Austin, TX 78701--2538
NSF Award
2326586 – SBIR Phase I
Award amount to date
$273,915
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to develop a biofeedback system that combines wearable sensors, real-time data capture, and immersive virtual reality visualization. This system has the potential to enhance the understanding of joint angles and movement patterns enabling in-depth analysis of human movement. The proposed technology targets a significant market opportunity in the athletic training and physical therapy industry, which is valued at $200 million.
This SBIR Phase I project addresses intellectual merit through a systematic research approach. The project involves designing and refining the biofeedback system, conducting extensive data collection, and implementing advanced algorithms for real-time analysis. The project's goals include developing a user-friendly interface, optimizing sensor accuracy, and creating a seamless biofeedback system for improved training and rehabilitation. Anticipated technical results include the design and development of a machine learning layer to classify and identify key components of movements in order to create a contextual database for further analysis to determine movement efficiency and highlight movement patterns as well as the development of a corrective exercise/feedback layer using the context from the machine learning layer to generate further insights into what is causing highlighted movement patterns This second later will incorporate corrective exercises that are suggested for improvement. Additionally, a real-time layer incorporating the first two layers into the real-time portion will be used for immediate feedback to the end-user, thus providing a closed bio-feedback loop.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CABRERA RESEARCH LAB LLC
SBIR Phase I: Thinkquery: Empowering People to Thrive in a Complex World
Contact
450 E MILLER RD
Ithaca, NY 14850--9435
NSF Award
2335521 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project empowers individuals with enhanced cognitive skills essential for success and innovation in the modern world. In today's global economy, the ability to think critically and creatively is crucial, but many people face developmental hurdles that hinder their economic competitiveness. Unlike existing cognitive tools, this innovation offers a user-friendly, chat-based approach that leverages each individual's language skills to cultivate transferable thinking abilities. The solution guides users through a systematic problem-solving process, helping them map their mental models, fostering metacognition, and enabling them to challenge assumptions and biases. Ultimately, the technology equips users to better comprehend and address a wide range of challenges. This project's primary aim is to support the diverse and underserved populations enrolled in community colleges. The technology enables students to learn at their own pace, break down developmental courses into shorter modules, and tailor content to align with their specific career aspirations. This adaptability and accessibility have the potential to transform education, providing a flexible and effective learning tool for a wide audience. The team addresses a pressing societal need for improved cognitive skills, enhancing not only individual prospects but also contributing to the nation's economic vitality.
This Small Business Innovation Research (SBIR) Phase I project focuses on enabling individuals to effectively navigate complex challenges in the 21st century by leveraging the Distinctions, Systems, Relationships, and Perspectives (DSRP) Theory within a machine-interpretable data structure integrated into a visual-structural recommender system. The technical objective is to empower users with a tool that facilitates in-depth exploration and understanding of various problems and topics. The project's key components develop algorithms that incorporate DSRP theory and Artificial Intelligence (AI)/Machine Learning (ML) techniques to create collaborative filtering and content-based filtering for generating user-specific questions. The solution creates a comprehensive reporting schema, coding, and statistical tools to validate empirical measures for different usage scenarios. The team also defines use case conditions and user experience design parameters to enhance the effectiveness of the technology. Initially, this project targets diverse, underserved, and disadvantaged students in developmental education programs who often struggle with college-level coursework. The innovation's accessibility, driven by the use of everyday language as inputs, makes it a commercially viable cognitive skills training technology with reduced friction and greater user-friendliness compared to existing solutions. The technology addresses both technical challenges and educational barriers associated with mind-mapping technologies, promising a significant impact on learning and problem-solving capabilities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CALI'S BOOKS, LLC
SBIR Phase I: Novel device to enhance the traditional paper book reading experience for young children
Contact
1419 MURRAY DR
Los Angeles, CA 90026--2113
NSF Award
2323385 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of an innovative, screenless, interactive educational device for early childhood education. The project will bring to market a book-like device that delivers audio content when the pages are pressed, establishing the viability of delivering mixed-media interactive content in science, technology, engineering, and mathematics for children from kindergarten to second grade. By performing a scientific study of how children engage with content on the device relative to the same content in paper and tablet form, this project seeks to prove the benefits of alternative, screenless, interactive learning. The project leverages fundamental educational science. It also has the potential to improve public scientific literacy and engagement with science and technology in the United States while offering important health benefits by reducing screen addiction in young children. Excessive screen time has been linked to a range of negative health outcomes, including increased risk of obesity, decreased sleep quality, and impaired social and emotional development. The project has the potential to generate significant revenue by commercializing the device both directly to consumers and through partnerships with schools.
This project will see the development of an innovative, screenless learning tool for young children, by seamlessly integrating technology into a traditional book format. The proposed platform consists of three major components: a book cover that houses swappable book inserts, embedded electronics that play audio in response to a page touch, and software that powers interactions and connectivity. A microcontroller recognizes an inserted paper book and offers a personalized interactive experience using content stored on the device. Button icons printed on the book pages line up precisely with a physical button grid embedded in the device, supporting learning activities. The success of this project requires the development of three hardware components and three software components that seamlessly work together in a connected ecosystem. The research and development team focuses on developing a workable device that can be brought to market and sold to customers, releasing an initial story-based content library, and conducting a user-testing study to learn about how children engage with the device relative to screen-based alternatives.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CAMBRIDGE TERAHERTZ INC
SBIR Phase I: Terahertz Imaging Radar for Law Enforcement
Contact
162 BROOKLINE ST
Cambridge, MA 02139--4540
NSF Award
2301538 – SBIR Phase I
Award amount to date
$274,927
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will improve public safety by furthering terahertz radar imaging technology for concealed threat detection. With increasing cases of weapons violence and mass casualty events across the nation, and an increase in the difficulty of detecting non-metallic weapons such as 3D-printed firearms and ceramic knives, a significant gap exists in threat detection technologies. This solution addresses a recognized need in an approximately $2 billion market which includes law enforcement and event venue security. Existing approaches (such as airport scanners and walkthrough metal detectors) are expensive, intrusive, and inconvenient or leave large gaps in detection capability. Terahertz radar imaging promises the performance of gold-standard airport scanners in a consumer grade, portable, and discreet device. By demonstrating a terahertz radar transceiver, this Phase I effort will de-risk a key technical element of this technology, which is critical for security applications and beyond. If successful, this project represents a significant step forward in addressing society?s concealed threat detection issues.
The intellectual merit of this project revolves around the design, implementation, fabrication and testing of a terahertz radar transceiver, a key component in the approach used in a personnel screening device. No such transceiver is currently available to purchase on the open market, let alone at the costs and volumes required for the proposed commercial applications. When paired with other elements of the imaging system, the result will be a three-dimensional radar imager which is capable of ?seeing through? dielectric materials such as fabrics and detecting concealed weapons and contraband, both metallic and non-metallic. The transceiver design effort will feature development of components such as frequency multipliers, amplifiers and mixers, and their electrical, mechanical, and thermal integration into a larger imaging system. This design phase will prioritize achieving cost, yield, and scalability metrics compatible with mass manufacture and widespread deployment. Key considerations involved in this effort are the signal-to-noise ratio (SNR) and Dynamic Range (DR) of the system, both important metrics in imaging performance and therefore weapons detection capability. The project leverages recent advances in terahertz integrated circuit technology. The anticipated result is the experimental demonstration of such a component for integration into the fully functional imaging systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CAPORUS TECHNOLOGIES, LLC
STTR Phase I: Electrode Materials and Processes for Atmospheric Pressure, Continuous Manufacturing of Multi-Layer Capacitors
Contact
14001 STONEGATE LN
Orland Park, IL 60467--7604
NSF Award
2151712 – STTR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to improve capacitor technology in power conversion equipment used to electrify our transportation systems. Capacitors are critical components to the systems needed to accelerate the energy transition from petroleum to other fuels. This project will develop new electrical materials and production processes for capacitors. The new electrical materials are formulated to be less hazardous to humans and the environmental while also being compatible with more efficient manufacturing processes. Benefits of the proposed technology include faster charging rates of electric vehicles and reduced sizes of on-board batteries, which lowers the cost and environmental impact of electric vehicle manufacturing. Reduced costs will allow a broader population access to electric vehicles. Through development of these new electrode materials and processes, manufacturing of capacitors in the United States will be available to serve the growing US electric vehicle industry.
This goal of the proposed work is to develop electrode materials and roll-to-roll processes compatible with an integrated, continuous manufacturing process for multilayer capacitor products. By combining additive manufacturing process in a roll-to-roll system, sequential deposition, drying, and curing of alternating layers of dielectrics and electrodes will enable production of multilayer capacitors in a single system at atmospheric pressure. Electrode inks and printing processes used in flexible/hybrid electronics do not meet the specifications to replace vacuum-based evaporation or sputtering of thin electrode layers for capacitor applications. The primary approach will be based on adapting the layer coating and alignment techniques developed for dielectrics to conductive materials. These electrode materials will improve upon state-of-the-art conductive inks with poor interfaces between particles to produce dense layers with uniform thickness and low surface roughness. This project seeks to provide prototyping of multilayer capacitors produced in discrete processing steps for verification of electrical performance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARBIDE RADIO INC
SBIR Phase I: Silicon Carbide Radio Frequency Switches
Contact
6301 LILLIAN WAY
San Jose, CA 95120--1817
NSF Award
2334387 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project focuses on wireless communication technolog, specifically the development of a special semiconductor known as silicon carbide (SiC), which has the potential to revolutionize the industry. Unlike traditional semiconductors, SiC can operate at much higher power levels and in harsh environments, making it ideal for wireless communication devices. Currently, the industry predominantly relies on gallium nitride (GaN) semiconductors, which are not only rare but also mostly imported, raising national security concerns. By demonstrating that SiC can match or even surpass the performance of GaN in radio frequency (RF) applications, this project aims to pave the way for a robust SiC RF semiconductor industry within the United States (U.S.). The RF switch market alone is estimated to be worth $2 billion by 2024. A successful SiC RF switch product would not only capture a significant share of this market but also establish the U.S, as a leader in RF semiconductor technology. The project has the potential to create jobs, foster innovation within the domestic semiconductor industry, and enhance national security by reducing reliance on foreign-produced semiconductor materials.
This Small Business Innovation Research (SBIR) Phase I project will produce commercially competitive RF switches made from SiC. The RF switches are intended for use in sub-6 GHz cellular infrastructure applications, such as base stations, where high power and ruggedness are difficult to achieve in conventional silicon-based technologies. SiC and, more specifically, SiC metal-oxide-semiconductor field-effect transistors (MOSFETs), have gained significant market share in the electric vehicle industry. In contrast, SiC MOSFETs are essentially non-existent in the RF industry. The main reasons are poor mobility, resulting in high on-state resistance, and high off-state capacitance. For an RF switch, the product on-state resistance and off-state capacitance are critical specifications, with lower numbers being better. This project develops two semiconductor innovations to reduce these factors while handling high power levels. Research focuses on developing the semiconductor fabrication processes to produce an RF switch integrated circuit product that is competitive with existing high power RF switches, such as those made from GaN having insertion losses less than 0.8 dB up to 6 GHz, isolation of around 20 dB, and handling high peak RF power levels of 50 dBm/100 W.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARRTECH LLC
SBIR Phase I: Filter Removal of Glass - A better way of filtering injectables
Contact
4539 METROPOLITAN CT
Frederick, MD 21704--9452
NSF Award
2232923 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business innovation Research (SBIR) Phase I project is an integrated, single needle filter which removes glass shards from injectable fluids. Liquid pharmaceuticals and medications are often stored in glass ampoules. To gain access to these medications, each ampoule is manually broken at the neck by a health care provider. This can result in glass shards entering the medication that can cause patient hematomas and/or internal bleeding. United States regulations currently mandate all ampoules must be filtered by health care providers prior to injection which requires a multi-step filter process using multiple needles and needle exchanges. This project aims to develop a single, effective, inline filter which that requires half the time of this current process, while improving safety for the patient and the healthcare worker by reducing the risks of needle stick injuries. The commercial potential is to become the standard of care for the $3 billion global filter market and consumes over six billion disposable glass ampoules every year.
This Small Business Innovation research (SBIR) Phase I project is a novel, disposable, inline, mechanical filter with optimal porosity and density to remove glass ampoule shards. The current practice of breaking ampules at their neck to access medication results in shards that are currently manually filtered using a filter needle prior to administration into the patient. The filter needle must be removed and discarded, and a second sterile needle placed on the syringe for injection. The company aims to develop a novel, all-in-one, integrated filter and needle system utilizing a single inner blunt needle with a novel filter located at the distal end versus the current proximal end where the Luer loc is located. This solution will enable a single step process for glass filtering and medication injection. The scope of activities includes engineering and validation tests of leakage, pull force, dead volume, labeling and packaging, handling safety, repeatability/consistency, and accelerated aging of the company?s proprietary design concepts. This project aims to provide an assembly suitable for human use that is manufacturable at scale in a cost-effective manner.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CASCADE BIOCATALYSTS INC.
SBIR Phase I: Enzyme Stabilization via Immobilization for Advanced Chemical Manufacturing
Contact
4911 UMATILLA ST
Denver, CO 80221--1313
NSF Award
2320044 – SBIR Phase I
Award amount to date
$274,918
Start / end date
12/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project enables environmentally sustainable, low-carbon, chemical manufacturing with long-lasting enzymes. The chemicals industry relies heavily on unsustainable petrochemical feedstocks as well as energy and materials inefficient processes. Nature renewably produces a diverse array of chemicals and materials, including lumber from air and sunlight and lifesaving therapeutics like penicillin. Biology creates molecules through the power of enzymes ? nature?s catalysts. While some enzymes have been leveraged to produce chemicals, enzymes are typically too short lived and expensive to create scalable, cost-effective chemical manufacturing processes. This project will allow enzymes to gain more share of the $40 billion catalyst space by scaling a patent-pending approach to keep enzymes lasting longer, decreasing their costs significantly. This project will be commercialized as a high-gross margin, recurring revenue business, supporting industrial green chemistry. The first application will be the production of flavors and fragrance molecules, relatively high value molecules that are currently produced in unsustainable, polluting processes. Ultimately, this solution will extend to higher volume, lower value chemicals for larger reductions in environmental pollution. Furthermore, the innovation will contribute to the United States by on-shoring chemical manufacturing processes that left the US due to the high environmental costs.
This Small Business Innovation Research (SBIR) Phase I project will demonstrate the commercial feasibility and scalability of heterogeneous polymers to stabilize enzymes through engineered polymer-enzyme interactions. The Phase I research and development builds on the team?s prior work on enzyme stabilization in industrial chemical manufacturing and will develop ultrastable enzymes to reduce the cost of sustainable manufacturing of flavors and fragrances. While this technology has been demonstrated for several early customers at the laboratory scale, a particular focus of this project is the scale up of the manufacturing process. This manufacturing involves state-of-the-art controlled radical polymerization processes that have yet to be commercialized. Traditionally, approaches to sustainable chemical manufacturing struggle with scalability and unit costs, and therefore, this project aims to de-risk scale and cost earlier in commercialization. While this scale-up will be done earlier in commercialization, it is done in collaboration with existing customers to ensure the products at scale provide value to the companies producing fine chemicals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CELLCHORUS INC.
SBIR Phase I: Development of arrays to record dynamic interactions between single cells
Contact
5000 GULF FWY RM 118
Houston, TX 77204--0001
NSF Award
2229323 – SBIR Phase I
Award amount to date
$274,988
Start / end date
06/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to enable experts in the biomedical field to improve understanding of how new therapeutic approaches are developed and perform in the context of a complex immune system. This technology could enable new therapies to translate to patients faster, at less expense, and with higher rates of success. These therapeutics, such as antibodies, cell and gene therapies, and vaccines, can deliver excellent results when they work, but available therapies do not work for all patients. To develop and deliver the next generation of therapies to improve the lives of patients, investigators need to be able to understand how immune cells and other cells move, interact, kill, and survive over time. This project allows researchers, developers, and manufacturing experts to understand the functional performance of new therapies earlier, more completely, and at lower expense. Such single-cell analysis is a multi-billion market among commercial and non-profit markets.
The proposed project will develop and rigorously validate a novel array consumable that enables scaling dynamic, single-cell analysis from an early access laboratory to any facility worldwide. Initial design and testing activities for the next generation arrays using non-scalable proof of concept production methodologies have demonstrated the value of the dynamic single-cell functional analysis platform. This project will develop and evaluate two options for producing the arrays, one with an embossing technique and one with a three-dimensional printing technique. Successful completion of this project will support scaling the only platform that can evaluate migration, contact dynamics, killing, survival, subcellular activity, and biomolecule secretion for the same individual cell over time and in high throughput to improve development and delivery of novel therapies faster, with higher rates of success, and at lower expense.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CENSYN INC
SBIR Phase I: PenEEG: An Objective Assessment Tool for Concussion and Recovery Management
Contact
35 CASPIAN
Lake Forest, CA 92630--1468
NSF Award
2304353 – SBIR Phase I
Award amount to date
$274,970
Start / end date
11/15/2023 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a mobile and compact Electroencephalography (EEG) concussion screening and recovery monitoring tool to reduce the time needed to seek proper patient care. Each year in the US, 5.5 million mild traumatic brain injury (TBI) or concussion cases are reported with athletes disproportionately affected. Most concussion assessments rely on subjective measures but have an estimated 50% false negative rate resulting in potentially harmful return to play. Current imaging tools detect structural versus functional injuries, and existing EEG systems are not readily usable for field applications. This system aims to provide a field usable, on-demand concussion screening tool that enables patients to seek care in a more rapid manner in the event of a concussive event. It will also reduce unnecessary emergency room visits during instances of non-concussions when used in conjunction with current assessment measures. The project presents an ultra-portable solution with quantifiable concussions measures. The innovation targets the $6.8 billion concussion care market opportunity within sports injury management, military health, and hospital sectors.
This Small Business Innovation Research (SBIR) Phase I project will develop a handheld electroencephalogram (EEG) device designed to simplify data collection for long-term brain health tracking. The device is a two-channel tool that can be used at multiple locations on the head to conduct rapid, quantifiable brain assessments. The system aims to overcome the current size limitations and training required for current brain wave-measuring equipment. The size and portability of the device enables use across a variety of situations including sports events, military applications, or at home/on-base during recovery. The project aims to address two technical challenges: developing a system to guide untrained users in effectively positioning the device to collect high-quality data and developing a discriminant function to sense a series of acute brain wave signal changes in individuals over time for detecting concussions. The objective of this project is to develop a usable prototype with suitable sensitivity and specificity when compared to current diagnostic screening measures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHASCII INC
SBIR Phase I: An Interplanetary Smallsat for Fast Connectivity, Navigation, and Positioning
Contact
1879 E ALTADENA DR
Altadena, CA 91001--2146
NSF Award
2322390 – SBIR Phase I
Award amount to date
$274,548
Start / end date
03/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks to deploy a commercial space platform in cislunar and deep space to provide fast connectivity, navigation, and positioning to space users. This cislunar network will include nodes in low-Earth Orbit, Geosynchronous orbit and Lunar orbit to create a secure and covert gigabit network for scientific, commercial, and military applications. This project will develop a revolutionary spacecraft that will be the heart of the new network. This product will be a small yet nimble spacecraft that uses lasers, a novel architecture, and machine learning software to provide high-data-rate omnidirectional coverage of its surroundings. The company plans to place clusters of this satellite as network nodes. It is envisioned that space users can use these interplanetary small satellites (and their network) for gigabit connectivity as well as accurate navigation and positioning in cislunar and deep space.
This project will develop a novel small satellite with embedded optical communications systems. It will be equipped with two distinct optical communications terminals, one for long-range connectivity and the second one for short-range, swarm connectivity. The small satellite?s long-range terminal consists of six optical transceivers evenly distributed around the body of the spacecraft to provide omnidirectional coverage. The transceivers will be fully integrated into and commanded by a fast processor. The small satellite will have a coherent modulation architecture operating at around 1550 nanometers. The transmitter design to be pursued during this project includes a distributed feedback laser diode, a phase modulator, an optical amplifier, a circulator, and a collimator. All these components will be connected by optical fibers. The seed laser will produce a 10-milliwatt laser beam, which is passed through the phase modulator where it is modulated at high speeds (10-100 gigabit per second). After the modulator, the modulated beam is boosted via an optical amplifier and passed through a collimator to generate a collimated, high-power beam. The collimator launches the beam into free space and directs it to a steering mirror for coverage of its field of regard. It is envisioned that the system could achieve transmission speeds as high as 100 gigabit per second.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COGNI TRAX
SBIR Phase I: Subtractive-waveguide based Display for Augmented Reality Smart Glasses using Spatial-temporal Multiplexed Single-CMOS Panels
Contact
978 LEITH AVE
Santa Clara, CA 95054--1950
NSF Award
2335927 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the realization of Augmented Reality (AR) displays for smart glasses that can show digital content in the full dynamic range, including the black color. The conventional optical components currently used in AR smart glasses cause the digital content to appear translucent and, hence, lack realism. The proposed work is on developing a display technology that controls per-pixel transparency in the virtual image plane, virtual objects, and 3D holograms for black color. The blocking of light for black-colored parts in a hologram can show as realistic physical objects over the background reality. Using this approach, each display pixel can be made black, semi-transparent, or transparent at a user?s will, making visibility of digital content possible even in direct sun-lit environments.
This SBIR Phase I project proposes a holistic display solution for AR smart glasses that consists of three key elements: a spatially-multiplexed Total Internal Reflection?based subtractive-waveguide combiner; a single photo-reflective spatial light modulator (SLM) that is illuminated by two spatially-multiplexed illuminants; and a temporal multiplexing algorithm whereby the two spatially-multiplexed illuminants can be selectively modulated by the SLM during their dedicated sub-frame times. Since pixel-wise transparency control allows hard-edge occlusion, hence the proposed smart spatiotemporal multiplexed approach enables a single display that achieves pixel-wise hard-edge occlusion using only a single silicon display panel, thereby reducing cost and complexity while increasing see-through efficiency and battery life performance. These technological improvements are industry firsts and together allow for addressing a market need for AR devices for outdoor well-lit scenarios.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COLOWRAP, LLC
SBIR Phase I: Novel, Non-Manual Solution for Mitigating Endoscope Looping in Riskier Colonoscopies
Contact
3333 DURHAM CHAPEL HILL BLVD STE A200
Durham, NC 27707--6238
NSF Award
2129569 – SBIR Phase I
Award amount to date
$255,801
Start / end date
08/15/2021 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a functional prototype for a novel abdominal compression device that prevents endoscope looping during colonoscopy, a common complication that causes pain, procedure failure, and increased risk of bowel perforation. Looping is typically countered with manual application of external pressure to the abdomen by nurses, which is inconsistently effective and can lead to staff injury. This project proposes a novel compression device that provides a safe and effective alternative to manual abdominal pressure to improve colonoscopy outcomes.
This Small Business Innovation Research (SBIR) Phase I project will address the technical challenges associated with engineering a colonoscopy compression device addressing the deficiencies of existing devices in patients with low body mass index (BMI) and low abdominal tissue volume. This project will accomplish this by first characterizing the differences in pressure applied by existing colonoscopy compression devices in high versus low BMI patients using pressure mapping. The results of this study will be utilized to design an adjustable and re-usable insert system that can be used during colonoscopy to apply different amounts of focused pressure. A prototype device will be produced and tested for localized pressure within a pressure range optimize to prevent looping in a low-BMI patient.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CONNECTED WISE LLC
SBIR Phase I: Autonomous Warning Triangle System (aWTS) for Emergency Stopping
Contact
3251 PROGRESS DR RM 138A
Orlando, FL 32826--2931
NSF Award
2222996 – SBIR Phase I
Award amount to date
$274,553
Start / end date
06/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to ensure the secure transfer of goods and/or passengers in commercial motor vehicles (CMVs) and prevent the likelihood of secondary incidents when a commercial motor vehicles (CMV) has made an emergency stop on a highway. All CMVs need to comply with traffic safety regulations and deploy emergency warning devices (e.g., safety triangles) during an emergency stop. Without the presence of a human driver, an automated CMV should also be able to automate emergency warning device placement. Proper placement of these warning devices can be life-saving for drivers of non-automated vehicles on a highway. The proposed project will increase the safety of external drivers by preventing any secondary incidents associated with the lane/shoulder blockage due to a CMV malfunction and protect drivers of non-automated and/or semi-automated vehicles by assisting in the deployment of emergency warning triangles on highways. This project aims to remove barriers to higher-order automated technology adoption due to lack of standardization.
The project will result in the design, research, and development of an affordable, after-market, reliable, and safe autonomous Warning Triangle System (aWTS) to ensure the safety of the automated and semi-automated commercial motor vehicles (CMVs) during an emergency stop without requiring human assistance. aWTS consists of three low-cost autonomous triangle reflector devices which are planned to optimally fit in a charging dock/enclosure where they will be safely stored during stand-by mode. When activated by the emergency signal transmitted from the CMV, the autonomous triangles are designed to move successively to their pre-determined destinations on the highway. The research and development activity during this Phase I project includes, but is not limited to: reviewing safety codes and regulations, investigating different highway scenarios and associated challenges, and performing computer simulations; developing proof-of-concept hardware that can demonstrate the proposed system?s technical feasibility and its integration to automated CMVs; determining the optimal placement and assembly of the autonomous reflective triangles by collaborating with auto manufacturers; investigating the potential cyber-security risks to develop secure communications between CMV and aWTS; and identifying the operational challenges and the design targets while considering the cost of deployment, lifecycle costs, functional use, and interoperability.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COVALABIO INC.
SBIR Phase I: Cell-penetrating monobodies targeting oncogenic KRAS
Contact
7084 MIRAMAR RD STE 401
San Diego, CA 92121--2343
NSF Award
2321926 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project lies in technological development of a new pharmaceutical intervention called cell-penetrating monobodies (CPM). The validation of this new CPM intervention will be demonstrated by designing potent and selective CPM-based inhibitors targeting certain cancers. The success of this project will establish a powerful pharmaceutical technology for designing personalized therapies to treat the oncogenic mutant-driven lung, pancreatic, and colorectal cancers, where treatment options are extremely limited. This project will also enhance the academia-industry partnership, strengthen a burgeoning life science ecosystem in the Buffalo area, and develop a globally competitive STEM workforce for the Western New York region.
The proposed project addresses a critical barrier in the clinical translation of monobodies - a class of powerful tool biologics that are not cell-permeable despite their small size. The CPM technology overcomes this barrier by combining orthogonal crosslinking ? a proprietary method to rigidify monobody structure through site-specific inter-strand crosslinking - with monobody surface supercharging. As a result, the CPM technology potentially possesses several innovative features: 1) genetic modifications facilitate recombinant production of CPM in bacteria both at research scale and for manufacturing; 2) high binding affinity and specificity toward intracellular oncogene targets can be readily obtained using well-established display technologies; and 3) robust cytosolic transport efficiency can be obtained owing to the rigid scaffold and tunable surface charge. This project aims to unlock the commercial value of CPM technology by identifying potent and selective inhibitors oncogenic KRAS mutants that proved to be elusive with the small-molecule approach. Extensive optimizations of charge distribution and physicochemical properties will be performed using a reported monobody-based KRAS inhibitor as a template, with a goal to identify one CPM with sub-micromolar inhibitory activity in the KRAS mutant-harboring cell lines.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CRABLINE ROBOTICS LLC
SBIR Phase I: Crab-like Robotic Platforms for Cutting Underwater Structures
Contact
19000 SHELBURNE RD
Shaker Heights, OH 44118--4947
NSF Award
2335382 – STTR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project develops a dexterous, crab-like aquatic robot for underwater construction and decommissioning of structures. With growing efforts to develop sustainable offshore wind energy infrastructure, like wind turbines, new technologies are needed to make the management of this infrastructure safer and more efficient. Existing practices often put human divers at risk in deep, cold, turbid ocean environments while existing aquatic robots or remotely operated vehicles (ROVs) cannot adequately manipulate tools to execute construction and deconstruction work underwater. This project seeks to develop a new class of aquatic robotics that are highly dexterous, inexpensive, and capable of expanding U.S. engineering knowledge and capabilities. This new type of robotic platform is needed by offshore construction and salvage contractors to reduce costs associated with infrastructure management and to improve safety practices. This technology provides underwater robotics capable of supporting the projected growth of marine construction and offshore energy development.
This project creates a crab-like robot that utilizes multiple robotic legs to stabilize around a target and deliver a tool, such as an exothermic cutting rod, to the desired target. Inspired by living crabs and their ability to pull inward to grasp a substrate, this new robotic platform will stabilize on a substrate and trace a pre-defined tool path. Using the inward forces of legs combined with adjustable end effectors, the platform will demonstrate easy detachment and secure adhesion to a substrate at different phases of the gait cycle. Novel approaches will be developed to traverse challenging craggy, slippery, and bio-fouled marine structures in order to precisely deliver tools to targets. With legs with more actuated degrees of freedom than the six supports of a Stewart platform, the robot will still be able to stabilize if one leg cannot find purchase during walking motions. The goal in this SBIR Phase I project is to demonstrate a new type of aquatic robots capable of tool stabilization and manipulation at depth.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CRYPTO TUTORS LLC
SBIR Phase I: Interest-Based Learning Management System to Ensure University Students are Qualified to Gain Web3 Careers
Contact
4421 CALM WATER CT
Orlando, FL 32817--1432
NSF Award
2333653 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project empowers post-secondary students, especially those from Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs), to seize lucrative opportunities in the rapidly growing blockchain job market, which currently faces the trend of outsourcing. Blockchain-related careers are among the most sought-after professions of the future, yet many students lack clarity regarding the blockchain career paths suitable for their interests and abilities. This career assessment technology will bridge this knowledge gap, enhancing students' understanding of various career possibilities within the blockchain industry. By doing so, the technology aligns with the needs of both businesses and educational institutions while contributing to the national welfare by facilitating the entry of young adults into high-paying careers. This project offers a unique career matching platform that guides students from diverse academic backgrounds, including both technical and non-technical majors, toward highly skilled blockchain positions.
This Small Business Innovation Research (SBIR) Phase I project seeks to address the shortage of a skilled blockchain technology workforce in the United States, which has resulted in the outsourcing of blockchain-related jobs to other countries. The primary research objectives involve quantifying the relationship between an individual's interests and their potential suitability for blockchain-related employment while offering versatile career path recommendations. This project examines key career attributes such as creativity, risk-taking propensity, and analytical skills, aiming to identify correlations with potential blockchain roles. The research will explore the hobbies and interests of current blockchain professionals and establish a mathematical formula that aligns attributes with various job titles, as reported by hiring managers. Field testing will be conducted at HBCUs and MSIs to validate the effectiveness of the formulas and scoring system, ultimately recommending suitable web3 blockchain job titles to students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CURIEDX, LLC
SBIR Phase I: Development of a Machine Learning System to Identify Streptococcal Pharyngitis with a Smartphone Image
Contact
634 REGESTER AVE
Baltimore, MD 21212--1917
NSF Award
2304268 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the lack of instant, remote medical tests for telehealth. This project could develop an accurate machine learning-based predictive model for strep throat. The business model delivers an artificial intelligence (AI)-based clinical decision support system as a Software as a Service subscription to urgent care telehealth services. The total addressable market for all telehealth point of care tests (beyond strep throat) in urgent care and primary care is $10.4 billion. This solution impacts antibiotic overprescribing and economics of health services. Currently, 34% of children and 75% of adults with pharyngitis receive unnecessary antibiotics, and this is 10-21% worse with telehealth. A remote point of care prediction for strep throat can potentially reduce the $22 million/year costs in unnecessary antibiotics and reduce drivers for drug-resistant bacteria. When pharyngitis is treated on telehealth it saves patients up to 1-3 hours per clinical visit and saves health insurance companies up to $100-400 per visit, compared to an emergency room or urgent care facility.
This Small Business Innovation Research (SBIR) Phase I project advances the field of machine learning by combining smartphone image analysis and deep learning. These strategies are applied to a novel use case in digital health as remote screening for clinical decision support. The technical challenge is the development of a predictive model to achieve sensitivity and specificity acceptable for clinical adoption, at a target of > 80% (similar to the rapid antigen strep test). The strategy to meet this challenge is to increase the size of the dataset and experiment with multiple prediction models until goal performance is achieved. The project will also include designing an authentication system that validates sufficient images as recorded by an untrained patient and creating an intuitive user interface that enables consistent recordings by patients.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DEEPLUX TECHNOLOGY, INC
SBIR Phase I: Lightweight Learning-based Camera Image Signal Processing (ISP) for Photon-Limited Imaging
Contact
981 MARWYCK ST
West Lafayette, IN 47906--7234
NSF Award
2335309 – SBIR Phase I
Award amount to date
$274,702
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation (SBIR) Phase I project will result from the ability to operate digital image sensors at lower light levels than is currently possible. The technology is expected to be deployable in any mid- to low-level camera device, with potential applications across all industries that leverage camera technology. Consumer applications that would benefit from improved low-light imaging include dashboard cameras and notebook cameras for videoconferencing; military and national security applications include night vision and autonomous navigation; while the technology will also enable improved diagnostic capabilities in medical procedures such as endoscopies. The technology is expected to have a direct impact on workforce development, and deployment of the solution will drive economics in consumer electronics.
This Small Business Innovation Research (SBIR) Phase I project aims to achieve photon-limited image denoising using a lightweight algorithm that has the potential to be implemented on a camera chip. Accomplishing this goal requires several technological breakthroughs, collectively leading to a new image signal processor (ISP) known as a Small and Learnable ISP Module (SLIM). The key to SLIM is to identify the bottlenecks of physics-based ISPs and replace them with customized learning-based modules. Specifically, SLIM consists of five innovations: (i) learning-based frequency demodulation, (ii) guided denoising, (iii) learned feature extraction, (iv) learned indexing, and (v) learned filtering. In Phase 1, the team proposes to optimize SLIM and implement it on a field programmable gate array (FPGA). This includes shrinking the size of the filters and streamlining the indexing scheme to further speed up SLIM, introducing new encoders to improve generalization, and optimizing the memory, communication, and processing through improved programming and real-data evaluation and demonstration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DURAVAX INC
STTR Phase I: Development of Thermostable Formulations of mRNA Vaccines and Therapeutics
Contact
704 WILLIAM AND MARY PL
Wilmington, NC 28409--8148
NSF Award
2404627 – STTR Phase I
Award amount to date
$274,991
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to overcome the cold-chain limitation for messenger ribonucleic acid (mRNA) therapy. Besides the COVID-19 mRNA vaccines developed by Moderna and Pfizer, many other mRNA vaccines and drugs are under development for treating cancers and infectious diseases, gene therapy, and cell therapy. The average global revenue of mRNA therapy in the next decade is projected to be ~$18 billion annually. One main bottleneck for the distribution of mRNA therapy products is the poor stability of the mRNA drug products, which results in high cold-chain costs, big wastage, and limited accessibility to rural areas. The thermostable mRNA formulation technology developed in this project will help pharmaceutical companies to save multi-billion dollars per year associated with low stability and expand the market to the rural US and tropical countries. The thermostable formulations will make the revolutionary mRNA vaccines and drugs accessible to the approximately 60 million rural population in the US and the approximately 3 billion people living in tropical countries without adequate cold-chain facilities. Expansion of the market will also lead to more affordable prices of mRNA therapy products for low-income, especially uninsured, families.
This Small Business Technology Transfer (STTR) Phase I project will provide a low-cost and scalable solution to eliminate the cold-chain challenges in the distribution of mRNA active pharmaceutical ingredient (API) and mRNA lipid-nanoparticles (mRNA-LNPs) drug products. mRNAs and mRNA-LNPs in aqueous solutions undergo degradation through various pathways. Currently, the only way to increase their stability without freezing is to remove water by lyophilization, which requires additional facility, costs, time, and process development. This STTR Phase I project aims to test the feasibility to store the thermostable liquid formulations of mRNAs and mRNA-LNPs at room temperature for transportation and long-term storage. The research plan is designed towards two objectives: (1) To demonstrate mRNA APIs with various lengths in the optimized granule formulations retain >90% activity after transportation at 20ºC for more than two weeks; (2) To demonstrate that the optimized thermostable formulations of mRNA-LNP drug products retain >90% activity after storage at 20ºC for more than six months and 50ºC for up to 7 days during tropical outdoor transportation. Completing the Phase I project will provide the evidence to support that thermostability of the proprietary mRNA and mRNA-LNP formulations can meet the industrial requirement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
E-2 UNLIMITED TECHNOLOGIES, LLC
SBIR Phase I: Safeguard Kids and Maintain Privacy
Contact
304 HILLTOP LN UNIT G
Annapolis, MD 21403--1518
NSF Award
2321317 – SBIR Phase I
Award amount to date
$274,996
Start / end date
11/15/2023 – 10/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I proposal is making online and digital interactions safer for children between the ages of 10 ? 14 years of age by using artificial intelligence technology to monitor text communication and inform their parents of potential danger in real-time. Youth aged 10 ? 14 years are particularly vulnerable to the risks of online activity since they are newcomers to the metaverse and they are likely getting a personal communication device for the first time. Parents want their kids to have the freedom and privacy to use their devices but fear the risks involved. This project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger (e.g., online predation, cyberbullying, and/or school violence) or risky behaviors (e.g., drug and alcohol use, and/or self-harm), so parents can intervene to protect their child. The app will provide an attractive alternative to existing products on the market because of its sophisticated artificial intelligence engine and because it does not collect and transfer all the phone?s data ? the solution reduces the risk of data leaks while still keeping parents informed.
This Small Business Innovation Research (SBIR) Phase I project is advancing the state of artificial intelligence and machine learning technologies by developing a detection algorithm that runs entirely on a mobile device and is tailored to the user?s activity. Unlike large language models, which are general and wide-ranging, and thus require a lot of computing at a central server, this technology will have a small footprint and be personalized and adapted for each family. Throughout this project, the team will collect and label textual communication directly from youth and use the data to improve the algorithm?s accuracy, as measured by precision and recall. The project team will also develop the technology to collect and process the data on popular models of cell phones and to alert the parent when needed. The project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger or risky behaviors, so they can act proactively to protect their children from harm.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EARTHEN CARBON LLC
SBIR Phase I: Accelerated carbon sequestration
Contact
1704 SE 54TH AVE
Portland, OR 97215--3332
NSF Award
2324810 – SBIR Phase I
Award amount to date
$274,390
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks to develop novel soil organic matter (SOM) amendment techniques focused on improving nutrient supply to crops, sustaining agriculture, and providing long-term, deep soil carbon sequestration to help combat climate change. New methods of developing persistent organic matter amendments in soil are urgently needed in the US and globally. The result of this work will be to introduce new soil fertility and carbon storage services that permanently sequester carbon in agricultural soils at an unprecedented rate. The approach is synergistic with other economic co-benefits, such as increasing crop yields, reducing fertilizer loads, reducing atmospheric carbon dioxide (CO2) concentrations as related to farming, and expanding biorefineries and forest management capabilities. These high-quality agricultural soil amendment services may eventually have a positive impact on the global environment.
This project seeks to develop a novel, soil organic matter amendment technique. The research and development will enable acquisition of critical benchmarking and verification data. Critical prototyping, initial verification, and benchmarking in a representative agricultural soil will be conducted so that the technique can then later be extended to other farms. This proposal seeks to: 1) demonstrate viable integration into operations on commercial farms, 2) demonstrate that the method is scalable to fields and acre-scale applications, and 3) perform initial stability tests to verify the carbon is chemically stabilized using in situ CO2 gas analyzers, 4) track carbon content changes, 5) perform laboratory experiments compared against controls to verify it is not vulnerable to oxygen exposure from root intrusion, and 4) validate soil fertility improvements including changes in soil properties like soil water-holding capacity, cation exchange capacity, and base saturation. The project will use field- and lab-incubated biweekly CO2 loss rates to estimate the mean residence time (MRT) of carbon and compare treatment plots against controls. The results will be validated with random field locations and control plots of land.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECOTUNE, INC.
SBIR Phase I: Fully Bio-Based High-Performance Biomimetic Material for Sustainable Fabric
Contact
123 WHITE FLOWER
Irvine, CA 92603--0121
NSF Award
2233212 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a sustainable, scalable, and high-performance alternative to natural leather fabric. Leather is one of the most widely used fabric materials in the world, with over two billion square yards produced through animal agriculture every year. The production of animal-derived leather emits greenhouse gases and pollution from the toxic chemicals used to process, tan, and dye animal hides. Current synthetic alternatives are made of non-renewable polymers such as polyurethane and polyvinyl chloride, contributing to petrochemical consumption and plastic pollution. This project aims to develop an alternative leather material that is 100% bio-based and environmentally friendly, and that meets industry requirements for mechanical, physical, and aesthetic properties. By engineering composite materials with superior performance and quality, this technology has the potential to reduce the environmental impact of leather-utilizing industries such as fashion apparel, footwear, furniture, and automotives.
This SBIR Phase I project proposes to use a biomimetic approach to developing high-performance materials that replicate the collagen microstructure and properties of natural leather. Current synthetic alternatives contain petroleum-derived binding or coating agents. This project aims to meet objectives to 1) develop novel compositional and processing methods to produce 100% bio-based crosslinked materials, 2) systematically characterize the mechanical, physical, and surface properties to evaluate performance features, and 3) demonstrate reproducibility and tunability in alignment with industry metrics. The proposed technology leverages innovation in chemical crosslinking to produce high-strength, ultra-durable, soft-to-the-touch materials for the next generation of sustainable fabrics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMPIRI, INC.
SBIR Phase I: A cancer diagnostic instrument to measure empirical treatment response
Contact
7505 FANNIN ST.
Houston, TX 77054--1953
NSF Award
2322382 – SBIR Phase I
Award amount to date
$274,930
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve personalized cancer care by developing a first in class cancer diagnostic instrument that can deliver clinically actionable, personalized, drug response data from individual cancer patients using the E-slice assay. The E-slice assay is a novel 3D culture-based assay which has been shown to accurately predict individual cancer patients? responses to treatments. The E-slice assay is currently registered as a Clinical Laboratory Improvement Amendments Laboratory Developed Tests (CLIA LDT). The cancer diagnostic market is expected to grow from $56 billion in 2022 to $162 billion by 2027, and this test and automation could capture a significant share of this rapidly expanding market. Beyond improving outcomes for cancer patients, the automation of this assay could have far-reaching implications, such as accelerating and economizing drug screening, discovery, and development for pharmaceutical and biotechnology companies, and academia.
This Small Business Innovation Research (SBIR) Phase I project addresses the most challenging and risky portion of automating the E-slice assay. The novel engineering solutions that the team proposes to develop will automate the processing of live human tissue samples from a needle biopsy or surgery, generate precision-cut slices, and then precisely position them in a tissue culture plate for downstream culture and analysis. The new device will do so in a manner that maintains sterility, minimizes thermal, chemical, and mechanical stresses, and performs in a highly reliable way. The primary technical challenges are ensuring reliable performance that is equal to or superior than manual methods. The technical milestones include meeting thresholds for reliability, sterility, and tissue viability compared to manual processing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ENABLE LIFE SCIENCES LLC
SBIR Phase I: Antibody Therapy that Targets Neoantigens in Acute Myeloid Leukemia via the Antibody Dependent Cell-mediated Cytotoxicity Mechanism of Natural Killer Cells
Contact
400 FARMINGTON AVE
Farmington, CT 06032--1913
NSF Award
2246487 – SBIR Phase I
Award amount to date
$274,975
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project focuses on the unique combination of cancer-specific antibodies and adoptive Natural Killer (NK) immune cells needed to offer personalizable cancer therapies. This innovation represents a platform technology that can spawn multiple innovative cancer treatments, which could positively impact life sciences innovation and, more importantly, advance the health and welfare of the global cancer population. This novel approach to immunotherapy of cancer is expected to be highly efficacious and, due to the specificity of its mechanism of action, virtually devoid of toxicity. This is significant in light of the fact that the national cost of cancer care is in the $200 billion range.
This project seeks to provide a unique combination of cancer-specific antibodies and adoptive Natural Killer (NK) immune cells that synergize to achieve high efficacy, avoid toxicity to healthy cells, and offer a scalable, resource-efficient and personalizable therapy for cancer. The project focus is antibody targeting of a neoantigen found exclusively in diseased Acute Myeloid Leukemia (AML) cancer cells, in order to develop an effective treatment for relapsed / refractory disease. The 30-50 candidate antibodies will be generated and tested by first immunizing rats, isolating the resulting antigen-specific B cells using a specialized fluorescence-activated cell sorting technique, sequencing and cloning the antibody genes, and expressing the antibodies in producer cells. Candidate antibodies will be tested for specificity (enzyme-linked immunosorbent assay) and binding strength (surface plasmon resonance) for the neoantigen target, whittling down the list to ~15 candidate antibodies. Further screening will be achieved by evaluating antibody induction of AML cell-specific killing by NK cells; readouts will include AML target cell death measured by flow cytometry and lactate dehydrogenase release, degranulation by NK cells (indicating killing activity), and cytokine release. The top-performing 3-5 candidates will eventually be selected for preclinical testing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ENCOORD INC
SBIR Phase I: A hybrid phasor/waveform simulation tool for the accurate and efficient simulation of large electric power systems with high shares of inverter-based resources
Contact
1525 RALEIGH ST
Denver, CO 80204--1594
NSF Award
2321329 – SBIR Phase I
Award amount to date
$274,375
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to develop refined approaches to power system dynamic stability assessments, enabling the efficient, mass integration of renewable energy into systems worldwide. Decarbonization goals and economic opportunity necessitate the increase of inverter-based resources, such as solar, wind, and battery energy storage. A dynamic stability assessment is required before the interconnection of every renewable, inverter-based resource on all power systems. Current simulation approaches do not capture the critical details of inverter operation or are too computationally complex and expensive to be effective with real-world systems. This results in the enormous potential for unique simulation capabilities that streamline this process. There is a global market opportunity for more effective and efficient planning solutions that enable power system operators to meet this need. In the United States, alone, the licensing opportunity for a solution is hundreds of millions of dollars. The proposed hybrid approach combines computational flexibility with
accuracy. This solution will leverage the maturity of these approaches and eliminate their weaknesses. The final solution will yield an invaluable, novel simulation tool for power system operators and planners navigating the challenges of the energy transition.
The intellectual merit of this project results from the development of mathematical methods that will comprise the foundation of this hybrid power system dynamics simulation tool. Existing tools have clear weaknesses. For example, reduced-order, phasor domain simulation approaches do not capture the critical aspects of inverter operation. Detailed waveform domain approaches are sufficient to capture relevant dynamics but are too computationally expensive to be effective with real-world systems. These domains are mature, but separately they do not meet the changing need. Hybridizing them in a single platform is a solution, but it requires research in the following three foundational pillars of the proposed tool: 1) autonomous boundary determination ? identifying the spatial (across the network) and temporal (across the simulation length) boundary that partitions the two simulation domains; 2) intra-simulation model order adjustment ? applying dynamical model granularity for all simulations, but singularly perturbing the differential systems to create algebraic relations and reduce computational burden when substantial detail is not required; and 3) seamless simulation mode switching ? identifying criteria necessary for switching between domains. With the successful completion of this SBIR Phase I project, the viability of the hybrid approach will be confirmed, and a roadmap for implementation will be realized.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ERROR CORP.
SBIR Phase I: Low-Density Logical Qubit Parity Coding
Contact
4405 EAST WEST HWY
Bethesda, MD 20814--4522
NSF Award
2213187 – SBIR Phase I
Award amount to date
$255,414
Start / end date
09/15/2022 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to accelerate the adoption of error correction technologies in the quantum computing industry. It is widely held that quantum error correction will be critical to realize the potential of universal quantum computing. An error-corrected quantum computer holds promise for making transformational discoveries in science and engineering that will have broad impact across traditional technology sectors. By developing resource-efficient quantum error correction design and decoding software tools, this Phase I project aims to hasten the era of error-corrected quantum computing.
This Small Business Innovation Research (SBIR) Phase I project will advance a new method for error syndrome extraction from a register of data qubits during the execution of an error-corrected quantum algorithm. In contrast to the standard approach to syndrome extraction, where each quantum codeword is treated independently, this new approach extracts error information from the entire quantum computer collectively. The algorithmic and cost advantage of the proposed approach is a reduction in the number of extra qubits required for error syndrome extraction. This project will focus on reducing the density of the quantum circuits used for syndrome extraction according to the new approach. Low-density quantum circuits are critical for robust quantum error correction since syndrome extraction is mediated by two-qubit entangling gates, which often have error rates higher than idling or memory errors occurring in the data qubits. Another objective of this Phase I project is to design low-density error correcting codes that promote locality in syndrome extraction. Local syndrome extraction is important for error correction in quantum processors that support limited connectivity between qubits. A final objective is to benchmark the proposed constructions and algorithms on simulated data and perform proof-of-concept experimental validation on cloud-based quantum computers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ESM GLOBAL PRODUCTIONS LLC
SBIR Phase I: Artificial Intelligence (AI)-Enabled African Language Database
Contact
63 FEDERAL ST
Portland, ME 04101--4222
NSF Award
2321575 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is creating a tonally proficient Artificial Intelligence (AI)-enabled translation database for African languages. There are no such product or service that can accurately translate African languages, as African languages have traditionally been under-resourced by Western corporations. By 2050, almost 25% of the earth?s population will be Sub-Saharan African and currently more than 60% of Africans are under 25 years old. The African continent is projected to have $5.6 trillion in consumer and business spending by 2024 and the U.S. is investing over $350 million to expand digital access and literacy and promote U.S. corporate investment in the continent. By expanding opportunities to accurately translate and learn African languages, this project will support economic growth for both the U.S. and African countries and support health and welfare by facilitating communication with African-speaking Americans and recent immigrants.
African languages are very diverse with more than 2000 distinct languages across the continent. They are difficult for non-native speakers to learn and for translation apps to correctly interpret, primarily due to the tonal and guttural sounds and slight pronunciation differences that make similar sounding words have completely different meanings. The proposed AI-enabled database is first-of-its kind. The project will establish the data processing, model training, and database evaluation steps necessary to produce AI-enabled databases. The goal is to train a database to decipher these tonal shifts and ensure that the correct meaning is conveyed, beginning with a large dataset of correctly spoken audio and visual examples of words and phrases. The primary objective of this project is to develop the entry-level, consistent, Machine Learning (ML) core functionalities and multimodal interactions in a database that can be utilized in the creation of other tonally based language ML/AI databases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ETHAR, INC.
STTR Phase I: Semantically-Enabled Augmented Reality for Manufacturing
Contact
1806 UNIVERSITY DR NW
Huntsville, AL 35801--5743
NSF Award
2335533 – STTR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project facilitates safer and more efficient human-centered manufacturing tasks. The introduction of context-sensitive work guidance through immersive technologies will expedite workforce training, enhance users' spatial awareness, and outperform existing manufacturing work instruction systems, leading to heightened productivity across industries. This development embodies the emergence of cyber-human relationships and Digital Twin and Smart Factory applications, reinforcing U.S. manufacturing leadership, bolstering economic competitiveness, and fortifying national security. The anticipated commercial Platform-as-a-Service (PaaS) solution is poised to benefit approximately 10,000 U.S. manufacturing firms. Beyond its economic implications, the first-generation, open-specification Reality Modeling Language (RML) developed in this project is expected to gain widespread acceptance in the international standards community, improving spatial system automation across diverse industry verticals. Ultimately, this system will render the physical world more accessible, searchable, and comprehensively annotated with data, unlocking new frontiers in user support, safety, and efficiency.
This Small Business Technology Transfer (STTR) Phase I project addresses mission-critical challenges for fully leveraging Augmented Reality (AR) tools in manufacturing environments. It draws upon ontologically structured data and a proprietary Artificial Intelligence (AI)-driven knowledge system for automating the generation and display of context-specific AR content in 3D space, eliminating the need for individually designed AR interactions. The solution enables training and work instruction systems to become spatially- and contextually aware, in order to adapt to dynamic conditions impacting worker safety and efficiency. The objective of this project is to demonstrate and quantify how automatically generated, spatially- and semantically aware AR can provide work guidance, machine status data, and hazard warnings to increase worker capabilities versus conventional guidance tools. The RML will be derived and logically describe and computationally code the 3D spatial scene of a simulated factory floor, and later, RML will be released as an open code library to the developer community. The system will sense the real world and objects in real-time, learn as input is received, and prioritize and render AR content communicating context-specific suggestions and warnings. This project will demonstrate integration between workers, their environment, and the tools engaged to complete their tasks so production personnel can act confidently, safely and effectively.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EXIGENT SOLUTIONS, INC.
SBIR Phase I: An Artificial Intelligence System to Accelerate Semiconductor Production using Physics-embedded Lithographic Foundation Model
Contact
3908 VERBENA ST
Aubrey, TX 76227--1998
NSF Award
2336079 – SBIR Phase I
Award amount to date
$274,985
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to expedite the wide adoption of next-generation semiconductor chips, which is a major factor in driving technological innovation across industries and societies. As technologies rapidly evolve, shifting to extreme ultraviolet lithography (EUV) systems in semiconductor manufacturing has significantly increased design and manufacturing complexities, leading to prohibitively high costs and stifling innovation. This project aims to alleviate the design and manufacturing bottlenecks by integrating leading-edge artificial intelligence into these complex processes. This innovation aims to significantly boost efficiency, reduce costs, and accelerate time-to-market for new chip designs, overcoming current limitations in next-generation process nodes. Importantly, this proposal is poised to strengthen domestic semiconductor capabilities, a crucial element for maintaining U.S. national security, global competitiveness, and technological leadership.
This Small Business Innovation Research Phase I project is focused on advancing state-of-the-art artificial intelligence for simulating photolithography in rapidly emerging semiconductor technologies. As technology evolves and process precisions improve, minor design and manufacturing deviations, such as the 3D mask effect and stochastic variations, can no longer be neglected. Addressing this arising technical challenge requires a swift and precise simulation tool, essential for optimizing yield, throughput, and time-to-market, to maintain competitiveness in this market. The proposed work will create the Lithography Foundation Model (LFM), a system with physics integrated deeply into its framework that understands the intricate dynamics of extreme ultraviolet lithography processes. The technical approach of embedding physical modeling into LFM enables rigorous accuracy across any permutations of process conditions. Coupled with leading-edge hardware-software optimization, LFM promises real-time simulations with exceptional precision. The versatility and modularity of LFM enables applications for various processes, including process simulation, layout correction, and manufacturability optimization.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EXOPOWER INC.
SBIR Phase I: In-Motion, Capacitive, Wireless Charging System for Material Handling Vehicles
Contact
2514 LAKE MEADOW DR
Lafayette, CO 80026--9162
NSF Award
2228928 – SBIR Phase I
Award amount to date
$251,522
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader and commercial impacts of this Small Business Innovation Research (SBIR) Phase I project will eliminate the downtime for battery charging of material handling vehicles (MHVs) (i.e., mobile robots and forklifts) with in-motion capacitive wireless charging, thereby increasing the productivity and economic competitiveness of warehouses. Implementation of in-motion capacitive wireless charging in warehouses and roadways would enable the use of much smaller batteries (up to 80% smaller) for most electric vehicles (EVs) and MHVs, dramatically reducing costs and making them less expensive than their gasoline powered counterparts. This dramatic price reduction will speed up the transition from internal combustion engines to electric vehicles. Mass roadway deployment of in-motion capacitive wireless charging would significantly reduce air pollution and the US dependence on oil, increasing US national security.
This Small Business Innovation Research (SBIR) Phase I project will develop a capacitive wireless charging system for in-motion charging of MHVs. The project will develop a robust, safe, and fully automated system capable of wirelessly charging an MHV on demand, at power levels up to 1 kW. The research will address three technical challenges: 1) achieving high power transfer in the presence of coupler misalignments; 2) activating and deactivating the charging apparatus in a seamless and safe manner; and 3) maintaining thermally stable continuous operation and achieving efficient rectification at 1 kW, 6.78 MHz with commercially available power semiconductor devices. The misalignment tolerance will be enabled through an enhanced coupler design that ensures full power delivery over a substantially enlarged area of overlap compared to conventional coupler designs. The automated activation and deactivation will be enabled by a sensing, control, and communication system comprising a modulated optical actuation scheme and power-transfer based decision making. The continuous power delivery will be enabled by a custom-designed thermal management solution. The efficient rectification at high frequency will be enabled by innovations in matching network design that mitigate the impact of the rectifier?s parasitics. Addressing these challenges will enable the technology to be commercializable.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Earth Mapping International, Inc.
SBIR Phase I: Dynamic OneSource Geospatial Information System for Maximizing Agricultural Yields
Contact
1365 COMMERCIAL CT
Norcross, GA 30093--3857
NSF Award
2313340 – SBIR Phase I
Award amount to date
$274,979
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the creation of a dynamic geospatial database that can be mined to further develop precision models of soil moisture and farm productivity that will aid small- to medium-sized farms. These farms cover almost 75% of the operating farmland in the U.S. Large companies in the agriculture industry benefit from the collection of digital farm data however, smaller farms are disadvantaged by the inaccessibility of agricultural digital innovation systems. The availability of timely digital information as inputs to field conditions will help small- to mid-sized farmers optimize their yields and potentially generate greater revenue. The proposed database will integrate multiscale and multivariate imaging and non-imaging geospatial and meteorological data into a single source. The merging of satellite-based geospatial data with airborne-geospatial data, a challenging task, will improve the accuracy of earth science data. Potential applications of the technology include medium- to long-term food security planning, drought mitigation, soil conservation, diversification, and expansion of climate-resilient and sustainable farming.
This SBIR Phase I project focuses on developing an integrated, one-source, dynamic geospatial database as well as precision soil moisture and farm productivity forecasting models to benefit small- and medium-size farms. The data inputs include (i) global navigation satellite system observations on a newly designed geodetic/meteorological network for significantly increased accuracy; (ii) airborne digital geospatial data from a fixed-wing platform to capture high precision and resolution nadir multispectral and color oblique imageries, lidar point cloud data, and data from un-manned aerial systems to capture seasonal hyperspectral imageries; (iii) satellite remote sensing data from commercial satellite high-resolution imageries; (iv) weather satellite data for hourly global precipitation measurements (GPM) fused with multi-satellite retrievals for global precipitation measurement mission (GPM); and (v) terrestrial data from existing geographic information systems and meteorological stations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FALCON FUEL CELLS INC.
SBIR Phase I: Ammonia and Syngas Impurity Tolerance for High Temperature - Proton Exchange Membrane (HT-PEM) Fuel Cells
Contact
28 LE PERE DR
Pittsford, NY 14534--3664
NSF Award
2320804 – SBIR Phase I
Award amount to date
$274,310
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project is the development of a fuel-flexible, high-temperature proton exchange membrane (HT-PEM) fuel cell that can operate on two carbon-free fuels: ammonia and syngas, both produced from waste biomass. The fuel-flexible HT-PEM fuel cell is uniquely suited for rapid adoption as a complete system that can run on a variety of fuels with only minor modifications to its fuel reformer design. The initial market for this technology is small to mid-sized unmanned aerial vehicles (UAVs), and these were valued at $1.1 billion in 2020 (expected to grow 240% by 2029). Due to the stringent weight and durability requirements in the UAV market, adoption of this technology in mobile and stationary power applications including backup power, marine power, and remote power generation is anticipated. Investigation of these fuel/technology combinations have not been widely researched and will contribute to the displacement of fossil fuel combustion technologies, lead to increased economic competitiveness of the United States, and support the national defense.
The intellectual merit of this project stems from the HT-PEM fuel cells' ability to run on a diverse set of upfront fuel sources with only minor modification of the final assembled system, while still providing the key attributes required in most applications. For widespread adoption of new electricity generating devices, remaining fuel agnostic is a key technological trait, as proven by the enduring success of the internal combustion engine. The HT-PEM fuel cell can serve as a similar core technology, contributing to the global transition from fossil fuels. Nevertheless, there exists minimal research when operating a HT-PEM fuel cell on reformed ammonia and syngas generated from waste biomass, two popular renewable fuels expected to be widely used during this transition. The key question for this research is: what is the maximum concentration of impurities commonly found in reformed ammonia and syngas that will still allow a HT-PEM fuel cell to be technically and commercially viable? The key objectives are to outline the HT-PEM fuel cell performance while operating on ever increasing contaminant levels and identify the stop-loss mechanisms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FARMSENSE INC.
SBIR Phase I: Automatic, Digital Classification and Counting of Mosquitos to Allow More Effective Vector Control
Contact
2025 CHICAGO AVE
Riverside, CA 92507--2201
NSF Award
2233676 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 05/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the creation of an end-to-end platform for digital mosquito surveillance that can support the vital work of vector control districts. Effective vector control is essential to reducing the spread of diseases including West Nile, Eastern Equine Encephalitis and Zika. Currently, mosquito surveillance is typically done using mechanical traps, which require significant labor to survive. The project will significantly improve the quality and ease of insect surveillance, thus allowing more effective mosquito control. This effort will improve mosquito suppression efforts, while reducing labor costs and the volume of pesticides that must be used. Reducing the volume of pesticides has further positive benefits to society at large: it will reduce pollution and colony collapse disorder in beneficial bees. Beyond area-wide surveillance, the hardware/ algorithms/ representations/ data-models created in this project will be useful to scientists that study mosquito-vectored diseases. For example, the solutions can be used to measure the effectiveness of a new attractant or repellent.
This Small Business Innovation Research (SBIR) Phase I project will investigate techniques to improve state-of-the-art mosquito classification and counting, with the goal of producing a platform that allows inexpensive, real-time, insect surveillance to support mosquito suppression efforts. Although digital sensors have the potential to remove the burden of manually counting the insects, currently the vector control technicians must still visit the traps frequently to change the carbon dioxide (CO2) gas cylinders (the lure) and the batteries. The reason why both CO2 and batteries deplete so rapidly is because they are left on all day. Because the team is sensing insects in real time, they have the unique ability to actuate the gas cylinders and fan/light to sample the distribution of insect arrivals. The team can also optimize the trade-off between conserving resources and the precision of measurement of mosquito density.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FENIX SPACE, INC.
SBIR Phase I: Novel Reusable Launch Platform: Two-Body Separation Under Unique Aerodynamic Circumstances
Contact
294 S LELAND NORTON WAY STE 3
San Bernardino, CA 92408--0131
NSF Award
2233168 – SBIR Phase I
Award amount to date
$274,996
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in its positive influence on both the growth of the Low Earth Orbit economy and stimulation of innovation in space technology. The growing demand for satellite launches is currently limited by a bottleneck of low availability, flexibility, and high cost of existing orbital launch services. Orbital delivery services enabled by this advanced in-flight separation system will enable a new level of launch responsiveness leading to lower costs, much greater contractual flexibility, and the availability of daily launches without the need for costly launch infrastructure, greatly accelerating time-to-market for satellite service providers and increasing their profitability. Low cost and frequent access to Low Earth Orbit will enable ubiquitous internet access, 5G capabilities, and valuable Earth observation technologies. The flexibility and reduced cost of these launch services will help maintain the United States' position at the forefront of space technology development and space research. The technology will provide the US Armed Forces access to a responsive, secure, flexible, and available gateway to space that will boost reconnaissance, observation, communication, and intelligence capabilities. Moreover, it will represent the most ecofriendly launch delivery service available, able to reduce carbon dioxide emissions by three times (3x) compared to ground launch.
This SBIR Phase I project seeks to demonstrate an innovative concept of in-flight aircraft/rocket separation in which the rocket is launched from the top of the carrier aircraft, instead of the widely used launch from beneath. This new separation system is the core innovation enabling an advanced air-launched orbital delivery system that will dramatically reduce the cost of dedicated satellite launch, minimize propulsion and structural requirements, and enable orbital delivery flexibility and precision, while significantly reducing the carbon footprint of space launch operations. The proposed concept will be the first top-carry air-launch service commercially available. The goals of the Phase I project are focused on building a prototype of the separation system and validating it in a sub-orbital test flight. The main technical challenge is to ensure that the design of the improved separation system will work under a broad range of real flight conditions. This technology will be achieved by research leading to a better understanding of aerodynamic behavior at the separation event and the development of an improved design methodology that considers all relevant design parameters and their aerodynamic effects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FINIKS FORGE, INC.
SBIR Phase I: Upcycling animal hair waste into regenerated textile fibers
Contact
24 BERKELEY ST
Somerville, MA 02143--1604
NSF Award
2317482 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project reduces the environmental footprint of the fashion industry by engineering regenerated sustainable textile fibers from protein waste. The millions of tons of industrial and post-consumer keratin waste produced every year from the food, beauty, and textile industries are targeted as sources of biomass to engineer sustainable and cost-effective protein-based textiles with properties comparable to animal fibers such as wool and cashmere. This project would allow the introduction of a new player in the eco-friendly fiber market space and contribute to the fight against the detrimental environmental impacts of synthetics. The repurposing and revalorization of keratin waste from the wool, leather and poultry industries would benefit a broad part of the US agriculture ecosystem. The fundamental research on protein self-assembly and biomaterial engineering necessary for the development of the keratin regenerated fibers will serve as a scientific asset in other industrial sectors including biomedical, high-performance materials, and green chemistry industries.
This SBIR Phase I project will develop chemical processes and material fabrication platforms to enable the upcycling of keratin protein waste into textile fibers proving processability through standard fabric manufacturing technologies. The target deliverable is planned to be achieved by 1) developing an efficient and sustainable method to extract keratin from animal hairs; 2) engineering the textile fibers at the molecular level to first match, and then improve the mechanical and sensorial properties of wool and cashmere; and 3) implementing a custom lab-scale fiber manufacturing process, demonstrating potential scalability into a multifilament production line. The following activities will be conducted to meet the planned milestones: 1) implementing a non-denaturing extraction process of keratin from hair waste and formulation of the extracted protein into a material processable through extrusion-based fabrication platforms; 2) reconstructing the fibrillar and anisotropic architecture of animal hair by chemically and physically regulating the self-assembly process of the extracted keratin during the fiber fabrication process; 3) modulating the hygroscopicity of the fiber by modifying the reactivities of both fiber core and surface; and 4) tuning the rheological properties and the liquid-to solid phase transition of the protein material under shear stress and during the fiber formation step, respectively.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FIRSTTHEN INC
SBIR Phase I: A novel caregiver-centered mobile app and artificial intelligence (AI) coaching intervention for pediatric Attention Deficit Hyperactivity Disorder (ADHD)
Contact
5338 EMERSON AVENUE
Dallas, TX 75209--5004
NSF Award
2335539 – SBIR Phase I
Award amount to date
$273,184
Start / end date
11/15/2023 – 10/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is its potential to improve approaches addressing pediatric Attention Deficit/Hyperactivity Disorder (ADHD), a condition affecting 10 percent of all U.S. children. The primary challenge families face is accessing psychosocial treatment, a crucial component of comprehensive care. Many families cannot access these interventions due to various barriers including cost, time, and a shortage of mental health professionals. This project introduces a self-guided, family-focused ADHD treatment mobile application complemented by a virtual coach. By addressing caregiver stress, which plays a significant role in treatment outcomes, this innovation offers a scalable, affordable, and effective solution. This initiative aligns with the National Science Foundation's mission to promote scientific progress and support the well-being of the American public, especially during the current youth mental health crisis. The potential commercial and societal impacts of this project include enhancing scientific understanding of ADHD treatment, providing a competitive advantage in the digital health sector, and addressing a significant market opportunity in mental health care.
This Small Business Innovation Research (SBIR) Phase I project utilizes artificial intelligence (AI) and large language models (LLMS) to create a scalable, accessible, and robust caregiver-centered mobile treatment system for pediatric ADHD, complemented by a virtual coach. The innovative aspect lies in merging human-centered design with rules-based conversational AI and an empathetic chatbot, aiming for a lasting, scalable impact on caregivers of children with ADHD. The intent is to broaden access to evidence-based psychosocial interventions, improve adherence to these treatments, and achieve superior outcomes. ADHD, a condition that hinders self-regulation and executive function, affects a significant portion of U.S. children. Despite the known advantages of early intervention, many affected children do not receive optimal care. The project's objectives include the co-design of the app, which incorporates a multi-module psychosocial intervention and caregiver coping techniques; the development of the virtual coach's role with clinician guidance using AI; and a proof-of-concept test involving caregivers. The project will assess feasibility and acceptability, and gather preliminary data on potential improvements in caregiver and child wellbeing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FLUXWORKS LLC
SBIR Phase I: Scalable Magnetically-Geared Modular Space Manipulator for In-space Manufacturing and Active Debris Remediation Missions
Contact
707 TEXAS AVE
College Station, TX 77840--1976
NSF Award
2335583 – SBIR Phase I
Award amount to date
$261,795
Start / end date
04/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the derisking and catalyzing of a novel backdrivable gearbox technology that will potentially step-improve robotic and automation system operating costs, mean-time-before failure, efficiency, high throughput, and manufacturing capabilities, especially in microgravity/space environments. Having the potential to isolate vibrations and operate far longer without maintenance compared to the status quo, integrating this backlash-free gearbox with commercial-off-the-shelf servo motors and controllers could enable commercial original equipment manufacturers (OEMs) and U.S. government entities to create platforms and commercial space stations with higher throughput and faster iterative research capabilities in the microgravity environment, offering a plethora of benefits for semiconductor, biotechnology, advanced materials, and other industries. The targeted specifications are relevant to end-effectors with flight heritage to enable rapid transition for lunar, low-earth orbit, terrestrial robotic manufacturing, and scientific applications. Through investment in this technology, this HUBZone-certified firm is concurrently creating STEM and manufacturing jobs in the HUBZone area in which the company resides and increasing exposure to STEM in the community at large. Moreover, the company?s products are and shall continue to be, fully U.S.-sourced and manufactured to stimulate the U.S. manufacturing economy and supply chain security.
This SBIR Phase I project proposes to develop and validate the operating principle of the patent-pending innovative flux angle mapping magnetic gear and determine space-actuator feasibility for the commercialization of magnetic gear technology. The proposed noncontact magnetic gear is an entirely new magnetic gearbox topology with a novel set of operating principles that differ from all other existing magnetic gearbox topologies and have never been demonstrated as an operational prototype. It has been validated previously by high-fidelity finite element analysis (FEA) simulation and analytical derivation. The first key objective of Phase I is to design, fabricate, and test a prototype FAM magnetic gearbox. The second key objective is to use FEA combined with the first prototype's experimental results to re-simulate and characterize the performance of a second-generation minimum viable product magnetic gear. The mechanism to assess success is the achievement of four milestones: (1) designing a manufacturable technology demonstrator, validating manufacturability; creating an operational prototype (2) demonstrating the expected gear ratio, validating the fundamental operating principle and (3) performing in concordance with the simulation results, validating our models; (4) designing a full-scale space-relevant gear with calibrated models, validating commercial feasibility.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FORM FINDING STUDIO LLC
SBIR Phase I: Computer Aided Design and Simulation Software for Origami
Contact
1267 WILLIS ST STE 200
Redding, CA 96001--0400
NSF Award
2233133 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enable widespread adoption of origami design principles in industry to create manufacturing efficiencies and promote technological innovation. Origami-inspired engineering has applications across virtually all Science, Technology, Engineering, and Mathematics (STEM) fields, yet existing computer-aided design (CAD) tools are extremely limited in their ability to model folded geometries. This Phase I project and subsequent commercialization effort will fill a gap in the market by creating powerful and user-friendly software to model folding, with target customers spanning a broad range of industries: product design, architecture, packaging, papercraft, education, manufacturing, and materials engineering. Academic publications resulting from the research and development conducted during this project will advance fundamental knowledge of the mathematics of folding. Furthermore, this work seeks to create positive educational impacts through ongoing collaborations with K-12 STEM educators to create engaging curricula in geometry, digital design, and manufacturing through papercraft.
This SBIR Phase I project will create an intelligent software system that facilitates the design and simulation of folded geometries via powerful origami editing techniques grounded in fundamental research. The Phase I research and development builds on the team?s prior work on origami design algorithms and efficient origami simulation methods to establish a novel design framework that supports intuitive editing of folded geometry by novice users. A particular focus of the project is the under-explored domain of curved crease origami, which promises new opportunities for high-performance materials engineering and expressive design. Phase I research studies will investigate key open research problems underpinning the CAD system; this work will establish efficient methods and mathematical bounds for critical origami design algorithms to be implemented by the software system. Primary technical hurdles of the Phase I project include: architecting a novel constraint management system to support interactive editing of origami designs, establishing novel computational design algorithms for curved crease origami, and developing core data structures and geometry processing methods to be used by the CAD system. Throughout Phase I, the team will work with customers and strategic partners to identify specific use cases of folding in key vertical markets, develop a Minimum Viable Product (MVP) software application, and evaluate technical progress in terms of its commercial potential.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FREE TO FEED, INC.
SBIR Phase I: Real-Time Allergen Detection Technology for Dietary Proteins Transferred to Human Milk
Contact
5545 N BEAHAM AVE
Meridian, ID 83646--5819
NSF Award
2321861 – SBIR Phase I
Award amount to date
$274,946
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide the first test to determine the allergen content of human milk accurately, quickly, and cost-effectively. As much as 25% of infants have reported allergic responses to dietary proteins found in human milk which often results in breast/body feeding termination. Breast/body feeding is incredibly beneficial to health and continuation of nursing is a human health issue. Studies indicate that human milk is superior to hypoallergenic formula, providing natural antibodies to fight illness, lowering the risk of sudden infant death syndrome, and reducing the probability of developing disorders such as diabetes and leukemia. There is currently no at-home, real-time test for milk allergens on the market.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a real-time at-home allergen detection test. This project lays the groundwork for providing the first mechanism to research early and often allergen introduction through human milk when the immune system has been shown to be susceptible to allergy reduction strategies. The company?s patent-pending technology has the potential to provide a tool to identify allergens quickly and cost-effectively, allowing parents to monitor the presence of likely allergen triggers. The test is performed by the user in a real-time, in an at-home setting, which is a significant advantage over existing tests that require samples to be sent to a laboratory for labor and resource-intensive assays. The lateral flow technology provides a rapid and easy-to-read result, allowing the user to quickly determine whether the milk contains specific non-human protein fragments which are also known to elicit allergic responses in some patients.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FREESCALE LLC
STTR Phase I: Development and Analysis of Functional NanoInks for Printed Neuromorphic Electronics and Smart Sensors
Contact
103 HAMPTON LEE CT APT 2C
Cary, NC 27513--5540
NSF Award
2334413 – STTR Phase I
Award amount to date
$274,972
Start / end date
03/15/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project from Freescale LLC will be on scalable additive manufacturing of micro and macro scales for analog electronics, artificial intelligence (AI), and sensing applications. The project will leverage recent advancements in electrohydrodynamic and micro-transfer printing, alongside AI-controlled manufacturing, to produce micro and macro-scale electronic devices with a submicron resolution. The resulting devices will have the capability of computing and sensing, similar to biological brains. The project will strengthen domestic microelectronics innovation and production capabilities and support US leadership in AI and quantum computing. New intelligent systems developed using these techniques can help address challenges in healthcare, aerospace, defense, transportation, energy, and more.
This Small Business Technology Transfer (STTR) Phase I project aims to demonstrate the manufacturing of
fully printed functional devices using an innovative multifunctional printing platform for next-generation electronics. The platform will provide development, optimization, and delivery of specialty inks with
conductive and semiconductive properties that will be printed on rigid and flexible surfaces to produce analog computing and sensing functionality. The platform will support printing at micro and macro scales, leveraging real-time feedback and artificial intelligence (AI) control for intelligent composition modification, delivery parameter optimization, and scalable manufacturing. Currently, conventional lithographic fabrication of functional devices is expensive and inefficient, as it requires complex supply chains, expensive hardware, and offshore production. This STTR project will combine precise inkjet printing for thin layer deposition and micro-transfer printing for large-area development to enable seamless fabrication of functional devices for sensing and analog computation in days instead of months, bypassing the complexities of modern silicon manufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FREYYA, INC.
SBIR Phase I: An ambulatory pelvic floor monitoring and feedback device for use in physical therapy
Contact
1305 S CONCORD ST
Salt Lake City, UT 84104--2901
NSF Award
2304490 – SBIR Phase I
Award amount to date
$275,000
Start / end date
11/15/2023 – 10/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel device that enables pelvic therapists to evaluate, diagnose, and treat patients during activities responsible for pelvic floor symptoms. One in four women in the US has a pelvic floor disorder and this disorder results in $20 billion in annual costs and negative recurring patient experiences. Pelvic physical therapy is the recommended first-line treatment but requires regular management, burdening the patient and clinical resources with each visit. Current systems are limited to static patient conditions with specific situational muscle conditions. This novel pelvic floor monitoring device aims to provide optimized pelvic floor muscle feedback during chronic ambulatory conditions when a significant percent of pelvic floor events occur.
This Small Business Innovation Research (SBIR) Phase I project is a novel device to reduce the burden of pelvic floor disorders in a patient self-managed manner. A wearable pelvic floor monitoring device will provide dynamic evaluation and treatment for chronic ambulatory conditions. This project aims to design and prototype the components and system of a pelvic floor force sensor for use during exercise. The device will be integrated into a comfortable and ergonomically fitted silicone shell with interchangeable sleeves to fit different patients? anatomies, and a wireless biofeedback software for communicating data from the device to the patient and therapist. The system will be benchtop tested to ensure accurate and robust performance of the sensors and data transmission. The ergonomic shape will be tested in a limited patient pilot for comfort and vaginal retention. Successful completion of this project will demonstrate the technical and commercial feasibility of a novel ambulatory pelvic floor monitoring and feedback device for patients.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FRINGE METROLOGY LLC
SBIR Phase I: Rapid and Accurate Large Aperture Surface Metrology for Future High Speed Communication
Contact
2842 N TUCSON BLVD
Tucson, AZ 85716--1824
NSF Award
2335106 – SBIR Phase I
Award amount to date
$274,769
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research Phase I project seeks to revolutionize how high-precision antenna dishes for satellite communications and radio astronomy are constructed. By developing an optical metrology system capable of measuring large antenna dishes with micron precision in minutes, this project addresses a critical bottleneck in the production of high-accuracy, low-cost, mass-manufactured antenna dishes. Current metrology methods like holography and photogrammetry are slow, costly, inconvenient, and lack the accuracy required for future dishes. The commercial impact of this project targets the growing multi-billion-dollar market of satellite communications and radio astronomy, with an addressable segment valued at approximately $2.3 billion for the next-generation Very Large Array (ngVLA) alone. The goals of this project not only promise to enhance global connectivity and defense communication networks but also support groundbreaking discoveries about the universe.
The intellectual merit of this project lies in its pioneering approach to optical metrology, stretching the capabilities of current systems to their limits for measuring objects up to 18 meters in diameter outdoors. The research objectives focus on overcoming fundamental challenges such as maintaining high precision and accuracy over large areas, construction of lightweight and portable hardware, and designing a system that is ready to be deployed by antenna technicians. Anticipated results include a prototype system capable of significantly advancing the field of optical metrology and providing a scalable solution for the high-volume production of precision antenna dishes. This innovation will produce significant advancements in satellite communication and radio astronomy by streamlining the construction and maintenance of high-precision dishes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Forward Edge AI, Inc.
SBIR Phase I: A Cyber Assured Space Internet Device
Contact
10108 CARTER CYN
San Antonio, TX 78255--2458
NSF Award
2327618 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project presents urgently needed improvements to cybersecurity in space to enable a larger scale, higher throughput, and a more securely interconnected ecosystem. This includes enabling high-throughput on-orbit manufacturing for the next ten years and is aimed squarely at small and medium manufacturers (SMM), large manufacturers, and original equipment manufacturers (OEM) that will supply large-scale space production industries. The ability to use Artificial Intelligence/Machine Learning (AI/ML) to remotely modify, optimize, and enhance the resiliency of Cube Satellites to cyberattacks is crucial to this evolving industry. The solution extends to the high growth commercial space industry-related Earth Observation (EO), and Direct Satellite to Device/Smartphone markets. The development of small satellites has notably increased the interest of private companies and government agencies in investing in this field, as it allows for more affordable access to new business models in space, including satellite constellations. Space applications, ranging from machine to machine (M2M), the Internet of Things, and Earth observation use cases, are expected to reach more than $22 billion in service revenue by 2031. The market is rapidly moving from an infrastructure-heavy investment cycle towards an as-a-service-focused recurring revenue business model.
This SBIR Phase I project will develop the technology needed to accelerate the commercial development of the hybrid space and terrestrial communications architectures, in-space manufacturing, and industrial infrastructure. ML algorithms that can differentiate between anomalies triggered by natural phenomena and cyber-attacks represent a significant advancement. This can be applied at increasingly larger scales, higher-throughputs, and speeds for robust security and acceleration of this sector. Through adaptability and precision, ML can significantly reduce the occurrence of false alarms but also excel at predicting the source of the anomaly and attributing the anomaly to its origin. Applying the ML predictive capabilities enhances early warning systems, fortifies cybersecurity measures, and ensures continuous monitoring in an ever-evolving threat landscape. The project would accelerate the integration of terrestrial telecommunications networks and satellite communications technologies, decrease costs, increase service coverage, and provide added resilience and multi-level security compatibility to the nation?s communication infrastructure. Mimicking the operational capabilities of the human immune system will allow for the long-term and evolving effectiveness of a space platform's cyberattack detection and response capabilities. This decentralized approach will be able to leverage decentralized autonomous organizations and strategic defense capabilities to accelerate human endeavors in space.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Funxion Wear
SBIR Phase I: On-Demand Color Changing Materials
Contact
8622 OLD MAPLE LN
Humble, TX 77338--2126
NSF Award
2304234 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project will validate the commercial potential of an erasable dye technology intended for apparel. The transformative nature of the approach lies in its ability to reduce environmental impact every time a new design is downloaded. The conventional apparel industry consumes vast amounts of water and emits significant amounts of carbon dioxide (CO2) for every piece of clothing produced. This project aims to drastically reduce these environmental implications while providing consumers with a quick and climate-friendly alternative. By tapping into proprietary light-programmable color-changing dyes, this endeavor seeks to disrupt the fashion industry. By targeting the millennial and Gen Z market segments, which are increasingly conscious of sustainability, the project foresees significant commercial uptake, initially in the $8 billion custom domestic T-shirt market.
The intellectual merit of this project stems from its unique combination of advanced functional materials science, chemistry, and manufacturing to create a sustainable apparel solution. At the heart of the method lies a proprietary dye system which can provide repeatable color changes. Unlike conventional photochromic dyes that degrade quickly under visible light, this dye system is engineered to be durable, enduring repeated cycles of color change. The research objectives focus on refining this dye system to make it commercially viable, especially for the initial use case of custom and re-printable T-shirts. With the successful realization of this technology, the fashion industry will witness a paradigm shift, paving the way for a more sustainable and innovative future.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GAIA AI, INC
STTR Phase I: Registration of Below-Canopy, Above-Canopy, and Satellite Sensor Streams for Forest Inventories
Contact
444 SOMERVILLE AVE
Somerville, MA 02143--3260
NSF Award
2234077 – STTR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to increase the volume and improve the accuracy of data on the world?s forests. Presently, when collecting data on forests, surveyors must choose between slow, laborious methods, or quick but inaccurate ones. This project uses recent advances in sensors and machine learning to greatly improve data collection speed without sacrificing accuracy. The resulting rich datasets enable the construction of true ?digital twins? of forests and open the door for higher fidelity modeling of forest growth trajectories. This information is useful both for timber firms seeking to maximize the potential of their assets and environmental groups projecting how changes today could impact a forest?s performance as a carbon-sink over the long term. The impacts on United States citizens are widespread. Here are two examples: improved efficiency in the timber industry brings down the cost and improves the quality of raw materials and turning forests into denser carbon sinks helps meet climate change goals. The availability of such broad and deep data on forests could also drive a boom in research and understanding about the more complex and nuanced relationships that drive forest health and productivity, launching entirely new sub-industries around forestry.
The key technological innovations explored in this STTR Phase I project are in constructing the most high-fidelity forest model (digital twin) by combining disparate information sources, each with their own advantages and disadvantages. Light detecting and ranging (LiDAR) and camera sensors on backpacks provide high-quality inventory metrics nearly 1000 times faster than manual measurements, but still require someone in the forest to wear the backpack. Satellite imagery scales almost instantly to entire forests and also through time with historical data but is limited by the top-down nature of satellites and the resolution they offer, especially when historical and free data sources are considered. Drone-based imagery sits in-between, with advantages and disadvantages of both. In practice, combining information sources that measure in such different ways can be very difficult. In this project, the team explores how to express LiDAR-based metrics to best associate them with top-down imagery from satellites and drones. From these associations, one can then build powerful machine learning models and specialize them to individual forests. This ability may enable the company to provide forest inventories and forest management recommendations to timber companies at any scale: with satellite imagery only or with a combination of backpack-LiDAR and satellite for the highest accuracy over the entire forest.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GEMINATIO
SBIR Phase I: Liquid-Enabled Advanced Pitch (LEAP) Semiconductor Manufacturing
Contact
50 MAKAMAH BEACH RD
Fort Salonga, NY 11768-
NSF Award
2304119 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2023 – 06/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of materials and processes for semiconductor manufacturing that will enable the progression of Moore?s Law and help to strengthen domestic semiconductor manufacturing capacity and capability. Recent supply chain issues have plagued the semiconductor industry, and this has had ripple effects throughout the American economy. The majority of advanced semiconductor manufacturing capacity is outside of the U.S. and this recent shortage has highlighted the need for domestic foundries both for economic vitality in the U.S. as well as national security and supply chain resiliency. In 2019, American semiconductor foundries directly employed 184,600 workers, down from 292,100 (-37%) in 2001. The main loss of manufacturing jobs was attributed to the utilization of offshore foundries. Currently, U.S. semiconductor manufacturing represents just 1% of global capacity and 80% of U.S. semiconductor manufacturing capacity is in the 200 mm (8-inch) format, which is not compatible with the most advanced, high-performance processes, limiting production to >65 nm nodes. This project will increase the competitiveness of currently established U.S.-based foundries as well as increase the performance of foundries that are under construction.
This project seeks to develop and validate the performance of several required materials to enable the integration of a novel semiconductor manufacturing process that has the capability to double the density of features in current cutting-edge semiconductor chip manufacturing processes. This solution may also simplify the overall manufacturing process, without the need for intensive capital expenditures. At the conclusion of this project, the performance of the developed materials and the resulting manufacturing improvement will be demonstrated on both 8-inch and 12-inch formats. The process begins with conventional photolithography on a chemically amplified resist to define a relief pattern. A Trencher material is then coated on top of and diffused into the pattern, creating a self-aligned layer of polarity-switched material at the sidewalls of the resist. A Masker is then applied to fill the openings in the pattern, and the final pitch-doubled pattern is revealed. The diffusion-controlled process achieves a similar result to alternative processes without the need for expensive tool upgrades. The technology can extend canonical lithography methods by up to 2 nodes, reduce production costs by more than 80%, and reduce patterning errors to improve yield. Importantly, the process is applicable to 8-inch wafers, bringing advanced node dimensionality to older fabs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GENASSIST INC
SBIR Phase I: Creation of antimicrobial MyoMatrix for functional muscle regeneration in a porcine model of volumetric muscle loss
Contact
1713 FREMONT ST
Cape Girardeau, MO 63701--1914
NSF Award
2304420 – SBIR Phase I
Award amount to date
$274,993
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an antimicrobial muscle-regenerating biomaterial into a commercial-ready product and address volumetric muscle loss injuries. In the context of defense medicine, severe muscle trauma often occurs in environments where external factors such as sterility are not well-controlled. This project is expected to demonstrate antimicrobial properties of this novel muscle-regenerating biomaterial to enable use in these environments. If successful, the broader societal and economic impacts of antimicrobial muscle-regenerating biomaterials are staggering. Volumetric muscle loss affects tens of millions of victims each year. Sixty percent of patients are left untreated, 30% receive a muscle flap transplant, and 10% of injured limbs are amputated. Total average lifetime costs for amputation now total over $700,000. Improved clinical outcomes resulting from the implementation of this technology could lead to hundreds of thousands of dollars in savings over the course of each recipient's lifetime.
This Small Business Innovation Research (SBIR) Phase I project demonstrates significant advances over the existing standard of care for the treatment of volumetric muscle loss, for which no treatment currently exists. The joint loss of cells and extracellular matrix creates an environment where muscle regeneration cannot occur, leading to muscle collapse and atrophy over time. This project effectively replaces the extracellular matrix lost in volumetric muscle loss and creates an environment where satellite cells may proliferate and differentiate into new muscle tissue. A technical concern raised by clinicians, especially those who work in austere environments in military medicine, is the risk of infection caused by implanting a foreign substance into a wound bed. To address this, Technical Objective 1 will focus on incorporating antibacterial agents to optimize the scaffold?s ability to promote muscle regeneration while also having an antibacterial effect. Structural and mechanical properties will be assessed, cellular viability ensured, muscle cell quality evaluated, and antibacterial properties measured. Technical Objective 2 aims to investigate these outcomes with a pilot porcine model of muscle trauma. It is anticipated that the proposed antimicrobial biomaterial will both combat the risk of infection and effectively regenerate functional muscle in traumatic muscle injuries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GFORCE ANIMATION INC
STTR Phase I: Fire Ground VR
Contact
26410 OAK RIDGE DR STE 112
Spring, TX 77380--4352
NSF Award
2333972 – STTR Phase I
Award amount to date
$274,828
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to revolutionize firefighter training by creating a virtual environment that mirrors real-world scenarios, such as interactive fire equipment usage. This training program reduces training costs, improves safety by reducing training injuries, and reduces the environmental impact of live firefighter drills. The potential commercial and societal impacts of the project include enhanced training effectiveness, broader accessibility and inclusivity, standardized training, research and development, crisis management and preparedness, and global collaboration. The project may also have applications in diverse fields such as emergency response, industrial safety, and specialized vocational training.
This Small Business Technology Transfer (STTR) Phase I project offers immersive training environments for firefighters, a departure from traditional classroom and live fire exercises. The technical innovation of this training solution incorporates mobility, real-time data sensors, and tactile feedback mechanisms, such as a haptic nozzle, to enhance the training experience. The project will employ a controlled laboratory setting to test the virtual reality environment, leveraging advanced technologies like gaming computers, spherical cameras, and specialized headsets. These tools blend real-world interactions with digital content, creating a virtual reality that mimics natural dimensions across various sensations. The project will also assess graphic technology's adaptability to integrate with online platforms for data management, ensuring secure access, storage, and retrieval. This adaptability ensures scalability and efficient data retrieval, further enhancing the training experience.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GOODMAN CONSULTING GROUP, LLC
SBIR Phase I: Pathogen Interception: A new method for finding and identifying genetic sequences
Contact
3749 N PLACITA VERGEL
Tucson, AZ 85719--1439
NSF Award
2230484 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be the ability to quickly and inexpensively determine the presence and genetic sequence of a wide variety of pathogenic organisms. Most importantly, this technology could be implemented without prior assumptions as to which organisms are expected. Sequencing will be accomplished by direct electrical identification of the building blocks, the bases, of the genomic sequence. The potential societal impact of this technology is to provide a method to screen individuals quickly (under a minute) for the presence of infections. Screening at ports of entry and in appropriate community settings will minimize disease transmission and allow for the quick identification and treatment of any infected individuals at US borders. In addition, beyond this immediate application, the technology may also enhance scientific understanding of normal genetic sequences in any organism. If its anticipated speed, high accuracy, and low cost are realized, this technology may find applications in human in vitro diagnostics and human genome sequencing. The studies in this Phase I project will lead to a proof-of-concept demonstration for an automated, commercial instrument.
The project seeks to determine the identity and order of the genetic building blocks, the nucleotide bases, comprising any genomic sequences present in a sample solution. This sequencing will be done by examining the ability of each base in the sequence to modify a tunneling current as it is passed by electrophoresis across two very closely spaced tunneling electrodes. Tunneling is a well-known quantum mechanical effect, and it is quite sensitive to the electrical configuration of the object (here a given specific nucleotide base) present between its electrodes. Experiments with this technology to date have been unsuccessful because genetic sequences have not been able to be moved slowly enough across the tunneling electrodes for their bases to be distinguished. The studies here will overcome this problem by modifications of the geometry and solution conditions of the electrophoresis and possibly with improved methods of tunneling current detection. The data obtained through the application of this technology is expected to enhance the current understanding of nucleotide base chemistry. The solution may permit the detection of nucleotide base modifications of potential biological and medical importance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRID MODERNIZATION SOLUTIONS, L.L.C.
SBIR Phase I: IoT-Enabled Intelligent Data Replication for Secure Redundant Monitoring
Contact
1960 S WASATCH DR
Salt Lake City, UT 84108--3326
NSF Award
2213221 – SBIR Phase I
Award amount to date
$248,975
Start / end date
09/15/2022 – 06/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Phase I project is to increase the visibility and availability of data used for control and automation of critical infrastructures. This research proposes the development of a novel technology that takes advantage of flexible, low cost, and low power internet of things (IoT) devices to replicate, transmit, and analyze relevant monitoring and control data. Blackouts in the U.S. cause tens of billions of dollars in outage cost annually. This technology will advance the nation's energy safety, security, and economy by improving the capabilities of critical infrastructure systems to respond to blackouts caused by anomalous events such as natural disasters (e.g., hurricanes, winter storms) and localized faults or cyberattacks. Therefore, the technology developed in this project will decrease restoration time and provide real-time defense against cyberattacks, reducing the loss of electricity to critical users such as hospitals and governmental facilities, and saving billions of dollars.
This Small Business Innovation Research (SBIR) Phase I project will advance the scientific knowledge required to enhance the resilience of critical infrastructures through the integration of IoT networks, monitoring and control technologies, and data analytics. Advances in the use of IoT devices for critical infrastructures integrated with security mechanisms will facilitate the technology transition of the current critical infrastructure. This project will explore and design novel mechanisms for data processing, light-weight encryption, and attack detection. The technology developed in this project will have widespread applications in monitoring and control, not only in the electricity sector, but also in many other critical infrastructures such as water, oil, and gas. A proof of concept will be developed to validate the feasibility of the proposed architecture and algorithms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GROUND CONTROL ROBOTICS, INC.
STTR Phase I: Weed Control Via Terradynamically Robust Robots
Contact
720 HUNTING VIEW POINT
Atlanta, GA 30328--2784
NSF Award
2335553 – STTR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project develops a robotic platform that can provide automated weed control throughout crop development stages. In recent years, weed control costs have been growing due to the rise of herbicide-resistant weeds and the increase in costs of agricultural labor. Additionally, increased demand for fruits and vegetables leaves these specialty crop farmers struggling to find options to increase productivity while keeping expenses manageable. Several companies offer automated weed control in vegetables; however, these large platforms struggle not to damage fruit in berry orchards. This project aims to develop swarms of robotic devices that can operate underneath the plant canopy to provide mechanical weed control for berries throughout the year without impacting plant growth. This technological development will enable domestic fruit production to meet the growing consumer demand and allow for less chemical use in fruit production, reducing herbicide-associated health risks to farm workers and consumers. Long term, these devices can augment weed control strategies in other crops and perform different agricultural tasks such as fungicide treatments and plant health monitoring, with the goal of automating agriculture to be more efficient and sustainable.
This Small Business Technology Transfer project aims to develop rugged, low-to-the-ground, multi-legged robots that can locomote in various agricultural fields. This technology builds off of recent works demonstrating the effectiveness of centipedes and centipede-like robots when traveling over diverse terrains. When properly coordinated, these mechanically redundant legged systems demonstrate robust locomotion in complex terrain without the need for sensory feedback. This project will leverage this platform and perform systematic robot experimentation and theoretical modeling to develop coordination schemes for various maneuvers in agricultural terrain analogues. These strategies will then be implemented on a hardened robot to reliably locomote beneath the canopy in crop fields and identify weeds using an onboard camera and computer vision techniques. This device will make use of low-cost components and principles of mobility in complex environments to deliver guaranteed locomotion in these unpredictable terrains. Eventually, swarms of these devices will be deployed on various crop fields to provide autonomous weed management throughout the growing season, decreasing the costs of production for farmers and consumers. This project will result in a robust robotic platform that can provide cheap, reliable, all-terrain locomotion and such a device can extend beyond agriculture to address other U.S. sectors such as search-and-rescue and defense.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GROUP1, INC.
STTR Phase I: Potassium Ion Battery with Intermediate Charge Rate Competes with Lithium Ferrophosphate (LFP)-based Lithium-Ion Batteries (LIBs)
Contact
3055 HUNTER ROAD
San Marcos, TX 78666--6460
NSF Award
2332113 – STTR Phase I
Award amount to date
$274,986
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project addresses the growing demand for "beyond lithium (Li)-ion" technologies by developing Potassium (K) Ion Batteries (KIB) as sustainable alternatives for Lithium (Li)-Ion Batteries (LIBs). In 2022, the market for Lithium-Iron Phosphate (LFP) batteries was valued at $12.5 billion, and projections suggest it will reach $52.7 billion by 2030, with a notable 19.7% compound annual growth rate (CAGR) from 2023 to 2030. The main driver behind this growth is the increasing adoption of electric vehicles (EVs). KIBs have the potential to become a cost-effective performance alternative to LIBs in EV and stationary applications with a domestic materials supply chain. The primary objective of this project is to enhance KIB performance, particularly focusing on enabling fast charge cycling for EVs applications. This endeavor aligns with the pursuit of a sustainable energy future, reduced dependence on critical materials, and the promotion of economic growth.
The intellectual merit of this project addresses a key question in ?beyond Li-ion? energy storage systems: Why do non-Li architectures, that should in principle function as well as Li architectures, fall short at faster charging rates and how can this be resolved? While individual non-Li components (cathode, anode, and electrolyte) are highly promising in terms of charge transfer and storage behavior, why does the holistic system fall short? In a broader sense, resolving this quandary could potentially enable other earth abundant non-Li architectures to become viable, enabling domestically sourced energy systems to flourish. The commercially focused effort operates at the core of structure-functional properties relations within non-Li systems, where there is markedly much less understanding versus existing LIBs. The project will unravel key structure-properties relations in the nominally more reactive K-based architectures. This collaborative effort will allow for a broad spectrum of learning, starting at basic mechanistic insight at meso scale and advancing to commercially relevant full KIB pouch cell testing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GROW OYSTER REEFS, LLC
SBIR Phase I: CAS: Biomimetic 3D Printed Metal Mold to Mass Produce Dry-Pressed, Modular, Biophilic Concrete Reef Substrate
Contact
4400 MECHUMS SCHOOL HL
Charlottesville, VA 22903--6951
NSF Award
2334667 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is focused on the development of an innovative 3D printed metal mold that works with industry standard concrete block production machinery to mass produce dry-cast, nature-based, concrete reef restoration substrate units. These modular units will be suitable for use for shoreline protection and ecosystem restoration along estuaries, rivers and vulnerable coastlines. Offshore, these units will provide the US offshore wind industry with the means to restore the seabed, while protecting cables, creating sanctuary reefs, increasing biodiversity, and improving water quality. Produced by existing concrete block manufacturers in coastal locations, or on-site, using the novel metal molds, the substrates, located in the inter-tidal zone attract and protect embryonic shellfish including oysters, mussels and clams, and a multitude of other aquatic organisms including crabs, fish, and submerged aquatic vegetation. In deep water, the same substrate units attract abundant cold-water corals and sponges. Working with nature, these units can help protect coastal communities from the impact of climate change, storm surge, rising water levels, and erosion ? creating jobs in concrete fabrication, restoring wetlands, reviving fisheries and commercial aquaculture, and increasing revenues from tourism ? with reefs teeming with life.
This SBIR Phase 1 project encompasses the design and fabrication of an intricate 3-D printed steel mold suitable for the production of dry pressed, biophilic concrete, modular shoreline protection and aquatic ecosystem restoration units. This project addresses considerations of ecological impacts, technical constraints in the concrete industry and both offshore and coastal infrastructure construction practices. Additive metal manufacturing will be used to fabricate the mold. Biomimetics, learning from the reef-building capacities of oysters, corals and other calcitic organisms, will inform the geometrically complex surfaces of the dry-cast, calcium carbonate rich, modular unit produced by the mold. The cast will resemble the benthic topography of a reef, providing a stable substrate for larvae that supports their growth from spat to maturity, providing protection from predators. Computational fluid dynamics (CFD) simulations will be used to examine water flow within and around the larval settlement surfaces. The unit will include fissures, cavities, cracks and crevices, dimples, linear channels, and large and small holes to provide a variety of interstitial spaces at multiple scales (micro and macro) that sustain multi-species cooperation in a diverse aquatic ecosystem.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GUARDIANSAT LLC
STTR Phase I: Space Debris Awareness Spectrum
Contact
512 FARRAGUT HOUSE RD
Bethany Beach, DE 19930--8018
NSF Award
2227213 – STTR Phase I
Award amount to date
$273,332
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will develop methods for space-based detection of orbital debris. This technology may decrease risks of collisions in space through real-time, accurate identification and modeling of objects within the respective orbits of the spacecraft. The system will also assist with potential path deviations. With the proposed space-based debris awareness technology, techniques could be employed to prevent future collisions and debris damage. A function of such a system could be for designating objects or debris that require emergency orbital removal due to the threats they pose to critical equipment. Additionally, the proposed systems can be used to detect and avoid kinetic attacks as well as the debris fields generated by them. Further, the proposed onboard sensors may detect a broad range of object characteristics, including size, velocity, composition, origin, and intent. Moreover, the solution will assist in intelligence gathering and identifying parties responsible for collisions. The proposed solution addresses the above-stated concerns by integrating orbital debris awareness platforms on host space vehicles to serve as watchdogs for the geostationary and surrounding orbital altitudes.
This STTR Phase I project proposes to investigate optimal methods for onboard satellite sensor systems to obtain full spherical space awareness for the host satellites, and thereby allow for better predictive and reactive collision avoidance of hostile threats and orbital debris. This technology could advance novel and transformative solutions for eliminating the threat of satellite collisions with orbital debris and enhance space awareness. The technology will improve space operation risk management margins and permit the space industry's safe growth. The proposed work will include research in three (3) key areas: 1) characterizing the debris environment with regard to detection and tracking in the microwave and optical spectrums using the aggregation of data from sensors currently in orbit; 2) identifying and prescribing optimal detection/tracking methods and technologies within the microwave spectrum to permit sensing of sub-centimeter-sized objects; and 3) pinpointing detection/tracking methods and technologies within the optical spectrum to allow sensing of sub-10 cm sized objects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
H-BAR INSTRUMENTS, LLC
SBIR Phase I: Liquid Helium Transmission Electron Microscopy (TEM) Sample Holder for Atomic Imaging of Next-Generation Materials
Contact
625 REVENA PL
Ann Arbor, MI 48103--3639
NSF Award
2322155 – SBIR Phase I
Award amount to date
$274,771
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research Phase I project aims to enable atomic- and nano-scale imaging of materials and devices at temperatures as low as 10 K through the development of a stable liquid helium transmission electron microscope (TEM) specimen holder. Though TEM imaging modalities are amongst the most powerful metrology tools used in materials science, a long-standing lack of stable ultra-low temperature capabilities limits the range of their application to materials and technologies that operate at relatively high temperatures. Stable ultra-low-temperature capabilities are urgently needed for state-of-the-art TEM machines to enable scientific discovery and development across a broad range of emerging, previously inaccessible fields. This project targets and expands the electron microscopy market (expected to exceed $10 billion by 2028) which is rapidly growing in tandem with metrology needs of semiconductor, quantum device, renewable energy, and life-sciences markets.
This project includes the development and testing of a novel cryogenic specimen holder with high stability as well as the quantification of high-resolution TEM imaging and stability metrics at liquid helium temperatures. To successfully gather atomic resolution or high-quality spectroscopic data, high thermal and vibrational stability, long hold times, and precise temperature control are necessary. Current low-temperature holders are not only incapable of reaching cold enough temperatures, but they suffer from significant instabilities and thermal losses, heavily affecting image resolution. They rely on small cryogenic dewars which lead to severe temperature fluctuations and vibrations as the unstable cryogen (liquid helium) rapidly evaporates. This project incorporates an innovative design with controlled liquid helium flow cooling, vibration decoupling, and precise temperature regulation over long hold times. The technology will result in the development of a commercial instrument that turns any TEM into an ultra-low-temperature imaging platform capable of characterizing novel materials for next-generation technologies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HELIX EARTH TECHNOLOGIES INC
SBIR Phase I: Retrofit Dehumidifiers to Enable Greater than 50% Air Conditioner Energy Savings Via Elimination of Latent Loads
Contact
1628 ELGIN ST
Houston, TX 77004--2836
NSF Award
2325126 – SBIR Phase I
Award amount to date
$274,921
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project focuses on the development of retrofit dehumidification systems for air conditioners (AC) to reduce latent loads and save more than 50% of the energy consumed by AC systems. Air conditioners consume more than $230 billion in energy annually worldwide, accounting for more than 4% of total global carbon dioxide (CO2) emissions. The goal of this SBIR Phase I project is to develop a drop-in solution for existing AC infrastructure to enable substantial reductions in energy use and operating costs for AC systems. These drop-in dehumidification systems have the potential to save the industry > $100 billion in energy costs and up to 1 gigaton of CO2 emissions annually. The innovation developed in this project will help mitigate the effects of global climate change, while simultaneously ensuring access to affordable cooling systems globally by helping substantially reduce operating costs for AC systems.
The intellectual merit of this project is in its utilization of a droplet filtration method, initially pioneered for space applications. This filtration method enables retrofit dehumidifiers that are powered by a liquid desiccant spray reactor that enables high-rate, high-efficiency dehumidification. The dehumidification approach in this project is differentiated from other state-of-the-art methods on the market today due to the method of liquid desiccant deployment, which enables high surface area contact between liquids and gasses. The filtration method enables high-efficiency dehumidification by capturing nearly 100% of fine droplets (<30 micrometers) at very low pressure drop (<100 Pascals) using three distinct filter length-scales. The meter-scale filters are additively manufactured with millimeter-scale helical pores that enable low-pressure-drop inertial capture of fine droplets, which are absorbed in the micrometer-scale porous medium of the filters via capillary forces. These filters enable dehumidifiers that operate 6-8x more efficiently than other methods on the market today and have very high process rates, resulting in a 20-fold reduction in system volume compared to other technologies. This Phase I project will mature the dehumidifiers from a lab-scale proof of concept to a system prototype for a window-scale AC unit.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HENDTECH LLC
SBIR Phase I: Computer Vision for Merchandizing Forest Products
Contact
111 BELLS CREEK DR
Simpsonville, SC 29681--4294
NSF Award
2329601 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from applying leading-edge artificial intelligence technology to the logging industry. Logging (wood harvesting) is the first step in the production of paper packaging, health and hygiene products, clothing fibers, and even resins that are used in our technology devices. The forest products industry employs nearly one million people and contributes hundreds of billions of dollars to the US economy each year. Yet, there has been very little technological innovation in logging in recent decades. This project aims to research and develop computer vision technology that will augment a person?s ability to grade harvested trees accurately. The resulting technology may increase the number of jobs available to unskilled workers in rural areas, ensure effective and efficient utilization of harvested trees, and increase revenues for thousands of small businesses in the wood supply chain.
This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate the feasibility of a computer vision system to augment the skills of human-machine operators in the tasks of grading and sorting logs. During the project, a suitable domain-specific dataset will be established, a new chain of computer vision models will be created and trained, and a fully integrated prototype will be deployed in a remote environment. To achieve these goals, the company will research the use of self-supervised learning to expedite the creation of a domain-specific dataset, along with adaptable chains of models and model compression to enable efficient inference at the logging site (i.e., without the need for cloud computing resources). The company will also create new methods for determining specific objects of interest (such as defects) and assessing the grade of each log. If successful, the project will demonstrate a computer vision system that is able to identify and locate specific logs of interest, track the logs, assess each log?s dimensions, locate defects on the logs, accurately determine a grade for each log, and give visual feedback to a machine operator ? all within the operator?s brief decision timeframe.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HERA HEALTH SOLUTIONS INC.
SBIR Phase I: Bio-erodible Contraceptive-Releasing Implant
Contact
11141 WELLSHIRE LN
Frisco, TX 75035--3637
NSF Award
2304404 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to provide a highly effective and long-acting implantable contraceptive for the 61 million American women in their childbearing years (ages 15 to 44), 70% of whom are at risk for unintended pregnancies. Unintended pregnancies accounted for half of the total pregnancies in 2022, and over 60% of unplanned pregnancies end in abortion, with an estimated 45% of abortions being unsafe, resulting in 5-13% of all maternal fatalities. Today, an estimated 7.5 million women aged 15?49 receive a treatment or hormonal drug via long-term subcutaneous arm implants. Once they reach the end of their lifespan, these implants must be removed, and complications can quickly arise. Not only are these procedures expensive, but they leave behind heavy bruising and scarring and some instances even require an operation for removal. The proposed product is the world?s first biodegradable contraceptive-releasing implant. The technology combines Food and Drug Administration (FDA)-approved material with a generic drug already on the market. It uses novel manufacturing methods and biodegradable materials, eliminating the need for implant removal and enabling the proper timing and therapeutic dosage. This novel delivery drug technology can be applied to different drug treatments in a sustainable and affordable manner.
This Small Business Innovation Research (SBIR) Phase I project aims to advance the future of long-acting reversible contraception by creating a biodegradable arm implant that delivers a consistent hormone dose and does not have to be surgically removed. The goal of this SBIR Phase I project is to characterize the drug delivery scaffold and demonstrate its utility. This project will de-risk the prototype to be used in Pre-Investigational New Drug Applications (IND) studies required by the FDA. The Phase I strategy will be two-fold: (1) de-risking operations by finalizing the prototype after evaluating the physical and chemical properties and (2) test the long-acting contraception implant prototype in a clinically relevant biological model to provide the necessary data for a successful IND launch. Progress of this project will provide a solid foundation for advancing the biodegradable contraception product toward commercial utility.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HEXAKIT, INC.
STTR Phase I: Cardiotropic Atorvastatin Liposomes for Myocardial Reperfusion Injury
Contact
2401 CHEVAL POINTE DR
Edmond, OK 73034--6085
NSF Award
2300933 – STTR Phase I
Award amount to date
$275,000
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project pertains to the critical need for pharmacologic treatments in large populations that suffer from coronary artery disease and that are subjected to procedures such as angioplasty or bypass surgery. While effective in correcting the reduced flow of blood to the heart tissue, these interventions also cause tissue damage categorized as ischemia reperfusion injury (IRI). A pharmacologic treatment is critically needed to address this residual injury that is a major cause of rehospitalization, prolonged hospital-stay, heart failure, and mortality. By deploying the proposed technology of heart-targeted vehicle for drug delivery, it will be possible to achieve effective cardioprotection, which will reduce patient distress and economic burden on the healthcare system for patients undergoing reperfusion procedures. This disruptive technology will impact myocardial reperfusion injury market worth $1.6 billion and influence the standard of care for over 1 million coronary artery disease patients that are treated by angioplasty or bypass surgery each year in the United States.
This Small Business Technology Transfer (STTR) Phase I project will develop Cardiotropic Atorvastatin Liposomes (CATLIP) to deliver cardioprotective benefits of atorvastatin to the heart, safely and effectively. The innovative CATLIP technology will deliver therapeutic amounts of atorvastatin to the heart tissue for treatment of IRI. Current methods of administration are inadequate in reaching the drug concentration needed for clinical efficacy. Serving a long-term goal of developing a myocardia-targeted treatment to mitigate IRI, the research objective of this proof-of-principle project is to attain effective delivery of atorvastatin in the heart tissue. CATLIP?s targeting approach is based on a small molecule targeting vector that selectively binds to the cardiomyosin exposed in the injured heart tissue. The research team will prepare and characterize liposomes loaded with atorvastatin and modified on the surface with the cardiotropic targeting vector. This preparation will be tested in an animal model of myocardial infraction to determine atorvastatin delivery in the heart tissue. Successful implementation of this project will create a proprietary product for treatment of IRI of the heart and demonstrate the potential of a targeting technology for application with other drugs for the same medical condition.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HISTONE THERAPEUTICS CORP.
SBIR Phase I: Epigenetic Remodeling of Natural Killer (NK) Cells for Blood Cancer Therapies
Contact
5757 S OAKLAWN PL
Seattle, WA 98118--3048
NSF Award
2303792 – SBIR Phase I
Award amount to date
$273,388
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to produce better alternatives to cancer treatment. The new solution will take advantage of the body?s natural anticancer defense system, an immune cell called a natural killer cell or NK cell. NK cells are able to recognize almost any cancerous cell in the body and can target both solid tumors and blood cancers. This gives NK cells a broad appeal for the treatment of many types of cancer. The team proposes a broad-spectrum cancer treatment by modifying NK cells to be more reactive to cancerous cells in the body. These modified NK cells could potentially be combined with current therapies to enhance their effectiveness, without increasing side-effects in patients. This project has the potential to benefit millions of people, especially in the United States where it is estimated that 40% of individuals will be diagnosed with cancer at some point in their life.
This project will use a patented epigenetic modifier to enhance the tumor killing abilities of NK cells. Many immune cell-based therapies rely on altering the genetic code of the cell that will be used to treat disease. However, there are associated risks in altering the genetic code and often the cell therapy may only work on a very specific subtype of cancer. Epigenetic modifiers do not change the underlying DNA sequence but can effectively alter gene expression. Furthermore, NK cells can target a broad-spectrum of cancers but in many cancer patients their tumor killing ability is often suppressed. The research goal is to use the patented epigenetic modifier to increase expression of key NK cells genes that will make them more sensitive to detecting and killing cancer cells. After targeting key genes, NK cells will be assessed for increased tumor killing ability and for how long this ability persists. More specifically, this project seeks to demonstrate that NK cells taken from a healthy donor can be epigenetically altered to enhance their natural function of killing tumor cells. This solution will lay the groundwork to develop a NK cell therapy where NK cells isolated from healthy donors are epigenetically modified to enhance their activity, then delivered to cancer patients to hunt and kill their cancer cells.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HOOFPRINT BIOME, INC.
SBIR Phase I: Bioengineering probiotic yeast to mitigate methane emissions from cattle
Contact
840 OVAL DRIVE
Raleigh, NC 27606-
NSF Award
2322126 – SBIR Phase I
Award amount to date
$273,111
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project develops a technology that could drastically reduce the impact of livestock production on the environment. Methane emissions from livestock account for over 10% of global greenhouse gas emissions, which must be reduced significantly in order to meet climate change reduction targets. Simultaneously, profit margins in beef and dairy farming are slim, leaving farmers unable to adopt climate-friendly practices that are too costly. This product could increase the profitability of cattle farming while playing a key role in achieving net zero emissions from the food system.
This team develops enzymes to be secreted from a probiotic yeast to eliminate methane emissions from cattle. The company has previously identified a set of enzymes that restrict methane production in the rumen of cattle. This project will further develop and package these enzymes in a probiotic yeast strain which has already been shown to increase milk yield by over 5%, thereby offering a dual benefit to the farmers. Project success requires a) screening an enzyme library to identify lead candidates for reduction of rumen methane, b) optimizing enzymes for further methane reduction, and c) demonstrating enzyme secretion and cost-efficient enzyme delivery by the probiotic yeast. Completion of these objectives will yield a product that will decrease cattle methane emissions by a minimum of 30%, and potentially by up to 98%, while simultaneously improving the health and productivity of cattle.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HOVERR INC.
SBIR Phase I: Quantum Propulsion
Contact
6520 GRAYSTONE MEADOW CIR
San Jose, CA 95120--1630
NSF Award
2303988 – SBIR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this SBIR project is to develop and commercialize a propellant-less electric vacuum thruster?a novel and cleaner method for object propulsion. This inventive thruster employs electronic components and sources to move objects, eliminating the need for traditional fuel. Successfully achieving these goals could potentially bring about a revolutionary transformation in the transportation industry. For example, a fully developed thruster could be used as a boost-on device for a wide range of current motors to increase efficiency (reduce energy consumption) while increasing range. Beyond developing the proposed thruster device into a usable product, this project also is expected to deepen the scientific understanding of its operational principles. All these enhancements hold the promise of enabling the device to move heavier objects with reduced energy consumption. Due to its suitability for use both on Earth and in space, a developed thruster product has the potential to improve the efficiency of all modes of transportation, including automobiles, boats, and spacecrafts.
This SBIR Phase I project proposes to develop and optimize the proposed electric thruster device, an exciting new way to move objects. Currently, objects and vehicles are moved using fuel-based propulsion technologies. This, coupled with the low efficiency of hydrocarbon and electric motor systems, is bad for the environment and not sustainable. This proposed product and technology platform presents a new type of cleaner propulsion technology. The proposed electric drive works by accelerating electrons between closely spaced electrodes in a capacitor using electric fields generated by a battery. The accelerated electrons form a Rindler horizon (Unruh Effect) behind the cathode of the capacitor which alter vacuum fluctuations within this zone. This modification creates a force that propels objects forward. The thruster device is expected to be cost-effective and lightweight, and initial experimental results appear promising. The project's goals are to (1) develop and improve a prototype using state-of-the-art materials and several design refinements, and (2) to confirm the technology's performance through third party validation. Demonstrating the thruster device's reliability and scalability is expected to provide a path to commercialization. Through development, optimization and validation, this project not only pushes the boundaries of propulsion through development of a usable product but also presents an exciting path as a platform technology with future potential for a wide range of practical, efficient, and environmental transportation solutions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Himet Materials LLC
STTR Phase I: Wafer-Integrated Soft Magnetic Composite Films for Inductors with High Power Density and Efficiency
Contact
16433 MONTEREY ST. SUITE 120
Morgan Hill, CA 95037--7168
NSF Award
2304631 – STTR Phase I
Award amount to date
$274,972
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to revolutionize the miniature-powered Integrated Circuit (IC) converter market, widely used in cellular phones, Internet of Things devices, and microsensors. The technology will provide form factor reductions of various modules, leading to the further miniaturization of on-chip components. A manufacturing facility can service several IC companies by providing foundry capabilities to integrate inductors according to each customer?s design. The technology can provide US manufacturers of such devices with a significant competitive edge in the very large mobile electronics and miniature electronics markets both in commercial and defense markets. Establishing manufacturing capability in the US will support a revival of component packaging and back-end integration business.
Mobile device miniaturization is increasing at a rapid rate. In on-board power converters, passive components such as inductors and capacitors are among the largest components. The non-availability of IC-compatible, low-cost, soft magnetic cores with low loss, high frequency (>10MHz), and high saturation magnetization limits the implementation of on-chip inductors. The project aims to create innovative, soft magnetic composite (SMC) materials for inductor cores. IC-compatible high-performance SMC films, with thicknesses that can be scaled to 50 microns and above without losing performance, will be developed for the first time. The project's initial goal will be to develop physical and electrochemical synthesis methodologies for high magnetic moment, low loss, SMC materials that can be used to fabricate on-chip inductors, replacing ferrite core-based inductors in circuits. The approach can be scaled to handle different ranges of power and can be integrated on wafers, package substrates, or boards. These cores will enable inductor thickness to be reduced by at least 10 times for use in low form factor, point-of-use, direct current (DC) to DC power converters and IC voltage regulator circuitry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IDEA51, LLC
SBIR Phase I: A Method to Expand Personalized Experiential Learning
Contact
1151 W MILLER ST
Boise, ID 83702--6965
NSF Award
2150912 – SBIR Phase I
Award amount to date
$245,844
Start / end date
06/01/2022 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project is to improve education and experiential learning. The proposed tool will support both synchronous and asynchronous learning while providing students with the opportunity to engage independently and connect their learning to internships, job shadows, service projects, and other real-world learning experiences. This project will enhance teacher capacity to guide and assess student learning, increase transparency and objectivity in assessment, and expand the learning ecosystem of schools by empowering students to engage in and validate authentic, real-world learning experience.
This Small Business Innovation Research (SBIR) Phase I project will develop a novel competency-based evaluation tool and learner recommendation engine designed to: assess a range of currently needed skills and competencies, aggregate assessment data for the purpose of generating a comprehensive learner record in real time, and generate personalized competency pathways and recommendations for learning and growth. The key intellectual merits of this proposal are the formulas used to aggregate assessment data over time and the algorithms used to generate personalized competency pathways and learner recommendations. The technical challenges are the development and testing of the associated algorithms to guide and evaluate learning in both academic and authentic, real-world contexts. Research conducted during this Phase I project enable testing and refining of the data aggregation formulas utilized by the assessment tool, as well as optimization of the learner recommendation algorithms used for the creation of personalized competency pathways.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IIAM CORPORATION
SBIR Phase I: Predictive Analytics and Machine Learning Modeling for New Patient Cancer Referrals
Contact
27 ANDERSON ST
Boston, MA 02114--3637
NSF Award
2304498 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to decrease patient referral wait times. Referral wait times are often long since offices need to retrieve a large amount of medical information on a patient before they are seen by a doctor. Unfortunately, medical records are often not stored in one place, making it difficult to gather the needed medical histories. Quick and complete medical record retrieval is especially important for cancer patients, whose conditions can quickly change. Critical patients need to be seen by doctors in a timely manner to begin treatment. The company is creating a technology that could help quickly retrieve medical information to decrease the time from referral to appointment. The company expects these algorithms to expedite document reconciliation by 7 days, thereby reducing the time from referral for the new patient appointment by 1 week. By facilitating quicker and more meaningful record retrieval, the algorithms are expected to improve treatment initiation by 7-14 days. The company plans to commercialize its technology for use in large academic healthcare systems, first focusing on those with high-volume cancer centers.
This Small Business Innovation Research (SBIR) Phase I project will advance a new patient referral predictive analytics software platform for cancer centers. This platform will streamline referrals, increase resource utilization, and optimize care pathways. The company?s deep learning algorithms will be developed to streamline record retrieval for new patient appointments and recognize critical medical conditions, resource capacity, local referral patterns, and at-risk socioeconomic factors. This intervention may reduce the mortality risk by 3.2-6.4% per week per patient. To achieve these objectives, the software will contain two major components a cloud-based platform for medical information exchange and an machine learning (ML)-based analytics platform. Once fully developed and launched, it is anticipated that real-world deidentified and aggregated clinical data from the exchange platform will be used to further train and refine the ML model. Prior to this stage, data from large publicly available and multi-institutional databases will be used to provide training data points for the model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ILLUMINANT SURGICAL, INC.
SBIR Phase I: Novel Camera-Projector Device Leveraging Markerless Skin Registration and Projected Augmented Reality Software to Enable Navigation for Minimally Invasive Procedures
Contact
855 EL CAMINO REAL
Palo Alto, CA 94301--2305
NSF Award
2321906 – SBIR Phase I
Award amount to date
$274,865
Start / end date
01/15/2024 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is a novel projection-based platform, enabling direct visual mapping during surgical procedures. The project aims to develop a system that directly projects images that guide surgical intervention in real time onto the patient. By enabling direct visualization and by requiring minimal consumable components, the project aims to address usability and cost barriers that hinder adoption of current surgical mapping platforms. This product targets the spinal lumbar surgical market accounting for nearly 200,000 U.S. procedures each year. Spinal surgery requires high levels of accuracy, with inaccurate interventions resulting in reoperation rates of up to 16%, and readmissions costing nearly $15 billion in both direct and indirect costs, as well as poorer patient outcomes.
This Small Business Innovation Research (SBIR) Phase I project aims to develop and validate a novel, projection-based, surgical navigation platform. The system utilizes three dimensional sensors to non-invasively orient to each individual patient and project visual anatomical references and guidance onto their skin surface, aiding surgeons in real time. This project will develop and validate the hardware and software to repeatably and reliably detect and align radiological images onto patients. It will also develop and validate the core algorithms needed to ensure the required accuracy and system performance suitable for surgical use. The prototype will be tested on bench-top phantoms and its performance compared to the defined industry-standard accuracy measures required for lumbar spinal surgical procedures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IMPERIUM TECHNOLOGIES, INC.
SBIR Phase I: An Industrial Internet of Things (IIoT) Electromechanical Steam Trap for Greenhouse Gas Reduction and Energy Savings
Contact
1900 VALLE VERDE DR.
Cedar Park, TX 78641--2642
NSF Award
2324530 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project addresses a longstanding steam industry problem, the undetectable leaking of steam traps. In North America, $500 billion worth of steam is made every year for diverse industries: oil & gas, chemicals, food, medical, utilities, etc. Around 20% of the lost steam contributes to 1.4 billion metric tons of greenhouse gas which would be enough to generate electricity for 15 million homes. The key steam system issue comes from failed or underperforming traps that go undetected. A correctly working steam system is a closed loop environment that maintains the required pressure and temperature for proper steam flow. Over time, steam converts to liquid condensation and is captured in traps to be cleared on a regular basis to maintain the steam system performance integrity. In this project, a new trap system is designed to replace the current passive mechanical technology. The system integrates an active electromechanical system and remote monitoring using Industrial Internet of Things (IIoT) sensors, providing steam operators with real-time monitoring and real-time data performance to identify steam trap and system issues for immediate resolution.
This SBIR Phase I project identifies the known flaws of current steam trap design and operations by applying innovative solutions to the design a new trap. Current traps are purely mechanical that, when exposed to corrosive, high-pressure and temperature environments with repeated water discharge, wear out for a shortened lifespan. This technology may result into an optimal-performing steam system that continuously monitors steam flow for the best operational performance and reliable water removal. When a trap fails and steam is discharged, energy is lost, requiring boilers to consume added fossil fuels to generate additional replacement steam with unwanted greenhouse gas emissions. The new steam trap will (1) improve reliability by doubling the trap lifespan from 2-4 years to 10 years, (2) reduce the number of moving parts, (3) incorporate electronic sensors to monitor water condensation levels versus relying on mechanical floats or discs to detect and discharge condensate, and (4) provide real-time monitoring to collect and track unmonitored operational parameters continuously. This system will retrofit with existing traps for cost-effective operations and to will reduce or eliminate greenhouse gas emissions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INAEDIS, INC
STTR Phase I: Rapid Dehydration and Stabilization of Biopharmaceutical Formulations at Room Temperature
Contact
78 JACKSON AVE
Princeton, NJ 08540--1674
NSF Award
2304461 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to serve international markets in drug formulation and delivery by allowing the pharmaceutical industry to avoid the critical vulnerabilities that plague traditional cold chain systems. By offering a robust solution for thermal stabilization, the technology will have far-reaching effects on population health and immunization. Additionally, the solution will substantially reduce the wastage of pharmaceuticals caused by inadequate temperature control during transportation, resulting in an annual equivalent of $35 billion. By providing an alternative to cold chain logistics, the technology will drive economic benefits in both pharmaceutical formulation and distribution, cementing the position of the US as an innovator and linchpin of the global pharmaceutical industry. This innovative method for the stabilization of biopharmaceutical formulations will improve the safety, reliability, quality, and availability of vital medicines that will facilitate vaccine immunization programs, prolong the safe shelf-life of biologics and vaccines, and reduce product wastage, the carbon footprint, and environmental impacts of pharmaceutical transportation and storage.
This project seeks to establish an innovative. room-temperature dehydration process that improves the thermal stability of biopharmaceuticals and circumvents the need for a cold chain supply. Cold chain breach has been associated with cases of vaccine-preventable disease or even adverse events following immunization, with one study reporting health issues suffered by 7% of patients administered with temperature-compromised vaccines (15% of these health issues were considered serious). Dehydration is a known thermal stabilization method, but current drying technologies are time-consuming, poorly scalable, energy inefficient, and potentially destructive due to the application of high stresses. This project focuses on thermal stabilization of formulation for robust vaccine transportation and storage solutions. The research and development establishes the efficacy, reliability, and applicability of rapid Room Temperature Aerosol Dehydration (RTAD) as a commercially promising platform for the dehydration of various biologic drug molecules. The application of RTAD to proteins and nucleic acids is investigated with two major classes of biological molecules. The quality and chemical/biological integrity of the dehydrated formulations will be demonstrated. Also, the biopharmaceuticals will be microencapsulated in a controllable manner. This effort will provide proof of concept supporting further RTAD technology development.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INDUSTRIAL ANALYTICS AND MODELING, INC.
SBIR Phase I: The Automated Forensic Economist: Towards Affordability, Transparency, and Efficiency in Forensic Economics
Contact
1601 E CESAR CHAVEZ ST
Austin, TX 78702--4585
NSF Award
2304596 – SBIR Phase I
Award amount to date
$257,604
Start / end date
09/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial impacts of this Small Business Innovation Research (SBIR) Phase I project capitalizes on the inefficiencies of the existing expert witness industry and brings affordability, versatility (unlimited scenario generation), simplicity, transparency, and
standardization to legal proceedings. The team will develop an ecosystem that will keep experts accountable and credible (using a peer-review system) and allow lawyers and their clients to be better informed with enhanced access to high-quality services. The team has validated that a profitable market exists for a standardized and automated method of evaluating economic losses in civil legal disputes in an automated, fast,
inexpensive, standard, and objective manner. The quality of expert witness services will increase across the industry, as experts will be able to focus more deeply on the more disputed issues of litigation rather than the automatable portions of the estimation process. Better-informed attorneys and firms will be able to counsel their clients and develop better legal strategies throughout the process, while judicial personnel and juries will benefit from improved legal and expert witness services, gaining access to more standardized information to make better, more-informed decisions and be less susceptible to biased or inaccurate opinions.
This SBIR Phase I project consists of a set of deterministic algorithms intaking user inputs (facts and data regarding parties in a lawsuit) and retrieving relevant data series from pre-harmonized external databases, which are then processed through a set of economic and statistical computations, producing a set of outputs, including an estimate of financial gains (losses) for the lawsuit characterized by user inputs. The proposed innovation improves on the inefficiencies of the existing expert witness industry in several dimensions, and as a result brings affordability, versatility, simplicity, transparency, and standardization. In Phase I, the algorithm and a usable prototype for capturing employment and personal injury-related financial gains (losses) estimation will be developed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INIA BIOSCIENCES, INC.
STTR Phase I: Non-invasive focused ultrasound treatment to modulate the immune system for acute and chronic kidney rejection
Contact
1209 N ORANGE ST
Wilmington, DE 19801--1120
NSF Award
2312694 – STTR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a novel medical device therapy for improving the clinical outcomes of patients receiving organ transplants. Over 100,000 kidney transplant procedures are performed worldwide each year, with up to 20% of patients experiencing rejection. Existing drug treatments, including immunosuppressants, often entail significant side effects with a high financial cost of nearly $30,000 per year per patient. This project aims to develop an external system for reducing inflammatory responses thereby reducing adverse events associated with the transplant and extending the lifetime of the new organ. Beyond kidney organ transplantation, the technology provides potential extensibility for other organ transplants as well as addressing various chronic inflammatory diseases.
This Small Business Technology Transfer (STTR) Phase I project aims to develop a novel ultrasound-based medical device therapy for reducing post-transplant organ rejection. The external system stimulates targeted nerves in the spleen to modulate the immune system through established physiologic pathways. The proposal aims to optimize various ultrasonic parameters in a transplant model to further development towards a functional prototype. The key objectives include 1) developing a pre-clinical transducer delivering the desired therapeutic ultrasonic waveform to the targeted splenic nerves, 2) optimizing the treatment parameters using an accepted preclinical skin allograft model, and 3) validating the reduction in pro-inflammatory cytokines in situ in accepted preclinical models. The results of this proposal will demonstrate the safety and feasibility of this technological approach toward eventual clinical patient translation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INNOTECH SYSTEMS LLC
SBIR Phase I: Precision Docking for Automated Charging of Unmanned Platforms and Electric Vehicles
Contact
2834 PARAISO WAY
La Crescenta, CA 91214--2018
NSF Award
2230483 – SBIR Phase I
Award amount to date
$274,048
Start / end date
06/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable automated and autonomous charging of a wide array of electric vehicles (e.g., electrified robots, cars and trucks, and drones) in adverse weather conditions. Examples include autonomous systems used in farming and logistics, electric vehicles in ports, and electric trucks. Despite tremendous progress and the proliferation of electric vehicles, an adequate, cost-effective, autonomous, and available charging infrastructure is currently lacking. This gap between need and availability is far worse in high power applications such as trucking. The proposed technology increases the deployment of autonomous mobile robots and drones in industries like agriculture and logistics which are currently suffering from labor issues. The technology may increase the deployment rate of commercial electric vehicle fleets that can contribute to reducing greenhouse gasses.
This SBIR Phase I project proposes to solve a key problem in the automation of the charging process for electric vehicles, namely precision localization and docking in adverse weather conditions. The conventional methods of localization for docking (e.g., infrared or vision-based) have limitations such as insufficient precision and limited performance in less-than-optimal environmental conditions. This team presents a high precision automated docking solution in the presence of clutter and removes objects that are potentially harming the Line of Sight (LOS). The goals of the proposed research and development are: 1) establishing that time averaged, multi-path signal characteristics in multiple spectral bands can identify locations within a known map or during a close proximity approach of the electric vehicle to the charger; 2) developing models suitable for Monte-Carlo modeling and simulation of an indoor environment or region in proximity of a charger benchmarked by some measurements and using such simulations for verification success; and 3) developing a high precision transponder based on wideband signaling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSILICOM LLC
SBIR Phase I: Knowledge Graph-powered Information Retrieval and Causal Inference
Contact
8117 VIBURNUM CT
Tallahassee, FL 32312--5701
NSF Award
2335357 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is as follows. The exponential growth of scientific literature poses two critical challenges: (1) missing important prior studies during research design can lead to resource and time wastage, incorrect conclusions, and missed discoveries, and (2) effectively utilizing the vast volume of scientific knowledge in raw text form has become increasingly difficult. This project aims to build disruptive, commercially valuable products that address these challenges, benefiting the pharmaceutical industry and academic research. In addition, the success of the project in developing advanced AI technologies will have a significant impact on the growth and development of the AI industry in Tallahassee, FL, and the broader southeast region of the United States.
This Small Business Innovation Research (SBIR) Phase I project aims to develop AI-powered, commercially viable applications enabled by a large-scale biomedical knowledge graph (KG) constructed recently using an award-winning natural language processing (NLP) pipeline. The KG has been further transformed into a causal KG by integrating causal relations and enhanced by incorporating data from 40 public databases and analysis results of some commonly used genomics datasets. To facilitate seamless access to the KG, the project team has developed a versatile query interface named iExplore. This interface enables highly accurate information retrieval and supports causal inference, providing users with valuable insights. In the current project, Insilicom LLC will further increase the coverage of the KG and build a novel literature alert system called iPulse. By combining the advancements in AI, the richness of the knowledge graph, and the utility of the query interface and literature alert system, this project will result in practical and commercially viable applications that will revolutionize the way biomedical knowledge is accessed, interpreted, and utilized.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTELLISAFE ANALYTICS LLC
SBIR Phase I: Comprehensive, Human-Centered, Safety System Using Physiological and Behavioral Sensing to Predict and Prevent Workplace Accidents
Contact
1354 OAKRIDGE ROAD
Mcdonald, PA 15057--2683
NSF Award
2321538 – SBIR Phase I
Award amount to date
$273,369
Start / end date
12/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to better protect workers from hazards in the workplace through the use of wearable technology to identify and predict accidents. Human-factor related accidents account for 80% of injuries and are not being addressed with currently available safety products. This solution utilizes wearable technology to automate the collection of physiological and behavioral data from workers. The data is incorporated into machine learning models to identify safety incidents and near-misses. This innovative approach to worker safety enhances scientific and technological understanding by using machine learning to interpret signals generated by a worker?s physiology and behaviors. Responses to hazards in the workplace are used to trigger alerts that predict and prevent workplace accidents. This safety system provides the basis for machine learning models that predict the likelihood of accidents so safety personnel can intervene before the worker is injured. The goal of this project is to prevent injuries, save lives, and enable companies to realize savings in insurance costs, liabilities, and lost time from the job.
This SBIR Phase I project aims to develop a safety system that uses the human body?s built-in sensors to identify safety hazards. By automating the continuous collection of real-time physiological and behavioral data using wearable technology, machine learning models will be developed to identify safety incidents, enabling the prediction and prevention of accidents. The intellectual merit of the research is to: 1) verify that humans respond in similar, measurable ways to slips and trips, 2) develop machine learning models to accurately identify slips and trips and their intensity, 3) develop machine learning models to assess the risk of future safety accidents, and 4) verify that data can be processed through the entire workflow to provide real-time alerts to the worker and safety personnel. Data will be collected from human subjects subjected to slips and trips using research-grade wearables. The anticipated output of this research will provide the basis for a safety system used to trigger safety alerts and identify risk levels to save lives and prevent accidents related to slips and trips.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTERLUNE CORPORATION
SBIR Phase I: Regolith size sorting technology for space resource utilization
Contact
3220 N 27TH ST
Tacoma, WA 98407--6208
NSF Award
2304616 – SBIR Phase I
Award amount to date
$246,028
Start / end date
10/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a core enabling technology for lunar in situ resource utilization: the ability to sort ?Moon dirt? (lunar regolith) by particle size. Size sorting is an important capability for nearly all in situ resource utilization activities that use lunar regolith as a feedstock material. By enabling raw lunar regolith to be sorted into multiple streams by particle size, the technology will provide appropriate feedstocks for lunar oxygen extraction systems, lunar 3-dimensional printers, and other applications. The use of the Moon?s resources is a disruptive capability that will enable missions there to ?live off the land,? making the development of this technology important for government agencies and industry alike. The many potential applications of lunar in situ resource utilization promise to make this a multi-billion dollar market.
This SBIR Phase I project proposes to develop and demonstrate a novel regolith size sorting system for use on the Moon that has 10x smaller volume, 5x lower mass, and greater reliability than traditional devices such as vibratory sieves (vibrating screens). The project will also develop a new lunar regolith simulant designed to mimic real lunar regolith?s particle size distribution and flow properties. While size sorting on Earth is well understood, size sorting dynamics on the Moon are not well understood and size sorting is identified as a gap in lunar technology road maps. The team will address performance and scalability risks by developing a device which uses rotating paddles to provide centrifugal motion to sieve the particles through a screen. A variety of centrifuge aspect ratios, paddle configurations, and rotational speeds will be tested to optimize throughput. Additionally, blinding (plugging) of the sieve by regolith particles will be characterized at different rotational speeds and addressed, if necessary, by developing and testing anti-blinding features on the rotating paddles, such as brushes and low-friction wipers. Finally, the device will be demonstrated to operate in lunar gravity on a parabolic aircraft flight using the new simulant.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KARIOS TECHNOLOGIES, LLC
SBIR Phase I: Development of a Novel, Sprayable, Large Volume Hydrogel Delivery System Platform
Contact
100 NORWICH ST
Charlottesville, VA 22903--6410
NSF Award
2304462 – SBIR Phase I
Award amount to date
$274,954
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a simplified system for applying compound in situ to form biomaterials during surgical procedures. Controlled biomaterial applications pose significant potential surgical advantages including for anti-adhesion, tissue sealant, and drug delivery purposes. The proposed platform will enable procedural consistency to provide new and improved ways to manage bleeding and reduce scar tissue formation during surgical procedures. This product aims to gain a share of the $1.5 billion adhesion prevention market and $1.2 billion hemostat market, and enable eventual site-specific delivery cells and drugs, depending on the biomaterial delivered.
This Small Business Innovation Research (SBIR) Phase I project will develop a ready-to-use, large volume delivery system for in situ forming biomaterials. The scope of activities includes transferring a novel, proprietary, in situ biomaterial with applicability as a tissue sealant, scar tissue reductant, and drug/cell delivery vehicle, into a novel single use applicator. The prepackaged delivery system will formulate the suspended biomaterial with the resuspension solution using an internal mechanical mechanism which delivers the biomaterial in a controlled aerosolized manner suitable for clinical use. This Phase 1 project aims to complete and validate prototypes with lyophilized biomaterials within good manufacturing practices, engineer the design of the syringe barrel and delivery tips/nozzles, and complete laboratory validation in a manner suitable for first in human use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KCORE ANALYTICS LLC
SBIR Phase I: Artificial Intelligence and Network Theory for Elections
Contact
229 EAST 28TH STREET
New York, NY 10016--8563
NSF Award
2309896 – SBIR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project promotes and enhances transparency in the democratic process. It accomplishes this by developing a social awareness system that can detect, understand, and predict opinion trends within a democratic society. Through the development of cutting-edge artificial intelligence (AI) techniques, the project contributes to scientific and technological knowledge by improving the prediction of election results and societal opinion trends with high accuracy. By employing machine learning, the project aims to surpass the limitations of traditional polling methods and provide a real-time predictor of election outcomes worldwide. The project will address the credibility of news on social media serving to strengthen the resilience of the population against misinformation. In addition, the project demonstrates a commitment to inclusivity by actively seeking the participation of underrepresented minorities.
This Small Business Innovation Research (SBIR) Phase I project aims to predict global elections in real-time through the integration of artificial intelligence, network theory, and big data science. By harnessing the power of advanced machine learning models and analyzing vast amounts of publicly expressed opinions on social media, the team offers accurate forecasts of election outcomes. This approach has the potential to disrupt the conventional polling industry, which faces growing uncertainties and challenges such as declining response rates and inherent biases in sampling. The research objectives entail tackling critical research and development challenges, including predicting voter turnout, effectively sampling rural areas with limited online coverage, filtering out bots and fake news sources, inferring the preferences of undecided voters, adjusting sample weights on a state-by-state basis, addressing the opinions of individuals not active on social media, and mitigating social desirability bias (where respondents conceal their intention to vote for controversial candidates). The anticipated technical results involve the development of a transformative machine learning architecture built upon Graph Neural Networks. The framework enables optimized resource allocation and significantly improves the precision of predictions. Ultimately, the results will empower decision-makers with reliable real-time information, facilitating informed choices, and enhancing the resilience of the democratic process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
L-Infinity Labs, Inc.
SBIR Phase I: Secure Image Recognition and Machine Learning Using Advanced Cryptography
Contact
378 EDMANDS RD
Framingham, MA 01701--3068
NSF Award
2304348 – SBIR Phase I
Award amount to date
$274,356
Start / end date
09/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be a significant step towards resolving the access vs. privacy dilemma of the big data era. The use of people?s biometrics, internet traffic, and financial, medical, and genetic data can enable better crime prevention, targeted ads, and health innovation, but at the expense of privacy. Data may also be too sensitive to be given to third parties. The immediate impact of adopting this technology will be greater security for sensitive image data with easier access to useful inferences. The solution will shift the paradigm of institutions storing sensitive data onsite to one in which even sensitive data is stored and accessed in the cloud. With the capability of private outsourced data analysis will come a marketplace for computational tasks, including machine learning as a service, that will spur research and deliver better results to patients and clients faster and without risk of exposure.
This Small Business Innovation Research (SBIR) Phase I project will adapt existing Deep Neural Network models to use a fully homomorphic encryption scheme to perform image classification on encrypted images. The primary challenge is to reduce the computational overhead of operations on encrypted data to make the scheme practical at desired levels of accuracy and security. The proposed research and development addresses this challenge through innovation in machine learning, computational number theory, approximation theory, and computer science. The goal of the proposed research and development is to demonstrate the commercial viability of secure image recognition by achieving a reasonable level of security, accuracy, and server cost. The team will experiment in training and testing modified convolutional neural networks (CNNs) for image classification using carefully chosen activation functions and/or approximations to the testing function, and simultaneously building onto existing homomorphic encryption libraries new functionality to compute these operations homomorphically.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LA LUCE CRISTALLINA, INC.
STTR Phase I: Silicon-Integrated Epitaxial Barium Titanate (BaTiO3) Chips for Photonics Applications
Contact
10500 DOUBLE SPUR LOOP
Austin, TX 78759--6914
NSF Award
2322389 – STTR Phase I
Award amount to date
$274,997
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader / commercial impact of this Small Business Technology Transfer (STTR) Phase I project is mass production of a standardized, large-area, silicon-based materials platform (wafer) for photonic integrated circuits. Photonics is the next step in information processing, using light signals instead of electrons. Such a materials platform is expected to revolutionize the silicon photonics market much like the introduction of silicon chips did for the microelectronics industry. The first step to successfully produce such wafers is to manage the extreme thermal stress arising from the combination of two materials (the optical material barium titanate (BaTiO3) and the silicon carrier chips) with very different rates of thermal expansion. Various processing techniques will be investigated to determine how such thermal stress can be mitigated. If successful, this new materials platform will used by telecom and data companies, and may enable new kinds of computing, such as photonic quantum computing. The total of these industries is expected to exceed $100 billion in combined market size by 2030.
This STTR Phase I project will address one of the critical issues of scaling up barium titanate on silicon technology to thicker and larger area wafers. Barium titanate and silicon have very different thermal expansions and since the integration is achieved by deposition at elevated temperature, cooling causes large stresses to develop. The resulting stress may result in cracks in the film or even in shattering the wafer. Stress also affects the optical performance of the material and therefore, its management is crucial for subsequent device fabrication. The company is developing a process that mitigates this problem (e.g., programmed cooling) which will affect wafer production throughput. In addition, the company must control the direction of ferroelectric polarization, an important customer requirement for making devices. Solving these two issues is crucial to successful commercialization of this technology. Barium titanate films of thicknesses ranging from 0.2 to 2 micrometers will be integrated on silicon and subject to different thermal histories. Residual stress will be measured by x-ray diffraction and corroborated with polarized Raman spectroscopy. The resulting crystal structure, morphology, polarization distribution, and electro-optic performance will be used as metrics for determining if the thermal processing was successful.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LAB2701 LLC
SBIR Phase I: Oscillator Processing Unit - Physical Reservoir Computing on the Edge
Contact
4376B N 372
Atwood, OK 74827--9738
NSF Award
2335448 – SBIR Phase I
Award amount to date
$272,615
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from creating the Oscillator Processing Unit (OPU), a computational processor that would be a disruptive technology for analog computing devices operating at the network edge. The edge computing device market is projected to reach $157B by 2032. Expanding on this, machine learning, especially deep neural networks (DNNs), relies on cloud infrastructure to conduct massive computation for both model training and inference, so OPUs would have beneficial security and environmental impacts since they would reduce reliance on the cloud. The proposed OPUs could overcome the von Neumann bottleneck while also enabling a smaller form factor, increased energy efficiency, and faster speeds. As the US seeks to reduce reliance on foreign microchip manufacturers, OPUs could also provide a powerful, viable alternative that could be manufactured in the US. The technological impacts of this project would result from a more fundamental understanding of how oscillators, which are one of the most prolific dynamic systems in the universe, can also be reconsidered as physical computers.
This Small Business Innovation Research (SBIR) Phase I project seeks to leverage two types of oscillator-based neuromorphic computers. By exploring the dynamics of oscillator computers, an improved understanding of how nonlinear dynamics are translated into computational ability will be developed. Further, this is expected to provide insights into how optimal oscillator cores could be constructed for Oscillator Processing Units (OPUs). These enhanced OPUs will converge two separate methods of analog computing: physical reservoir computers and adaptive oscillators. Ultimately, since an oscillator core?s memory and processing are not independent, OPUs could provide a solution to the von Neumann bottleneck. This work would establish a fundamental scientific understanding of the link between physics and information. Leveraging these two disparate forms of neuromorphic intelligence will also be the basis of a powerful Oscillator Processing Unit capable of acting as both an AI inference processor and a generalized computing processor.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LAVO LIFE SCIENCES INC
SBIR Phase I: A physics-based machine learning platform for crystal structure prediction of small drug molecules
Contact
1066 AMSTERDAM AVE NE
Atlanta, GA 30306--3543
NSF Award
2227936 – SBIR Phase I
Award amount to date
$274,990
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to accelerate and reduce the cost of the early stages of small molecule pharmaceutical research. The number of drugs a pharmaceutical company can bring to market is limited by the time, cost, and complexity involved in developing each drug. The research and development process typically takes around 10 years, and few drugs make it onto the market each year. This technology may be especially impactful in improving the frequency at which small molecule drugs are developed for understudied diseases, which collectively impact over 30 million Americans. By reducing the cost and time to market for new pharmaceuticals, the project could advance the industry and bring life-changing therapeutics to underserved people who are suffering from illnesses where there are presently no drug options.
This project develops technologies to solve the crystal structure prediction (CSP) problem. The crystalline structure of small molecules and peptides determines many pharmacological characteristics including solubility, oral bioavailability, shelf-life stability, and toxicity. Experimental determination of the crystal structure is expensive and requires significant human labor to conduct, so a computational approach would reinvent the characterization of small molecule drugs. The proposed technical innovation combines a novel energy prediction models based on quantum chemistry with a machine learning method for efficiently sampling the vast space of possible crystal structures. The resulting technology will help pharmaceutical companies de-risk their drug development process by allowing them to analyze crystal structures computationally before having to synthesize them in the lab.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEAFICIENT INC
SBIR Phase I: Improving indoor agriculture grow light efficiency with adaptive light shaping
Contact
163 TUNNEL RD
Evans City, PA 16033--9378
NSF Award
2304339 – SBIR Phase I
Award amount to date
$274,525
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in accelerating the transition to a more sustainable food supply chain, which could democratize access to healthy foods and lessen food insecurity. The US system for growing and distributing fresh food is inefficient and insufficient in the context of climate change. Controlled environmental agriculture (CEA) is seen as a potentially revolutionary way to supply food demands with limited resources. Despite this promise, the high energy requirements of creating lighting and cooling in enclosed environments to support photosynthesis has caused CEA not to realize its promise. In the project, a novel solution to improve energy efficiency in CEA farms is proposed where advanced optics, machine learning, and computer vision are used to ensure that all of the light that is emitted by synthetic light sources is optimally used for plant photosynthesis and growth. The project offers a plausible way to create reliably profitable operations for CEA producers which would lead to enhanced access to fresh produce for consumers and decreased reliance on conventional agriculture to meet the world?s food needs.
Within current commercial grow systems for controlled environment agriculture, a substantial portion of the photons are wasted as they are not incident onto photosynthetically active biomass and are absorbed by the surrounding grow rack and media. This project will prototype and systematically test a light production system that dynamically shapes light such that it is rendered only onto the photosynthetic areas of the plant. To accomplish this, the project will develop and evaluate (within three crop varieties) a closed-loop system to autonomously detect the three-dimensional shape of the growing plant and dynamically adjust the light intensity and projection area to optimize power efficiency and biomass growth. Successful completion of the work in this project will result in a novel technology that is systematically tested to yield similar quality produce using a fraction of the energy consumption of current state-of-the-art systems. Deployment of this technology would help to improve the unit economics of controlled environment agriculture produce items and accelerate adoption of controlled environment agriculture farming practices that potentially consume less water, utilize land resources more efficiently, and eliminate the need for chemical pesticide/herbicide treatments.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEARN COLLABORATE INC.
STTR Phase I: Enabling Student Project Collaboration with Artificial Intelligence Augmented Mentorship
Contact
11220 MOORPARK ST.
Studio City, CA 91602--2659
NSF Award
2243452 – STTR Phase I
Award amount to date
$274,927
Start / end date
03/15/2023 – 06/30/2024 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer Phase I project is in improving both student learning and workforce readiness through interdependent learning experiences. The project will create project-based environments that promote skills such as communication, critical thinking, problem solving, time management, creativity, and teamwork ? all mirroring professional work environments. The technology will also promote development of skills such as project management, writing, business and data analysis, design, and presentation. Project collaboration requires that students interact frequently throughout the project completion process, including frequent mentor or teacher interactions. Such an interdependent environment creates a real-world dynamic that better prepares students to enter the workforce. The platform developed by this project is likely to create significant societal impact while participating in the fastest growing e-learning sector.
The proposal seeks to develop a collaborative community platform using proprietary project collaboration models integrated with Artificial Intelligence (AI) augmented mentorship to enhance student workforce readiness. The technology will be designed to provide the right piece of information to the students and mentors at the right time. By analyzing and unifying all the content under a domain-specific semantic representation, the system will be able to aggregate and organize all the content and identify the piece for intervention that is contextually most useful. To make project collaboration and mentorship easier between students and mentors in a trustworthy manner, modeling will be done utilizing minimal supervision. This modelling will include combining contextual embeddings from language models with graph-based neural networks to capture interactions across multiple facets. The technology will build upon explainability of deep neural networks to provide an appropriate level of transparency into the decision making, both for the users to learn to trust the platform, as well as for the platform developers to build systems that aid in reliable, trustworthy, and fair mentoring.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEXEL SYNERGETICS, INC.
SBIR Phase I: Handheld Devices for Practical Simultaneous Translation
Contact
5676 NW 132ND AVE
Portland, OR 97229--2420
NSF Award
2212978 – SBIR Phase I
Award amount to date
$255,994
Start / end date
09/15/2022 – 06/30/2024 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project on a handheld simultaneous translator advances the state-of-the-art technologies in natural language processing and machine learning acceleration. Beyond technical contributions, the novel translator will likely have a significant impact on a wide range of domains, such as military personnel deployed in foreign countries, businesspeople participating in multilingual meetings, medical service providers, law enforcement, customer support services, diplomats and political representatives, local governmental entities providing services to citizens in the preferred language, and international tourists. As such, the project will have broader impacts in increasing economic competitiveness, advancing health and welfare, and improving military capabilities of the United State. Furthermore, the project helps to enhance equity in education and STEM literacy by enabling better access to educational resources to people of diverse backgrounds, especially immigrants, women, and underrepresented minorities in some countries/regions, who were previously disadvantaged due to limited prior educational access or limited access to foreign language courses.
This Small Business Innovation Research (SBIR) Phase I project focuses on the research and development of innovative algorithmic optimizations and a purpose-built translation device to enable fast, accurate and low-power inference for simultaneous translation. The overall approach is to exploit the unspoken but implied connections among language elements at various levels to guide the learning model. Specific techniques are investigated at the phoneme-level, work-level, and sentence-level. Collectively, these innovations aim to reduce the computation complexity of simultaneous translation by orders of magnitude while increasing translation accuracy. A systematic and comprehensive methodology is also being established that allows fast implementation of the inference hardware via high-level synthesis and reports detailed statistics on translation accuracy, latency, power, and area to facilitate a thorough evaluation of the research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIEBOLD TECHNOLOGIES LLC
SBIR Phase I: High-Efficiency Liquid Desiccant Regenerator for Desiccant Enhanced Evaporative Air Conditioning
Contact
400 STAN DR
Melbourne, FL 32904--1000
NSF Award
2335500 – SBIR Phase I
Award amount to date
$266,556
Start / end date
01/15/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project develops air conditioning technology, unveiling a high-efficiency, liquid desiccant regenerator that promises to unlock the full potential of liquid desiccant air conditioning (LDAC). The solution promises substantial energy savings for families and industries alike. For families, the technology translates into reduced energy costs, offering tangible financial relief and enhancing their quality of life. On an industrial scale, it stands to reshape the power requirements of various sectors, paving the way for more sustainable and cost-effective operations.
The project is focused on overcoming the efficiency barriers that have historically impeded LDAC's widespread adoption relative to today?s vapor-compression air conditioners. A suitable membrane technology is adopted for the regeneration of the liquid desiccant as it promises to substantially improve the coefficient of performance for the LDAC. The plan is to develop design specifications for an LDAC that combines the size and cost characteristics of today?s conventional air conditioning systems with the anticipated leap in energy efficiency. The key challenge is in designing a system where membrane behavior at extremely high salt concentrations is robust and predictable. The experimental development is focused on the assessment of performance of various membranes under various flow rates and salt concentrations. The resulting experimental data are modeled with established mathematical models from literature. Computer simulations of the liquid desiccant regeneration process are developed using the experimental membrane models to demonstrate the regenerator's feasibility and predict its efficacy and value.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIFELAB STUDIOS, INC.
SBIR Phase I: Using ChatGPT and Machine Learning to Power Positive Change among Justice Involved Youth
Contact
27500 N 115TH ST
Scottsdale, AZ 85262--7501
NSF Award
2333168 – SBIR Phase I
Award amount to date
$274,574
Start / end date
12/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to test the benefits of artificial intelligence (AI) to enhance a platform which aids justice-involved youth to develop protective factors for positive change. The project uses advanced machine learning and large language model technologies to optimize the platform's effectiveness and support this vulnerable group, many of whom have adverse childhood experiences, so that they can break the cycle of re-offending. These enhancements empower youth by creating more relevant growth recommendations offering tailored, strengths-based feedback to break the cycle of recidivism and support the transition into productive societal roles. The platform has commercial potential with opportunities for deployment across 3,143 U.S. counties, which collectively serve 800,000 justice-involved youth annually. Successful implementation may alter the life trajectories of these youth, such that they can make positive life changes. This transformation would lessen the economic burden on our already stretched penal systems, while unlocking the potential of these youth to contribute positively to society.
This project integrates state-of-the-art machine learning and large language models to fortify an innovative social growth platform, enabling justice-involved youth to make positive life changes. The platform is underpinned by a research-validated growth cycle, and features a dynamic feed governed by intelligent algorithms, specialized protective factor journeys, and a narrative-centric approach that leverages strength-based, social connectivity. The project will facilitate the refinement of the algorithmic architecture behind the dynamic feed to enhance user engagement, thereby promoting protective factors. Large language models will be integrated to serve as an intelligence-augmented mechanism to bolster the strength-based feedback loop within life integration stories.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIGHT RESEARCH INC
STTR Phase I: Snapshot, on-machine metrology system for high-precision optical manufacturing
Contact
4815 N ROCK CANYON RD
Tucson, AZ 85750--6064
NSF Award
2322208 – STTR Phase I
Award amount to date
$274,524
Start / end date
10/01/2024 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project advances precision manufacturing. The on-machine metrology system will have a transformative effect on highly efficient and precise optical manufacturing, additive manufacturing, and precision machining. These industries currently face a shared technical challenge: the lack of real-time quality control during fabrication. The on-machine metrology tool's real-time quality control capabilities will not only drive efficiency in high-precision manufacturing but also contribute to reduced manufacturing costs and enhanced product quality. Overall, the project's anticipated outcomes include an efficient high throughput manufacturing process with on-machine metrology, the development of a compact, snapshot, multi-wavelength on-machine metrology system, and the establishment of a next-generation innovation and entrepreneurship training program.
This STTR project seeks to develop a compact, snapshot, dual-mode, multi-wavelength interferometric system for in situ metrology in high precision manufacturing. The lack of real-time quality control during fabrication is a critical hurdle, leading to delays and manufacturing errors. This system integrates unique techniques to overcome this challenge and enhance throughput and accuracy. The technology utilizes a polarization-based, multi-wavelength, snapshot technique providing real-time measurements of machined surfaces with minimal environmental impacts. By offering instant feedback on surface quality, reducing iterations for diamond tool centering, and improving throughput and accuracy, the system becomes the smallest interferometric system suitable for integration into existing equipment for in situ metrology. The project's goal is to develop a market-ready, on-machine metrology system through prototyping, software development, and performance validation. This real-time, in-situ metrology process is estimated to achieve efficiency improvements of 30% or more in diamond-tool alignment and 50% or more in surface metrology. Successful development and commercialization of this system will hold significant intellectual merit, overcoming a critical hurdle in high-precision manufacturing and enabling real-time quality control.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LITTLE ROOM INNOVATIONS, LLC
STTR Phase I: A Novel Prescription Process that Customizes Prosthetic Feet for Individual Patients
Contact
2560 PRAIRIE ST
Ann Arbor, MI 48105--1448
NSF Award
2233114 – STTR Phase I
Award amount to date
$274,975
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a novel process for providing customized prosthetic feet. Current prescription methods match patients with prosthetic feet designs based on the patient?s weight and level of physical activity. However, this method often neglects patient variabilities in terms of posture and walking gait and results in suboptimal force distribution and a mismatch in biomechanics. These problems, in turn, result in a multitude of potential chronic issues including issues with gait, balance. and pain. This proposed system aims to develop a novel fitting system and fabrication process to provide customized prosthetic feet based on optimized mechanical stress distribution models. The system aims to benefit the 420,000 highly active US patients who utilize prosthetic feet each year.
This STTR Phase I project will address a clinical need by developing a novel prescription approach to developing custom prosthetic feet. The novel process utilizes a prosthetic foot model with adjustable stiffness properties in conjunction with an optimization algorithm to determine individual patient?s customized prosthetic foot settings. Custom prosthetic feet will be fabricated and fitted for use in individual patients. The prosthetics will then be validated in a limited proof of concept study to demonstrate improvements to kinematic and kinetic behaviors. The goals are to closely match the participant's intact ankle and foot measurements and to improve patient satisfaction outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIVEDX INC.
SBIR Phase I: An inclusive machine learning-based digital platform to credential soft skills
Contact
1625 S BIRCH ST
Denver, CO 80222--4110
NSF Award
2317077 – SBIR Phase I
Award amount to date
$274,993
Start / end date
01/01/2024 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to enable people who aspire to higher education and/or career opportunities to create a demonstrable portfolio of soft skills based on their lived experiences. Soft skills (e.g., problem-solving, teamwork, leadership, etc.) are as important as hard skills for individual success. However, current soft-skill assessment tools are subjective, inefficient, and inconsistent. This is especially painful for marginalized populations such as minorities and women, who often possess valuable soft skills such as stress management and conflict resolution, but do not have the tools to demonstrate it. The proposed solution will change how people?s lived experiences and the soft skills associated to those experiences are valorized. This technology may open the door to better educational and professional opportunities in the U.S., to increased economic competitiveness (since higher education plays an increasingly critical role in the economic competitiveness of a nation), to advanced health and welfare of the American public (since adults with higher education often live healthier and longer lives, and enjoy better financial situations), and to a more developed and diverse STEM workforce (by focusing on valorizing the social and cultural capital of minoritized students).
This project proposes a digital platform that provides soft-skill credentialing guided by lived experiences. The main innovation behind the proposed solution is a proprietary system that combines Machine Learning (ML) and Natural Language Processing to analyze the candidate?s experiences and apply different evidence-based social-emotional assessment frameworks to accredit the soft skills embedded in each experience. This solution may be the first time a proprietary ML technology will be integrated with a large language model to provide soft-skill credentialing upon lived experiences. The main technical challenge is avoiding bias in the assignation of soft-skill credentials. Other technical challenges are: 1) the potential scarcity of training data; 2) the correct definition of credential categories; and 3) the ability to explain the ML models. This project is intended to address these challenges by 1) developing a proof-of-concept prototype of the accreditation model; 2) conducting a preliminary analysis of its fairness when assessing marginalized groups; 3) reformulating the accreditation algorithm in case any bias is detected; and 4) evaluating, with real datasets, the performance of the credential classifier, the bias mitigation strategies, and the explanations generated for each assessment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LLC BG BIOLOGICS
STTR Phase I: Biocontrol of Pythium pathogens in hydroponic greenhouses
Contact
230 S CHURCH ST
Bowling Green, OH 43402--2815
NSF Award
2304251 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project is to develop a targeted biological pesticide for the control of pythium pathogens in the hydroponic greenhouse production of leafy greens. Fresh market production of tomatoes, cucumbers, peppers, lettuce, and spinach is shifting to hydroponic greenhouse operations because these operations are more efficient in their use of land, water, and fertilizer than conventional operations. Despite these advantages, pythium pathogens are a major threat to their economic viability. The accidental introduction of pythium pathogens into the recirculating water in these operations can result in complete crop losses as the pathogen spreads rapidly through the water and infects the roots causing root rots and leaf yellowing. In lettuce, root rots impair nutrient absorption and slow plant growth rates. Crop rotation cycles must be extended to produce the same amount of product, and ultraviolet (UV) irradiation of the recirculating water may be needed to mitigate disease losses. The reduced integrity of plant roots may enable pathogenic bacteria in the water to migrate via the plant vascular system into the leaves and potentially cause disease. One such case of E. coli-contaminated lettuce has already reported. Thus, there is a need for the development of an organic-based approach for this disease problem.
The proposed project will assemble a collection of pythium pathogens that reflects the genetic diversity of these pathogens in different hydroponic facilities. This collection of isolates will take into account several parameters: 1. geographic diversity, 2. crop species (arugula, basil, cannabis, lettuce, and spinach), and 3. production system e.g., deep water raft hydroponics, vertical hydroponic systems and small scale, family-owned operations. This project will evaluate 10 Pseudomonad strains that have exhibited contact-dependent killing of all pythium strains from a smaller collection of pythium isolates to identify the most potent combinations of these biocontrol agents. A bioinformatics approach will be used to identify the genes responsible for the killing phenotype. Targeted gene deletions will be made in a sequenced strain and virulence assays of the mutated strains will be used to assess the role of specific genes. This strategy is expected to identify the genetic basis for host-specific killing of pythium species and provide evidence that these microbes are not pathogens of humans or plants.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUNEXUS SPACE, LLC
SBIR Phase I: Silane Recycling from Decommissioned Photovoltaics using Microgravity-analog Fluidized Bed Reactor with Sonication.
Contact
1449 7TH ST
Denver, CO 80204--2011
NSF Award
2323566 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable on-orbit manufacturing by providing raw materials recycled or sourced in space, directly on-orbit. Manufacturing hardware on-orbit can potentially relieve the costs and qualification lead times of space operations by significantly reducing launch costs. However, on-orbit manufacturing will still require inexpensive feedstock. This project?s business approach which is space production from in-space materials addresses this core problem of orbital manufacturing. This project will bring significant transformations to a wide range of space activities, promoting a circular space economy, lowering the cost of orbital power, and simultaneously providing an economic incentive for satellite/debris reclamation, thus mitigating orbital debris and congestion. Providing raw materials sourced in space for on-demand, on-orbit manufacturing holds the potential to increase the economic competitiveness of the US through financially feasible space operations by reducing launch mass, costs, development time, and current payload and size limitations, supporting the US national defense by improving military power projection and logistics resilience, supporting future scientific studies of the solar system and deep space, expanding the limits of long-term exploration missions, and reducing dependence on cargo missions through in situ manufacturing and recycling capability.
This SBIR Phase I project proposes to develop a novel approach for recycling photovoltaics in an orbital environment. The vacuum environment of space will be optimal for many steps in semiconductor manufacturing and can be considered a high-potential application for orbital manufacturing, enabling silicon production to scale well beyond the current constraints of terrestrial vacuum chamber bottlenecks. However, while the vacuum will be beneficial overall to silicon production, nearly every process in modern chemical manufacturing is reliant on gravity and needs to be adapted to function in a microgravity environment. This project focuses on the development of a fluidized bed reactor (FBR) for microgravity analog production of monosilane gas from end-of-life silicon photovoltaics and various hydrogen sources, as it constitutes the most critical step in the silicon production line. Within the scope of this project, particulates produced from PV cells will be characterized, a basic model of the thermochemical reactions will be developed to determine design parameter nominals and a benchtop prototype to characterize the mechanics of particle and gas flows in an analog to microgravity will be developed, establishing its feasibility for in-space processing for the envisioned applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUTRIS, INC.
SBIR Phase I: Massively Parallel Protocols for Software-based Wireless Systems
Contact
1437 HEARST AVE
Berkeley, CA 94702--1532
NSF Award
2322307 – SBIR Phase I
Award amount to date
$273,383
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project lies in its potential to implement state-of-the-art radio communication systems faster and less expensively. Radio systems are an essential part of everyday life, serving roles from entertainment to public safety. But modern radio systems, designed to use the limited number of available frequencies efficiently, are expensive to develop and deploy. A major reason for the high cost is that custom silicon chips are needed to do the processing that converts a weak radio signal into useful data. This project aims to make radio systems much cheaper to build. Instead of building custom chips, the team uses commodity computers and specially designed software that can run the radio processing tasks at high speed. This speed is enabled by technology that analyzes radio processing tasks and turns them into software which runs on a processor with many individual computing cores. The economic impact is twofold: that technology can reduce the cost of existing systems, such as cellular LTE and 5G base stations, it also makes possible new applications which are too expensive to build from custom hardware.
This SBIR Phase I project seeks to understand how to develop the processing needed in modern radio system quickly and efficiently. The team also seeks to address the features of communications protocols that are hard to implement because the computations are too complicated or too much data needs to be examined before the final output is generated. They will also address the opportunities to change the protocol to eliminate the bottlenecks. The technology will measure the how fast key radio algorithms run on commodity computing hardware and how much time is spent on essential, but not productive, tasks such as moving data between memories. The objective is a quantitative estimate of how much data can be transmitted or received by a radio implemented purely in software. Ultimately, the team will design protocols that scale with the number of processor cores: twice as many processors giving twice the data throughput.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LYDIAN LABS, INC.
SBIR Phase I: High-efficiency, electrified reverse-water gas shift for sustainable fuels production
Contact
3 DARTMOUTH ST
Somerville, MA 02145--3866
NSF Award
2304536 – SBIR Phase I
Award amount to date
$274,042
Start / end date
11/15/2023 – 04/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to directly and immediately lower the long-term costs of e-fuels (electrofuels), or fuels derived from electricity, carbon dioxide and hydrogen. The e-fuels produced by the process represent an important alternative for fossil fuels in aviation, shipping, and other areas of transportation that are challenging to electrify. The societal impact of the system would allow low-carbon or even carbon-neutral, drop-in replacement e-fuels for fossil fuels. Applied at scale to the aviation sector, this technology could enable reduction of greenhouse gas emissions of roughly 1 Gigaton (Gt) annually. Extending e-fuels usage into additional sectors such as shipping and long-haul ground transportation could enable up to 3-5 Gt annual reductions in emissions. Commercially, the e-fuels developed in this project could provide a viable alternative for a multi-trillion-dollar market for fossil fuels in these sectors if they can be made cost effectively. The research would demonstrate a solution that can achieve substantially lower capital costs and operating costs of producing e-fuels.
This SBIR Phase I project builds and demonstrates a bench-scale reactor for a high-temperature reverse water-gas shift (RWGS) process with electricity as the only energy source. Despite its potential to mitigate emissions, the RWGS reaction has not been widely deployed due to the high temperatures required and the difficulty in achieving uniformity within conventional chemical reactors. The micro-structured materials presented in the project have shown unprecedented reaction rates and process intensity in initial experiments at the lab-scale. The research will focus on improving these materials, and their durability and incorporating them into an integrated reactor system. The technical project will include: (1) developing a multi-scale model of the reactor to optimize the geometry of the reactor materials; (2) prototyping and fabricating the optimized reactor materials; (3) modifying the micro-structured materials with coatings and active metals as needed; and (4) testing of the reactor system to optimize the reaction. At the end of the project, the system will be ready for integration into a larger pilot-scale system that should unlock unprecedented cost reductions for carbon dioxide and hydrogen derived products and broader applications within green chemistry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MACULA VISION SYSTEMS INC.
SBIR Phase I: Automated Gram Stain Interpretation Via Digital Holographic Microscopy
Contact
11630 N DRAGOON SPRINGS DR
Tucson, AZ 85737--9761
NSF Award
2321453 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 04/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the improvement in hospital laboratory results by automating and standardizing a manual test procedure that is critical for the diagnosis of infections. Faster, higher quality and less expensive test results will help to ensure that patients receive timely treatment with the appropriate medications, reduce employee burnout through the automation of tedious laboratory tasks, and lower healthcare costs. Just as automated blood analyzers largely replaced manual blood cell counting, the proposed platform will eventually replace manual counting of bacteria and yeast cells. The new imaging technology developed as a part of this project will generate advanced manufacturing jobs and increase the economic competitiveness of the United States by introducing an innovative product to a market dominated by foreign firms. Long-term benefits to society include decreased antimicrobial (medicines that kill microorganisms) resistance as infections are managed with fewer unnecessary antimicrobials.
This Small Business Innovation Research (SBIR) Phase I project involves the development of a novel microscopy platform for automating the interpretation of tests performed in hospital laboratories. This project fills an important gap specific to microbiology labs that are facing a trained labor shortage without affordable automated alternatives. Microbiology labs in hospitals are responsible for examining patient samples (e.g., urine and blood) for the presence, type, and quantity of microscopic organisms (e.g., bacteria and yeast). This project includes the engineering of a special light source, a customized camera, and a suite of artificial intelligence (AI)-enabled algorithms to analyze the microscopic images captured by the camera. Once the platform is built, its performance will be evaluated on real patient samples to demonstrate the feasibility of the technology by comparing it to experienced human lab technicians. The project will measure how often the platform produces the correct answer as well as how long it takes. The platform will also be tested in terms of image quality to demonstrate that it can take pictures of the smallest bacteria and accurately capture color.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAMMAE BIOSCIENCES, INC.
SBIR Phase I: Development of an enzymatic method to produce compounds found in human milk at commercial scale
Contact
3500 S DUPONT HWY
Dover, DE 19901--6041
NSF Award
2304250 – SBIR Phase I
Award amount to date
$271,443
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to assess an affordable enzymatic method for producing marketable natural compounds usually found in human milk. Once this strategy is validated, it could be implemented by domestic and industrial users. The technology is capable of transforming the lactose in milk to highly desirable compounds. These rare and valuable compounds can help enhance growth of beneficial gut bacteria and are building blocks of human breast milk. These compounds are widely desirable to fortify infant food, where they play a role in intestinal health, supporting balanced gut microbiota, benefiting immunity, and improving cognitive brain health. Furthermore, new research suggests that affordable technologies for food fortification containing stable bioactive natural compounds will benefit the healthy gut beyond infancy and across life stages. As such, this technology opens new business opportunities for food and dietary supplement manufacturers aiming to develop unique gut-strengthening nutrition solutions.
The proposed project will enzymatically generate compounds found in human milk, including N-acetylglucosamine (LacNAc). The research plan consists of testing the scalability of enzyme ?-hexosyltransferase (BHT) production, which will be heterologously produced by K. phaffi. To validate industrial scalability, product generation, and yields from 100 L working volume bioprocessing reactors, the BHT generated will be utilized to catalyze the repeated addition of galactose to N-acetylglucosamine (GlcNAc). The products, in addition to galactooligosaccharides, will include LacNAc disaccharides, generated by sequential transgalactosylation reactions. The recovered products will be tested in preclinical safety/toxicity studies. Data collected during this study will allow for a more precise cost-benefit analysis, which will include product yields, carbon balances, microbiome benefits, and metabolic data. Cost savings are expected from a more efficient enzymatic biosynthesis method for producing LacNAc due to BHT specificity, synthesis in one-step reactions, low-cost substrates, sustainability, and overall low environmental impact.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MANTEL CAPTURE, INC.
SBIR Phase I: Optimizing Composition of Novel Molten Alkali Metal Borates for Carbon Dioxide Capture
Contact
750 MAIN ST
Cambridge, MA 02139--3544
NSF Award
2332658 – SBIR Phase I
Award amount to date
$274,724
Start / end date
02/01/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a molten salt-based carbon capture system that can be applied to a number of different emission sources with easy integration into the existing site. The technology can be applied to hard-to-abate industries such as industrial heat, cement, steel, and hydrogen production, or in hard-to-abate geographies where coal, oil, and natural gas are likely to remain prevalent fuels for decades. The technology can also support carbon dioxide removal from biogenic sources. Net-negative emissions can be achieved in sectors such as pulp and paper, waste-to-energy, and bioenergy. The molten borate carbon capture technology can be used to decarbonize heavy industry by capturing carbon dioxide at the source. These industries dominate global carbon dioxide emissions emitting over 23 billion tons per year, a greater than $1 trillion market at $50 per ton of carbon dioxide. The advancement of this molten borate carbon capture technology could have the potential to decrease the costs of carbon dioxide capture by solving the efficiency penalty associated with high temperature separations in carbon capture.
The intellectual merit of this SBIR Phase I project resides in the discovery of a molten borate composition that can reduce the cost and increase the design flexibility of future carbon capture systems. The addition of other metals and or changes to the mixing ratio are expected to lead to reductions in melting point and the ultimate working temperature of a system where these salts are employed. This research aims to probe this unexplored phase space by synthesizing and testing an array of salt compositions that have modified alkali metal and mixing ratio content compared to the reference. Reductions in molten borate melting point have the potential to mitigate freezing concerns and reduce upper material temperatures, ultimately decreasing the cost, and increasing the potential for widespread adoption of this novel carbon capture technology.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MARWELL BIO INC.
SBIR Phase I: Advanced Deep Learning Technologies for Designing Humanized Antibody
Contact
470 NOOR AVE #1011
South San Francisco, CA 94080--5957
NSF Award
2304624 – SBIR Phase I
Award amount to date
$274,822
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to accelerate antibody design and engineering through the development of proprietary computational approaches. Compared to conventional antibody drug development approaches that are often lengthy, costly, and inefficient, this innovation may offer a more efficient and cost-effective alternative. The proposed approach aims to create better therapeutic-grade antibodies while unlocking novel antibody design possibilities. The market opportunity addressed by the proposed technology is significant, as the global therapeutic antibody market for cancer and infectious diseases is projected to reach $235 billion by 2028. This project has the potential to transform the field of antibody discovery and provide new therapeutic options for patients.
This Small Business Innovation Research (SBIR) Phase I project aims to develop an artificial intelligence (AI)-based platform that efficiently designs novel antibody drug candidates with possible lower toxicity and immunogenicity risks. The research will involve developing novel and proprietary AI based models to create best-in-class antibody therapeutics and validate them through state-of the-art in-silico experiments. To successfully complete this Phase I project the company plans to: a) develop a novel computational model to design antibody hit sequences, b) demonstrate the scalability of the proposed computational model in designing antibody hit sequences against diverse targets, c) assess biological values of the antibody hit sequences predicted by the computational model. The expected technical outcomes involve a more rapid and efficient process for designing therapeutic antibodies, resulting in lower development expenses and a quicker path to market. The AI technologies have the potential to design the most promising therapeutic antibodies to treat infectious diseases and cancer in months rather than years, reducing the time and resources needed for the pre-clinical development of therapeutic antibodies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MATMERIZE, INC.
SBIR Phase I: A Physics-Informed/Encoded Polymer Informatics Platform for Accelerated Development of Advanced Polymers and Formulations
Contact
850 NEW BURTON ROAD
Dover, DE 19904--5786
NSF Award
2322108 – SBIR Phase I
Award amount to date
$273,706
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
Errata
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Abstract
The broader/commercial impacts of this Small Business Innovation Research (SBIR) Phase I project are to transform the way in which polymeric materials are developed. Adopting the most advanced artificial intelligence (AI) techniques, the proposed technology seeks to dramatically accelerate the exploration of new polymer formulations, efficiently and accurately discovering those with targeted performances and applications, and ultimately minimizing the time and the cost needed to develop new and superior functional materials. This technology will enable the targeted development of polymers for specific applications such as packaging or energy storage, while ensuring full recyclability. New polymer designs of this type can help alleviate the current global problem of plastic waste. Given that polymers are one of the most important classes of materials in use today, the impact of this SBIR Phase I project is expected to be significant and far-reaching.
This Small Business Innovation Research (SBIR) Phase I project aims at transforming the state-of-the-art AI-based technology currently used to discover and design functional polymers. Since the beginning of polymer informatics about a decade ago, this AI-based approach has quickly become a powerful tool to design new functional polymers. At the center of this technology are the machine-learning models, trained on past data and used to evaluate the polymeric materials yet to be synthesized. Currently, the models are developed by purely ?learning? the available datasets independently, ignoring numerous physics-governed correlations across data of different polymer classes and properties that come from different sources. Without proper awareness, the models can easily violate the relevant physic rules and render unphysical results, especially when the training data are not sufficiently large. In this project, the company will develop two deep learning architectures in which known and important physics-governed correlations are secured. The architectures will be the most advanced deep learning tools to combat the small and sparse data problems that are very common in and important for polymer informatics. The new technology is expected to significantly transform the development and deployment of functional polymers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAXWAVE LLC
SBIR Phase I: Long-Range, Millimeter-Wave, Wireless Power Beaming with Enhanced Efficiency
Contact
2616 DUBLIN WAY
Waunakee, WI 53597--9457
NSF Award
2334557 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks to drive high-tech industry development in the Midwest region of the United States. This team develops and deploys wireless, power-beaming technologies for applications in both civilian and military contexts. The project explores wireless generation and distribution of mass energies through electromagnetic waves. The resulting technology spans applications from the wireless charging of vehicles to green energy distribution and solar power beaming. Immediate applications include long-distance flights of heavy-duty drones, which can be remotely charged from terrestrial power beaming stations. With the addition of relay drones, this technology may also establish a resilient airborne energy distribution network for military purposes. In the long term, the technology's scalability enables solar power beaming, a significant leap toward carbon-free green energy production.
This Small Business Innovation Research (SBIR) Phase I project addresses the fundamental limitations of existing wireless power-beaming technologies. Conventional methods suffer from poor efficiency and require large physical dimensions for Radio Frequency transmitters and receivers. These limitations have made a long-range power-beaming solution impractical. To overcome these obstacles, this project aims to develop a unique operational mode for wireless power-beaming technology: power beaming at the near-field zone using millimeter waves. This approach offers significant advantages, including improved efficiency, compact dimensions, outstanding long-range performance, and safe operation. By leveraging the extended near-field range of a transmitter operating at millimeter waves and utilizing an adaptively controllable collimated beam, the technology can significantly enhance power efficiency, allowing power to be transmitted over much greater distances. Furthermore, a uniquely devised frequency plan within the low-loss region of atmospheric transmission windows enhances the system's resilience in adverse weather conditions. The utilization of shorter wavelengths in the millimeter-wave spectrum enables substantial reductions in the size of transmitting and receiving systems. Precise control of the transmitter's focal point ensures a secure and reliable power-beaming connection between subsystems. This technology has the potential to revolutionize wireless power beaming, facilitating efficient transfer of high powers and unlocking capabilities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAYFAIR GROUP LLC
SBIR Phase I: Intelligent Interactive Guidance System for Litigated Insurance Claims
Contact
150 W MAIN ST
Norfolk, VA 23510--3403
NSF Award
2329603 – SBIR Phase I
Award amount to date
$274,999
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project enhances the efficiency, fairness, and cost-effectiveness of the United States' property and casualty insurance claims processes. This project aims to develop an advanced, artificial intelligence (AI) powered guidance system that will transform how litigated insurance claims are managed and resolved. By enhancing the decision-making process of claims professionals with automated, evidence-backed guidance, the system will significantly reduce the time and expense currently required to resolve claims, resulting in quicker payouts to claimants and decreasing the burden of legal costs. The system's innovative approach will assist in identifying critical case information, supporting claim professionals in making more informed decisions. The project has the potential to improve the overall transparency and reliability of the claims litigation processes, engendering greater trust in the insurance system. Additionally, by streamlining operations, it could lead to more efficient use of resources within the insurance industry, lowering insurance premiums for consumers and businesses.
This SBIR Phase I project represents an opportunity to significantly improve the processing and handling of litigated insurance claims. The project?s research objectives include the development of a novel approach for information extraction from massive unstructured data collections typical in insurance claims and summarization frameworks for presenting the extracted information, enabling a concise yet comprehensive view of complex claims data. The project aims to design a visualization interface that aids understanding and facilitates more informed decision-making by claims professionals. The research applies cutting-edge AI and machine learning techniques to these objectives, expanding past the boundaries of current capabilities in data analytics within the insurance industry. The anticipated technical results include demonstrating the feasibility of this innovative system to quickly and accurately present relevant decisional information from a broad array of data, providing users with essential insights for making decisions. By improving how information is processed, summarized, and presented, the project is expected to lead to better, faster decisions in litigated insurance claims management, setting a new standard for technological applications in the field.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MECHANO THERAPEUTICS LLC
STTR Phase I: Mechanically Controlled Drug Delivery Platform for Joint Environments
Contact
3401 GRAYS FERRY AVE
Philadelphia, PA 19146--2701
NSF Award
2304235 – STTR Phase I
Award amount to date
$275,000
Start / end date
06/15/2023 – 05/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project seeks to address the strong clinical need for a single injection/dose sparing delivery system that can safely release therapeutics in the joint space over time in a controllable dosing manner for sustained symptomatic relief. Early and efficient treatments that mitigate inflammation are becoming increasingly critical to ease the care and cost burdens associated with musculoskeletal conditions, which impact 1.71 billion people globally. The proposed platform, which can be applied to a wide variety of drugs, including small molecules, proteins, and biologics will address the market need for improved drug delivery systems by providing a tunable drug delivery system that is responsive to different degrees of mechanical force created by different movement types. The solution will allow for more precise delivery of drugs when and where they are needed. This feature will translate to fewer injections, fewer systemic side effects, and overall improved drug efficacy compared to current offerings, in turn providing improved patient quality of life and outcomes. The proposed mechano-activated drug delivery platform is expected to have a major impact in controlling musculoskeletal diseases by improving efficacy of Food and Drug Administration (FDA)-approved treatments and enabling new therapeutic strategies.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop a force-stimulated drug delivery system that uses the body?s natural physiological loading of musculoskeletal environments for controlled release of nearly any drug. The technology is based on the tunable rupture profile of proprietary mechano-activated microcapsules - translating to fewer injections, fewer systemic side effects, and overall improved drug efficacy. Preliminary work has demonstrated the ability of the microcapsules to encapsulate and release viable biological therapeutics upon mechanical force, to provide tunable mechano-activation thresholds, and to stay and rupture within a living joint. For this Phase I project, a proof-of-concept study will be conducted to establish the feasibility of the mechano-activated microcapsule drug delivery platform in a biological joint environment. This study will be accomplished by evaluating the anti-inflammatory therapeutic effects of interleukin-1 receptor antagonist (IL-1Ra), a drug with established ability to inhibit acute joint inflammation, delivered via mechano-activated microcapsules in an established equine model of Interleukin-1-beta (IL-1beta)-induced acute joint inflammation, in comparison to soluble formulations. This study will provide a basis for investigation into more specific disease applications, models, and terminal outcomes where modification of the disease process over the long term can be evaluated.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MEDFREE, INC.
SBIR Phase I: Novel Self-Closing, Transcatheter, Edge-to-Edge Repair Device to Percutaneously Treat Tricuspid Valve Regurgitation Using Jugular or Femoral Vein Access
Contact
9165 RUDDER WAY
Newark, CA 94560--7311
NSF Award
2322197 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project develops a novel medical device enabling minimally invasive surgical revision and repair of the tricuspid valve. More than 1.6 million patients in the U.S. suffer from moderate to severe tricuspid valve regurgitation (TR) resulting in a market-size exceeding $2.4 billion by 2028. The prevalence of this repair increases with age, with women over 4 times more likely to be affected with TR than men. There are no Food and Drug Administration (FDA)-approved percutaneous devices for TR treatment. Isolated TR surgery is rarely performed due to the inherent risks associated with major surgery with post-operative complications resulting in high morbidity and mortality rates of 36.1% among severe TR patients. Hence, only about 8,000 of all U.S. patients with moderate to severe TR currently receive surgical treatment.
This Small Business Innovation Research (SBIR) Phase I project develops a novel, percutaneous, catheter-based device and procedure for surgically revising the tricuspid Valve in patients suffering from Tricuspid Regurgitation (TR). The tricuspid valve is the largest of the four heart valves presenting unique challenges due to its complex anatomy including 3 thin leaflets and location. The valve is difficult to access using traditional femoral vein access. This project aims to provide a novel, low-profile catheter and implant device via the jugular vein. The Phase I objectives include demonstrating the ability to grasp valve leaflets, validating the design using a benchtop model simulating human conditions, further designing, developing and validating an animal model, and performing a transcatheter tricuspid edge-to-edge repair (t-TEER) procedure via the jugular vein in a lab setting. The results from the technology development, bench testing. and preclinical models will further the system towards eventual human use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MEDICARBONE, INC.
SBIR Phase I: Design and Development of Minimally-Invasive Orthopedic Fracture Fixation Using Intramedullary Sleeve and Injectable, Light-Triggered Bone Cement
Contact
2820 E FORT LOWELL RD
Tucson, AZ 85716--1518
NSF Award
2322411 – SBIR Phase I
Award amount to date
$273,563
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the current challenges associated with an increase in the incidence of orthopedic injuries and surgeries. The technology will stabilize and repair broken bones in the US and globally. Trauma, degenerative bone diseases, and bone tumors often result in broken bones that require a procedure called intramedullary nailing. Intramedullary nailing involves nailing metallic implants to bones stabilize bone fractures. This procedure often results in complications such as infection, rotated limbs, and failure to achieve complete rigidity, which may eventually lead to patient discomfort and significantly increased costs due to revision surgeries. Consequently, there is an urgent need for an intramedullary nail technology that is less invasive, cost effective, and customizable to the patient?s anatomical requirements to enable improved bone fracture healing and avoid burdensome revision surgeries. When additional corrective surgery is required to treat any post-operative infections or surgical placement mistakes, the implant removal should be less invasive and not cause any additional morbidity. There are currently no such proven technologies available that meet the above criteria.
This project will primarily focus on the development of an intramedullary (IM) sleeve system with an in situ, photocurable, and removable polymeric resin system. There are four main objectives: 1) design and development of a multi-layered IM sleeve prototype, 2) synthesis and optimization of am in situ photopolymerizable polymeric resin system in the IM sleeve, 3) removal of the cured polymeric resin system from the IM sleeve using minimally invasive tools and methods, and 4) in vitro, in vivo biocompatibility, and demonstration of the customized IM prototype device in a sheep cadaveric tibia bone. The research will generate new knowledge in designing and synthesizing a novel polymer formulation with additives that helps in fast setting with improved mechanical properties. The project will also enable extraction of photocured polymers using existing removal technologies. For physicians, this research could result in novel, minimally invasive treatments that could drastically reduce the surgical time and improve the patient recovery times.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MELLICELL, INC.
SBIR Phase I: Industrial-Scale Technology for Drug Development in Mature Human Fat Cells
Contact
55 CHAPEL ST STE 100
Newton, MA 02458--1060
NSF Award
2322443 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to increase the scale and throughput of novel technology with the potential to enable the discovery and development of next-generation therapeutics for obesity and the array of associated medical conditions that can be ameliorated with weight loss. This technology could also be expanded to therapeutic development to address other reproductive and ageing disorders characterized by diseased fat cells.
This project may enable drug development in human fat cells at a previously unattainable quality and scale. For the last 50 years, the first stage of drug development in adipocytes has been limited by the lack of a tractable system that faithfully reproduces the clinical features of mature fat cells. The technology in this project could efficiently turn adult human stem cells into fat cells and accelerate their maturation thousands of times relative to conventional methods. Adipocytes generated by this new technology may more closely match the cellular shape and size, gene expression profile, and function of mature fat cells in adults. Scaling the technology will require development of novel devices for automation and the design and testing of customized protocols. Success will be determined by measures of manufacturing quality control and specific properties of mature human fat tissue.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
METABOB INC
SBIR Phase I: The Development of an Artificial Analysis (AI) Static Code Analysis Platform to Increase Software Developer Productivity
Contact
340 E MIDDLEFIELD RD
Mountain View, CA 94043--4004
NSF Award
2318738 – SBIR Phase I
Award amount to date
$246,700
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to increase the speed and accuracy of software development in a wide range of industries and to make software developers more productive. The technology will decrease the time spent reviewing code by shipping higher quality and defect free code and will further ensure more secure software that is less prone to outside attacks. This SBIR Phase I project develops a cloud-based artificial intelligence (AI)-based static code analysis tool which can find complex and severe problems early in the process of software development. Unlike existing static analysis tools, the tool developed in this project will learn automatically from bug fixes, explain the errors found, and make recommendations on how to fix them. Results will help organizations and developers in the finance, healthcare, and defense industries where code reuse is important for security and compliance reasons. Overall, this project fits well with an increasing trend of organizations integrating more AI into their operations and a growing market for software development tools.
This SBIR Phase I project combines the latest advancements in machine learning and natural language processing to develop a new, intelligent way to find and explain software errors. The project focuses on developing a software architecture that enables the analysis of a complete model hierarchy, establishing a technique to effectively and quantitatively evaluate the validity of explanations generated for flagged bugs, and integrating the disparate components into a single analysis framework. The project will consist of three models which will be developed and integrated as part of the overarching system architecture: (1) a code fault detection model utilizing a graph attention network, (2) a generative transformer to build explanations and suggestions, and (3) a graph-to-graph transformer to generate mutations to the code architecture to resolve the flagged bugs. The project will leverage recent advancements in transformer-based and graph-based neural networks and therefore propel the current state of research for efficient code review processes forward.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MIDWEST ELECTRIC PROPULSION COMPANY (MEPCO)
SBIR Phase I: A compact, 3-level, high efficiency, 4-port, modular universal power conversion system with Internet of Things (IOT) using Wide Bandgap (WBG) devices
Contact
4212 N 76TH ST
Milwaukee, WI 53222--2002
NSF Award
2153880 – SBIR Phase I
Award amount to date
$255,920
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project focuses on developing a universal power conversion system that addresses the unmet needs of the fast-growing electrification and energy storage industries whether it is related to electric vehicles (EV), EV charging, EV charging infrastructure, grid storage, or electric boat applications. The proposed modular and scalable power conversion system is based on the latest generation of power semiconductor devices, silicon carbide (SiC), and can be used across many applications extending over wide power and voltage ranges. The project aims at making the system extremely compact and achieving extremely high efficiencies, which cannot be achieved by silicon-based systems. This modular system configuration can easily be adopted to develop medium voltage-based EV charging application which will be the future for the EV commercial semi trucking industry. Furthermore, due to modularity and scalability, system integration becomes easy and less time-consuming decreasing the cost and helping the adaptation of electrification.
This SBIR Phase I project proposes to develop a multi-input, multi-output modular, scalable, and highly compact wide bandgap-based, four-port universal power conversion system which can be applied to electric propulsion and other power conversion applications. Variants of this system are suitable in electric vehicle charging, grid-connected energy storage, distributed energy, and electric boat propulsion. The intellectual merits of the proposed research and development work is the highly compact and efficient nature with multiple power ports supported by a high frequency transformer switching at hundreds of kilohertz resulting in an anticipated size reduction of 50 times, and a weight reduction of at least 5 times compared to existing technologies. The proposed highly integrated, four port system is based on the combination of next generation wide bandgap gallium nitride and silicon carbide devices. Three ports of the four port system will include, the battery port, propulsion motor port/AC grid connection port and 12V-48 volt auxiliary port, realized by using SiC based 3-level power electronics building block (PEBB).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MINTANGIBLE, INC.
SBIR Phase I: IP Programmable Rights Units On Blockchains
Contact
12405 NORTHLAKE PL
Henrico, VA 23233--6636
NSF Award
2335060 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to revolutionize global participation in the intellectual property ecosystem. This company's innovation signifies a paradigm shift in how society comprehends and manages intellectual property, paving the way for increased value creation and democratizing a system historically marred by complexity, cost, and opacity. Leveraging the inherent characteristics of blockchains?decentralization, peer-to-peer dynamics, transparency, and cryptographic verifiability it is possible to establish an open, efficient, and inclusive system for intellectual property licensing and transactions. This project?s innovation will break down barriers, both legal and economic, for creators across diverse fields, including artists, writers, filmmakers, and scientific and business innovators. Technical understanding of cost-efficient blockchain based platforms, today one of the biggest barriers to large scale blockchain based use cases, will be enhanced due to the efforts of this project. Additionally, enhanced technical understanding of composable legal representations and models while maintaining business meaning will be achieved. The global intellectual property rights market is projected to be $21B by 2029 and the blockchain token/NFT market is projected to be $211B by 2030. This disruptive enabling technology has significant commercial potential.
This SBIR Phase I project proposes to demonstrate the ability to deconstruct intensely complex prose based legal constructs representing intellectual property rights into ?programmable rights units? and operate these units on any blockchain in a compute efficient and cost efficient manner. The objectives are twofold. First, the project will accurately deconstruct prose-based legal documents into composable IP licensing elements, ?programmable rights units,? and represent them in non-lossy semantic meanings. These deconstructed units must be capable of execution on blockchains in a commercially viable way. Second, the project will demonstrate the ability to implement composable programmable rights in a blockchain-agnostic form. This objective is crucial for commercial success as the proliferation of blockchains will continue, thus, supporting many blockchains is required for a broad addressable market. These objectives will require usage of modeling techniques, linguistic pattern analysis (natural language processing and otherwise), technical architectural cost impact analysis as well as algorithmic evaluation of leading edge technologies such as zero knowledge proofs and cryptographically independently verifiable artifacts and identities. The anticipated results will be a proven, blockchain agonistic platform that accurately represents the semantic meaning of complex IP rights business models that can be automatically interacted with for executing commercial transactions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MITHRILAI CORP.
SBIR Phase I: SaiFE: Trusted AI with Hardware Security Enforcement
Contact
1107 CRAB ORCHARD DR.
Raleigh, NC 27606--3517
NSF Award
2333126 – SBIR Phase I
Award amount to date
$272,773
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is centered on elevating economic and societal well-being by significantly enhancing the security posture of Artificial Intelligence (AI) and Machine Learning (ML) hardware and systems, which are increasingly ubiquitous and used in safety/security-critical applications. As this project analyzes hardware attacks and pioneers new defenses, it ensures a more reliable foundation for AI/ML technologies that society relies upon for healthcare, finance, and national security. The commercial potential is substantial; as developers deploy these fortified systems, they mitigate the risk of costly breaches, fostering trust and accelerating adoption. Economic benefits also extend to a reduction in expenditure related to cyberattacks and an increase in market competitiveness for secure AI/ML products. Furthermore, by deepening understanding of hardware vulnerabilities and defense mechanisms, the project pushes the frontiers of scientific knowledge in cybersecurity. As a result, the innovations from this project are poised to reinforce critical infrastructure against hardware-centric threats, thereby safeguarding the digital economy and reinforcing the United States' leadership in secure technological advancements.
This Small Business Innovation Research (SBIR) Phase I project conducts a transformative approach to addressing the acute problem of securing AI/ML hardware systems against emerging hardware attacks such as side-channel and fault injection attacks. Recognizing the vulnerability of these systems to hardware exploitation, the project aims to comprehensively analyze the attack vectors and devise innovative defense mechanisms. The proposed research is set to employ a multi-layered methodology that integrates cutting-edge cryptographic techniques and novel machine-learning algorithms to enhance hardware security. Through rigorous experimentation and validation, the anticipated technical results include the development of trusted hardware modules, the establishment of a benchmarking framework for hardware threat assessment, and the creation of adaptable, resilient defense architectures. This will significantly advance scientific understanding of hardware security in the context of AI/ML, potentially setting a new standard for industry practices, while addressing a critical vulnerability in modern computing infrastructure.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MOIRES INSTRUMENTS, LLC
SBIR Phase I: A Radio Frequency Quadrupole Stark Decelerator to Identify Isomers and Conformers and Measure their Effective Dipole Moments
Contact
805 BRANDON MILL CT
Elon, NC 27244--8300
NSF Award
2208750 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will lead to a new type of analytical instrument and associated businesses, specializing in the identification and characterization of chemical isomers and their different conformational forms (conformers). Isomers are molecules with the same constituent atoms but arranged differently. The identification of isomers and their conformational forms is of critical importance to pharmaceutical and agrochemical industries since the metabolites of many medications or agrochemical compounds are often isomers of one another. Since some of these metabolites may be harmful, safety and efficacy studies require careful analytical ?method development? work to quantitate their presence in clinical samples, soils, and foodstuffs. Unfortunately, current analytical methods for identifying molecular isomers are cumbersome, slow, and involve trial and error work ? presenting a significant bottleneck to regulatory approval. The proposed technology seeks to provide a rapid and robust instrument for isomer analysis, dramatically reducing pharmaceutical and agrochemical development costs and extending patent exclusivity sales ? while enabling the experimental identification of conformers for the first time. Access to this new information has the potential to transform agrochemical ($220 billion total addressable market (TAM) in 2022) and drug discovery ($82 billion TAM 2022) sectors, while generating new well-paying, high-tech jobs.
This SBIR Phase I project proposes to develop a novel mass spectrometer that works on neutral molecules rather than ions. It uses high electric fields to manipulate and distinguish molecules, separating them by the magnitude of their electrical polarity which, in turn, is highly sensitive to the molecule?s 3D shape. Molecules may be pushed or pulled by the fields depending on their orientations in the field and the magnitude of their polarity (?dipole moment?). Since molecular isomers weigh the same, their identification via mass spectrometry is complicated and typically requires time-consuming ?method development? work. The proposed instrument aims to reduce this work by using dipole moments to distinguish all isomers and their conformers in a single spectrum ? with an axis labeled by mass-to-dipole-moment ratio, rather than mass-to-charge ratio. This technology uses microfabrication techniques to miniaturize and planarize a previously demonstrated quadrupole device described in the academic literature, creating an array of microscopic quadrupole channels. The additional patent-pending deceleration feature, coupled with velocity selective detection, should result in 2-to-3 orders of magnitude higher isomer/conformer discrimination capabilities over the literature device. Finally, this universal detection methodology will allow for continuous throughput, which is ideal for interfacing with standard analytical instrumentation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MOLECULAR SURFACE TECHNOLOGIES LLC
SBIR Phase I: Catechol Linker Oligosaccharide Combinations for Antimicrobial Surfaces
Contact
33 TECHNOLOGY DR SOUTH
Warren, NJ 07059--5298
NSF Award
2143961 – SBIR Phase I
Award amount to date
$255,862
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase 1 project is a decrease in the devastating effects of deep implant-related infections. The technology could result in advances to the clinical health and welfare of the American public by improving clinical outcomes and decreasing morbidity and mortality. The technology addressed by this project may protect surgical implants, such as joint replacements and spinal fusion systems from bacterial colonization and developing infections. This technology could significantly reduce the greater than $3 billion cost to the US healthcare system from implant related infections. This antimicrobial technology could be used beyond medical applications for such things as food packaging to decrease foodborne diseases and more than double shelf-life of certain food products. Additionally, the linker technology developed through this project may be used to create super slick or self-cleaning surfaces with applications in the aerospace and marine industries resulting in increased fuel efficiency and performance.
The project aims to develop a homogeneous, covalently bound, linker molecule attached to medical implant material (titanium alloy) upon which a quaternary ammonium-modified oligosaccharide will be subsequently attached. Oligosaccharides are known to be biocompatible and quaternized oligosaccharides are highly potent antimicrobials. A treated medical implant could possess a powerfully antimicrobial surface so that, during surgery, any bacteria that encounter the surface will be killed. In this way, it is hoped that the avascular surface of the implant will not serve as a site for biofilm formation and growth and thus, reduce the incidence of perioperative infections. The key to any successful surface modification is the quality of the chemical attachment of linkers and active molecules to that surface. Polyphenols and catechols such as dopamine are ideal candidates for investigation as these molecules are generally known for their facility in forming thin films onto a wide variety of surfaces. Using dopamine as a model system, catechol analogs will be electrochemically attached, and the resulting thin films analyzed for attachment, thickness, ease of further modification, and morphology. Atomic Force Microscopy (AFM), UV/Visible spectroscopy, soak/stress protocols and microbiology will be used to gauge the success or failure of a thin film plus oligosaccharide combination.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MORNINGBIRD MEDIA CORPORATION
SBIR Phase I: A Fully Electric Space Vehicle Propulsion Engine
Contact
259 CHESWICK DRIVE
Madison, AL 35757--8712
NSF Award
2318600 – SBIR Phase I
Award amount to date
$272,800
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a fundamental change in the way spacecraft propulsion can be achieved, perhaps leading to orders of magnitude faster space travel. Recent physics breakthroughs suggest that the development of an electromagnetically powered engine could enable high-speed travel under the right conditions. Commercially, there is great potential to decrease transit time to destinations on earth, to low-earth orbit, to the moon, and to destinations further in our solar system. Success in developing this engine will initially be developed by improving satellite positioning and accessing orbits. Further scale up of this propulsion system could serve as a platform technology to enable increased access to space due to reduced need for chemical propellant and enhanced speeds.
This SBIR Phase I project develops and tests a prototype engine by verifying the creation of electromagnetically driven propulsion. By utilizing a complex dielectric material as the environment where electromagnetic energy is introduced, the proof-of-concept engine will verify that the weak and strong force conditions are not violated and that a positive energy density can initiate nanoscopic distortions, to demonstrate novel electromagnetic propulsion in the form of further scalable engines. A number of researchers have begun building upon the work of Albert Einstein?s general relativity theory and now Miguel Alcubierre?s metric that suggests that a vessel can be propelled by selective distortion. Two key goals are the development and implementation of the complex dielectric material, and the determinization of the radio frequency power required to achieve sufficient propulsion. The project approach will include: (a) mathematical modeling, (b) comprehensive simulations of different embodiments of the approach, (c) experimental verification of nanoscopic distortions using an established laser interferometry approach, and (d) design and testing of the prototype propulsion engine. Beyond the initial prototype, the next stages include an optimization of the power/distortion metrics, association of the distortion to thrust, and maximization of the thrust to weight ratio. Ultimately, this research is expected to lead to enhanced electric propulsion that will be applicable initially to satellites, but ultimately, to a wide range of on earth and off planet propulsion.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MOTION GRAZER AI, INC.
STTR Phase I: Swine Automatic Lameness Sensor (SALS)
Contact
325 E GRAND RIVER AVE
East Lansing, MI 48823--4384
NSF Award
2232959 – STTR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase 1 project is to provide an in-farm sensing system that will notify sow (adult female swine) farmers of early signs of animal lameness, and thereby reduce early sow mortality and enhance farm productivity. The technology uses artificial intelligence to analyze pig locomotion in order to spot subtle patterns indicative of lameness. Early detection of lameness will enable farmers to take corrective actions rather than waiting for lameness to deteriorate to sow death or culling. Early culling or sow death is a major economic cost to farmers and a large fraction of death and culls is due to animal lameness. Successful application of the technology being developed in this project promises to reduce early sow mortality and culling, leading to additional litters per sow and so provide a significant economic boost to farmers. With patent applications for key components of the sensing system, farmers will install sensors in hallways and obtain health measures for each sow when she moves between rooms. The projected annual revenue is $3.0 million.
This Small Business Technology Transfer (STTR) Phase I project proposes combining an imaging sensor with artificial intelligence to create a unique sensing system to unobtrusively and remotely diagnose lameness in sows (adult female swine) as they traverse hallways. This project seeks to validate two key technical contributions. First, precise 3D animal posture and locomotion are estimated for sows moving beneath a ceiling-mounted sensor. High accuracy is achieved through a novel annotation technique that overcomes difficulties in inaccurate manual location of skeletal landmarks. Second, a data-driven approach is used to train a deep neural network to learn the most discriminating combinations of posture and gait for determining lameness in walking sows. A self-supervised neural network sidesteps the need for extensive manual annotation and expert annotation is only required for lameness assessment. Together, these two contributions will enable a transformative technical capability of a remote sensor that can automatically diagnose early-stage lameness in sows.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NATIONAL RESOURCE CONSULTANTS, LLC
SBIR Phase I: A Carbon Capture System for Algae Cultivation and Biochemicals Production using Hybrid Solar Lighting
Contact
1603 BARRINGTON DR
Manhattan, KS 66503--8661
NSF Award
2324850 – SBIR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to mitigate CO2 (carbon dioxide) emissions into the atmosphere from point sources by developing a cost-effective carbon capture technology using a hybrid solar algae cultivation system. The team seeks to develop a method to use algae to produce biochemicals and biofuels. The algae cultivation system will utilize deep photobioreactors operated under controlled environmental conditions so as to obtain high area biomass productivities at a low land footprint. An algal biorefinery approach will be used to produce organic chemicals from the carbohydrate fraction, biodiesel from the lipids fraction, and end use for the residue. The adverse effects of CO2 accumulation include the frequent incidences of wildfires, flooding, intense hurricanes, and the acidification of the marine environment. The annual cost of wildfires alone in the U.S. in terms of damage to human health and the ecosystems is estimated to range from $71 to $348 billion. Growth rates of algae and the ability to absorb CO2 are about ten times that of terrestrial plants. This project will provide a
sustainable carbon capture technology as it primarily relies on solar energy to capture CO2 and produce high value bioproduct. Implementation of this technology would also provide significant employment opportunities in diverse areas.
The project will develop a hybrid solar/Light Emitting Diode (LED) lighting system within a photobioreactor to obtain high algal productivity and carbon dioxide capture from point emission sources. The novel hybrid solar lighting system will provide internal illumination at optimal intensity and temperature conditions to maximize carbohydrate productivity. The carbohydrate fraction of the algae will be processed to obtain high value platform organic acids using a proprietary low pH fermentation process. The goal of this project is to a obtain proof-of-concept for a photobioreactor design that will maximize volume per unit surface area so as to obtain high areal carbohydrate productivity with a small land area footprint and low external energy input. Fiber optic lighting will be used to provide internal illumination. The project scope also includes the feasibility of converting algae via acid hydrolysis to sugars and subsequent fermentation of these sugars to high value organic acids.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEARSTAR FUSION INC
SBIR Phase I: Hypervelocity Gradient Field Fusion
Contact
13935 WILLARD RD
Chantilly, VA 20151--2936
NSF Award
2304408 – SBIR Phase I
Award amount to date
$265,965
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a more rapid lower-cost development path to a commercially attractive highly modular fusion power plant. Although early stage in its conceptual development, this technology has the potential to leapfrog past current fuel cycle models to provide cheaper, advanced aneutronic fuel systems that reduce or eliminate neutron reaction products and may also eliminate the need for tritium. The abundance of fusion fuel from seawater could provide strategic energy security and economic security to the U.S. and allied nations by phasing out need for hostile foreign fossil fuel suppliers. The commercial impact of this project includes grid based clean fusion energy is literally could extend to a $T+ market if expanded to meet global power demand, with a market pull driven by the need for clean abundant inexpensive energy. This technology will support a wide range of science and engineering jobs, and manufacturing jobs in both the energy and aerospace industries. This project will perform computational modeling and analytical calculations to show scientific and engineering feasibility prior to a focused follow-on experimental development program.
This SBIR Phase 1 project proposes to research and develop a new, simpler, and cheaper approach to fusion energy for grid based electric power. In this approach, a small fusion fuel capsule is accelerated to 10 km/s and injected into the throat of a strong magnetic field coil where it is symmetrically crushed to ignite and burn the gaseous fusion fuel contained within. While conceptually appealing and straightforward, some key components are partially unproven and require extensive research to show feasibility. First, the fuel capsule implosion and resulting fusion burn are not yet studied in sufficient detail to understand the potential plasma physics problems, including plasma-wall interactions, end losses, preheat, and overall energy yield and gain. Second, the novel railgun design needs development with a plasma armature and distributed power input using mass-produced moderate voltage capacitors and solid-state switches in order to achieve the estimated 10 km/s required to induce fusion and long life-time components. Extensive computational modeling and analytical calculations and design will be performed to de-risk the concept and establish a point design for a Phase 2 experimental validation of the concept.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEUROSOMNICSLLC
SBIR Phase I: Non-invasive Closed Loop Neuromodulation to Treat Obstructive Sleep Apnea
Contact
8748 DOUBLE EAGLE DR
Las Vegas, NV 89117--5803
NSF Award
2304265 – SBIR Phase I
Award amount to date
$269,942
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a non-invasive, externally worn appliance for treating obstructive sleep apnea (OSA), a condition affecting over 88 million Americans (26% of the American adult population). Those impacted by OSA are at risk of serious comorbidities such as diabetes, stroke, and heart disease. Many sufferers remain untreated due to intolerance to current treatment options with adherence and compliance rates as low as 40%. The economic impact is estimated at $30 billion resulting in $150 billion aggregate indirect costs due to motor and workplace accidents as well as productivity losses each year. The technology aims to capture part of the $18 billion sleep device market which remains significantly under penetrated due to approximately 80 million undiagnosed cases in the US alone.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a non-invasive, dental neurostimulation device capable of activating the motor nerve fibers supplying the muscles responsible for dilating the upper airway in a controlled, non-perceptible manner. The appliance will be integrated with multiple sensing and stimulation electrodes to activate precise nerve branches in order to provide continuous innervation of relevant upper airway muscle groups, without interfacing directly with the nerve branch itself. Algorithms employing machine learning will be used to process neural electrode feedback signals and control electrical field stimulation waveforms. The project will consist of appliance design, benchtop testing, and overnight sleep studies in patients to build datasets and construct new algorithms. A software application will then be developed to automate routines in real-time in order to demonstrate concept feasibility of a new non-invasive therapy for obstructive sleep apnea.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEURX MEDICAL LIMITED LIABILITY COMPANY
STTR Phase I: Endovascular Thrombectomy System for Ischemic Stroke
Contact
8516 PARKWOOD LN
Philadelphia, PA 19128--1309
NSF Award
2136438 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve survival and functional outcomes for stroke patients. Stroke remains a leading cause of death among Americans and is the largest source of long-term disability in the U.S. and around the world. Every 30 seconds, an American suffers a major stroke, most commonly caused by a clot obstructing a large cerebral artery supplying a critical area of the brain. This project?s clot-removal technology aims to enable rapid and efficient removal of clot from the cerebral vessels using minimally-invasive image-guided techniques, thereby improving the chances of full recovery and an independently functional outcome. The broader benefit for society is to reduce death or permanent disability from ischemic stroke with its resultant family, community, and economic burden.
This Small Business Technology Transfer Phase I project will lead to the development of a medical device to enable efficient removal of blood clots from the brain arteries of a stroke victim. The platform technology is constructed from microscopic tubes of superelastic metal alloy integrated with a proprietary pattern of laser-cut apertures. The device can be delivered to the stroke clot through a microcatheter to create a shape-formed array of clot-capture elements within a patient?s artery. Tandem capture devices optimize the clot capture system and can be positioned on either edge of a clotted segment within a brain artery. Optimal shape, thickness and materials of the clot capture elements and the delivery system will be characterized, developed, and verified. The proposed work will utilize a previously validated model of stroke thrombectomy to characterize and quantify fundamental clot capture parameters (clot stabilization, retention, and retrieval) among multiple discrete capture node embodiments. Radial force, coefficient of drag during withdrawal inside a cerebral blood vessel and device trackability will be measured for each design using robust three-dimensional human anatomic models of cerebral vessels. The project will enable a design freeze of the optimal device design and validate its performance using a preclinical animal model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEXGEN CANCER DETECTION LLC
SBIR Phase I: Enrichment of Cancer DNA for Improved Cancer Diagnostics from Blood
Contact
2132 21ST AVE SM
Lino Lakes, MN 55038-
NSF Award
2321908 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the diagnosis of residual cancer cells, after treatment of cancer patients. The test will be conducted early and accurately using a simple blood draw. Twenty percent of cancer patients will experience cancer recurrence. Unfortunately, cancer recurrence is not diagnosed until years after initial treatment when the cancer has often metastasized, resulting in poor patient outcomes. As a result, 7% of cancer patients suffer from debilitating fear of cancer recurrence. Early and accurate diagnosing of residual cancer cells will improve the outcome for the 20% of cancer patients who experience recurrence. Additionally, it will help the 7% of cancer patients who suffer from debilitating fear of cancer recurrence. Overall, the costs of treating cancer will be lowered by diagnosing cancer earlier.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a highly accurate diagnostic test for residual cancer from a blood draw. DNA (deoxyribonucleic acid) from cancer cells circulates through the blood stream. This cancer can be detected because of mutations in the DNA of cancer cells. However, cancer DNA is rare compared to normal DNA, which makes diagnosing cancer from a blood draw difficult. Proof-of-concept data has shown that accuracy can be greatly improved through the enrichment of cancer DNA from a sample. After the sample is collected, the DNA goes through rounds of duplication, except a blocker is added to prevent normal DNA from duplicating. Through this process the cancer DNA becomes a larger percentage of the overall DNA in the sample and can be more accurately detected. This project will develop a collection of tests for accurately diagnosing residual colorectal cancer. The key tasks of this project are: 1) demonstrate the clinical robustness of the optimized test method, 2) develop additional tests to cover most colorectal cancers, and 3) demonstrate the sensitivity and specificity of the test methods. This project will lead to earlier and more accurately diagnosed cancer recurrence.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEXT-ION ENERGY, INC.
SBIR Phase I: A unique aerogel-based separator technology for safety and ultrafast charging of batteries
Contact
1777 DEL LAGO
Yuba City, CA 95991--6905
NSF Award
2304448 – SBIR Phase I
Award amount to date
$274,537
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will improve battery market and contribute towards the shift to affordable and clean energy solutions. The company?s novel aerogel membrane separator exhibits performance characteristics that address the major limitations of existing batteries. The enhanced durability and stability provided by the membrane make batteries highly suitable for electric vehicles (EVs) and other applications, such as mobile phones, tablets, drones, cordless power tools, and e-bikes. Electric vehicles offer the most likely solution to reduce the environmental impact of transport in the US by contributing towards a significant reduction in the usage of fossil fuels and the subsequent emissions of greenhouse gases. This technology seeks to improve the overall lifespan of batteries and ensure that they can endure rigorous usage conditions, thereby increasing the reliability and range of EVs, while decreasing the frequency and time of charging and battery replacement. Similarly, in the realm of electronics, the extended battery life translates into enhanced device performance, reduced downtime, and ultimately improved user experience.
This SBIR Phase I project examines the technical feasibility of the company?s aerogel technology as a separator membrane. This membrane is formed by a unique 3-dimensional orientation and functionalization of hexagonal boron nitride sheets (h-BN) combined with boron nitride nanotubes (BNNTs). Current separators are limited by poor thermal stability, subsequently causing the battery industry to face challenges such as long charging times, safety risks associated with high heat generation rates, and low battery performance due to the lack of enough energy capacity. This solution allows for ultra-fast charging (extending the battery rating to 10C) and improved safely (allowing batteries to operate up to 200 °C), while enhancing cyclability, capacity, and power density. The research activities that will allow characterization of the aerogel are functionalization of the membrane with various chemical moieties to enhance ion conductivity, internal series resistance, and lithium plating resistance and investigation and testing of the aerogel pore size formation for a uniform size distribution to prevent lithium plating and penetration of active particles, while maximizing ionic conductivity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEXTGLASS LLC
SBIR Phase I: Low-Cost, High-Performance, Vacuum Insulated Glass Window
Contact
12009 MONTROSE VILLAGE TER
Rockville, MD 20852--4162
NSF Award
2233584 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is technology to improve the efficiency of building energy consumption. Windows account for about 30% of building energy losses and 7% of US carbon emissions. Vacuum insulated glass (VIG) windows are 4-5 times more insulating than a typical double-pane glass windows and are almost as insulating as the surrounding walls. A low-temperature production method will make vacuum insulated glass much more affordable. Such highly efficient and low-cost vacuum insulated glass will enable replacement of widely used double pane windows thus reducing the building carbon footprint. This decrease in pollution is especially significant given the push for net zero energy buildings and net zero greenhouse gas emissions by 2050. Major sectors that will benefit from such window developments are residential buildings, commercial buildings, and supermarkets (freezer/cooler doors). Market research indicates the VIG market is more than $25 billion.
This SBIR Phase I project will develop low temperature, vacuum insulated, glass windows that dramatically reduce the production cost of the currently available vacuum insulated glass (VIG). Although vacuum insulated glass products are highly efficient and have been produced for more than 30 years, they have not found market acceptance due to very high cost and poor seal reliability. Current high temperature, VIG manufacturing processes are slow and require expensive vacuum furnaces resulting in high costs. The proposed flexible seal VIG manufacturing process is a low-temperature production method that is much faster, thus requiring much lower capital investment, bringing VIG costs much closer to that of double pane windows. The novel flexible seal design of the proposed VIG also improves long-term seal reliability by eliminating thermal expansion stresses experienced by current rigid VIG seals. The performance and long-term durability of small VIG samples made using the low-temperature seal were validated. However, scale-up must be demonstrated before successful VIG development. The current project aims to scale up the proposed VIG manufacturing process and subject full-scale samples to rigorous accelerated weather, temperature, impact testing. A secondary seal will also be developed to prevent it from weather and gas permeation to ensure 50+ years of window life.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOMI MATERIALS CORP
SBIR Phase I: Scalable Synthetic Mucin Biomaterials
Contact
720 FORT WASHINGTON AVE APT 1L
New York, NY 10040--3711
NSF Award
2304237 – SBIR Phase I
Award amount to date
$273,962
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project includes the commercialization of synthetic materials that reproduce the structures and functions of mucus gels. Nature deploys mucus to address a wide range of soft material needs, including as lubricants, adhesives, and barriers, and natural mucus is currently being investigated for filling many of these same roles in consumer products. The synthetic mucins can impact various markets including skincare, dermatology, healthcare, and materials industries. Furthermore, synthetic analogs of mucins can advance the scientific frontiers through a better understanding of the role of mucus in digestive, respiratory, and immune systems. The societal impacts of this project include the national economic benefits resulting from being the first to bring to market an entirely new class of biomimetic materials.
This SBIR Phase I project proposes to address technical hurdles related to the sustainable scalability, biocompatibility, and tailorability of synthetic mucus biomaterials. The current commercial manufacturers of natural mucus directly harvest the mucin biomaterials from animal mucus. Such a practice poses challenges related to purity, scalability, and reproducibility, which preclude its incorporation into many of the envisioned applications. To overcome the challenges, this project designed a synthetic mucin prototype and seeks to achieve the following goals: i) reconfigure the chemical process to reduce costs, production time, and environmental impact; ii) understand the tolerance of epithelial cells to these synthetic mucins; and iii) demonstrate a relationship between the chemical structure and material properties of synthetic mucins so they can be tailored to meet particular customer demands. Taken together, these efforts will remove many of the major barriers to the commercial viability of synthetic mucins.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOUVAI INC.
SBIR Phase I: A Mixed-Computation Neural Network Acceleration Stack for Edge Inference
Contact
800 N CRESCENT HEIGHTS BLVD
Los Angeles, CA 90046--6902
NSF Award
2304304 – SBIR Phase I
Award amount to date
$274,915
Start / end date
12/15/2023 – 08/31/2024 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to improve the sustainability of artificial intelligence by reducing carbon emissions for training neural networks and performing inference at the edge. Additionally, the technology will spawn new applications and use cases for edge inference (including personal health, advanced data analytics, and informed decision-making), resulting in significant improvements in people's lives and well-being. The commercial potential is substantial (i.e., tens of billions of dollars annually), as are the potential economic benefits to US high-technology industries.
This Small Business Innovation Research (SBIR) Phase I project sets out to develop a mixed-computation neural network acceleration stack utilizing optimally designed and provisioned hardware resources. This acceleration stack empowers a heterogeneous hardware realization of a neural network inference engine whereby computations required in various network layers may be done by using different number systems and different precision levels. The acceleration stack can thus achieve very high inference speed and energy efficiency while maintaining the inference accuracy compared to a homogeneous hardware realization of the network using 16-bit floating point computations. To support the design, optimization, and runtime efficiency of this edge inference accelerator, a full suite of software and design automation tools comprising a distiller for neural network architecture optimization and training, a logic synthesizer for generating optimized gate-level realization of very large and complex Boolean and multi-valued logic functions, a compiler for generating and scheduling control-flow and data path instructions that are executed on the target fabric, and a runtime system for orchestrating data movement will also be provided. The resulting edge inference accelerator will be deployable on resource-constrained, energy-limited, and cost-sensitive edge devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOVINEER, INC.
SBIR Phase I: Computational Synthesis of 3D Printed Composite and Infill Layouts
Contact
1511 AVIATION CENTER PKWY
Daytona Beach, FL 32114--3857
NSF Award
2334913 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project expedites the growth of additive manufacturing for end-use parts through automated design software. Additive manufacturing has emerged as an appealing alternative to traditional subtractive manufacturing to fabricate end-use parts with tailored stiffness and strength. A critical production stage required to unlock the potential of additive manufacturing for end-use parts is the design process, which currently requires extensive engineering experience and high engineering design time. The new technology will allow a paradigm shift from the current slow, tedious, and failure-prone design process to an automated design process. The algorithm utilizes high-performance computing and designs components based on strength, specific material properties, and manufacturing constraints. The technology is expected to reduce engineering design time and, as a result, the production cost and time, which will enable the industry to scale production. Additionally, by using the automated design process, the material distribution can be tailored to achieve the desired structural responses, and lightweight structures can be fabricated. The reduction in weight results in a reduction in fuel consumption in aviation and auto industries, which will provide both ecological and economic benefits.
This Small Business Innovation Research (SBIR) Phase I project advances the state of the art by (a) developing novel approaches to optimize layout, fiber paths, and plastic infill distribution, (b) generating additive manufacturing toolpaths based on structural performance and efficiency, and (c) implementing multiple failure criteria to understand failure loads in composite additive manufacturing. Due to the significant cost difference between continuous fiber filament and plastic infill, it is crucial to consider the design of fiber paths, carbon fiber reinforced regions, and plastic infill layout. Another challenge is that current design processes do not include a single failure criterion that can predict failure under different loading scenarios. To address these two challenges, the team is investigating a stiffness and strength-based topology optimization for composite additive manufacturing that will enable the design of the geometric layout and toolpath for 3D printing simultaneously. Anisotropic material properties for stiffness and strength in different directions are implemented to utilize the full potential of composite parts. Toolpath constraints such as curvature, minimum length, and width are also implemented in the optimization process to prevent print failure. Finally, an intelligent slicing program will be developed to control the movement of the 3D printer nozzle and eliminate part failure due to stress concentration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NU PLANET PHARMACEUTICAL RADIOISOTOPES, INC.
SBIR Phase I: Low-Cost Isotope Battery for Long-Lived Applications
Contact
16674 N. 91ST STREET, SUITE 103
Scottsdale, AZ 85260--2761
NSF Award
2304501 – SBIR Phase I
Award amount to date
$274,821
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project includes creating radioisotope materials which can be used for high performance power production decay batteries used in deep space, medical applications, unmanned drones, and other uses. These materials will be able to provide electrical power for months or years at a time enabling game changing technologies by enabling ubiquitous and readily available nuclear power to become a reality. Not only can this technology be used for power, but the specific isotopes produced can also support efforts to fight cancer, perform medical imaging, and explore natural resources. According to Allied Market Research, nuclear driven battery markets are expected to reach $87.2 billion by 2026.The unique capabilities of radioisotopes can provide many benefits in many different areas, but their rarity often limits their use.
This SBIR Phase I project seeks to generate a power-producing radioisotope material from a naturally-occurring source and show that it can be used for power in a long-lived nuclear battery. The technical hurdles for this project include being able to use radioisotopes not currently considered for decay batteries and generating useful amounts of radioisotopes for an attractive cost. In order to overcome these hurdles, a functioning prototype will be constructed and driven with isotopes made at NPPR to empirically show feasibility. This will be accomplished by demonstrating the ability to induce radioactive decay in the feedstock, collecting the radioisotope produced, and showing its use in a power source. With the developments made in this project, radioisotopes will be more readily available. Medical, aerospace, defense, and many other markets will see great opportunities for advancement with the newly available materials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NUTHATCH ROBOTICS, INC.
SBIR Phase I: Three Dimentional (3D) Printing With Embedded, Layer-Crossing, Continuous Carbon Filament Reinforcement
Contact
63 BEDFORD RD
Lincoln, MA 01773--2031
NSF Award
2213040 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to increase the all-around strength of three dimentional (3D)-printed polymer objects, which will make such objects more useful for structurally-stressed prototypes and manufactured products (including prototypes and products that are physically large). The prposed strength gains are expected from embedding continuous carbon-fiber filaments in multiple directions within the body of a 3D-print. Designers and engineers seek to tailor internal carbon-fiber arrangements to suit their specific needs. The resulting carbon-fiber-reinforced objects (as with 3D-printed objects in general) may be produced without the expensive and/or time-consuming use of molds, tooling, or specialized hand-labor. By facilitating the cost-effective production of strong, plastics-based custom and low-volume manufactured products, this project seeks accelerate product development, foster entrepreneurship, and encourage manufacturing endeavors within the United States by making it easier to turn imagined concepts into strong, functional objects in the physical world.
This SBIR Phase I project seeks to develop a process for embedding continuous, layer-crossing, carbon-fiber filaments within the body of a Fused Deposition Modeling (FDM) 3D print in order to provide tensile and shear reinforcement along planes orthogonal to the 3D printed layer. The goal of the research is to employ quasi-parallel filaments oriented orthogonal to 3D print layers, reducing the interlayer weakness and resultant structural anisotropy characteristic of FDM prints. The project will further examine the use of more complex filament arrangements to provide selective reinforcement in directions and along paths specified by a product designer. The overall strength, stiffness, and toughness will be assessed adn compared to conventionally-manufactured engineering plastics. The embedding process, which will take place simultaneously with the layer-by-layer creation of the print, will be achieved by combining the actions of FDM printer nozzles with those of automated robotic filament manipulators. The project will examine the geometric range of printed parts and components that incorporate reinforcing filaments, with initial goal of printing reinforced shell-like objects that continuously curve along multiple axes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPAL HTM INC
STTR Phase I: Novel Medical Equipment Utilization Tracking System for Improved Patient Safety and Hospital Efficiency
Contact
3827 FAWN LN
White Plains, MD 20695--3310
NSF Award
2321886 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project relates to the development of a novel system capable of measuring medical equipment utilization with high accuracy and scalability. This innovation will arm healthcare technology managers with the insights needed to optimize inventory size and composition according to actual patient needs, thereby saving hospitals an estimated $23.3 billion annually in equipment-related costs, in addition to making possible usage-based predictive maintenance that can effectively prevent dangerous equipment failures. Beyond these core value propositions, comprehensive medical equipment utilization insights may be leveraged to facilitate strategic resource management in public health emergencies, increase energy efficiency of healthcare facilities, and improve regulatory surveillance of emerging equipment safety issues. The results of this project will form the basis for a hardware-enabled service and clear the path towards development of deployable products, clinical pilots, and early sales. Through commercialization under a sustainable business model, the envisioned product will substantially increase the economic competitiveness of US hospitals, which comprises one of the largest sectors of the American economy. The project will also advance the health and welfare of the American public through improved medical device safety and management.
This Small Business Technology Transfer (STTR) Phase I project will establish technical and commercial feasibility for an innovative, asset-agnostic, medical equipment utilization tracking system which will integrate state-of-the-art techniques for non-intrusive load monitoring, deep learning, and edge computing in order to overcome previously insurmountable asset monitoring challenges posed by the heterogeneity and churn of hospital equipment inventories. Key technical hurdles to be addressed relate to the capture and characterization of medical equipment electrical load data, real-time translation of this data into accurate usage statistics suitable for hospital decision-making, and distributed implementation of this process through non-invasive sensor modules that are broadly compatible with sundry medical equipment. The proposed research will overcome these hurdles through (i) systematic collection and analysis of power consumption data from a representative group of medical equipment under various operational states, (ii) formulation, training, and validation of adaptive artificial neural networks that predict usage from power data, (iii) construction of a proof-of-concept intelligent sensor module, and (iv) system performance testing in a simulated clinical environment. Through completion of these objectives, this project will advance knowledge in the fields of hospital asset management and industrial Internet-of-Things.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPERA BIOSCIENCE, INC.
SBIR Phase I: A low-cost, bacterial production platform for the manufacturing of high purity recombinant proteins and growth factors
Contact
1801 MAPLE AVE # 5240
Evanston, IL 60201--3149
NSF Award
2233507 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to introduce a cost-effective way to produce recombinant proteins and growth factors for the cultivated meat industry. Cultivating animal cells to create animal tissues, including muscle and fat, allows manufacturers to create real animal meat as an alternative to animal-farmed meat. Producing meat in this method may provide a healthier, safer, and more ethical source of real animal meat. This manufacturing process avoids industrial animal farming and consequently uses significantly less land and water. It also avoids the greenhouse gases emitted by industrial animal farming and may emit far fewer greenhouse gases. Cultivated meat could result in a healthier public as well since its controlled production will likely result in fewer foodborne illnesses and avoid the cramped conditions of industrial animal farms that can breed new illnesses. The ability to grow meat in nearly any location increases the nation?s food supply chain resilience and reduces dependence on foreign food imports. Finally, by reducing the amount of industrial animal farms, cultivated meat reduces the need for animal slaughter.
The proposed project will demonstrate the ability of the innovation to solve several challenges in the current production of recombinant proteins and growth factors in traditional protein manufacturing platforms that prevent manufacturing at lower costs and with high purity. Cultivated meat has the potential to disrupt the >$1 trillion meat industry, but the ability to source high purity, cheap proteins limits the commercial adoption of cultivated meat products. The innovation could produce proteins at cheaper costs than existing platforms because it bypasses expensive and time-consuming operational manufacturing steps while still achieving high purity. The critical technical objectives of this project include: 1) the establishment and comparison of a production benchmark for recombinant growth factor production against the current industry standards, 2) the optimization of the growth conditions necessary for the protein production platform to achieve improved yields, and 3) the creation of a manufacturing platform optimization toolkit to increase the quality and amount of usable protein produced. The knowledge gained at the completion of this project may provide valuable insights into the ability and conditions to promote high production levels of proteins and growth factors while providing data illustrating the improvement when compared against current industry standards.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPTIC FRINGE CORP.
SBIR Phase I: Artificial Intelligence (AI)-Aided Part Identification for Coordinate Measuring Machines
Contact
8 COBBLESTONE WAY
North Billerica, MA 01862--2915
NSF Award
2222967 – SBIR Phase I
Award amount to date
$274,536
Start / end date
01/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a new generation of smart machines used in the measurement of parts and assemblies. The team has demonstrated that this technology can convert existing coordinate measuring machines to self-driving autonomous machines. The ability to automatically measure parts is an important feedback link in the process chain that will enable fully automated manufacturing of the future. Specifically, this automation will reduce the specialized skill required to use a Coordinate Measuring Machine (CMM). The innovation will enable workers to operate a CMM and get a precise part measurement. This device is especially helpful as the skilled manufacturing/metrology workforce is retiring as it gives new employees the ability to provide accurate information with little/no training. This innovation also gives the manufacturing companies an option to buy a new machine or upgrade their existing coordinate measuring machine. While the focus of this proposal is part identification, this technology has ready applications in Computer Numerical Control (CNC) machining, robotics, and automated assembly lines. This capability will make the US manufacturing sector stronger and more technologically advanced.
The objective of this proposal is to develop a new technology to identify machined parts and assemblies. This technology will be implemented on coordinate measuring machines (CMM), which are used widely in the manufacturing sector to measure the shape and size of parts. The proposed technology will enable autonomous measurements of parts allowing a higher level of automation. In this identification technology, the team will use live images from a camera, multiple solid model/Computer Aided Design (CAD)-generated images, and advanced image processing. Applying Artificial Intelligence (AI)/Machine Learning (ML) to the image processing of part images will ensure correct part identification. Correct identification of parts as seen by the camera is the remaining unsolved challenge to achieving self-driven automatic measurements of parts. Most machined parts are textureless and most of the information is contained in the edges. Current image processing techniques work well with texture-rich parts but are unreliable with textureless machined parts. AI/ML enhanced image processing using edge and shape information is a promising approach, solving this problem will lead to the birth of a new generation of CMMs that can measure parts automatically.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ORBITAL SERVICES CORPORATION LLC
SBIR Phase I: Optimizing Safety and Fuel Efficiency in Autonomous Rendezvous and Proximity Operations (RPO) of Uncooperative Objects
Contact
408 FRANKLIN ST UNIT 1
Melrose, MA 02176--1825
NSF Award
2311379 – SBIR Phase I
Award amount to date
$274,999
Start / end date
02/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project will enable a novel class of in-space proximity operations. This research has the potential not only to sustain and improve space operations, but also to strengthen national security and result in a thriving economy in space. The expected advances include sophisticated capabilities for satellite inspection, repair/upgrade, end-of-life servicing, debris remediation, and even manufacturing and assembly operations. This project's emphasis on the safety, robustness, and autonomy of missions also ultimately paves the way for safer human spaceflight operations and contributes to vital areas like debris mitigation and collision avoidance. This effort also extends to the exploration of frontier technologies such as asteroid mining. This project's approach creates commercial opportunities and unlocks the in-orbit servicing, assembly, and manufacturing value chain.
This SBIR Phase I project will synthesize Neural Lyapunov functions, which can be integrated into filter schemes for any type of control system that accepts state feedback from multi-sensor measurements. The primary objective of this study is to enable the inspection and capture of uncooperative, uncontrolled, and unprepared objects. This ability is achieved by fusing data from multiple sensors and applying barrier functions, rooted in Neural Lyapunov theory, to ensure safety within actuation limits and state constraints during the docking and 'combined stack' phases (i.e., when a servicer is docked with a client spacecraft). Furthermore, this technology developed path planning algorithms that use real-time optical measurements to account for the detumbling rates of client satellites, ensuring safer inspection and docking maneuvers. These steps are critical for ensuring safe autonomous operations during the docking phase and combined stack maneuvers. The final outcome of this research is to develop a mission design, analysis, and planning tool to help operators account for different mission scenarios involving in-orbit proximity operations, while analyzing tradeoffs of safety assurance versus fuel optimization.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OSMOSES INC.
SBIR Phase I: Optimization and scaling of ladder polymers for membrane-based gas separations
Contact
750 MAIN ST
Cambridge, MA 02139--3544
NSF Award
2151444 – SBIR Phase I
Award amount to date
$253,815
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
Errata
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Abstract
This broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to develop membrane solutions to address opportunities in the gas and vapor separation market. Today, this market is dominated by energy-intensive thermal processes that have large carbon footprints, such as distillation and absorption/stripping. The current membrane solutions often lack the flux, recovery, and stability required for many applications. The membranes that will be developed in this project are formed from novel polymeric materials that have the highest combinations of permeability and selectivity out of all polymers reported in the open literature. If deployed commercially for renewable and/or traditional natural gas purification, these membranes could reduce energy consumption and product loss by over 40% and over 80%, respectively, compared to current commercial membranes. In this way, the advanced membranes being developed could save up to $2 million per day in product loss that is currently flared from commercial membrane systems, resulting in both savings for the customer and a reduced environmental footprint. Related opportunities in other gas and vapor separation markets could also be enabled by this research.
The intellectual merit of this project is to develop gas separation membranes from a novel class of polymers with record performance. To this end, this effort aims to scale polymer synthesis, form thin films, test developed membranes using complex gas mixtures, and develop an optimized techno-economic model for market applications. These objectives are of practical importance for manufacturing and commercialization, but they are likewise important for scientific and technical innovation in polymer science and thin-film formation. Moreover, testing these materials in thin film form under complex gas mixtures will provide data on stability under relevant conditions. The research on polymer scaleup and thin film formation is critical for refining technoeconomic assumptions for capital costs, and the testing of complex gas mixtures is critical for refining assumptions on process energy costs and cost savings from product recovery. Accomplishment of these objectives will enable new innovations related to the formation of membrane modules that can be tested and evaluated with industrial gas mixtures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OSO SEMICONDUCTOR INC.
SBIR Phase I: Ultra-low loss beamformer and combiner-first technology for lower power, consumption phased arrays
Contact
1572 JENEVEIN AVE
San Bruno, CA 94066--4135
NSF Award
2335496 – SBIR Phase I
Award amount to date
$274,992
Start / end date
12/15/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project is to develop a new phased array communication technology which will be able to achieve lower power consumption, smaller form factors, and more affordable price targets. Phased arrays antennas are essential for satellite communications and the broader 5G, defense, and automotive radar markets. The company?s new phased array architecture will significantly decrease the power consumption and the number of silicon chipsets that are required. This is particularly important in thermally limited and power-constrained environments like mobile platforms and satellite communication systems and leads to the reduction of batteries, bulky power supplies, and additional cooling components. Addressing the high cost and power consumption of these phased arrays will have a significant, positive impact on the commercial opportunity by enabling step changes in performance (like data rates and capacity) or reducing costs for sensitive customer segments.
This Small Business Innovation Research Phase I project will demonstrate a more power-efficient and cost-effective phased array semiconductor technology. This technology uses a novel ultra-low loss, high-linearity, passive beamforming circuit in a unique low-power architecture. In the receive configuration, this technology will be able to achieve a 75% reduction in power consumption due to a 4x reduction in the number of receiver signal chains. In Phase I, the company aims to advance their ultra-low loss beamforming technology to achieve even lower losses, which will enable the combination of the beamformer with their unique low-power architecture. The following objectives realize these goals: 1) development of the novel ultra-low loss beamformer and integration with a receive front-end, 2) fabrication and performance of benchtop testing on the integrated receive circuit, and 3) performance of over-the-air testing of small and moderately sized phased arrays using the receive circuit. The low-power beamforming technology will overhaul current phased arrays, eliminating many of the lossy, power-intensive and expensive components traditional units require. This technology will enable the creation of higher performance, lower cost phased arrays for many critical industries ranging from satellite communication to 5G to radar.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OTHERWORDLY LLC
SBIR Phase I: Automated Detection of Confounds and Inappropriate Context to Promote Prosocial Learning and Cognition
Contact
7804 GARLAND AVE
Takoma Park, MD 20912--7712
NSF Award
2304423 – SBIR Phase I
Award amount to date
$274,990
Start / end date
07/15/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of Artificial Intelligence (AI)-based algorithms that generate content for word-meaning video games at an affordable cost. Word-meaning games support literacy, fluency, critical thinking, and cross-cultural understanding for players of all ages and backgrounds via adaptive vocabulary scaling systems and accessibility options for players with visual or motor difficulties. Science, Technology, Engineering, and Mathematics (STEM) literacy is supported by incorporating STEM content in a mix of entertaining and serious content. These prosocial and cognitive impacts are essential for personal and professional growth, cultural competence, and will be measured by game learning researchers. The project will also contribute to the field of natural language processing and machine learning through the addition of new benchmarks to open-source resources. Success in reducing content creation costs could lead to licensing content to other game publishers and the creation of additional word-meaning games on the market, benefiting players. This project is uniquely positioned to help retain game industry jobs in the U.S. and contribute to the growth of the industry.
The technical innovation of the project is threefold: 1) development of algorithms for unrelated word content generation, 2) development of appropriateness and offensiveness filters for natural language content, and 3) evaluation of a word-meaning game?s ability to improve cognitive function and social awareness. This research and development has the potential to address a gap in the field of natural language processing on unrelatedness. Part of this effort contributes to open-source benchmarks for future research. Similarly, social bias is a prevalent and well-known issue in machine learning models, potentially offensive or inappropriate word combinations need to be detected and avoided via newly developed algorithms that explicitly detect and avoid publishing such content. To achieve both goals, a variety of machine learning techniques, including those that leverage existing large natural language models, will be employed and evaluated for accuracy. Using these algorithms as a foundation for content creation, the word-meaning game will integrate the generated content. The program will be evaluated with regard to its ability to increase social awareness and confidence with an expanding vocabulary. Specifically, the study will evaluate both brief gameplay and long-term gameplay and measure efficacy with in-game metrics and surveys.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OTORO ENERGY INC
SBIR Phase I: Low Cost Metal Chelate Flow Battery for Long Duration Energy Storage
Contact
1740 38TH ST
Boulder, CO 80301--2604
NSF Award
2321989 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project develops the chemistry for a new flow battery used to store energy for the electric grid. The battery chemistry uses abundant minerals and materials that can be sourced and manufactured in the United States. These flow battery materials support long duration energy storage of 4 to 100 hours ? enough to back up the grid and support increased use of intermittent power sources such as solar and wind. This flow battery technology aims to meet aggressive cost targets for grid-scale storage, positioning the company to take advantage of the domestic and international market demand for energy storage. The battery system provides an opportunity for the U.S. to own high impact battery technology and claim a leadership position in the long duration energy storage market.
This SBIR Phase I project seeks to lower the materials costs of a metal chelate flow battery for 10+ hour storage durations with greater than 80% round-trip efficiency. The goal is to develop a material purification process that uses low-grade minerals and removes key impurities with minimal waste. This goal will be achieved through the development and construction of a chemical purification system that selectively removes the impurities present in the low-grade minerals. The process will be validated by the demonstration of a flow battery operating with 10+ hours of continuous discharge at full power. The research and development effort focuses on a holistic solution to flow battery performance via a new chemistry that optimizes cost, abundance, safety, and performance in a single platform for long duration energy storage. Areas of development include electrolyte purity, sensitivity to precursors, processes development, system fouling and electrolyte purity sensitivity, purification system design and recycling, and 10-24 hour discharge battery performance demonstration incorporating the new purification process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OWLFLY
SBIR Phase I: Machine to fabricate a bioinspired insulation material: The Concatenator
Contact
19 HILL RD
Frenchtown, NJ 08825--4008
NSF Award
2232908 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in the development of a novel, and more benign than fiberglass, thermal insulation technology for use in homes across the United States. Improvements in insulation technology have the potential to reduce energy use nationwide, along with all carbon emissions associated with the production and transmission of that energy. According to the Energy Information Administration, 51% of all residential energy in the United States is used for heating and cooling living spaces, which amounts to about 11% of the total energy consumption of the country. This project aims to use the principles of biomimicry to develop a more effective batt insulation. Unlike other insulation materials, unprotected exposure by the insultation installers will not aggravate respiratory issues, which is increasingly important for homeowners and working people who suffer from the long-term effects of COVID-19. This project seeks to push the potential and affordability of this new technology while creating new American jobs.
The project is inspired by the nests of yellowjacket wasps that live in pockets of permafrost high above the Arctic circle. The nests are protected from extreme temperatures by the hollow wall structure surrounding the nest?s interior. This structure can be adapted to create insulation panels that are highly efficient, lightweight, water-resistant, non-combustible, non-toxic, non-dusting, and irritant-free. The project focuses on the development of such a thermal insulation material in an efficient way to keep its price point competitive with the current products. This involves designing a manufacturing machine capable of producing the new insulation quickly and consistently. To further push the thermal performance of the material, the company will also develop a complementary machine that can scan insect specimens in museum collections to assess biological structures that are highly reflective in infrared wavelengths and use the data to address management of radiative heat transfer. The team will apply a six-sigma approach to quality control for improving the insulation manufacturing process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OmnEcoil Instruments, Inc.
SBIR Phase I: Prostate cancer diagnosis with an integrated endorectal MRI and targeted transrectal biopsy
Contact
2936 LAKEVIEW BLVD
Lake Oswego, OR 97035--3648
NSF Award
2037190 – SBIR Phase I
Award amount to date
$255,787
Start / end date
12/15/2020 – 11/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve detection of prostate cancer, a highly prevalent fatal cancer in men. Approximately one million prostate biopsies are performed annually in the U.S. Unfortunately the standard diagnostic method is imprecise and inefficient. The proposed project will advance a new method that uses Magnetic Resonance Imaging (MRI) to target biopsies for improved detection.
This Small Business Innovation Research (SBIR) Phase I project will advance diagnosis of prostate cancer by developing a system that combines an endorectal MRI coil and a multichannel array of transrectal biopsy needle guides and allows for endorectal MRI with in-bore biopsy as a single rapid integrated procedure. The project will advance a procedure that optimally combines endorectal MRI and MRI-targeted biopsy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PARADOCS HEALTH INC.
SBIR Phase I: Tackling Healthcare?s Paradoxes: Quality Patient Care, Provider Workflow, and Data Security
Contact
2450 HOLCOMBE BLVD. STE X
Houston, TX 77021--2041
NSF Award
2233197 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide a new tool for physicians to potentially automate the preparation of insurance documentation and facilitate claim building which may help to lower provider costs and increase patient access to and quality of care. Physicians can spend up to 50% of their time performing non-clinical tasks which have also been associated with physician burnout, a psychological condition known to result in medical errors, lower quality of care, higher costs, and overall poorer patient outcomes. The proposed innovation is a proprietary algorithm that leverages data to automate the completion of insurance form documentation. This new technology aims to resolve workflow bottlenecks and complement existing clinical workflows by delivering a simpler provider experience by streamlining the preparation of medical form documentation.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a machine learning-enabled electronic medical record access toolset designed to automate and streamline the preparation of insurance form documentation. A major issue in the US healthcare system is the process through which healthcare providers seek reimbursement through health insurance companies. Filing claims and seeking prior authorizations on procedures or tests from insurance companies is a manual process that is slow and error prone, often resulting in delays in treatment or even rejection, jeopardizing patient health, and resulting in higher costs. Designed for physicians, the proposed technology will facilitate claim building using pre-trained natural language models to extract medical text and relationships from various inputs including patient and provider demographic information as well as payer information, clinical taxonomy, functional features, and relations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PARTHIAN BATTERY SOLUTIONS, LLC
STTR Phase I: Novel State of Health Measurements Through Advanced Lithium-ion Battery Modeling for Secure and Scalable 2nd-Life Battery Deployment
Contact
281 DON KNOTTS BLVD
Morgantown, WV 26501--6737
NSF Award
2304417 – STTR Phase I
Award amount to date
$274,951
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the accelerated adoption of electrification and other next-generation technologies, like renewable energy. This project proposes a technology to effectively manage end-of-life lithium-ion batteries through reuse. Enabling these batteries to be safely incorporated into a circular/reuse economy is essential for society to meet the goals of sustainability and net-zero carbon emissions. Extracting further value from post-consumer batteries through reuse provides an economic incentive for original equipment manufacturers to responsibly decommission up to 100% of their retired battery units, thereby foregoing the need to dispose of the battery and manufacture a new one in its place. The proposed technology?s ability to create a practical and safe battery reuse market will not only create a net-negative carbon footprint for the batteries but will also alleviate the stresses currently faced within the lithium (Li)-ion supply chain and bring forward Li-ion technology at more affordable prices. Additionally, the detailed state of health analysis performed by the technology will allow for more informed decision-making in regard to second-life battery allocation, enabling energy storage project managers to lower upfront investment on energy storage, without sacrificing on safety and performance.
This STTR Phase I project proposes to develop a novel approach to attain rapid and accurate state of health determinations for second-life lithium-ion batteries. The bespoke technology will utilize novel battery modeling and data analytics to establish an understanding of battery health beyond capacity degradation. The technology?s ability to capture the ensemble effect of numerous battery degradation mechanisms is a significant and needed advance over the incumbent state of the art in battery health analysis. As increased rates of degradation in specific cell parameters would lead to unique performance and operating limitations within the battery, it is imperative to take these parameters into consideration with a state of health assessment, or there is a risk of fatal operating event occurrences such as thermal runaway. This project?s objectives include the development of the rigorous electrochemical model to model the highly complex capacity fading mechanisms within Li-ion batteries, and the development of an algorithm-based state of health estimator that will utilize real-time data and project remaining useful life estimates for second use applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PERSEUS MATERIALS, INC.
SBIR Phase I: Fast and low-energy manufacturing of high-performance, fiber-reinforced composites
Contact
550 OAK ST
Mountain View, CA 94041-
NSF Award
2304621 – SBIR Phase I
Award amount to date
$265,072
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will establish the thermal and mechanical limits of novel, fiber-reinforced, plastic composite materials (FRPs) and pioneer a fast-manufacturing process for these FRPs. FRPs have the potential to achieve significant lightweighting and subsequent greenhouse gas emissions reductions by displacing steel and aluminum in many industries including aerospace, automotive, construction, infrastructure, marine, and wind energy. However, difficulties in their processing and slow production have made FRPs too expensive for widespread adoption. If successful, the proposed project will enable FRP adoption in more price-sensitive industries such as automotive and infrastructure for widespread greenhouse gas emissions reductions. A shorter-term market that can be addressed with this technology is the FRP mold market. FRP molds are used to make FRPs but are also themselves made of FRPs. Cheaper FRP molds with shorter lead times are a major need for manufacturers. The domestic market for mold making was estimated to be $21.6 billion in 2020. As the FRP market continues to grow, the mold making market is expected to grow in kind.
The intellectual merit of this project includes new, fiber-reinforced, plastic composite materials (FRPs), associated manufacturing processes, and methods of optimization thereof. The core innovation is resin chemistry with a unique form of low energy, rapid curing. This project will be the first critical step in developing new manufacturing processes that exploit this curing phenomenon for faster, cheaper FRP fabrication. This Phase I research is split into three stages. In stage 1, the effect of different resin components on the final thermal and mechanical properties of the FRP parts will be evaluated. In stage 2, a prototype system will be developed for fast fabrication of large test specimens. Common failure modes will be understood, and optimal processing conditions will be determined. In stage 3, different form factors of fiber fillers will be used. This project will establish the fundamentals and common failure modes of a novel, more efficient FRP manufacturing process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PHOTONECT INTERCONNECT SOLUTIONS INC
SBIR Phase I: Development of a Chip Technology for Cheaper and Easier Photonic Device Manufacturing
Contact
280 RHINECLIFF DR
Rochester, NY 14618--1622
NSF Award
2304400 – SBIR Phase I
Award amount to date
$274,996
Start / end date
06/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the advancement of manufacturing technologies for industries such as telecommunications, data communications, sensors. and defense. Most of the internet relies on data centers to process data, and this processing is accomplished via a device called an optical transceiver. These transceivers house an optical fiber, which is as thin as a single strand of human hair, attached to a chip device to transfer information to/from the data centers. The optical fiber is so small that it is very difficult to precisely connect the fiber to the chip, often resulting in performance losses. With >100,000 transceivers per data center and >2,700 data centers in the United States, it is important to have good fiber connection for reduced power consumption and increased performance. Technology companies are also looking for chips with multiple fibers, making the need for better fiber placement even greater. In this project, the company focuses a new technology that makes fiber placement on a chip faster, more accurate, and cheaper. This new technology uses a special component that enables fiber placement with precision while improving the device performance 4 times.
This Small Business Innovation Research (SBIR) Phase I project addresses major pain points for optical transceiver companies: cost and time to package an optical fiber to a silicon photonic chip. The proposed product consists of a fusion splicing machine and a novel silicon dioxide mode converter. The mode converter localizes heat from the laser, enabling fusion while simultaneously decreasing the loss level. This technology packages silicon photonic devices without compromising performance. It significantly improves packaging speed from 10 minutes to 2 minutes, increases power efficiency by 4X, and provides a 50% savings. The company has demonstrated coupling losses lower than the industry standard of 3 dB on specialty chips. The research objectives involve improving coupling losses to around 1 dB, demonstrating splicing with foundry chips, and improving the strength of the fusion splice for improved reliability. The completion of these objectives will result in extremely low loss photonic packaging applicable for use with foundry chips, increasing the commercialization potential of the technology. This technology will enable customers to package single or multi-fiber devices with high efficiency, low cost, and at high volumes, ultimately increasing production capacity across many industries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PIKE ROBOTICS INC.
SBIR Phase I: Autonomous Inspection Robot for Seal Inspection of Floating Roof Storage Tanks
Contact
2204 TOM MILLER ST
Austin, TX 78723--5381
NSF Award
2233637 – SBIR Phase I
Award amount to date
$274,703
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
he broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to develop an autonomous, robotic inspection system to eliminate manual inspection methods in confined and dangerous spaces. The innovation will use a robot to provide quantitative condition and emissions data for an estimated 150,000 floating roof tanks in the nation?s aging infrastructure. The Environmental Protection Agency (EPA) and similar agencies across the globe, require tanks to be routinely inspected, but companies also want to remove personnel from confined spaces and avoid exposure to poisonous gasses, asphyxiation, heat exhaustion, falling accidents, etc. Confined space entries caused 1,300 U.S. deaths between 2011 and 2018. The autonomous robot reduces expenses related to maintenance and repair and allows better quantitative assessment of the seal integrity, which allows companies to perform maintenance based on the asset condition and not frequency-based schedules. An industry trend in recent years is to recreate the state of their assets digitally - both visually and quantitatively. The high-resolution data provided through this effort supports these 'digital twins.' Also, once the robot is certified for explosive environments, design features can be reused to produce other robots which further improve development cost and safety.
This SBIR Phase I project will create an autonomous robotic inspection system which eliminates manual, confined-space inspection methods and requires only one technician to deploy the robot from the top of the tank wall. The wall-climbing robot is capable of inspecting both the floating-roof storage tank?s upper (weather) and lower (primary) seals using a bifurcated (inverse periscope) geometry which places sensors in the gap between the seals while prime movers, adhesion elements, and a controller are above the seals. The bifurcated design simplifies safety feature design by minimizing the size and complexity of device components between the seals. The bifurcated design enables the continuous use of a tether for isolating the power source and provides a positive pressure surge system. After insertion, the robot proceeds to circumnavigate the inner tank shell in a stable manner, overcoming the large frictional forces that exist between the tank wall and the upper seal. The robotic system gathers real-time, high-resolution, and continuous data about the state of the seals. High-resolution visual data characterizes the top of the seal, and a proprietary physical ?feeler? mechanism characterizes the seal gap. This information results in a fast, safe, and accurate inspection of the tank?s seal.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PLANCK ENERGIES INC.
SBIR Phase I: CAS: Climate-Eco-friendly Biocoating for Passive Cooling of Infrastructure
Contact
150 HUNTINGTON AVENUE
Boston, MA 02115--6806
NSF Award
2321446 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project seeks to reduce global warming using an innovative passive cooling technique. The project will develop an environmentally friendly, passive cooling coating that can help reduce the temperature of buildings. The coating is expected to provide energy reductions ranging from 5-25%, depending on climate and building characteristics. The solution may reduce the need for traditional compressor-based cooling systems (e.g., air conditioners), which require a constant supply of electricity and coolants, stressing the environment through the greenhouse effect. The company expects to generate commercial revenues from both the paint-like coating featuring biocompatible passive cooling fibers and raw hydroxyapatite (HAP) fibers. Main customer target groups for the paint matrix include commercial and residential building owners that are looking for ways to lower their electric bills while lessening their negative environmental footprint.
The proposed innovation is founded on self-cleaning, fire-resistant, cooling fibers formulated with HAP. HAP cooling fibers will be integrated within a paint matrix for ease of application and cost-effectiveness. The aim is to develop and commercialize this environmentally friendly, passive cooling material as a coating with multiple functionalities. The team will identify environmentally friendly, paint-based materials within cost constraints, determine paint-fiber compatibility, and validate the cooling performance of candidate composites. The durability of the paint materials will also be confirmed. The project will focus on the design of a small-scale manufacturing line capable of producing fiber-based cooling paint at pilot scale for repeatability and field validation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
POINTPRO, INC.
SBIR Phase I: A Fully Autonomous Prognostic Digital Twin for Smart Manufacturing
Contact
47 W 4TH AVE
Columbus, OH 43201--3212
NSF Award
2317579 – SBIR Phase I
Award amount to date
$274,564
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project seeks to assist industries reduce their downtime for scheduled, preventative maintenance. Industries with high-value assets like manufacturing facilities, engines, satellites, reactors, etc., often incur significant expense due to a lack of usable insights into productivity optimization. The forecasting technology and the developments stemming from this project will have general applicability and enable the use of prescriptive prognostics (when and what to repair) in diverse markets. Additionally, the methods developed in the project for training deep learning systems on limited data would have broad application within the machine learning (ML) community. Frequently, projects are limited by access to and availability of data. The methods developed in this project could be applied to small sets of medical data or financial data, as they are entirely defined on time series variables and dynamics.
This SBIR Phase I project has two main goals. First, to develop a technology that will enable full autonomy in the extraction of meaningful feature sets from raw sensor data. An autonomous feature selection procedure developed in this project will exploit the combination of powerful control-theoretic results with modern ML tools to discover non-obvious linear and nonlinear features. This solution will provide a physics-informed architecture, allowing users to incorporate available physics knowledge with that emerging from the data, configuring a robust, flexible, and autonomous feature extraction mechanism. Second, the team will construct a robust, multi-modal, sensor emulator to address data insufficiency in order to train the ML components. This opportunity is in response to the limited availability of data in manufacturing sector, especially time-series sensor data in operational systems. The sensor emulator will be formed via combinations of modern ML-based generative tools in a manner that exploits their proven effectiveness while being able to work with high-dimensional signals and small training datasets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
POLYMER SOLUTIONS INC
SBIR Phase I: Versatile Polymers for Making New Components in Space and Eliminating Solid Waste
Contact
1820 THE EXCHANGE SE
Atlanta, GA 30339--2088
NSF Award
2231988 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to address the need for recycling plastics that have surpassed their useful life. The ?plastic?s revolution? of the mid-twentieth century has greatly added value to society but has also created highly durable plastics that are used to make objects of limited life-expectancy. There are limited cost-effective alternatives to many of these polymers. Every day, 8 million pieces of plastic are thrown into the ocean amounting to 10 million tons per year. Although there are approaches to decompose or depolymerize the polymers used in common plastic parts, these methods are not generally efficient across the dimensions of cost, energy use, time for degradation, or scalability. An extreme example of the need for energy and time efficient depolymerization of polymers is in space missions. There is a very high cost of disposing solids in earth?s orbit and removing space-junk which must be monitored and avoided by orbiting satellites. Even more challenging is the need for reusable materials during extended space missions due to the lack of raw materials.
This SBIR Phase I project proposes to develop a polymer-based plastics technology that allows for rapid, low-energy, triggerable disposal of plastics when a space mission has been completed. This project also proposes to carry out the disposal of plastics so that the products can extend their value and be recycled to make the same or different objects in space. Closing the polymer-carbon cycle has potential to extend space missions, lower the amount of supply materials needed, and reduce the amount of orbiting space junk. This project is developing a unique family of polymers which can be easily depolymerized back to the starting monomers via a photo or thermal trigger. The polymers are composed of cyclic, low ceiling temperature polymers. The low ceiling temperature means that once a single chemical bond in the polymer is broken, two ends are formed which instantaneously lead to depolymerization of the entire polymer molecule back to its original monomers. The depolymerized monomers can be evaporated to make the plastic parts ?disappear? or can be captured and used to repolymerize a new plastic component. This project will develop specific depolymerization triggers and a continuous-flow polymerization reactor for synthesizing plastic parts in space (and elsewhere for on-earth applications).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
POLYPV, LLC
STTR Phase I: Solution processed flexible semitransparent organic photovoltaic (OPV) modules for greenhouses
Contact
201 PROMONTORY POINT DR
Cary, NC 27513--6000
NSF Award
2213220 – STTR Phase I
Award amount to date
$256,000
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to develop a disruptive technology that reduces the environmental impact of greenhouse-based agriculture while simultaneously improving its economic potential through the application of semitransparent organic solar cells onto the greenhouse glazing (i.e., windows). Greenhouses can be a form of high productivity farming that conserves land and water making them an attractive form of sustainable and climate resilient agriculture. However, greenhouses consume significantly more energy than conventional farming. For greenhouses to be a part of a sustainable agriculture future, there is a need to reduce their energy demand. Prior research has demonstrated that organic solar modules integrated into greenhouse structures may reduce or even eliminate external energy demand while not negatively impacting crop production. The global commercial market of conventional greenhouses will reach $50.6 billion by 2025. The growing greenhouse market translates to gigawatt solar power market size. The added economic benefit of organic solar module adoption in greenhouses provides a path for widespread adoption of organic solar modules and the growing greenhouse market.
This STTR Phase I project proposes to develop flexible, semitransparent, organic solar cells that are tailored specifically for greenhouse glazing integration. The organic solar cells will contribute to the energy production of such greenhouses and may completely eliminate greenhouse energy needs, providing a more environmentally sound form of agriculture. To make this vision of low energy demand greenhouses, there is a need to make high-performance flexible organic solar cells. This solution will be achieved through the optimization of the active layer, the electrodes, and the encapsulation processes. The three primary research tasks are to: (1) produce photoactive inks that are compatible with large-scale coating and have tuned transmittance; (2) achieve high transparency and physically robust, transparent, conducting electrodes based on silver nanowires produced using scalable coating methods; and (3) develop large area, low-cost, transparent, and flexible encapsulation layers. If successful, these solar cells will have advantageous operating characteristics not achievable with other solar cell technologies, providing a unique commercial opportunity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
POWDER WATTS, LLC
SBIR Phase I: Low-Cost, Vision-Enhanced, High-Efficiency Heat Cable Control System
Contact
2750 RASMUSSEN RD
Park City, UT 84098--5492
NSF Award
2224907 – SBIR Phase I
Award amount to date
$274,922
Start / end date
07/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be realized through the development of vision-enhanced, smart control for heat cables. Heat cables are installed on millions of roofs in North America to prevent build-up of roof-damaging ice dams but they currently have flawed, rudimentary controls, and consume large amounts of energy (tripling the energy consumption of a typical home during the winter months). Combining information from easy-to-install roof cameras, temperature sensors, and local weather forecasting, a machine learning system will turn on heat cables only when needed. A total of 8 billion installed feet of heat cable on roofs and gutters in North America annually consume 135 Terawatt-Hours of electricity and emit 52 Megatons of carbon dioxide and methane. Preliminary data indicate this consumption, the associated costs, and carbon dioxide and methane emissions can be reduced significantly, creating a large commercial impact for residential and commercial building owners, a payback period for the customer of one winter season, and a considerable decrease of the nation's carbon footprint. Because of heat cables' large electrical power consumption, the technology will also provide electrical utility companies with a tool to stabilize the electrical grid and load balance, contributing to national energy security and competitiveness.
This SBIR Phase I project proposes to pursue innovations to enhance the energy efficiency of heat cable systems. This system will including an energy harvesting system to power a roof-mounted, camera-based, sensor system that uses machine-vision and machine-learning to precisely control roof heat cables based on their primary function: the prevention of ice dams. Surprisingly, little is known about optimal heat cable control, including key input variables such as temperature, weather and the variability and role of roof features (type, angle, orientation). Collecting and analyzing these data will further the understanding of optimal heat cable control. Heat cable power consumption will be compared to historical and model-derived power consumption. Technoeconomic analysis will help to fine-tune and scale the revenue model. The energy harvesting technology based on trickle-charging the roof-based camera system battery will make the system cordless, easy to retrofit to existing installations, and low-maintenance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRAG LLC
SBIR Phase I: Bioreactors for Upcycling Pyrolyzed Polystyrene Waste into Organic Fertilizer
Contact
171 FRANKLIN RD
Lake Mary, FL 32746--3609
NSF Award
2303842 – SBIR Phase I
Award amount to date
$274,718
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to enable the recycling of common polystyrene foam waste into soil amendments: creating a valuable agricultural product out of a pernicious and ubiquitous waste. Annually, millions of pounds of polystyrene waste fill landfills, blot roadsides, or pollute waterways ? making up 80% of all ocean plastic waste. Taking centuries to decompose, when finally broken down polystyrene may have terrible impacts on health. This project seeks to combine proven technologies with newly discovered abilities in microorganisms to digest polystyrene, to demonstrate a means by which polystyrene can be reconstituted into nutrient-rich material useful in agriculture. Because of the vast supply of polystyrene waste and the great commercial need to dispose of it, this project taps into a commercial potential not only to provide waste disposal services to a much underserved market but can do so while simultaneously producing a valuable agricultural good. This project supports the NSF?s mission by advancing the science of bioremediation, advancing the health and welfare of the nation by removing a harmful waste product from the environment, and supporting national prosperity by providing a much-needed service to a large industry.
This project seeks to use a unique combination of technologies to demonstrate that polystyrene foam waste can be processed and bioremediated rapidly into a soil amending ?castings? ready for use in gardening, farming, or landscaping. The project's research and development effort lies in the complex process of converting polystyrene from an unprocessed waste into both bioplastics and organic acids by way of thermal and biological methods, before further amelioration by decomposer organisms and the formation of a usable agricultural product. Bioreactors featuring numerous strains and species of microbes never-before deployed for this purpose will be used in tandem with macro-organisms whose capabilities for this application are likewise mostly or entirely unstudied. This research will uncover the specific abilities of numerous species to digest polystyrene waste at multiple scales and will evaluate several potential pathways through which the resulting digestate could be further processed. Large sample sizes, stepwise variances in conditions, and permutations of species? combinations will be used to ensure statistical veracity. These methods, coupled with the use of cutting-edge analytical equipment, will ensure a high precision in results.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRAIRIELEARN, INC.
SBIR Phase I: An online learning and assessment platform for sophisticated and secure exams
Contact
60 HAZELWOOD DR
Champaign, IL 61820--7460
NSF Award
2304241 – SBIR Phase I
Award amount to date
$274,981
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to provide a robust and sophisticated assessment tool to a wider range of STEM (Science, Technology, Engineering and Mathematics) educators to improve student learning, make teaching more efficient, and reduce the incidences of cheating. The core technology of this technology is an online platform for creating and delivering high-quality assessments that are auto-graded by artificial intelligence (AI) algorithms, providing immediate feedback to students. The technology provides students with the opportunity to practice questions in a personalized environment until mastery is achieved. The auto-grading features reduce grading effort, allowing instructors to focus on course design, incorporate more frequent and second-chance testing, and have more time to directly help students. The platform can automatically generate and grade personalized assessments for each student, which helps to minimize cheating and enables repeated practice by students. This learning experience is suited to help minorities, first-generation college students, and students of low socioeconomic status, who have traditionally had less access to the highest quality human instructors. Making STEM education more effective will facilitate the creation and continuing support of a highly educated STEM workforce and is important for national competitiveness in related fields.
This Phase I project aims to develop a no-code, graphical authoring environment that will allow instructors without prior programming experience to create AI-based auto-graded content. Instructors will be enabled to create sophisticated, auto-graded assessments by combining the existing core AI technology of this project with the following innovations: a) a no-code, graphical authoring using block-based language and data-flow visualizations; (2) new AI auto-graders for structured data, such as student data analyses within spreadsheets, by using verification algorithms to specify and check constraints on student answers; and (3) a graphical interface to use the new AI auto-graders for structured data, including associated data-flow visualizations. All three of these new capabilities will be evaluated via user-focused studies with a small group of instructors from a variety of backgrounds and programming skill levels, ranging from novice to expert. These semi-structured qualitative studies will follow a grounded theory approach, addressing metrics specific to each objective.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRENOSTIK, LLC
SBIR Phase I: A Student Learning Dashboard
Contact
21 MEADOW GLN
Irvine, CA 92602--1625
NSF Award
2232826 – SBIR Phase I
Award amount to date
$274,471
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in improving retention in higher education and increasing graduation rates. Currently, the average U.S. college dropout rate is 40%. Moreover, underserved Science, Technology, Engineering and Mathematics (STEM) student populations are more likely to leave school without a degree. Due to the COVID-19 pandemic, increased financial insecurity and mental health challenges have negatively impacted student learning. This project aims to develop a student learning dashboard platform that acts as a co-pilot during students' higher education learning journey by delivering targeted, personalized, and real-time actionable assistance. The solution holistically identifies each student's unique learning motivation challenges (e.g., subject difficulty, relevance to career goals, social and economic constraints, etc.) and provides specific recommendations to overcome barriers. Coaching students to learn how to learn more effectively based on their own context fosters a growth mindset, grit, and agency to help them become successful lifelong learners. The application also significantly improves diversity, equity, and inclusion in higher education, especially in STEM, and thus increases effective workforce training.
This Small Business Innovation Research (SBIR) Phase I project uses machine learning to understand each student's unique learning challenges, map how barriers affect learning motivation, and influences coursework engagement. Machine learning is applied to analyze qualitative and quantitative learning motivation and behavior data to identify gaps so real-time, targeted, and relevant guidance can be delivered while the students are still progressing through the courses rather than waiting until it might be too late for intervention. This project provides descriptive, predictive, and prescriptive recommendations to simulate one-on-one, personalized advising at scale and at a lower cost. The technology also acts as an early detection system when students show the first sign of academic and non-academic struggles affecting their mental state of readiness to learn. When in-person human intervention is required, instructors, academic advising, and/or relevant on-campus student support services can be alerted. This project can be used by any educational institution or private company providing in-person, flipped/hybrid, remote, synchronous, or asynchronous instruction formats.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PROJECT VESTA, PBC
SBIR Phase I: Enhanced Blue Carbon: a novel carbon dioxide removal strategy for climate change mitigation
Contact
1210 26TH ST
Denver, CO 80205--2100
NSF Award
2246965 – SBIR Phase I
Award amount to date
$273,994
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to combat climate change, enhance coastal resilience, and counter ocean acidification. This project will develop a nature-based approach that deploys Olivine sand safely into salty marshes for atmospheric carbon dioxide removal (CDR) while restoring marsh ecosystems. This project will contribute societal value by driving innovation and new approaches in Earth Sciences, Ocean Sciences, and Marine and Coastal Engineering. It will produce a rigorous, cost-effective method for carbon dioxide removal to generate carbon credits that can be bought on carbon exchanges to achieve net-zero emissions. Once at scale, the technology could permanently capture millions of tons of carbon/year at < $100 per ton. The impact on the lives of US citizens could be significant, both through green job creation and through climate crisis mitigation.
This project will develop Enhanced Blue Carbon (EBC), a novel, nature-based, carbon dioxide removal (CDR) technology that combines and improves two of the most cost effective, scalable, and permanent CDR technologies: Ocean Alkalinity Enhancement (OAE) and Blue Carbon (BC). The proposed research consists of a field trial that will produce a carbon quantification model, ecological impact report, and Life Cycle Analysis (LCA) determining the efficiency and safety of EBC. This experiment is the first of its kind and is a critical step in developing a third-party accredited measurement-reporting-verification (MRV) methodology that directly connects EBC to carbon markets. The efficiency and safety of EBC will be assessed through geochemical and biogeochemical characterization of porewater, sediments, and biomass collected during the field trial. This data will be integrated in a proprietary 1-dimensional reactive-transport model that can be used to estimate carbon removal potential in EBC projects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PROMEDIX, INC.
STTR Phase I: Electronic Measurement of Capillary Refill Time to Improve Outcomes from Sepsis
Contact
4640 S MACADAM AVE
Portland, OR 97239--4232
NSF Award
2212728 – STTR Phase I
Award amount to date
$255,750
Start / end date
02/15/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a novel external system for rapidly diagnosing sepsis by measuring capillary refill time (CRT). Independent clinical studies have demonstrated the utility of CRT for detecting sepsis. Current methods for monitoring capillary refill times rely on physical examinations that are both prone to human error and inconsistency. The company aims to develop an automated diagnostic and monitoring device for objectively and repeatably quantifying capillary refill time for use in a clinical setting. If successful, the technology may have widespread potential use in emergency departments, clinics, ambulances, or at home.
This Small Business Technology Transfer (STTR) Phase I project develops a new finger-sensor interface for monitoring CRT that ensures contact between the finger and sensor across a range of finger sizes and validate the system in human use. The objectives are to ensure human factors engineering to enable use in a broad range of patients by a wide range of caregivers. A novel algorithm to improve sensor performance and provide user feedback on noise or aberrant signals will also be integrated. The system will be tested in a group of patients at risk for sepsis to demonstrate the device reliably and accurately measures the CRT across a wide variety of patient demographics and the device is easily usable by a wide range of caregivers including physicians and family members without extensive training. A successful Phase I outcome is a system enabling the consistent ability to collect high-quality measures of CRT in patients at risk for sepsis and to provide the user with ongoing measures of signal quality.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PROVIZIGEN LLC
STTR Phase I: Injectable Biotherapeutic for Treatment of Post-Traumatic Osteoarthritis
Contact
111 FOURTH AVE APT 2M
New York, NY 10003--5245
NSF Award
2335299 – STTR Phase I
Award amount to date
$275,000
Start / end date
11/01/2023 – 10/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project develops an injectable therapeutic to treat post-traumatic osteoarthritis (PTOA). PTOA is a painful disease of the cartilage caused by external mechanical force. The current treatment for PTOA involves an invasive surgical procedure - total joint replacement - which is often associated with infections and may need a revision knee replacement. There is no disease-modifying osteoarthritis drug nor a non-surgical cure for these patients. While some drugs help mitigate pain, they have no effect on disease progression, and their use can be limited greatly by their potential severe side effects. This solution serves as the first and only treatment to slow the progression of PTOA, which would prevent PTOA patients from potentially suffering a lifetime of pain and expenses. As a result, customers will potentially save thousands of dollars, acquire peace of mind that they have taken the only action to help prevent the development of osteoarthritis, and most of all, prevent a cycle of increasing pain, medical issues, and associated treatments with their injury.
This Small Business Technology Transfer (STTR) Phase I project will lead to an optimized, deimmunized therapeutic that changes the disease progression of post-traumatic osteoarthritis (PTOA). The solution combines a unique thermoresponsive hydrogel carrier capable of sustained delivery of a therapeutic protein that enables disease modification when delivered via a single injection, avoiding the surgical procedure in total joint replacement. State-of-the-art computational tools will be employed to improve the properties of the hydrogel and experimentally test the constructs for function.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PUMPKINSEED TECHNOLOGIES INC
SBIR Phase I: Developing Vibrational spectroscopy with metasurface optics (VISMO) for label-free, high-resolution, high-throughput protein screening
Contact
380 PORTAGE AVE
Palo Alto, CA 94306--2244
NSF Award
2233672 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to facilitate improved biomanufacturing and the transition to a sustainable bioeconomy. Proteins are the working molecules of biology and can be used for products spanning sustainable fuels, pharmaceuticals, plastics, and packaging materials. Cell-based manufacturing can produce millions of variations of proteins, yet existing tools do not provide the resolution, throughput, or sensitivity to screen the cell sequence and structure. The resulting services and products will reduce the time and cost to optimize protein-based products, en-route to a sustainable bio-based economy and improved personal and planetary health. The approach will enable simultaneous, minute-scale measurement of millions of samples, increasing the suite of detectable molecules beyond any available technology. The technology will enable collection of dynamic information about protein-protein and protein-drug interactions will dramatically improve the lengthy and costly cycles associated with drug development and synthetic biology-based optimization of protein-based products and accelerate advances for the US bioeconomy. The technology may enable the transition to personalized medicine, where medical professionals can access patient-specific proteomic and drug-interaction data in real-time, to maintain wellness, monitor disease emergence and progression, improve treatment efficacy,
and extend health spans.
This project aims to develop vibrational spectroscopy with metasurface optics to screen for proteoforms. The research objectives are to determine protein sequence and structure, utilizing the vibrational scattering spectra of the protein. Aim 1 of this project will develop a nanostructured silicon chip that strongly amplifies the vibrationally-scattered light from proteins, for high-sensitivity analysis. Aim 2 of this project will develop cutting-edge machine learning algorithms to provide interpretability to the Raman spectra, including the wavenumber features that correspond to the primary, secondary, and tertiary structure of the protein. Aim 3 of this project will develop microfluidic capabilities that enable high-throughput sample processing, with up to 3 million molecules analyzed per square centimeter. Upon completion, this Phase I project will de-risk the technological foundations for label-free, high-resolution, high-speed protein screening and sequencing technologies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
QUANTUMMED INC
SBIR Phase I: Metal-implanted materials (MIMs) for fast, cost-effective and reproducible mixing
Contact
201 WEST 5TH STREET SUITE 1500
Austin, TX 78701--0061
NSF Award
2303540 – SBIR Phase I
Award amount to date
$268,521
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project includes improving the reproducibility of automated life science workflows while simultaneously reducing their carbon footprint. Automated life science workflows are increasingly prevalent in medical (e.g., laboratory tests and diagnostics) and research (e.g., next generation sequencing) applications, and mixing is a ubiquitous and often repeatedly performed operation in these assays. The novel mixing technology to be developed will confer myriad benefits. By reducing assay turnaround times and improving assay reliability, it will decrease wait times for medical screening, diagnosis and monitoring, enabling faster diagnoses and treatments. By decreasing the materials costs of the assays, this technology may reduce the costs of medical testing and improve access to care. It also can enhance partnerships between academic and industry laboratories by giving academic laboratories access to industry workflows that are currently prohibitively expensive. Finally, by eliminating a substantial portion of the single-use plastic consumed by assays, this novel mixing technology will help curb the waste generated by life science assays, which will help alleviate the single-use plastic waste crisis.
The proposed project will deliver an innovative mixing technology that is based on a photo-acoustic streaming phenomenon. Briefly, when glass implanted with metal nanoparticles (metal-implanted materials (MIMs)) is excited by a pulsed laser, it causes an adjacent fluid (liquid or gas) to begin streaming for the duration of the illumination. This streaming creates an opportunity to precisely control mixing, but key technical challenges include optimizing the MIMs? form factor and devising an effective, yet also inexpensive, illumination system. The proposed project?s objectives address these challenges by: (i) evaluating the effectiveness of mixing solutions with a novel MIM form factor that can be incorporated easily into existing automated life science workflows, (ii) determining if functional MIMs can be fabricated in bulk by procuring them from a supplier and characterizing them for nanoparticle implantation and laser-induced solution streaming, and (iii) testing an alternative laser light source that powers mixing and consists of a low-cost light emitting diode (LED) laser.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RADIANT SPACE SYSTEMS, INC.
SBIR Phase I: Artificial Gravity Stabilization System for Space Habitats
Contact
3737 CASA VERDE ST
San Jose, CA 95134--3364
NSF Award
2335173 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project enables an entirely new class of space habitat that will enable humans to live and work in space without endangering their health. In the near future, improvements in launch capability will radically increase the number of people traveling to space to take advantage of what can only be done in microgravity. These include researchers studying the next lifesaving medicine, workers manufacturing high-purity semiconductors for the next generation of computers, and tourists wanting to experience the freedom of space and the sight of Earth. These individuals share a common need: easy access to microgravity to fulfill their purpose of being in space while simultaneously not enduring significant health impacts from microgravity exposure; thus, both microgravity and artificial gravity need to be accessible in the same space habitat. Development of platforms such as these would help enable an acceleration of in-space R&D, along with supporting higher throughput of in-space experimentation and R&D. The solution is very large, expandable non-rotating space habitats, with an internal rotating centrifuge large enough for astronauts to live and work in when not needing microgravity. These centrifuges need an advanced stabilization system because as astronauts move around the centrifuge, the center-of-gravity shifts, which due to the rotation would induce a wobble.
This SBIR Phase I project proposes to solve the stabilization problem while avoiding flaws of previously proposed approaches and is also applicable to traditional rotating space stations. The objective of this research is to build representative lab-scale prototypes of the stabilization system and develop a control system model to prove the efficacy of this stabilization system when at full scale. This includes capturing the responsiveness required for the system to stabilize human motion, such as walking, proving redundancy is present, and characterizing the overall impact centrifuge mass distribution has on the stabilization control system. Further prototypes will demonstrate its ability to package within an expandable habitat module, while additional analysis will quantify the cost benefits of designing a habitat incorporating a large internal centrifuge and stabilization system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RADMANTIS LLC
SBIR Phase I: Adapting uncrewed aquaculture management to control sea lamprey and to protect wild salmonid fisheries of the Great Lakes
Contact
5470 LARCHWOOD LN
Toledo, OH 43614--1247
NSF Award
2212614 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project focuses on improved methods for detecting and suppressing sea lampreys in the Great Lakes, a pest species that currently requires relentless, sustained, and costly control efforts at ecosystem scale. The project initiates the development of small, relocatable, field-deployed devices, capable of performing a range of assessment and selective control functions. Success in this effort will introduce an important new tool to bolster environmental health outcomes at an ecosystem level, and benefit commercial fisheries estimated at $7B annually. By replacing chemical and manual control of exotic invaders, the project contributes to the preservation of ecosystem integrity and function, biodiversity, and environmental quality of the Great Lakes, a vital natural resource providing water security for more than 35 million people in the region. With worldwide damage from aquatic invaders exceeding $300 billion annually, innovations driving advances in ecosystem protection and restoration will have wide appeal and application wherever habitats require protection. Broadening the available tool set empowers managers and local communities to act against exotic invaders at the level where causes and consequences are most acutely felt.
This project performs a feasibility study of existing technologies from aquaculture workflows for adaptation to the uncrewed control of sea lampreys in the field. The essential features of such a device are inherently similar to recently emerged solutions for automated fish management in robotic aquaculture systems. Existing models for detection and classification are expected to transfer well to a class as morphologically distinct as lampreys. The primary challenges to this project most likely arise from the unique biology and sensory ecology of a species whose responses to the physical device used here are completely unknown. A set of artificial stream experiments aims to entrain lampreys into devices placed into their path. How might lamprey react to a device optimized for the specific needs of imaging, classification, and selective removal? Informed by detailed knowledge of lamprey chemosensory ecology, the work also examines the efficacy of pheromonal cues for channeling lamprey movement through the device.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RAPA TECHNOLOGIES LLC
SBIR Phase I: Comfortable, Easy-to-Insert Hearing Protection Earplug
Contact
64 BONNER RD
Meriden, NH 03770--5151
NSF Award
2233135 – SBIR Phase I
Award amount to date
$274,976
Start / end date
07/15/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel hearing protection device which reduces the societal cost of noise induced hearing loss. Noise induced hearing loss is the one of the most prevalent occupational injuries in both US industry and the military, affecting more than 10 million workers at a total preventable economic cost exceeding $100 billion. Most employers rely primarily on personal hearing protection devices to limit exposure on a sustained basis. However, issues limit their real-world performance and leave a majority of wearers with sub optimal protection. Up to 80% of workers wear hearing protection in an inconsistent manner which significantly reduces their effectiveness. This project aims to develop a novel passive hearing protection device which significantly increases hearing protection by incorporating a pass-through communications channel in a form factor that enables proper insertion, comfort, and convenience, and is suitable for long term use and compliance.
This Small Business Innovation Research (SBIR) Phase I project will develop an earplug that incorporates a novel geometric design and materials to provide unique, tailored physical and acoustic properties. The design significantly increases sound reduction while preserving frequency balance and speech intelligibility to accommodate pass-through communications, in a form factor that enables greater comfort and convenience than traditional devices. Theoretical modelling of sound attenuation will be translated into prototypes that demonstrate performance measures in laboratory test fixtures, followed by a patient validation study. The project aims to demonstrate that the company?s new ear plug provides superior sound protection of up to 40 dB suppression while enabling improved communication. Incorporation of attributes preferred by users enables greater adoption compared to existing designs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RAPID FORENSIC CELL TYPING, INC.
STTR Phase I: Advancing DNA Testing with a Novel Platform for Processing Touch Biological Evidence
Contact
800 E LEIGH ST STE 1234
Richmond, VA 23219--1539
NSF Award
2243209 – STTR Phase I
Award amount to date
$270,578
Start / end date
07/01/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project addresses two societal issues in the justice system: an individual's constitutional right to a speedy trial, and inherent human biases in law enforcement when gathering and processing evidence. Backlogs in processing DNA evidence can lead to extended jail time for defendants unable to post bail and may violate their rights, particularly for crimes they did not commit. Rapid analysis of evidence samples can free up court dockets and save money for institutions holding people awaiting trials due to testing backlogs. In addition, the number of people exonerated by the re-analysis of forensic evidence after serving years in prison rises every year, underscoring the potential impact that testing decisions can have for individuals, families, and society at large. This technology reduces the number of samples tested and the potential for sample selection bias by rapidly identifying which samples may be probative to the investigation and thus warrant DNA testing.
The proposed project will develop a new technology that utilizes flow cytometry to analyze non-genetic attributes of cell populations within forensic evidence. This technology will allow forensic laboratories to rapidly determine the probative value of samples before DNA profiling. Machine learning algorithms will compare morphological measurements and autofluorescence properties of individual cells recovered from ?touch? epidermal cells to identify features that vary with attributes of the person who deposited the cells (e.g., chronological age, biological sex, and/or ancestry). This technology will enable forensic laboratories to rapidly identify which samples have biological material that is probative to the case and which samples have biological material that is unrelated. This will allow labs to prioritize samples for DNA testing more precisely and potentially provide key contextual information for the sample. By allocating resources more efficiently, this innovation will reduce costs, speed up results and reporting, and reduce delays in DNA testing turn-around times. The solution will also prevent undue delays in the legal system, improve the accuracy of case analysis, and ultimately improve the quality and reliability of forensic analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RATTAN LIFE SCIENCE INC.
SBIR Phase I: Engineered Induced Thymic Epithelial Cells for Novel T Cell Immunotherapies
Contact
893 RATTAN TER
Sunnyvale, CA 94086--8642
NSF Award
2234041 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop novel off-the-shelf T cell immunotherapies. Adoptive Cell Therapy (ACT) has revolutionized medicine for cancer patients, as evidenced by the remarkable success of CAR-T therapies in treating advanced and refractory leukemia and lymphoma. Despite the success in blood malignancies, solid tumors, representing approximately 90% of cancers, remain difficult to cure. To eradicate large tumor masses and reach complete remission, successful ACT requires persistent, in vivo anti-tumor effects. Studies have highlighted the correlation between greater ACT efficacy and transferring T cells with capacity of in vivo expansion and memory formation. Among major T cell subsets, naïve T cells have been identified as the optimal cell source for ACT compared to further differentiated cell types. In vivo, naïve T-derived effector cells demonstrate robust proliferation, potent tumor-killing and resistance to terminal differentiation and exhaustion. In vitro, these cells have significantly higher efficiency for blood malignancies and solid tumors. This project may enable large-scale and renewable production of homogenous T cells with optimal and persistent tumor-killing properties. This approach aims to address the unmet challenges of T cell exhaustion, improve scalability, reduce repeated blood collection, and offer broad patient access.
The proposed project aims to develop a platform technology for generation of iPSC-derived nai?ve CD4+ and CD8+ T cells with fidelity, reproducibility and scalability. The platform employs a proprietary method to generate iPSC-derived thymic epithelial cells as a critical element to enable naïve T cell production. The rationale resides in the natural biology of the Thymus, where the transition of immature CD4+CD8+ double positive T cells to nai?ve CD4+ or CD8+ T cells requires interaction with thymic epithelial cells through a process called positive selection. Concerns have been raised regarding the therapeutic efficacy associated with current Notch-activation based iPSC-derived T cell methods because T cells developed through sole Notch activation are phenotypically and functionally different from nai?ve T cells. Major technical limitations in Notch activation-based extrathymic differentiation methods are addressed by providing biologically relevant thymic positive selection signals. The resulting product enables a significant advance in the development of iPSC-based T cell immunotherapies with clinically relevant cell fidelity. Reproducibility and scalability of the proposed platform will be assessed and optimized in a bioreactor to demonstrate viability for commercialization.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RAVEN SPACE SYSTEMS, INC.
SBIR Phase I: 3D Printing Reentry Capsules
Contact
1913 W. 45TH AVE.
Kansas City, KS 66103--3513
NSF Award
2330355 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this I Small Business Innovation Research (SBIR) Phase I project is to accelerate humanity?s utilization and exploration of space. The International Space Station spends $1 billion annually on cargo transport but has limited opportunities for payload return each year. This bottleneck is caused by outdated reentry vehicle production that hinders microgravity research and in-space manufacturing developments. The problem is becoming more pressing as commercial space stations are expected to increase space cargo return demand significantly in the next decade. By using 3-dimensional (3D) printing, manufacturing and refurbishment of entire reentry capsules (both the structure and heat shield) is 10 times faster and an estimated 95% lower in cost compared to traditional manufacturing. This innovative 3D printing solution will increase the cadence and lower the cost of space station cargo resupply and return, promoting the development of a robust low Earth orbit economy. Frequent returns of high-value payloads from space will have substantial impacts on several industries including pharmaceuticals, semiconductors, fiber optics, etc. The technology will also provide rapid low-cost development of vehicles for various atmospheric entry or hypersonic applications including space resource return, deep space probes, rapid global delivery, hypersonic flight testing, and more.
This SBIR Phase I project will develop 3D printing of high-strength heat shield materials. The research will test 3D printed specimens to demonstrate the feasibility of the first ever, entirely 3D printed capsules capable of surviving reentry from space. The core innovation is a platform technology that will be capable of rapid, large-scale, direct ink write 3D printing of aerospace-grade thermoset composite paste materials for the first time. To achieve this, the commercially available and widely proven thermoset resins will be cured directly at the point of deposition in seconds using a novel rapid heating method. These materials typically require hours in an oven to cure, so the project is expected to demonstrate curing the highest-performing aerospace-grade materials faster than they have ever been cured before. This in-situ curing direct ink write 3D printing innovation will be a breakthrough in aerospace composite manufacturing. The composite formulations used in the project will be made of the same raw materials as used on flight-proven reentry capsule heat shields, but tailorable to be as strong as aluminum at half the weight. The composites will perform as both the structure and heat shield on reentry capsules.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RED SHIFT ENERGY, INC.
SBIR Phase I: Carbon-Free Hydrogen Production by Plasma Dissociation of Hydrogen Sulfide
Contact
5921 KING TRL
Corpus Christi, TX 78414--6312
NSF Award
2233170 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is connected to creating a large-scale source of low production cost, carbon-free hydrogen. This hydrogen will be produced from hydrogen sulfide (H2S). Nearly 8 million tons of H2S are processed by the energy industry each year. Sulfur recovery units (SRUs) are used to safely manage H2S. SRUs utilize an old Claus process and are unprofitable because of high capital and operational costs, in addition to low revenues due to sulfur overproduction. In contrast to the Claus process, H2S plasma dissociation recovers sulfur and hydrogen, whereby the sulfur can be used for oil desulfurization or as a commercial product. Dissociating H2S in plasma and producing hydrogen will make SRUs profitable and will reduce the industry's carbon dioxide emissions. This technology will diminish societal needs for fossil fuel production and increase energy security during the transition to renewable energy. The team will develop a numerical model for the high-speed, two-phase, vortex flows that will have a general academic interest and can be applied in the chemical and energy industries.
This SBIR Phase I project proposes to develop a plasma technology for the dissociation of H2S to sulfur and hydrogen, replacing Claus plants in Sulfur Recovery Units. Phase I will focus on three innovations that are critical for the H2S dissociation development program. The major goal is the high energy efficiency expressed as Specific Energy Requirement 1.5 kWh/m3. This goal will be achieved by a special design of the arc plasmatron with an extremely high speed of gas rotation that will result in hydrogen-sulfur separation in the reaction zone, the chemical equilibrium shift, and the internal recuperation of the sulfur clusterization and condensation energy. The second innovation will be the development of a gas-dynamic and chemical-kinetic model for the numerical simulation of two-phase (gas and sulfur particles) vortex flows with a high speed of rotation. Third, the stability of the cathode and plasmatron operation will be tested with different gas mixtures that imitate the composition of real flows at refineries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
REEGEN INC
SBIR Phase I: A clean, biological solution to sustainable energy?s rare earth problem
Contact
343 CAMPUS RD
Ithaca, NY 14853--6007
NSF Award
2304412 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to reduce the negative environmental impacts of rare earth element (REE) production through the development of a clean, sustainable system for REE extraction and purification using biology. Such a system would allow for affordable, low-impact REE production in the United States which, in turn, would reduce dependence on REE imports, alleviating a significant supply risk and concerns for national security. REEs are critical for manufacturing many modern electronics and sustainable energy technologies, including electric motors and wind turbine generators, solid state lighting, battery anodes, high-temperature superconductors, and high-strength lightweight alloys. Such applications are increasing demands on the global REE supply, which is predominantly controlled outside of the United States due to the cost of environmental regulations and labor. Nearly all REE production today comes from mining ore, which can cause its own environmental detriment, and will not be able to meet the rising demand for REEs. To bridge the gap between supply and demand, and attenuate the impacts of mining, REEs will be recovered from various waste and end-of-life sources, promoting a circular economy. The recovery of REEs from secondary sources would create new jobs, especially with the development of new infrastructure for the collection and pre-processing of REE-containing materials.
The output of this SBIR Phase I project is an end-to-end biological system for REE recovery that can replace the most environmentally damaging steps from source to market, including bio-extraction, selection, and separation of REEs. The use of microorganisms for each step allows for a much cleaner process, and genomic optimization for rapid customization to a variety of REE feedstocks. REE bio-extraction is done with biodegradable lixiviant produced by optimized microbial strains. Bio-selection is done with REE-specific ligands immobilized in a synthetic biological matrix. Finally, bio-separations are done through the selective sorption and desorption of different REEs to engineered bacterial membranes in columns that bind specific REEs with different affinities. Genetic customization is enabled through comprehensive identification of the genetic elements underlying a trait of interest, followed by incorporation of genetic engineering for optimization of the overall commercial process. In Phase I of the project, efforts are focused on the identification of the variables that most contribute to efficiency, as well as the genetic mechanisms driving those variables.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
REMEDIUM BIO, INC
SBIR Phase I: Development of an Adjustable Gene Therapy Platform Technology
Contact
1116 GREAT PLAIN AVE
Needham, MA 02492--2344
NSF Award
2240683 – SBIR Phase I
Award amount to date
$274,966
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impacts of this Small Business Innovation Research (SBIR) Phase I project include the development of a gene therapy platform that will allow the use of genetic therapeutics in areas beyond rare diseases, tackling large unmet clinical needs such as diabetes, osteoarthritis, and autoimmune diseases. The project will also enable significant reductions in the costs of gene therapies and protein-based therapeutics. Finally, the development of the proposed platform technology will enable the production of medical treatments that are injected less frequently, produce a potentially more optimal treatment profile, and prevent complications related to missed doses or therapeutic overdose. The societal and commercial impacts of this technology are significant, as the proposed technology could greatly expand the potential of gene therapy, while replacing other biologic-based therapies with a lower cost alternative. The technology has significant commercial value but is, at the same time, able to greatly reduce societal medical costs associated with current treatment approaches.
This project develops a dose-adjustable gene therapy mechanism that can be used to up- or down-regulate a gene therapy dose, following initial administration. Despite recent advances and regulatory approvals, gene therapy remains limited due to its inherent shortcomings in dose adjustment ? once a gene therapy dose is administered, it cannot be increased or decreased by secondary intervention. On the other hand, many therapeutics require adjustment of the initially prescribed dose over a period of weeks or months to optimize the efficacy and side-effects profile. This project aims to develop and characterize the first, fully adjustable gene therapy, capable of predictable post-treatment dose adjustment. To accomplish this, a number of technological hurdles will be addressed as part of the project including non-viral delivery of genetic material to human cells, the ability to control the gene expression in a predictable and measurable manner, and the assurance that any adjustability is safe to the patient organs, tissues, and cells that neighbor the treatment area.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RESET WATER LLC
STTR Phase I: Electrochemical Water Treatment Devices to Combat Harmful Algal Blooms
Contact
65 MAIN STREET
Potsdam, NY 13676--4039
NSF Award
2321315 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is in the development of a harmful algal bloom (HAB) mitigation technology. HABs are cyanobacterial plumes that are often acutely toxic to aquatic organisms, animals, and humans because of the cyanotoxins released by them. HABs have become an emerging threat to the recreational use of lakes and drinking water supplies. It is challenging for conventional centralized water treatment processes to mitigate HAB events and cyanotoxins that occur frequently and irregularly due to increased nutrient discharge and global climate change. The direct economic impact of HABs in the U.S. is estimated to be $50 million per year. The proposed HAB mitigation technology aims to intercept of eliminate such blooms at the early stage. The technology is based on electrochemical oxidation and features faster removal of both cyanobacteria and cyanotoxins. The solution should also result in fewer disinfection byproducts compared with conventional chlorination and ozonation methods. The technology uses cheaper, locally sourced electrode materials thereby reducing capital costs and potential supply chain challenges. These improvements could make the technology accessible to larger customer base and as such, improve water quality for larger populations. In addition, energy consumption may be reduced significantly allowing for more effective treatment. The reduction in HABs would ensure the continued use of water resources for recreation, reducing health risks and increasing property values of lakeside residences.
The project is focused on the development of an innovative electrochemical technology to remove HABs safely and effectively from bodies of water. Removal of harmful algal blooms is accomplished through an electro-oxidation (EO) process that does not require the addition of any chemicals, is quick, and easy to use. Phase I research and development will include the development of new electrode materials aimed at reducing the electrode costs by up to 50% by substituting the base metal and the dopant in the coated electrode material. The team will also evaluate the environmental impact of the treatment process on non-algae model organisms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RESILIENT LIFESCIENCE, INC
SBIR Phase I: Development of wearable medical device to detect and treat opioid overdose.
Contact
100 S COMMONS
Pittsburgh, PA 15212--5359
NSF Award
2335577 – SBIR Phase I
Award amount to date
$274,964
Start / end date
03/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel wearable medical device providing on-demand field delivery of naloxone for intervening in instances of opioid overdose or similar medical emergencies. CDC data indicates opioid overdose was the leading cause of death for Americans under 45, responsible for claiming over 80,000 American lives in 2022. Naloxone delivery represents the current standard method for acutely stabilizing the effects of opioid overdose, but approximately 69% of opioid overdose deaths occur without a bystander present to administer the intervention. This project proposes a wearable device that integrates an external non-invasive sensor coupled with a drug delivery system capable of delivering a subcutaneous injection of naloxone upon opioid overdose. This poses the potential to save 50,000 American lives due to opioid overdose each year.
This Small Business Innovation Research (SBIR) Phase I project is to develop and validate two components for a novel external system to detect and intervene during instances of opioid overdose, using sensor-derived measures of oxygen saturation and respiratory rates. A novel self-contained wearable mechanical, low-power drug delivery mechanism and a novel naloxone formulation will be developed and validated for stability under simulated use conditions. The first component, a self-contained patch-based drug delivery platform, will be designed and validated for reliable mechanical delivery, enabling multiple consecutive doses of custom naloxone within the physical and power constraints of the wearable system. The naloxone formulation will be validated for stability during accelerated age testing at elevated temperatures indicative of daily wear conditions. The components will be integrated into a prototype system with the company?s algorithm integrating heart rate, respiration, and oxygenation to complete a prototype system suitable for future human use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RESILITIX INTELLIGENCE LLC
SBIR Phase I: CAS: DIGITAL TWIN FOR CLIMATE RESILIENCE ANALYTICS
Contact
15730 WHITEWATER LN
Houston, TX 77079--2545
NSF Award
2335269 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project augments community resilience to climate hazards by improving the situational awareness of public organizations, officials, and emergency managers. The project is focused on harnessing the data revolution in dealing with climate hazards. The team develops a digital twin technology for disaster preparedness, response, and recovery. Climate hazards (hurricanes and floods, in particular) are the most prominent stressors for communities in the United States and worldwide, causing dire physical, social, and economic hardships. The outcomes of this research have the potential for significant societal benefits that could enhance the public safety of millions of U.S. residents exposed to climate hazards and potentially lead to millions of dollars in avoided disaster management costs through proactive preparedness. The project could transform the ability of decision-makers, emergency managers, and responders to tailor their strategies and technologies to enhance situational awareness in dealing with climate hazards.
This Small Business Innovation Research (SBIR) Phase I project delves into the intricate challenges of creating and designing a state-of-the-art digital twin technology that harnesses the power of community-scale big data and machine intelligence, offering a proactive and predictive lens on community preparedness, evacuation measures, protective actions, and post-emergency event recovery. The research activities include: (1) creating and testing computational methods, algorithms and metrics for specifying the extent of a populations' preparedness, evacuation planning, and recovery at the block group scale in near-time; (2) prototyping and optimizing the architecture of a web-based digital twin platform with effective data fusion and computation workflows in order to implement the created methods and algorithms and visualize the output insights in an intuitive, timely, and decision-friendly manner; (3) evaluating the performance of the aforementioned computational methods embedded in the digital twin technology prototype in the context of recent climate hazard events; and (4) demonstrating the use case of the digital twin prototype for emergency response and management applications through existing and growing partnerships.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
REVISION AUTONOMY INC
SBIR Phase I: Scientific Discovery Translation of Snow-Covered Road Perception Software to a Lane Detection in Snow (LDIS) Product
Contact
4717 CAMPUS DR STE 100
Kalamazoo, MI 49008--5602
NSF Award
2304352 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is improved automotive transportation safety, usability, and equity for the general public which reduces the annual 5,300 fatalities, 418,000 injuries, and billion-dollar losses from inclement weather crashes in the United States. The technology identifies the driving lane using camera data processing in challenging driving conditions such as congested intersections and bridges, dark tunnels, and during sun glare and active snowfall. Addressing these problems also enables U.S. technology competitiveness in the global automotive market, development of technologies relevant to national defense and energy efficiency applications, expansions of existing university courses, and entrepreneurial engagement from underrepresented communities. The foundation for the proposed research is the utilization of camera and global positioning data specifically for navigation in snow using real-time machine learning methods without an overreliance on deep learning. This technology can be implemented in current vehicles, enabling a widespread commercial impact and a strong means to grow a viable business that is generating tax revenue and offering technology jobs to the local community.
The strong technical innovation of this work is a hierarchical computer vision system built using a resilience engineering methodology, individually tuned classifications, camera and GPS fusion, and fast processing machine learning. This system provides verification of successful performance with respect to human-observed ground truth without an overreliance on deep learning so that it can be successfully validated by automotive companies using standard practices. This innovation allows current driving assistance products to remain functional when they are needed most: in low visibility, low traction situations. This research aims to verify the innovation in two-lane intersections, bridges, tunnels, under sun glare conditions, in 100+ miles of active snowfall, and in instances of misleading environmental information. Data for these instances will be collected and the existing technology will be modified and improved.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RIVALIA CHEMICAL CO
SBIR Phase I: Sustainable Rare Earth Element Production from Coal Combustion Byproducts
Contact
310 W. 112TH ST APT 2B
New York, NY 10026--3245
NSF Award
2335379 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Phase I Small Business Innovation Research (SBIR) project is to enable rare earth element (REE) production without mining, by harvesting REEs from coal combustion byproducts, namely coal fly ash. The U.S. produces over 100 million metric tons of coal fly ash each year through burning coal for power and has more than two billion metric tons in storage ponds across the country, estimated to contain up to 100 years? worth of U.S. demand of REEs. What is missing is a sustainable, scalable, and economic method of separation. REEs play critical roles in many different technologies, ranging from national defense applications to manufacturing and consumer electronics, to healthcare treatments, and much more. One particularly important industry is clean tech, where REEs are used in high-performance wind turbines and electric vehicles. Currently, the U.S. lacks a stable domestic supply of REEs and is reliant on mining efforts in foreign nations that lack similar labor and environmental protections. This dependence is a strategic vulnerability. Harvesting REEs from coal ash would build a sustainable, diverse, and resilient supply chain of materials needed to support the clean energy transition, as well as create new jobs and provide utilities with an economic pathway to better utilize ash and empty existing ash ponds.
This SBIR Phase I project will optimize a novel ionic-liquid-based recovery process to harvest rare earth elements (REEs) from coal fly ash. The ionic liquid in question has a high binding affinity for REEs and additionally displays unique thermomorphic behavior: upon heating, water and the ionic liquid form a single liquid phase, and REEs are leached from coal fly ash via a proton-exchange mechanism. Upon cooling, the water and IL separate, and leached elements partition between the two phases. The recovery strategy exploits this behavior in a new method that represents a breakthrough technology: the ionic liquid can extract the REEs directly from the solid ash without the need for digestion and separate the REEs from bulk elements. This dramatically lowers chemical consumption and waste generation and simplifies costly downstream processing. In Phase I of the project, efforts are focused on improving REE concentration in the IL phase, developing new processes for purifying REEs from ionic liquid concentrate, and validating the process for a variety of coal ash samples. The output of this project is expected to be comprehensively tested and validated recovery process ready for scaling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ROBIGO, INC.
SBIR Phase I: Engineering the Plant Microbiome to Reduce Disease in Crops
Contact
750 MAIN ST
Cambridge, MA 02139--3544
NSF Award
2232769 – SBIR Phase I
Award amount to date
$274,999
Start / end date
05/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a platform technology that enables a novel mode of action for protecting crops from disease. Facing increasing disease pressure and a changing climate, growers around the world spend $80 billion on nearly six billion pounds of pesticides each year, and yet still experience yield losses of 20-40% due to pests and disease. Broad-acting, chemical pesticides - currently the industry standard - are losing both efficacy and public support as resistance to pesticides spreads and the negative environmental impacts become clear. There is a pressing need to fundamentally redesign crop treatments to create a more sustainable and efficient food system. Leveraging synthetic biology, CRISPR, and data science, this SBIR Phase I project addresses this need by developing a new class of microbial biopesticides that precisely target and kill crop pathogens without adversely affecting beneficial microbes, insect pollinators, or humans. With an initial focus on treating tomatoes (320,000 acres in the US, $32 million addressable market), this project sets the stage for providing solutions for major global markets like citrus ($600 million), olives ($1.8 billion), and rice ($2.7 billion).
The project provides targeted solutions for bacterial diseases in agriculture. Historically overlooked and underserved by the agricultural community, bacterial diseases have become increasingly devastating over the past 10 years due to a lack of effective treatment options, growing antimicrobial resistance, and climate change driving higher disease pressures. Building from a prototype system, this SBIR Phase I project aims to engineer improvements that will increase the efficacy and tractability of the microbial biopesticide in outdoor agricultural environments. This includes applying molecular biology techniques to increase microbial colonization within complex microflora to increase product efficacy, extend microbial persistence in plants to provide longer protection, and reduce the rate of resistance to extend product lifetimes. Furthermore, this project will develop a bioinformatics algorithm to better program the microbes to specifically target only the disease-causing pathogens. Finally, the team will demonstrate product efficacy in lab-grown tomato plants with the goal of surpassing the industry standard of 70% efficacy and will compare performance to two industry standard chemical pesticides. Successful completion of this project will result in a novel method to introduce protective traits to crops without genetically modifying the plant itself.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ROSEBUD BIOSCIENCES INC.
SBIR Phase I: Drug discovery using stem cell derived organoids
Contact
63 VIA FLOREADO
Orinda, CA 94563--1924
NSF Award
2304222 – SBIR Phase I
Award amount to date
$274,829
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable the development of new therapies for rare diseases in children. An estimated 350 million people worldwide - half of which are children - suffer from an estimated 7,000+ known rare diseases annually, yet 95% of rare diseases still lack treatment. Even though >80% of rare diseases are genetic in origin, there have been relatively few actual drug discoveries. This is an enormous problem as 30% of children with rare diseases will not live to see their 5th birthdays. To address this, drug development can be accelerated by screening investigational drugs against micro-organs (?organoids?) that resemble young organs and have the same gene mutations as the patients. In a simple petri dish, organoids enable the direct study of the relationship between a patient?s genes and his/her disease. Such organoids present an opportunity to rapidly identify new disease mechanisms and targeted therapies. The team is scaling organoid technology into an automated drug development platform that is high throughput, robust, and applicable to multiple genetic diseases in children.
This project advances drug development for pediatric rare diseases by accomplishing two primary objectives: (1) automated heart, liver, and brain organoid derivation from human stem cells, and (2) automated machine learning (ML) detection of disease in organoids derived from patients with genetic diseases affecting any of these three organs. To do this, a combination of robotics and specific protocols will differentiate tissue- and disease-specific organoids under standardized conditions. The organoids are monitored with microscopy as they transition between tissue state. The ML model learns what healthy organoids look like and uses that information to identify when an organoid exhibits a disease phenotype. These objectives are important for reducing batch-to-batch organoid variability and human error that can confound drug discovery efforts. In these same organoid models, drug screening and development will be performed to try to reverse or retard the disease phenotype unique to each disease. The result of this research will be the production of organoids with high accuracy and precision, as well as an automated means for detecting changes in heart, liver, and neural organoids that will be essential for finding new therapies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ROTOHEATER LLC
SBIR Phase I: CAS: Advanced Thermal Oxidizer to Cost-effectively Control Greenhouse Emissions from Small Sources
Contact
716 FOUNTAIN STREET
Ann Arbor, MI 48103--3269
NSF Award
2326861 – SBIR Phase I
Award amount to date
$256,657
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks to reduce air pollution, specifically emissions of the greenhouse gas methane, toxic/carcinogenic organic compounds, and odors. Reduction in these emissions serves the public interest by improving human health, well-being, and the environment and is in alignment with NSF?s mission to promote innovative unproven technologies that can benefit society. These emission reductions will be accomplished through the development of a new type of air pollution control technology that can be cost-effectively applied to small emission sources that cannot be effectively controlled using existing technologies. These small emission sources are numerous, and in some cases, located near sensitive or overburdened communities, so the emissions control will have a large impact. The improved cost effectiveness and simplicity of this technology should reduce increasingly more stringent regulatory compliance costs, freeing up both human and capital resources for productive use in other areas.
This SBIR project will support research and development (R&D) into an air pollution control technology for combustible gases that uses a novel, patent-pending, continuous heat regeneration system to enable re-use of thermal energy in a thermal oxidizer. The effort will focus on investigating the fundamental heat transfer, fluid dynamics, and material science of the invention as well as construction and testing of full-scale prototypes to increase the durability and reduce the performance risk. This continuous, regenerative, thermal oxidizer system is unlike any existing pollution control technology and will enable a significant reduction in size and complexity compared to conventional technologies. The system will be mass-produced, unlike existing systems that are custom built. The combination of reduced size, reduced complexity, and mass-production should result in a large reduction in cost. The new system has other advantages such as reduced warm-up time, greater flexibility in applications, and greater safety.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Rhodium Scientific, LLC
SBIR Phase I: Space Biobank: Enabling High Throughput Space-Based Biotech R&D
Contact
1300 BAY AREA BLVD # B275-5
Houston, TX 77058--2505
NSF Award
2419674 – SBIR Phase I
Award amount to date
$273,968
Start / end date
03/15/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project establishing a space biobank represents a direct and real expansion of space access to a broader customer base, enhancing the scale and scope of commercial space markets. The low Earth orbit (LEO) environment has been shown to be a unique testbed to discover and develop novel drugs, therapies, and nutraceuticals. As biology adapts to space, changes in physiology can provide scientists with new drug targets and secondary metabolites. In addition, physiological studies conducted on astronauts have generated high-value datasets capable of supporting a variety of aging related initiatives. These studies support the use of the LEO environment for the development of therapies treating cognitive function loss, cardiac health reduction, muscle atrophy, and bone loss. Past results from space-based R&D indicate that by enabling more biotech missions, society stands to benefit from breakthroughs in agriculture, regenerative medicine, drug discovery, and biomanufacturing. Space Biobank will become the platform that enables on-orbit discovery and scalable production through reliable access to this unique biological and physical environment.
This SBIR Phase I project will develop a space biobank, the first repository for microbial species produced from and optimized for the space environment. This initiative aims to democratize space-based research by facilitating broader community engagement. Unlike the well-established engineering standards within the space industry, biological standardization for organisms and scientific processes is lacking. The space biobank addresses this gap, enabling teams to streamline pre-flight development, conduct experiments using space-flown strains, and enhance mission comparability. The PI?s company has operated a dozen ISS missions focused on both growth and production through targeted biomanufacturing and bioprospecting/drug discovery missions. The resulting strains and those developed for and on future missions will be made available to the biotech market through the space biobank. A suite of postflight characterizations will determine metabolic and functional modifications observed in the space environment prior to inclusion in the space biobank. Overall, the key benefits of the space biobank include 1) a significant reduction in mission development timelines; 2) a source of flight-adapted and proven biological samples to de-risk mission objectives; 3) a global mechanism for scientists to engage in space-derived experiments; and 4) a central repository for all space-flown microbial samples.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SALUS, LLC
SBIR Phase I: Digital Underwriting Platform for Underserved Borrowers
Contact
1300 SOUTH BLVD
Charlotte, NC 28203--0085
NSF Award
2322241 – SBIR Phase I
Award amount to date
$274,541
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will enhance the understanding of predicting default risks for borrowers that lack traditional access to loans and credit. The project will result in a digital platform that efficiently underwrites borrowers for small dollar loans using an innovative technical approach. The project will allow any lender to use the platform to efficiently make small dollar loans, sparing traditionally under-served borrowers from costly alternative financial products. This technology helps financially vulnerable households maintain stability when financial emergencies strike.
This Small Business Innovation Research (SBIR) Phase I project develops more effective ways to underwrite small dollar loans for traditionally underserved borrowers. Nearly half of the adults in the U.S. lack a prime credit score that is sufficiently high to allow them access to loans and credit. Traditional lenders are hesitant to lend to applicants with lower credit scores, due to a perceived higher risk of loss. The systems and information that are used to generate credit scores have limitations that can prohibit credit-worthy borrowers from receiving small dollar loans. The project will investigate alternative methodologies of underwriting small dollar loan applicants. The research will test these alternative methodologies and compare them to traditional credit scoring as a determinant of credit risk, and by extension, loan application approval. Upon completion, the project will demonstrate that an alternative underwriting methodology can generate lower default rates and more equitable lending decisions for small dollar loans when compared to traditional credit scores.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SAMARA AEROSPACE, INC.
STTR Phase I: A Reliable and Efficient New Method for Satellite Attitude Control
Contact
1995 E COALTON ROAD #62-201
Superior, CO 80027--4538
NSF Award
2310323 – STTR Phase I
Award amount to date
$274,993
Start / end date
02/01/2024 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project offers significant changes to the conventional concept of spacecraft orientation control by providing increased agility, along with reduced mass, volume, and cost. These advantages open doors to new scientific and commercial opportunities. The project addresses the demanding needs of future space observatories and commercial spacecraft that require high agility systems, currently unachievable with existing attitude control solutions. Moreover, this system, as a more affordable 3-axis control option, is set to increase access to space for lower-budget missions, making space exploration more accessible than ever before. The systems application is envisioned to enable advances in sectors such as satellite-to-satellite communications, adding momentum to global digital connectivity initiatives.
This STTR Phase I project seeks to develop a Multifunctional Structures for Attitude Control (MSAC) system and increase its efficiency and reliability, pushing it towards achieving readiness for flight demonstration. The project addresses the existing challenge of the system's fatigue strength and its compatibility with the harsh space environment, factors crucial for its commercial success and durability in its intended application. This project's aim is to design a flight-capable system, drawing on the insights from lab-scale tests and prototypes. It also seeks to simultaneously improve the system's mechanical and electrical design to elevate efficiency and reliability standards. Through this research method, the team anticipates a better understanding and eventual mitigation of potential failure modes, paving the way for the realization of a robust, space-ready prototype. The anticipated technical results from this endeavor have the potential to revolutionize the spacecraft attitude control market.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SANGTERA INC
STTR Phase I: Microhydraulic Actuator for High-Accuracy, High-Speed Position Stages
Contact
1 LORING RD
Lexington, MA 02421--6907
NSF Award
2335170 – STTR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 06/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop the key technology to enable the building of high-precision, high-throughput, semiconductor advanced packaging systems to enable broad adoption of the 3D integration of chiplets for next generation high-performance computing. With the rapid increase in the need for computing power associated with artificial intelligence development, self-driving cars, and next generation mobile devices, the semiconductor industry is transitioning to integrate semiconductor devices in 3D. This technology will extend the growth curve known as Moore?s Law beyond the limit of packing additional transistors onto individual chips. This project may also demonstrate the general feasibility of microhydraulic actuator technology, paving way for its development and applications in other fields of robotics.
This Small Business Technology Transfer (STTR) Phase I project seeks to control electronics and design protocols to reach 100 nm in position accuracy in the design of semiconductor advanced packaging systems. The high-speed position stage will be based on the microhydraulic actuator technology and provide an improvement of 100x over the as designed step size. The team will develop the necessary electronics, hardware, control software, and measurement techniques to achieve the position accuracy, while maintaining the high responsiveness of the microhydraulic actuator. The plan includes assembling test actuators, developing and testing the control hardware and software, as well as establishing the capabilities of position measurement systems based on charge control, capacitance feedback and optical image feedback. The team will use these measurement systems to assess the movement accuracy and precision of the actuator and its control system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SCDEVICE LLC
SBIR Phase I: Radiation Tolerant, High-Voltage, Silicon Carbide Devices
Contact
3359 NW 123RD PL
Portland, OR 97229--8301
NSF Award
2304486 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to enable smaller, lighter, and higher-performance satellites, thereby making satellites cheaper to manufacture and launch. Lighter satellites reduce launch costs or permit greater payload performance for a given mass. Less fuel is required to launch lighter satellites, reducing the environmental impact of greenhouse gases generated during launch. Internet connectivity through satellite is becoming increasingly pervasive, and if costs continue to decline, it might become ubiquitous, supporting workforce development and educational outreach in hitherto unserved places. Many components, such as power supplies, can be made lighter and smaller when silicon carbide semiconductors are utilized in place of silicon high voltage devices in applications such as aerospace and satellites. The ultimate goal is to replace all silicon high-voltage devices in satellites and aerospace with silicon carbide products. It has been demonstrated that conventionally designed commercial high voltage silicon carbide materials cannot withstand the high radiation levels encountered in outer space applications. The objective of this project is to develop, manufacture, test, and demonstrate the viability of silicon carbide high voltage semiconductor products that are resistant to radiation levels comparable to those encountered in space.
Commercially available silicon carbide (SiC) power devices are not approved for use in heavy ion radiation environments due to their susceptibility to catastrophic failure and burnout at voltages below 20% of the specified voltage when exposed to radiation. Consequently, SiC high voltage devices are not currently used in space applications, despite the fact that they offer very compelling features for mission-critical applications. Using simulation tools, the team has created a SiC junction barrier Schottky diode that can operate at up to 1200 V under high ion radiation. A radiation-resistant silicon carbide junction barrier Schottky diode rated at 1200 V will be designed, produced, and tested for radiation resistance. To accomplish the target radiation performance, a multi-pronged strategy will be applied, including novel device designs to reduce the electric field and mitigation of thermal runaway caused by ion strike when the device is under reverse bias. Schottky barrier materials with improved thermal stability will be used. Successful implementation of the intended approach will open the way for the integration of SiC Schottky diode devices in space applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SCREEN360.TV, INC.
SBIR Phase I: A platform for cross-cultural collaborative learning by 6th-12th graders based on synchronous watching of international films from different locations
Contact
17033 SE RIVER RD
Portland, OR 97267--5503
NSF Award
2321956 – SBIR Phase I
Award amount to date
$273,998
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in exposing students to cultures other than their own to foster empathy, not only for others, but to better understand themselves and their own culture. The 21st century workforce requires multilingual, curious, collaborative, empathetic learners. Yet, immersive opportunities to exercise empathy cross-culturally are difficult to access and empathy requires practice. Geographic and cultural knowledge from travel abroad programs is proven to increase empathy, but such experiences serve relatively few students. Schools need a cost-effective and safe way of equitably delivering immersive cross-cultural engagement to meet increasingly global demands. This project intends to present the international film festival as a rich learning atmosphere, replicable at scale to serve learners well beyond the traditional audience diversity and number. The immersive experience will be delivered to respond to learning needs in the classrooms, after-school programs, hospitals, and refugee centers. The films will be expertly curated, globally streamed, co-viewed across time zones, and enhanced with moderated curriculum.
This project replicates and magnifies aspects of the film festival model which correspond to social impact business innovation, specifically, empathy. Multiple identified paths to empathy in each session are activated and reproduced through discussion, analysis, gamification and assessment. This series of assessments engages the learner to better understand how they learn, while reinforcing the memory of learning of a culture outside of their own as integral to their developing worldview. The project also establishes a foundation for both media and cultural literacy. The platform will activate non-generative artificial intelligence (AI) in service of matching profiles, scheduling, automation, assessment tabulation and reporting, and archiving. The technology will employ generative AI with AR (augmented reality) in service of translation in post-film discussion as well as location-based information to enable additional points of empathy for discussion. With respect to assessments, AI will be used to provide feedback to participants, impacting learning episode memory. The assessments will also serve in the facilitation of qualitative assessments so that participants receive timely reports, illuminating similarities and differences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SET POINT SOLUTIONS LLC
SBIR Phase I: Set Point Solutions - Safeguarding Lives By Enabling Communication in Austere and Remote Environments
Contact
143 RAMIREZ WAY
Toto, GU 96913-
NSF Award
2212209 – SBIR Phase I
Award amount to date
$246,858
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project will extend the range of on-hand wireless communications devices to austere and remote environments. Public safety agencies will now be able to utilize available resources more efficiently, precisely geolocating distressed individuals and/or connecting individuals in need with specific resources and personnel to facilitate their rescue. The propeller-enabled Projectile Assisted Repeater/Relay Of Transmissions (PARROT) technology will benefit the civilian market that requires communication in remote locations or emergency situations. Potential customers include individuals whose vocation or vacation takes them into austere locations where the ability to communicate effectively may be compromised. Additionally, the PARROT would be a lifesaving piece of equipment for individuals whose work often requires them to be in areas lacking robust or functioning communication infrastructure: commercial truck drivers, Customs and Border Patrol (CBP) agents, Federal Emergency Management Agency (FEMA) responders, search and rescue teams, etc.
This Small Business Innovation Research (SBIR) Phase I project highlights how communications solutions historically evolved by modulating the specific frequency range, whereas the approach applied to solving this problem is to allow the user to prescribe the location of a relay and rapidly introduce that physical relay (capable of loitering for sufficient time to allow for two-way communications) into their environment. The envisioned device could utilize existing tools to deploy its innovative technology. Additional variants could be developed as part of all-in-one kits supplied to outdoors enthusiasts. The principal scientific and engineering research objectives are to engineer, develop, and design electronic components small enough to fit in the desired form factor, yet rugged enough to withstand the significant set-back forces associated with ballistic, short-tube launches. Computer aided design/manufacturing (CAD/CAM) processes will be used to model, prototype, test, and evaluate the design. Once that task is completed, the device will be able to safeguard the lives of first responders and outdoors enthusiasts globally.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SIMPLYBREATHE L.L.C.
STTR Phase I: Steroid-eluting thread for the treatment of rhinitis
Contact
96 TERN ST
New Orleans, LA 70124--4413
NSF Award
2305502 – STTR Phase I
Award amount to date
$255,045
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this this Small Business Technology Transfer (STTR) Phase I project is a novel, minimally invasive, surgical option for reducing complications and improving outcomes for rhinitis patients. A bioabsorbable, steroid-eluting suture and surgical implant procedure will be developed to improve outcomes for 6 million patients suffering from rhinitis under the care of otolaryngologists, or ear, nose and throat specialists. The proposed suture system and surgical suite implant procedure enables a temporary therapy that replaces the need for current chronic, daily, topical sprays and/or long-term immunotherapy with a single in-office visit. The bioabsorbable, drug-eluting platform also provides potential extensibility for eluting other medications including antibiotic and antifungal therapies.
This Small Business Technology Transfer Phase I project aims to deliver a prototype steroid-eluting dissolvable thread with an introducing surgical tool. The project is comprised of several steps including the formulation of dissolvable polymers, and prototyping using Hot Melt Extrusion (HME). This effort will advance the platform design and development of optimized drug-elution thread for use in the nasal cavity. The system will be designed using the preferred steroid of mometasone furoate and characterized for drug elution properties in a preclinical animal model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SIXLINE SEMICONDUCTOR, INC.
STTR Phase I: Next-Gen Radiofrequency Transistors on Silicon via Aligned, Residue-Free Carbon Nanotubes
Contact
5262 BISHOPS BAY PKWY, UNIT 214
Middleton, WI 53597--8829
NSF Award
2322200 – STTR Phase I
Award amount to date
$274,503
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project seeks to overcome the highest risks facing the commercialization of a novel semiconductor for wireless communications devices. As the demand for wireless communication increases (e.g., cell phones, WiFi, Internet of Things devices), wireless component suppliers and manufacturers must utilize new materials and integration methods to yield necessary increases in data bandwidth, energy efficiency, and functionality, while shrinking component footprint. Carbon nanotubes offer a solution to this problem. A carbon nanotube is comprised of an atomically thin layer of carbon rolled into a seamless tube. Carbon nanotubes act like tiny semiconducting wires that can significantly outperform current semiconductors such as silicon and gallium arsenide. When aligned into dense arrays, nanotubes offer superior wireless characteristics including high frequency and linearity, which are vital for next-gen communication technologies. Importantly, carbon nanotubes can be deposited onto existing semiconductors (such as silicon), enabling the previously unfeasible integration of multiple types of high-performance circuits on the same chip, allowing for more functionality in less space. By addressing problems related to wireless communication, this project will have widespread societal impact and underpin the wireless radiofrequency technologies of tomorrow, while bolstering American competitiveness in this important sector.
The project will leverage recently developed carbon nanotube alignment technology that overcomes the materials and manufacturing challenges that have limited previous nanotube research and development. The room-temperature alignment technology is fast, cost-effective, and area-scalable ? enabling seamless industry integration. The technical innovations of this project will be to: (1) develop approaches to remove organic processing residues that coat the surfaces and interfaces of nanotube arrays and decrease the performance of nanotube-based wireless communications transistors; and (2) fabricate and demonstrate wireless communications transistors based on aligned nanotubes that do not suffer from the effects of such impurities. Spectroscopic measurements of residues, electrical measurements sensitive to impurities, and additional high frequency transistor characterization will be used in a feedback loop to inform residue removal process development. Specific activities will focus on: (1) systematically studying the effect of different treatments to selectively remove residues; (2) determining how the treatments depend on array density; and (3) fabricating and testing wireless communications transistors. The project will provide a database of impurity removal rates for a library of treatments, a demonstration of transistors free of performance loss from residues; and a demonstration of nanotube-based transistors integrated on silicon.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SKYWALK INC.
SBIR Phase I: Overcoming interaction barriers in augmented reality via wearable multimodal sensing
Contact
855 EL CAMINO REAL, SUITE 13A - 230
Palo Alto, CA 94301--2305
NSF Award
2322424 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project enables people to intuitively interact with augmented reality technologies. Currently, augmented reality input modalities can be extremely unreliable, making it nearly impossible to use traditional mouse-and-keyboard applications on these devices. The company is proposing a device that may overcome this interaction barrier by allowing augmented reality manufacturers the ability to make more complex and meaningful applications. The device will turn human hands into cursors, turn any surface into a touchscreen, and unlock new human-computer interactions. Using this device with augmented reality headsets is expected to prove advantageous for potential applications in education, medicine, defense, and manufacturing.
The company is building an interface for augmented reality input, paving the way for a differentiated path to increasing augmented reality content. This technology could allow for rapid communication of information at a rate falling between that of typing on a computer and physically speaking, unlocking untapped productivity for users of augmented reality platforms. These outcomes will be met through the development of a reliable and functional wrist-worn, near-infrared sensor network that will improve the capture of input data. Unlike current devices, this technology is not hindered by the cameras' limited field of view or obstructions, or by the unreliability of other wearable input capture devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SNOCHIP INC
SBIR Phase I: All-Semiconductor Nanostructured Lenses for High-Tech Industries
Contact
98 MARION DR
Plainsboro, NJ 08536--2016
NSF Award
2335588 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/01/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is to develop lightweight, compact, and all-semiconductor-manufactured optical devices based on metasurface technology. The manufacturing process of conventional optical devices involves techniques that face challenges in integration, assembly, and testing as well as long turnaround times and high costs. This lens technology, called metalenses, is superior to conventional lenses, which are typically made of glass or plastic. Metalenses are made from arrays of nanostructures, and these nanostructures interact with light at the nanoscale, allowing for precise control of the light properties. This project will significantly reduce the complexity of fabrication process where metalenses will be integrated with a semiconductor laser diode in a conventional manufacturing facility without the need for any additional or special equipment. The novel metalenses will be engineered and made of special multilayered thin films with high reflectivity. The metalenses will have wide application across a spectrum of industries, including, but not limited to, imaging, sensing, telecommunication, aerospace, and defense. The realization of this project will amplify global competition within the photonics industry and increase the competitiveness of the United States. It will increase employment opportunities across diverse high-tech domains, including chip manufacturing, photonics and optics.
This Small Business Innovation Research (SBIR) Phase I project aims to address the limitations of conventional methods for the control of laser beams. The innovation offers a novel approach to design and fabricate a spatial-dispersion-engineered metalens through cost-effective wafer-scale manufacturing. The metalenses will have the potential to replace the distributed Bragg reflectors (DBRs) in both top- and bottom-emitting Vertical Cavity Surface Emitting Lasers. This goal is to achieve either low (< a few degrees) or high divergence (> 30 degrees) angles. The metalenses will be designed with a proprietary algorithm and special code based on an application programming interface linking and enabling data exchange between different design software and will have design flexibility such that wavelengths of interest could be achieved by linearly adjusting each film thickness followed by an optimization. The project's key objectives are (1) the validation of the concept and exploration of its limitations, (2) the experimental fabrication and characterization of the designed metalenses, and (3) the development of scalable manufacturing pathways for the integration of such metalenses with laser chips.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SOFI TEC LLC
STTR Phase I: Development of Modular Reactors to Convert Methane to Alcohols at Low Temperatures
Contact
122 GRANDVIEW TERRACE DR
Youngsville, LA 70592--5536
NSF Award
2151256 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop affordable and efficient new chemical processes for the conversion of natural gas to alcohols, which will reduce the emissions of methane and help mitigate carbon dioxide (CO2) emissions. The affordable capture and conversion of methane emissions to alcohols is expected to have environmental benefit and provide a commercially valuable market that can be developed for remote areas where flaring and venting of methane occurs. The direct release or flaring of methane results in greenhouse gas emissions. The conversion of as little as 10% of the currently-flared methane emissions can satisfy the global methanol demand which is an estimated $55 billion/year industry. A recent Global Methane Assessment showed that human-caused methane emissions can be reduced by close to 45% in this decade. This project will have an impact in areas where the highest methane emissions occur, such as oil and gas producing regions.
This STTR Phase I Project develops a high-risk technology based on modular reactors that utilize novel electrodes and cell architecture to directly capture and convert methane to alcohols and hydrogen. Using newly developed methods, the project will demonstrate the feasibility of affordably converting methane to value-added fuels at atmospheric pressure and low temperatures in the field. The proposed technology focuses on the application of process intensification at modular-equipment scales suitable for deployment and transport between remote locations where gas is being vented or flared. The modular reactors are compact, integrated, and transportable. They have a large turndown ratio and can operate continuously under varying feed rates and gas compositions. These reactors have the potential to convert a high fraction of methane, lessening the requirements for outgassing capture. This project will use advanced additive manufacturing, electrochemical modeling, gas sensing, and process scale up.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SOSTOS LLC
SBIR Phase I: A web portal for artificial intelligence (AI)-based comprehensive discovery of repositioning drugs
Contact
591 HERMAN AVE
Morgantown, WV 26505--2031
NSF Award
2334510 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project accelerates the development of potential new drug options for improved survival outcomes of cancer patients with greatly reduced time and costs. This project will use a novel artificial intelligence (AI) technology that utilizes big data to comprehensively discover repositioning drugs for treating refractory non-small cell lung cancer (NSCLC) patients after exhausting all therapeutic options. Drug repositioning (also known as drug repurposing) involves the investigation of existing drugs for new therapeutic purposes. The software product enables oncologists to select repositioning drugs and design clinical trials. This project will specifically aid oncologists who do not have options to treat cancer patients after the prior therapies failed as well as their patients. The novel partnership between subject experts in academia and industry will increase the effectiveness of the technology. The software product built during the project can facilitate the research and development at pharmaceutical companies, benefit millions of cancer patients, and reduce the healthcare burden by improving the quality of care.
This Small Business Innovation Research (SBIR) Phase I project will test the feasibility of developing a software product developed using a patented artificial intelligence (AI) technology that enables oncologists to choose among repositioning drugs for the treatment of lung cancer in patients with failed prior therapies. Based on established proofs of concept, this project will develop a software product with a cloud-based backend data portal with more than 378 therapeutic compounds discovered using AI technology for treating lung cancer. The solution will also have a web-based frontend with a graphical user interface for oncologists to select a repositioning drug based on patient responder characteristics and new indications for treating lung cancer. Since the safety profiles of repositioning drugs are established, the efficacy test of their new indications can bypass preclinical studies and Phase I clinical trials. The software product can accelerate Phase II/III clinical trials of the new indications of existing drugs for Food and Drug Administration (FDA) approval. Meanwhile, this solution will also facilitate new drug development for pharmaceutical companies. Once feasibility is validated, the team will expand the software product to other cancer types.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SOWN TO GROW, INC.
SBIR Phase I: Sown To Grow - Measuring Growth in Trusting Relationships between Students and Educators with Natural Language Processing and Machine Learning Technologies
Contact
515 CROFTON AVE
Oakland, CA 94610--1520
NSF Award
2322340 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project seeks to help educators to develop deeper relationships with their students, assist schools in identifying students who lack strong relationships and need additional support, and help school districts understand the emotional health and relationship strength of their schools. Student emotional well-being, student absenteeism, and teacher burnout are some of the most pressing problems facing K-12 education today. A significant body of research shows that positive student-teacher relationships help students adjust to school, contribute to social skill development, promote academic performance and resiliency, decrease absenteeism, and foster engagement. Schools struggle with relationship building at scale - it takes time to form connections, not all students are willing to open up, and teachers need help and training on understanding and responding to the varied experiences and needs of their students. This project, if successful, will help schools address these challenges at scale. Additionally, the data from this project will help teachers contribute to learning science and behavioral health research, while providing a blueprint to the education technology industry on how to implement advanced technology in an ethical and transparent manner that augments, rather than replaces, existing education structures and systems.
This project builds an innovative technology that will understand and measure the strength of the student-teacher relationships at scale. The technology will develop new frameworks for defining trusting relationships based on the depth of student reflections, teacher responses, and how responses change and grow week over week. Advanced natural language processing (NLP) and machine learning (ML) techniques will model these frameworks based on real student-teacher interactions. NLP typically focuses on using models to understand text inputs and predict/generate responses. Through this project, the team seeks to use new NLP/ML techniques to understand and assess the interactions and levels of trust between individuals. The NLP/ML models will analyze the depth of student reflections and interpret the nature of the teacher responses separately. The output of these two models will then be combined to understand the strength of student-teacher relationship by creating a student-teacher relationship trust metric. This metric will help understand student-teacher relationships at scale across schools and districts all over the country.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SPACE KINETIC CORP.
SBIR Phase I: Electromechanical Mass Transfer System for Space Operations
Contact
2420 ALAMO AVE SE STE 104
Albuquerque, NM 87106--3217
NSF Award
2335593 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to advance a novel electromechanical platform for in-space logistics to facilitate economic development, technical and scientific advancement on the lunar surface, and in other low gravity environments. On other celestial bodies (e.g. Mars), this platform can similarly be utilized to enable early exploration and development with minimal wraparound infrastructure investments. The subject of the SBIR project is an electromechanical mass transfer system; this will be the first such innovation that enables a cost-effective mass transfer in low gravity environments leveraging centrifugal acceleration. This platform can enable the movement of resources through space without the use of consumable fuels or on-board propulsion systems, unlocking more cost-effective space operations. The successful execution of this project will enable swift TRL raising of the platform. The comprehensive testing and validation process will demonstrate the capabilities of our technology to potential customers and stakeholders, providing tangible evidence of its reliability, accuracy, and efficiency. The successful development of the platform can provide the mobility required to empower robust exploration, science, and economic development on the surface of the Moon. This platform will be more economical than other alternatives due to its low mass and plug-and-play functionality. Ultimately, the system aims to provide the cheapest, most comprehensive logistics services that catalyze the promising lunar market.
This SBIR Phase I Project will address the technical challenges associated with transporting resources across the lunar surface with a novel electromechanical "throwing" platform. The platform, which utilizes an electromechanical system to throw payloads across the lunar surface, offers an innovative solution for lunar surface logistics and other space-based mobility problems. The goals of the proposed R&D include developing a reliable, accurate, and energy-efficient prototype and demonstrating its feasibility and capabilities on Earth. Lunar operations are complex and expensive, and with novel technology such as the proposed platform, customers and other stakeholders will be looking for assurances that the platform will be both repeatable and accurate. Wear and tear on the system, varying environmental effects such as variable Lunar gravity, and built-in system inaccuracies such as error bands around release angle and velocity can cause a failure that could put customers at risk. The purpose of this effort is to demonstrate with specific hardware improvements that the platform can safely and repeatably deploy assets across the lunar surface.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SPACE TANGO LLC
SBIR Phase I: Consortium for High Throughput CubeLab by Space Tango
Contact
611 WINCHESTER RD STE 100
Lexington, KY 40505--3726
NSF Award
2416101 – SBIR Phase I
Award amount to date
$274,939
Start / end date
03/01/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to address some of the most impactful health research questions by using high throughput techniques in the weightless environment of Low Earth Orbit (LEO). When studying diseases or developing treatments on Earth, cellular models are often used to ?stand in? for humans during the development phase because of the high number of trials that can be performed in a short period of time. The microgravity environment offered in LEO, provides a unique laboratory where some diseases can be studied more efficiently than on the ground. This project?s technology is being developed to allow for an unprecedented number of samples to be studied in space, and making world-class health research finally achievable by providing the statistical significance that could only be achieved on Earth. The consortium being formed brings us together with a group of world-class researchers in fields such as cancer research and drug delivery. Beyond potential health impacts, these studies will encourage the small businesses involved to develop products and strategies for the future, both on Earth and in space.
This Small Business Innovation Research (SBIR) Phase I project will double the current capacity of a biological platform technology to enable nearly 600 individual samples in one payload. All samples will be hosted in an environmentally-controlled, sealed system, matching the best incubation conditions available on Earth, and flown in space during this Phase I project for 30 days on the International Space Station (ISS). This high throughput system will allow for numerous start-ups and labs, including collaborators from Notre Dame, the University of San Diego, Mithrilome, Encapsulate, Massachusetts General Hospital, and Mount Sinai Icahn School of Medicine. These collaborators will fly specialized cells, groups of cells, and nanomaterials to screen for the best candidates in which to target further translational research and commercialization efforts. Enough statistical evidence will be gathered to match the quality of any ground-based study that could be carried out. The members of the consortium will carry out research related to Rett syndrome, Alzheimer?s disease, biomanufacturing of health-related products, drug delivery formulations, brain cancer, gastrointestinal cancer therapies, and the heart.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SPACERAKE, INC.
SBIR Phase I: Multiple Access Laser Communication Terminals for Optical Orbital Hotspots
Contact
1 KENDALL SQ, SUITE B4401
Cambridge, MA 02139--1661
NSF Award
2319654 – SBIR Phase I
Award amount to date
$274,120
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project lies in the development of an Optical Orbital Hotspot network that will enhance satellite data collection and utilization. This innovation is projected to make small satellites operating more efficient and accessible, thus empowering businesses, agencies, and new entrants. The expected result is an increase in data generation and transfer, improving connectivity to cloud-based services and Low Earth Orbit (LEO) space-based platforms. By decreasing the technical and cost barriers to LEO access, rapid innovation will be enabled, leveraging existing aerospace research. This development is aligned with a growing market, with the satellite laser communication market expected to reach $4.1B by 2031. The commercial implications are vast, including opportunities to address an even larger satellite ground station market, with the potential to enable transformational opportunities across various sectors.
This SBIR Phase I project proposes to develop and refine the technology for an Optical Orbital Hotspot network integration and implement advanced beam steering technologies. The primary challenges lie in the creation of multi-access lasercom terminals (MALT) and the development of orbital optical hotspot technology. The research will mature the optical designs of the MALT and compact user lasercom terminal systems (micro-LCT). Research and objectives to be addressed range from operations development to preliminary hardware design. The anticipated technical results will include the establishment of orbital models, multibeam steering technology development, interface and requirements definition, and design for the MALT and micro-LCT systems. These efforts will collectively solve the 'last mile problem' for small size, weight, power, and cost satellites, enhancing capabilities and lowering high data rate communication barriers in the Earth observing systems market.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
STARGAZER DESIGN TECHNOLOGIES INC
SBIR Phase I: Designing the Future: Generative Configuration Design
Contact
573 FREMONT RD
Chester, NH 03036--4192
NSF Award
2333122 – SBIR Phase I
Award amount to date
$274,644
Start / end date
01/15/2024 – 09/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project develops generative artificial intelligence (AI) algorithms that assist engineers and designers in developing new products. As a sustainable Software-as-a-Service (SaaS) business model, engineers can design more quickly than ?brainstorming? and thereby discover novel, high performing solutions. For the aerospace and defense sector, this technology will be used to quickly design innovative solutions to counter growing threats from potential near-peers. The short design cycles lead to less wasted effort in reengineering solutions to fit within rapidly changing program requirements. The technology may also be used to decarbonize air travel. By lowering the barriers to entry for design engineering, this project will enable a broader cross-section of the American populace to engage with design, engineering, product development, and invention. The results of this project can accelerate the promotion of safer, more efficient, and more cost-effective products in various industries.
This Small Business Innovation Research (SBIR) Phase I project advances the state of the art in generative artificial intelligence, particularly regarding algorithms? ability to engage with complex non-media datatypes and develop methods that can generate novel cyber-physical system architectures in the absence of large pre-existing databases. Currently, computer-aided engineering software excels at rendering precise analytical results for the dynamics of a given system architecture but offers little to no information as to the variety of architectures that can satisfy performance requirements. Simultaneously, generative AI currently excels at generating media products without the constraint of performance, physics, or logic. This project will develop a framework for incorporating simulation-based physics information into generative algorithms to enable engineers to create physically realizable systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SUBSEASAIL LLC
SBIR Phase I: Hermetic, Expeditionary Sailing Vessel
Contact
4420 HOTEL CIRCLE CT STE 215
San Diego, CA 92108--3423
NSF Award
2126527 – SBIR Phase I
Award amount to date
$255,923
Start / end date
03/15/2022 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project is to leverage technical innovations in multi-hull sail management and autonomy to design a sailing vessel that provides fast, economical delivery of supplies to remote locations. This technology seeks to be able to use multi-hull sailing vessels more reliably for the delivery of supplies such as fuel, water, food, and medicine. Current options are limited by cost, lack of supporting infrastructure (ports), and shipper interest. The vessel is designed to de-risk the supply chain with particular focus on underserved locations. The key technical innovations address a vulnerability of multi-hull sailing vessels - catastrophic capsizing - by providing a controlled submerging capability and a method to right a flipped vessel with the goal to be able to re-surface and continue a voyage. The surface system will use a pivoting mast for passive, real-time corrections.
This Small Business Innovation Research (SBIR) Phase 1 project addresses the logistical and economic limitations of current systems that deliver supplies to remote locations. Rather than attempting to optimize the elements of the current delivery systems, the technology seeks to address island inaccessibility to large vessels, lack of cargo flexibility, increasing weather risks, and capital and operating economics by addressing the capsizing vulnerabilities of a surface sailing vessel and managing ballast system. Capsizing occurs when the center of gravity (CG) is higher than the center of buoyancy (CB). In mono-hull vessels, the keel is the primary design element that maintains this ratio. Multi-hull designs introduce different challenges. Vessel surface control will be managed by a passive wing sail control system that provides real time corrections. Submerged performance will be managed by pumps and ballast for corrective action. The primary research objectives are to design, evaluate, and optimize a heeling wingsail system (pivoting masts and hull involvement), and to design, evaluate, and optimize a ballast system for controlled submerging as well as to right capsized vessels.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SUNAIRIO INC.
SBIR Phase I: High Fidelity Climate Simulation Powered by Generative Adversarial Networks
Contact
509 S EXETER ST
Baltimore, MD 21202--4369
NSF Award
2335370 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the creation of a broad (1,000 outcome), hyperlocal (less than 3 km) climate simulation archive that can be used by power grid planners and energy industry investors to better understand forward-looking risks to grid reliability and renewable energy asset viability. This simulation data will be pre-computed for all locations within the Electronic Reliability Council of Texas (ERCOT) power grid, enabling planners and investors to quickly model the probabilistic impact of different renewable energy capacity pathways and different electrification trends. Ultimately, this data will support a more reliable grid and faster energy transition because decision-makers will have access to a single source of future weather data that incorporates extreme events, natural variability, and climate change.
This Small Business Innovation Research (SBIR) Phase I project proposes the creation of a climate simulation engine that generates synthetic hourly local weather patterns for many locations and many weather variables (all that are needed to model energy resources such as utility demand, wind generation, and solar generation). The project will not rely on physics-based global climate models due to the computational intensity of those models and the need to model local rather than regional or global weather. Instead, this project will research an innovative combination of statistical simulation with artificial intelligence (AI), leveraging the strengths of each to compensate for the weaknesses of the other. For example, statistical simulation models are precise but do not scale, while AI simulation models can scale almost without limit but are not precise. The project research will investigate a new method to impose precision (via known statistics) on AI pattern generation, yielding a high-fidelity climate model at scale. The expected technical result of the project is the creation of a simulation engine that can simulate 1,000 outcomes of hyperlocal hourly weather over the state of Texas--with accuracy similar to a pure-statistics model benchmark while keeping the cost of cloud computing resources low.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SURGIC, LLC
SBIR Phase I: Surgical training platform with customizable training scenarios enabled by 3D printing and artificial intelligence
Contact
3911 4TH ST
Lubbock, TX 79409--9805
NSF Award
2304526 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a customizable surgical training platform supported by artificial intelligence. Existing surgical simulators allow trainees to practice in safe environments prior to operating on patients. These simulators are limited in recreating the challenges of the operating room and providing feedback to assess trainees? performance. The technology developed in this project focuses on forming a better understanding of methods and techniques to recreate synthetic patient anatomy and how to provide higher quality assessments of surgical training procedures. The project will provide a platform for improved medical training of medical students, residents and surgeons that results in better skilled medical practitioners that deliver higher quality patient outcomes.
This Small Business Innovation Research (SBIR) Phase I project focuses on raising the quality of surgical training platforms by improving the realism of recreated anatomy and enabling scenario customization during training. The project uses techniques of 3D printing, mechanical testing, and machine learning to characterize the properties of synthetic anatomy and objectively assess trainees? surgical performance for each scenario. The artificial intelligence will be trained by mechanical measurements of synthetic anatomy before/after training operations from users. Comparisons of surgical performance will be conducted between experienced, practicing surgeons and inexperienced/less experienced medical students. The anticipated results are the development of a customizable surgical platform that provides objective feedback on a personalized basis to improve the standards of surgical practice among trainees.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SWAY INNOVATION CO.
SBIR Phase I: Ester and Polyester Modifications of Seaweed-Derived Colloids to Improve Melt Processing and Compatibility with Renewable Polymers
Contact
1743 ADDISON STREET
Berkeley, CA 94703--1501
NSF Award
2302043 – SBIR Phase I
Award amount to date
$272,397
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a new type of melt-processable pellet made utilizing phycocolloids derived from different seaweed materials. Today, the commercial plastic packaging industry is reliant on the polymerization of petroleum derivatives, which are then compounded or melt-processed before being converted into finished goods. Mounting consumer backlash against plastic waste, domestic and international regulations, and an increased focus on curtailing dependence on petroleum are driving the demand for compostable packaging solutions that can service the biodegradable packaging market which is set to grow to $812 billion by 2030. By using seaweed as an alternative feedstock, the team's goal is to eliminate the need for more environmentally intensive inputs including petroleum as well as other terrestrial crops. Furthermore, this material technology is being designed for compatibility with existing plastic manufacturing infrastructure ? thereby streamlining a path to scale and cost competitiveness. The anticipated outcome of this project is the development of the first commercially viable polymeric material predominantly derived from seaweed, that is melt-processed and compostable. This breakthrough will unlock a renewable plastic replacement that meets essential requirements for cost, scalability, and environmental impact.
The intellectual merit of this project focuses on the development of a viable pathway for creating melt-processable pellets from seaweed. The goal is to enable the conversion of these pellets using conventional machinery to produce flexible film packaging. The main technical challenge to overcome in achieving successful commercialization is that seaweed materials do not melt at suitable processing temperatures, as do traditional polymers. Consequently, the resulting material does not possess the necessary mechanical properties required for flexible packaging. To address this challenge, the team will explore the tempering of seaweed chemistry and associated materials with selected commercial compostable polymers. This approach aims to achieve comparable strain at break, tensile strength, and stiffness to conventional thin film packaging while ensuring home compostability. While previous research and applications have explored the use of seaweed for less economically viable film technologies, the unique contribution of this effort lies in combining varying seaweed chemistries and implementing them as a melt-processable seaweed material.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SYNTHETIC VECTOR DESIGNS, LLC
SBIR Phase I: Directed evolution of site-specific bacterial transposase genes to alter specificity and efficiency of insertion of large DNA segments into restorable gene fusions
Contact
4340 DUNCAN AVE STE 252
Saint Louis, MO 63110--1110
NSF Award
2234291 – SBIR Phase I
Award amount to date
$274,999
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to develop methods to facilitate the efficient, reproducible insertion of large DNA segments into stable locations on bacterial vectors, viral and non-viral shuttle vectors, and the chromosomes of prokaryotic and eukaryotic host cells comprising novel target sequences plus helper and donor vectors that could impact many areas of synthetic biology. Directed evolution experiments will be carried out to recover genes encoding bacterial transposase variants that have altered specificity or increased efficiency of transposition, compared to those recovered by products encoded by the wild-type transposase genes. Homologues of the bacterial target site will be used to recover genes encoding variant transposases that should function efficiently in eukaryotic cells. Modified helper and donor vectors will also be constructed with promoters and genes having optimized codon preferences to facilitate the efficient, direct generation of composite vectors harbored in eukaryotic cells, and eventually, the efficient, reproducible generation of cells harboring large DNA insertions at one or more specific stable sites within a host cell chromosome.
The proposed project will exploit the key properties of the bacterial Tn7 transposon system for much broader utilization in many aspects of systems biology. Genes encoding transposases and accessory proteins will be mutagenized to alter the specificity and enhance the efficiency of insertion events in both prokaryotic and eukaryotic cells. This platform could have advantages over other gene transfer approaches by allowing stable, precise insertion events without the subsequent remobilization or the creation of indels/rearrangements at the target site. The ability to move large segments of DNA in such a manner would benefit many fields of synthetic biology.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SYZYGY OPTICS LLC
STTR Phase I: Curved Volume Phase Holographic Gratings: Efficient and High-Resolution Hyperspectral Imaging
Contact
536 MEADOW RUN
Chapel Hill, NC 27517--8022
NSF Award
2233096 – STTR Phase I
Award amount to date
$275,000
Start / end date
07/15/2023 – 06/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Technology Transfer Phase I project will develop a completely new class of spectrometer, the spherical transmission grating spectrometer (STGS), which utilizes curved volume phase holographic (VPH) gratings coupled with a spherical mirror to deliver aberration-corrected spectral images over the full field of view. The market is projected to reach $35.8 billion by 2026, at an annual growth rate of 18.4%. End-users range from astronomy to agriculture, manufactures, and third-party integrators (e.g., drone companies). Current technologies are too costly or do not possess the size, weight, and power (SWAP) properties required for practical value delivery. Furthermore, in low light conditions or in applications that require aberration-free high-resolution images (e.g., defense-based imaging), current technologies on the market cannot meet customer requirements. This solution promises to solve these issues. Agriculture and defense are the two leading market applications and represent the primary entry points for this technology.
The intellectual merit of this project will enable a transformation in the spectroscopy and the hyperspectral imaging (HSI) market by enabling low-cost, superior image quality spectrographs. The product will be a novel spherical transmission grating spectrometer (STGS) for hyperspectral imaging. Preliminary STGS designs, invented in a collaboration with astronomers at the University of North Carolina Chapel Hill and Southern African Large Telescope employ a combination of a spherical mirror and a spherically-curved transmission grating to deliver fully aberration-corrected spectral images with no field distortion. Challenges to their production are the design, fabrication, and testing of this spherical volume phase holographic (VPH) grating. These spectrographs represent a new paradigm in optical spectrometer design, and the team has developed a suite of STGS designs that will allow them to build a new generation of distortion and aberration free spectrographs that are simple, small, and lightweight. The key objectives for this project are: 1) to develop a curved grating manufacturing processes to match design and market goals, 2) to design and fabricate a prototype testbed HSI for design validation and high-throughput quality testing, and 3) to create finalized optical designs for STGSs in the F/2 to F/2.5 range.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Solsona Enterprise LLC
STTR Phase I: Vertical Structure Thin Film Transistors for High Performance Displays and Internet of Things Devices
Contact
7088 TATLER RD.
San Diego, CA 92131--3924
NSF Award
2014979 – STTR Phase I
Award amount to date
$224,900
Start / end date
05/15/2020 – 06/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to improve the performance of flat panel displays of various form factors and sizes. One of the key subsystems of a flat panel display is a TFT (Thin Film Transistor) backplane that drives the pixels in the panel. There are increasing demands for improved resolution and frame rate in displays, posing significant challenges on the performance of the TFT backplane. The proposed STTR research will produce TFT devices that are several orders of magnitude faster using existing semiconductor materials. This technology will lead to more capable solutions for displays, printed electronics, and internet-of-things applications.
This Small Business Technology Transfer (STTR) Phase I project develops a novel Thin Film Transistor (TFT) design for displays and other electronics that require transistors. Conventional TFT transistors switch current laterally and are difficult to reduce below micron-level sizes. The proposed research will produce TFT transistors that switch current vertically. The path length across which the switching occurs is much shorter in the vertical devices and therefore the switching happens faster and can carry more current than conventional designs. This project develops a vertical TFT using amorphous indium gallium zinc oxide semiconductors. The project will advance the development of a prototype vertical TFT.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TAUMAT LLC
SBIR Phase I: Innovative Solid-State Phase Change Cooling to Supercharge Central Processing Unit (CPU) Performance
Contact
10010 PORTLAND PL
Silver Spring, MD 20901--2114
NSF Award
2322115 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project aims to establish a new approach to high-performance central processing unit (CPU) thermal management that focuses on the development and application of innovative solid-solid thermal energy storage (TES) materials and hardware. Increasingly, steady-state cooling solutions are unable to keep up with the required operating frequencies and resulting thermal loads of temperature-sensitive computing and electronic components. As a result, these components are throttled down to reduce heating. This results in the desired temperature reduction but inevitably leads to clock speed and performance reductions as well. The proposed project aims to challenge this existing tradeoff and produce CPU heat sinks that can maintain 3X computational performance ?sprints? with no added weight/volume nor electrical energy expenditure, in a scalable and easily deployable, drop-in form factor. Fueled by a global demand for high-performance computing, internet-of-things, and handheld electronics, the market for high-performance CPU coolers is rising with a market size of about $2.04 billion and a compound annual growth rate of 3.73-4.64% over the next decade. The target solid-solid TES heatsink is transferable to battery fast charging, system-on-chip devices, and the power electronic market.
The intellectual merit of this project resides in newly-identified thermal energy storage materials to shift the paradigm in CPU cooler design away from simply maximizing steady-state heat dissipation towards an optimized approach that combines high steady-state dissipation with high-capacity thermal storage. This Phase I project has three primary research objectives: i) develop analytical and numerical topology optimization approaches to identify ideal thermal energy storage material properties and composite heat transfer/capacity structures for CPU applications: ii) leverage data-driven shape memory alloy discovery using an artificial intelligence framework to identify and ultimately arc-melt new thermal energy storage materials that exhibit high-latent heat, high-conductivity, low hysteresis, and/or the ideal combination of material properties based on CPU requirements: and iii) design, fabricate, and test prototypes for model validation and concept demonstration. These technical efforts, combined with risk reduction and mitigation steps, and techno-economic and manufacturing analysis will enable leap-ahead improvements in an ever-expanding array of high-power, thermally limited applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TEMPRIAN ONCOLOGY, INC.
STTR Phase I: Monobenzone (MBEH) Supercarriers: Production and Melanoma Treatment
Contact
411 N OAK PARK AVE
Oak Park, IL 60302--2270
NSF Award
2327009 – STTR Phase I
Award amount to date
$275,000
Start / end date
12/01/2023 – 11/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project develops a novel cost-effective treatment for melanoma that allows treatment delivery both at home and in remote geographic locations. The importance of the project is reflected in the 100,000 individuals that are diagnosed with this devastating skin cancer annually as well as by 8,000 patients a year being lost to the disease. The proof of concept is a step towards the development of a novel therapy for the treatment of stage III and IV melanoma. The overarching goal is to develop surgically accurate drug delivery at both the tissue and cellular levels that will result in a tissue-level triggering of an immune response that heightens the impact of the drug. The solution should drastically decreased side effects when compared to competing treatment alternatives. The method allows for off-the-shelf delivery, giving patients living in remote locations access to state-of-the-art therapy. Annually, >$5.7 billion is spent on melanoma treatment in the US. Drugs targeting stage III and IV disease make up $1.5 billion (26%).
This Small Business Technology Transfer (STTR) project aims to demonstrate proof of concept for supercarriers that will treat stage III and IV melanomas. The application employs lauroyl-monobenzone to produce selective anti-melanoma action and effective immune activation, packaging the drug in biocompatible nanoscale liposomal particles for selective melanoma delivery. The design enhances efficacy while minimizing side effects by transporting the active ingredient directly to the tumor. Due to the selective uptake of nanoparticles by tumor cells rather than healthy tissues, and because supercarrier contents are released only when the nanoparticles enter the lysosomal/melanosomal compartment, the impact will be felt primarily, if not exclusively, by the tumor. Tyrosinase converts the prodrug into a quinone that haptenizes the melanosomal enzyme(s) present to generate neoantigens with increased visibility for T cells. The resulting direct and indirect melanoma cytotoxicity form the key to supercarrier treatment success. Low toxicity, combined with simple off-the-shelf delivery, enhance patient quality of life. As enhanced immune activity comes without patient-specific tailoring, the application allows for convenience and an attractive cost-to-quality ratio. Flexible, close-to-home drug delivery, few side effects, low cost, and enhanced life expectancy are expected to build the reputation of the drug, propelling the demand.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TENVOS INC.
SBIR Phase I: VoxCare: Artificial Intelligence-based Monitoring for Substance Use Indicators in Youth
Contact
3395 RIVERMONT ST
West Sacramento, CA 95691--5443
NSF Award
2335605 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 09/30/2024 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to reduce the $740B a year burden of substance use. Healthcare costs, crime, and lost productivity are only a fraction of the problem that has claimed over 100,000 lives in 2021 alone. The proposed innovation is a novel AI-based technology integrated into a mobile app that allows the assessment of drug use or alcohol intoxication based on voice signals. Substance and alcohol use disorders are prevalent across every stratum of our society. Not only are the users impacted, but the penumbra of individuals impacted includes every citizen in the US. Preventing early exposure to illicit drugs and alcohol lowers the likelihood of developing severe addiction later in life. By disrupting normal brain development, various substances increase the long-term negative effects on a child?s life. Given the skyrocketing rates of depression and anxiety among teenagers, the wide availability of highly potent synthetic substances, and the ease of access to drugs, parents feel ill-equipped to protect their children.
This Small Business Innovation Research Phase 1 project will help advance knowledge in several important areas, such as artificial intelligence capabilities, leveraging digital media platforms for data collection, synthetic audio data generation, and using the mix of temporal and spectral domains for audio analysis. Each area is an active research field, but the combination of all these areas into a product for analyzing voice to detect intoxication caused by various substances has not been previously attempted by academia or industry. The company?s technology relies on the unique impact that each substance use has on neuromotor function, as manifested by the bio-mechanical process of voice production. By comparing the voice signal against the speakers? baseline voice, the technology will flag abnormal deviations of acoustic features that are typically consistent with intoxication. The field of voice analysis integrates a range of features and signal characteristics to extract valuable insights from voice signals. The primary objectives are to develop and deploy this AI-based technology in ubiquitous devices such as mobile phones while ensuring its performance in real-life conditions and achieving soft real-time processing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TERRAGIA BIOFUEL INC
SBIR Phase I: Advanced multi-locus genome engineering to enable consolidated bioprocessing for the low-cost conversion of lignocellulose to hydrocarbon fuels and products
Contact
15 THAYER DRIVE
Hanover, NH 03755--4404
NSF Award
2112323 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to test an innovative new approach to generating industrially valuable microorganisms. If successful, the new approach will be demonstrated by improving the ability of an engineered bacterium to convert components of biomass into fuel. The benefit of that research will be to help develop a technology that can convert domestically-produced, non-food biomass into fuel at a low enough cost that it can become a significant part of America?s energy solution. The United States would realize multiple benefits from the production of such low-cost cellulosic biofuels. However, realization of this objective requires innovative new approaches that meaningfully decrease the cost of conversion.
This project seeks an innovative new approach to engineering bacterial phenotypes with an unknown genetic basis, while at the same time producing strains useful for a method of biomass conversion called Consolidated Bioprocessing (CBP). The technology will expand the complexity of phenotypes that can be developed in industrial microbes by non-directed /evolutionary methods by taking advantage of natural competence, which is the ability of some bacteria to take up DNA. The solution demonstrates the feasibility of a technique called Continuous Evolution with Multiplex Natural Transformation (CE-MuNT), in a program of selection for commercially valuable phenotypes that have a complex, uncharacterized genetic basis. By using massive and rapid genetic transfers that do not require human intervention, it may be possible to rapidly create a large set of genetically diverse mutants that can then be selected for the targeted characteristics. Importantly, the approach is not limited by the significant knowledge gaps that exist about the organism. The project will initiate studies aimed at catalytically converting biomass-derived ethanol to hydrocarbons that are suited to aviation and heavy-duty applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
THERMAL BATTERY CORPORATION
SBIR Phase I: Delivering Confidence and Reliability in Thermal Batteries for Utilities Using an Aggressively Cycled Test Loop for Pumps, Pipes, Joints and Valves
Contact
1 BROADWAY
Cambridge, MA 02142--1100
NSF Award
2342586 – SBIR Phase I
Award amount to date
$275,000
Start / end date
10/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is focused on developing an energy storage technology that stores electricity as heat and converts its back to electricity whenever needed using thermophotovoltaics (TPV). If successful, the innovation will help transition the United States (US) towards a fully renewable electrical grid. The company is developing one of the only battery technologies able to deliver a cost per unit energy (CPE) for energy storage that will enable the use of renewables by the electrical grid. The innovation will also reduce the production of carbon dioxide (CO2) during the production of electricity and may do the same for transportation and industrial processes. The solution will also support the US?s national defense by increasing the economic manufacturing competitiveness of the US and improving energy security, as well as enabling utility customers to benefit from significant cost savings.
The intellectual merit of this project is focused on the development of a thermal battery system that takes electricity from any source and converts it to extremely high-temperature sensible heat in inexpensive graphite blocks. The innovative feature is its ability to decouple power and energy, enabling any discharge duration between 1-100 hours. Currently, no other system can achieve such great and variable discharge levels at such low cost. The company will build two test rigs to test the pumps, pipes, joints, and valves, and then to test the thermophotovoltaics modules under aggressive thermal cycling conditions. The technical objectives are to: (1) set up the induction furnace system to prescreen materials and components; (2) determine which grades of graphite from large-scale suppliers can meet the specifications of future commercial demonstrations; (3) pre-screen approaches to sealing; (4) quantify the reaction strength of the bonding agent and determine how it can be used in products; and, (5) verify that the system installed seals sufficiently well so that future test loop work will not be delayed. The prototype?s hardware will be scaled-up and the critical components will be stress-tested. The company has already developed a fully-functioning, integrated system at a small scale, 1-10 kilowatt-hour-electric (kWh-e), that works as a proof-of-concept. The reliability of the full-scale hardware in the test loop must be demonstrated prior to building a 1 megawatt-hour-electric (MWh-e) scale demonstration. The company is developing one of the only battery technologies able to deliver a cost per unit energy (CPE) of <$25/kWh-e for energy storage which will enable the full penetration of renewables onto the electrical grid.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
THERMOCAP LABORATORIES INC
SBIR Phase I: High-Throughput Direct Ratiometric Calorimeter for Drug Discovery
Contact
2350 NW SAVIER ST UNIT 108
Portland, OR 97210--2788
NSF Award
2402322 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2024 – 02/28/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the production of the first high-throughput and low-cost Differential Scanning Calorimetry (DSC) instrument. DSC is an extremely powerful tool for drug discovery that has low adoption due to high costs and low throughput of only one sample every two hours. The power of DSC is the thermodynamic measurements, which do not require any prior specific knowledge of the molecules being studied and do not require any labels. By not requiring any specific knowledge, it is possible to screen a wider variety and a higher quantity of compounds in the search for new drug molecules. The instrument to be developed from this project will be capable of processing 24 to 96 samples every two hours, thereby making DSC-based drug discovery commercially viable. Innovations from this project will also reduce the cost of producing DSC instruments, making them widely accessible for research and educational purposes. An added benefit of the reduced costs is the potential also to be utilized as a teaching tool. The combination of unique drug discovery knowledge and low costs will serve to reduce the costs associated with discovering and analyzing potential new drug molecules.
This Small Business Innovation Research (SBIR) Phase I project comprises the research and development activities required to produce a high-throughput differential scanning calorimeter. A unique feature of the proposed instrument is the utilization of single-use, sterile sample cartridges that can hold 24 to 96 samples. These cartridges will enable high-throughput sample processing compared to currently available instruments. Current instruments use sensors and heaters that are permanently attached to the sample cells. This project will address the technical challenges associated with using non-permanently attached sensors and heaters to enable a sample cartridge that can be inserted and removed from the instrument. Activities of this project will identify optimal materials and components and determine the layout of sample cells to maximize the number of sample cells in each cartridge. These activities will minimize risks associated with producing a production-ready instrument and deliver maximum customer benefit.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TIAMI LLC
SBIR Phase I: Intelligent Repeaters for Pervasive Millimeter-Wave Wireless Broadband Connectivity
Contact
10041 WILD ORCHID WAY
Elk Grove, CA 95757--4345
NSF Award
2335455 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks to enable pervasive, next-generation, mobile broadband connectivity across the United States through the development of an intelligent wireless repeater. Equal access to high-speed broadband connectivity is integral to the economic security and competitiveness of the United States. However, widespread disparities in broadband access continue to persist, especially in underserved urban and rural areas. This project will transform the economics and complexity of delivering ultra-high throughput wireless connectivity over large areas. The associated total addressable market is expected to reach $660 million by 2027 at a compound annual growth rate of 59%. The successful development of the hardware and software solutions in this project will disrupt the telecommunications industry and pave the way for optimal usage of new high-frequency spectrum bands, thereby unlocking the potential of next-generation mobile broadband connectivity.
This Small Business Innovation Research (SBIR) Phase I project addresses the current shortcomings of fifth generation (5G) wireless networks that have failed to provide Gigabit-level data rates and sub-millisecond latency across wide areas. This failure is because millimeter-wave 5G networks at frequencies of 28 GHz and higher have very poor propagation range, and building a hyper-dense network of millimeter wave base stations for pervasive coverage is prohibitively expensive. Millimeter wave repeaters are an appealing solution to extend network coverage at a fraction of the cost of deploying new base stations, since they have a simpler software stack and do not require fiber backhaul. However, network operators have a strong aversion to deploying repeaters today since current repeaters have fixed transmission power and beam directions regardless of the actual traffic conditions on the macro network, which increases inter-cell interference and reduces spectral efficiency. The corresponding lack of pervasive millimeter wave 5G coverage exacerbates the digital divide in the U.S. and harms the national and economic security. This SBIR Phase I effort will design and prototype an intelligent 5G repeater that addresses these pain points.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TIWAZ TECHNOLOGIES, LLC
SBIR Phase I: Beyond thin-film optics: Resonant grating-based optical component technology
Contact
3010 PITKIN DR
Arlington, TX 76006--2044
NSF Award
2304394 – SBIR Phase I
Award amount to date
$274,883
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to simplify and significantly reduce the cost of optical component fabrication. Optical components, with well-known examples being mirrors, polarizers, and lenses, are essential building blocks in a host of civilian and military systems including imaging, telecommunications, and laser systems. Current optical component technology is a multi-billion-dollar industry and is based on multiple layers of films deposited in vacuum chambers. The proposed innovation realizes a new optical component class with the functionality of multi-film assemblies generated in a single layer with attendant savings in time and cost. The project focuses on the long-wave infrared spectral domain where traditional thin-film technology is impractical due to the extreme film thicknesses needed. The long-wave domain covers a region of atmospheric transparency essential for terrestrial imaging, medical and industrial laser technologies, and night-vision systems.
This innovation focuses on optical component fabrication that is based on gratings that are index-matched to a sublayer thereby avoiding localized, particle-type resonances. This attribute imbues the components with tolerance to parametric deviations essential for practical manufacturing. The new physics is based on lateral leaky Bloch modes and attendant lattice resonance. It is different from the interference-based physics of classic thin-film optics. Therefore, a new dimension in functionality with high levels of spectral diversity and control is brought into the optical component arena supporting many societally valuable applications. In Phase I, relevant fabrication processes will be developed to show the potential for scale-up to mass production. The effort delivers three main high performance component types (reflectors, filters, and polarizers) that meet stringent specifications in terms of efficiency and bandwidth.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TOP GRAIN TECHNOLOGIES, INC.
SBIR Phase I: Advanced Manufacturing of Oxide Dispersion-Strengthened Superalloys for High Temperature Creep and Hydrogen Environment Applications
Contact
4200 SAN JACINTO ST
Houston, TX 77004--4853
NSF Award
2335531 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research Phase I project is to advance the conversion of gas turbines for power generation to utilize sustainable hydrogen as a fuel. Although hydrogen offers zero exhaust emissions, it poses challenges due to its higher flame temperature and reactivity with alloys compared to natural gas. This project focuses on developing a high-temperature alloy system, fabricated through additive manufacturing, ensuring longevity and reliability in hydrogen combustion environments. Through scaling a patent-pending thermal treatment, the project aims to enhance the alloy's material properties for durable aftermarket parts like vanes, blades, shrouds, and panel segments. These components can surpass the properties of existing precision investment castings and are essential for converting industrial gas turbines to efficiently burn hydrogen, currently powering a significant portion of US combined heat and power and global electricity generation. The carbon abatement potential is substantial, with the conversion of one targeted segment capable of reducing over 1 GT of CO2 emissions. The innovation extends to manufacturing advanced, high-value components for aerospace jet engine repair and overhaul, presenting a potential Year 3 production revenue of $20 million and providing critical supply base resiliency for hard-to-source components in gas turbines.
This Small Business Innovation Research Phase I project aims to advance additively manufactured, high-temperature alloy research, focusing on applications in hydrogen combustion within industrial gas turbines. The project will fabricate mechanical and environmental test specimens using an alloy composition containing oxide dispersion-strengthening constituents designed specifically to withstand reactive hydrogen conditions. Testing will encompass critical properties like creep resistance, low cycle fatigue, and hydrogen embrittlement. A pivotal aspect involves post-processing the alloy through directional heat treatment and modifying the grain structure to enhance creep resistance, which is critical in the high-temperature operation of vane segments, shrouds, blades, and gas turbine components. Studies show superior properties compared to existing additively manufactured superalloys and precision investment cast equivalents. The project's objectives include optimizing the alloy, refining manufacturing conditions, and obtaining key performance data for service conditions. Preliminary design curve data will be established, facilitating the fabrication of components for hot-fire testing and retrofitting into real gas turbine engines. This initiative promises significant progress in high-temperature alloy capabilities, particularly for advancing hydrogen combustion technology in industrial gas turbines.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TOTAL ANALYSIS L.L.C.
SBIR Phase I: Combating Pathogens, Helios-1 Onsite Universal Detection
Contact
8314 CLOVERLAWN ST
Detroit, MI 48204--3268
NSF Award
2304483 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is protection against pathogen-related infections. Currently, detection tests for pathological agents are laborious, time-consuming, expensive, and require advanced technical expertise to conduct. The proposed portable, onsite pathogen detector will allow for fast, specific, sensitive, and cost-effective pathogen tests that can be conducted with minimal personnel training and equipment. The solution is intended to be used at healthcare centers, transport nodes, defense facilities, and any other site where the spread of infectious diseases is a possibility. This technology will benefit the population?s health and welfare, by facilitating the implementation of pathogen detection routines that reduce the risk of large-scale infections. Such infections disproportionally affect under-represented groups. The solution will also improve the national defense against bioterrorism, since the proposed technology could be as standard as a typical metal detector used in large, populated venues, on the battlefield protecting troops, or at airports to keep the traveling public safe. The nation?s economic competitiveness may also improve, since the proposed solution could mitigate and even avoid the economic consequences of a health crisis.
The proposed project seeks to prove that Matrix Assisted Ionization can be coupled with Ion-Mobility Spectrometry (MAI-IMS) for pathogen detection and identification. The recent pandemic outbreak has demonstrated the necessity of rapid, on-site, and accurate pathogen detection devices. The proposed method is to use the existing IMS technology and modify it to detect pathogens by fabricating a Matrix assisted ionization vault (Helios-1) that overcomes the biomolecule volatility restriction of all current ion mobility spectrometers. A crucial technical hurdle is finding the device's optimal ionization and operational environment. To overcome this challenge, the most similar conditions to mass spectrometry must be found, which will involve experimental tests to determine the adequate environmental conditions and the engineering modifications of the MAI extension chamber to adapt IMS for non-volatile biomolecule detection. Standardize organism sample conditions and protocols are also needed. This challenge represents a critical step to prevent variation caused by the extraction of the sampling procedure. This challenge will be tackled by testing different extraction procedures until they meet the criteria for satisfactory performance. Additionally, machine learning algorithms will be employed for pathogen recognition. All of the above will help prove the feasibility of the proposed MAI-IMS-based pathogen detection and identification platform.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TPL LLC
SBIR Phase I: Clean Iron and Nickel Powder Production for Steel Construction on the Meridiani Planum of Mars and Cathode Manufacture for Lithium-Ion Batteries on Earth
Contact
7025 ALDEN DR
West Bloomfield, MI 48324--2017
NSF Award
2233554 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a technology to explore the utility in the ubiquity of iron on both Earth and Mars. The ores of many metals are iron-rich, mixed materials, including those of 33+ metals critical for a sustainable future. However, high iron content is a nuisance for most established metal extractions. For example, iron, rare earth elements, and unextracted aluminum remain in the vast tailing ponds generated by aluminum feed processing. This project develops a better method for processing many mixed-material industrial wastes and ores. The method is called fast iron carbonylation and is expected to lower the cost of iron and nickel powders, add value by making better concentrates of rare earth elements and many other energy metals, and clean up metal processing and waste sites. This process will inexpensively and profitably produce metal feeds for battery manufacturing and enable the benefits of clean electric transport. The fast iron carbonylation-based steel-making hardware is rugged, simple-to-operate, and light weight.
This SBIR Phase I project develops and tests a reactor to carry out fast iron carbonylation. Iron and nickel carbonylation are reversible, exothermic gas/solid reactions. Carbonylation in state-of-the-art, industrial-scale reactors is significantly impeded such that, at large scales, achieving high per-unit volume reaction rates is challenging. The proposed fast iron carbonylation reactor seeks to drive the reversible reactions far from equilibrium to achieve net carbonyl production at least 10 times faster than state-of-the-art carbonylation. The project will run tests on relevant mixed-material metal ores and industrial wastes at scales much larger than are typical for benchtop experiments (~5 kg samples). These tests aim to extract close to 100% of the iron and nickel in the test samples and produce residues that can be readily processed to produce high value concentrates of rare earth elements and other critical metals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TREES ROI LLC
SBIR Phase I: CAS: Tree Root Quality Inspection System with Noninvasive Evaluation
Contact
25 ELDERBERRY LN
Hinesburg, VT 05461--3020
NSF Award
2333948 – SBIR Phase I
Award amount to date
$274,990
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project improves the quality, value, benefits, and life span of nursery stock trees, so they will grow and thrive in the landscape where people live. Trees, with their myriad benefits for human health, ecosystem services, and climate mitigation achieve their full potential when they thrive long term. Current methods fail to adequately address tree root quality. By modernizing root inspection, this technology will not only improve industry standards and boost economic competitiveness, but also promote environmental stewardship on a global scale. With this technology, arborists and growers may be able to identify above-ground tree root defects and take corrective action to promote good quality root systems that are needed for these important tree assets to grow to maturity.
This SBIR Phase I project focuses on the development of a 3-dimensional, non-destructive, ground penetrating radar (GPR) computed tomography (CT) system with cutting-edge software analytics to inspect and assess the quality of container-grown root systems in nursery stock trees. This innovation is based on the understanding that the GPR signals are generated by the large differentials between live tissues and the surrounding soil. The technology detects serious root system defects that could cause early tree mortality if not corrected before the tree is planted. The data will be collected with the help of an innovative apparatus designed to seamlessly capture 3D root data from container-grown trees using a commercial GPR system with a wireless antenna that works as a secondary layer around the container, emulating the precision of an X-ray CT scanner. A novel root quality classification model will inform the development of a root analysis software program to build an initial GPR dataset for the machine learning model and subsequently to adopt an active learning approach. Initial experiments will focus on a sufficiently large number of one or two species of trees.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TRESTLE OPTICS LLC
SBIR Phase I: Broadband focusing for non-invasive cell metabolomics
Contact
42 SCHUBERT CT
Irvine, CA 92617--4067
NSF Award
2221721 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is aimed toward advancing sustainable production of chemicals using synthetic biology. Here, single-cell microbes are engineered to produce valuable metabolites using enzymes rather than sourcing these chemicals from petroleum. Developing genetically engineered cell strains with high yield remains an ongoing effort due to the complexities in how genetic code leads to phenotype expression. This problem is addressed using a bottom-up approach to screen microbe populations at the single-cell level. The method deployed to identify metabolite content in individual cells is based on infrared (IR)-absorption spectroscopy which is label-free, quantitative, and non-destructive. Synthetic biology is poised to disrupt the chemical value-chain by providing an alternative to petroleum-based chemicals that is sustainable and carbon-neutral. Once a highly productive cell is identified it can be selectively propagated to create enriched cell lines. Innovations in optical microscopy are required to improve the performance of the cell screening instruments, which will allow high-resolution focusing across a broad spectral range. The upgraded platform will optimize yield more quickly, providing value by reducing the upfront cost to develop new industrial cell strains.
The proposed project emphasizes optical engineering to develop a microscope designed for high-resolution chemical imaging based on molecular vibrational IR-absorptions. This is achieved by deploying focusing elements that operate over a broad spectral range that extend standard optical microscopes to include mid-infrared light sources. The optical instrument will be used to evaluate chemical content in industrial microbe strains and develop enriched cell lines. These single-cell microbe populations are engineered to produce enzymes used to catalyze the synthesis of valuable metabolites. Yields from individual cells, however, are variable due to genetic mutations in the population. Therefore, a quantitative analytical tool based on IR-spectroscopy that can non-destructively identify highly productive cells for selective propagation is extremely desirable. This bottom-up approach for metabolomic cell screening and directed evolution is an innovation as it is label-free, non-invasive, and has strong chemical specificity. In this project, the team will study an industrial microalgae strain used as a low-cost feedstock supplement and identify cells rich in protein content to enhance the overall protein yield.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
UNINET LLC
SBIR Phase I: Software-Defined Networking and Resource Virtualization in Low Earth Orbit (LEO) Satellite Constellations
Contact
116 COURT ST
New Haven, CT 06511--6955
NSF Award
2304470 – SBIR Phase I
Award amount to date
$274,944
Start / end date
09/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the extension of state-of-the-art terrestrial 5G technologies to non-terrestrial satellite networks. Non-terrestrial networks (NTNs) are the ideal hosts for many commercial applications involving monitoring, reconnaissance, and remote sensing such as agricultural planting, remote factory operations, and industrial automation. These applications will demand significant computation and bandwidth resources from NTNs. Virtualization technologies like software-defined networking (SDN) and network slicing are key enablers for similar applications in terrestrial networks, but satellite networks pose a unique set of challenges to existing 5G technologies. NTNs have complex and highly dynamic topologies caused by both the predictable movement of satellites as well as unpredictable weather events interfering with satellite-to-ground links. Extending 5G algorithms to NTNs enables new applications and unlocks additional network capacity without launching any new satellites. 5G virtualization also simplifies access to satellite constellations. Customers can interact with multiple satellite networks via the same virtual network interface, eliminating the need to learn different interfaces for different constellations. This Phase I project will explore more efficient networking solutions that satellite network operators can use to supply the growing demand for satellite internet.
This SBIR Phase I project explores methods of extending SDN and virtual network slicing technologies into space given the challenges posed by NTN topologies. First, it proposes a "NextG" framework for non-terrestrial SDN using existing 5G technologies whose core orchestrator can create end-to-end slices for seamless communication over terrestrial and NTN. In SDN, one or multiple software entities called controllers are responsible for the control of the network. The number and locations of controllers in the network and how often these controllers communicate can be selected to balance latency in the NTN and the overhead costs from sending synchronization messages. This project explores the use of deep reinforcement learning algorithms to learn optimal controller placement and synchronization strategies. Second, network slices are independent virtual networks that share a common infrastructure of network resources. Offline algorithms are used to allocate network resources to slices based on the requests of the virtual network operator. Subsequently, online algorithms dynamically reprovision network resources in real-time depending on the slices' actual resource usages. The team will investigate integer programming techniques for virtual network embedding that scale to larger NTN topologies and deep reinforcement learning agents for online resource scaling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
UNSPACE LLC
SBIR Phase I: Resilient Gravitronic Communication System
Contact
269 BEACHWALK LN
Port Aransas, TX 78373--4821
NSF Award
2236806 – SBIR Phase I
Award amount to date
$272,050
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the need for the universal availability of communications, especially in places where traditional communication methods are compromised or unavailable. Global tension, vulnerability of communication satellites, an increase in the frequency of natural disasters, physical barriers, and human space exploration make resilient communications more important than ever. Since matter is practically invisible to gravitational waves (GWs), such waves can transmit information through a planet or turbulent atmosphere without requiring relay satellites. In the coming decade, components of a coherent gravitational wave communication system have the potential to address these challenges and deliver foundational technology for other advanced applications such as ground based orbital cleanup, planet and planetoid matter composition analysis, asteroid deflection, and wireless energy transfer systems to name a few.
This SBIR Phase I project proposes to build upon research that shows dynamic source mass configurations can change the local gravitational field in regimes detectable by current technology. By improving the gravitational field detector?s sensitivity, implementing fine grained control of local changes in the gravitational field, and comprehensively isolating the system from non-gravitational influences, an improved characterization of induced gravitational field changes may be developed. These advances could lead to improved research tools and methods that are a pathway to the development of future system configurations that generate coherent gravitational waves. This research is an essential step toward directly or indirectly transmitting and receiving modulated information by a resilient gravitational communication system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
United Semiconductors, LLC
SBIR Phase I: Universal Crystal Growth Capsule and Novel Wafer Dicing Tool for In-Space Manufacturing
Contact
10571 CALLE LEE
Los Alamitos, CA 90720--2572
NSF Award
2419346 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) project is in advanced semiconductor technologies that are of critical need for emerging autonomous systems, networked sensing technologies, artificial intelligence enabled systems, aerospace, and defense surveillance systems. In-Space manufacturing under microgravity conditions enable unique materials characteristics and advanced semiconductor device designs with significantly higher performances, thus providing the most appropriate platform for meeting the technological and market demands. A novel class of semiconductor based composite materials with unique characteristics for numerous large scale emerging applications including, magnetic sensing, thermoelectrics, photovoltaic power generation, quantum computing devices, etc. will be developed. The proposed manufacturing plans will benefit the US national defense and civilian industry. The In-Space manufacturing platform will boost the yield and reliability for high performance device technologies, meeting the demand of the multi-billion US$ market. Lessons learnt from this project will accelerate the space materials production with potentially higher profit margins for sold goods and attract private sector investments in space manufacturing business. This will help the US domestic industry to gain and/or maintain leadership in many critical technology sectors. There is a need for higher throughput, higher iteration in-space R&D and manufacturing to drive to meaningful advantages, and this project will enable an acceleration of such translational R&D in semiconductors and other key sectors. Additionally, Workforce Development (WFD) for training engineers and technicians in Space based manufacturing are in perfect alignment with the priorities of the ?CHIPS for America? Workforce Development plans.
This SBIR Phase I project proposes to create innovative component design and manufacturing approaches for developing two critical hardware necessary for In-space manufacturing and application of high purity semiconductor grade bulk crystals. A universal crystal growth capsule design will be designed and fabricated for leveraging microgravity conditions during crystal growth and providing high throughput of space grown materials. For processing high cost, low defect content premium space grown crystals, a novel wafer dicing tool for damage-free thin film fabrication directly from ingots will be developed. The universal capsule design will incorporate advanced high temperature fluid dynamics components that are necessary for maximizing the beneficial effects of microgravity on crystal growth. The innovative wafer dicing tool architecture leverages advanced optics fabrication technologies for creating the dicing tool. The Phase 1 project will demonstrate crystal growth of single-phase alloy and multi-phase composites of semiconductor-based materials. Fabrication of micron-scale thick wafers with millimeter scale cross-section for discrete semiconductor device from bulk crystals will be demonstrated.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VALCON LABS, INC.
STTR Phase I: Self-healing Power Electronics for Urban Air Mobility Applications
Contact
1761 BUTANO DR
Milpitas, CA 95035--7006
NSF Award
2233521 – SBIR Phase I
Award amount to date
$274,944
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to increase safety and reduce weight and redundancies for many vehicular systems and electronic devices. This project will also enhance autonomous systems integration in terms of diagnostics and enable reconfiguration for a variety of safety-critical applications. The proposed self-healing, fault-tolerant, power electronics have a large market beyond Urban Air Mobility (UAM) applications and can be implemented in a wide range of markets from transportation, to space/aerospace, biomedical devices, and microgrids. The ability of power electronics to self-diagnose faults, engage redundancy, reconfigure, and maintain operation will be fundamental in such safety-critical applications. This project will initially be applied to the safest and most sustainable Urban Air Mobility vehicles of the future offering best-in-class user experiences that can drastically improve the lives of U.S. citizens by reducing travel time with improved safety. Potential applications and use cases include on-demand air taxis, airport shuttles, personal air vehicles, last-mile delivery, air ambulance, military applications, and rescue missions.
The goal of the proposed effort is to create self-healing, high-power-density, reconfigurable, and modular power electronic converters (dc/ac inverters, dc/dc converters, and ac/dc battery chargers) and architectures for Urban Air Mobility (UAM) applications. The main technical objective of this project is to improve fault tolerance in the event of battery module or motor failure in the presence of several other healthy batteries and propulsion motors. The second objective is to explore machine learning techniques in dc/ac inverter and ac/dc charger applications. The third and final objective for this project is to study the impact of the proposed self-healing modular power electronics architecture on battery state-of-charge, life, and propulsion system performance in a safety-critical UAM application. Reliability models that consider healthy and various reconfigured system architectures will be established.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VAYUH INC
SBIR Phase I: Subseasonal Forecasting and Climate Risk Analytics Combining Physics and AI
Contact
465 40TH ST
Oakland, CA 94609--2586
NSF Award
2335210 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project lies in the development of a weather forecasting and climate prediction tool for subseasonal forecasting, extreme weather events, and long-term climatological changes. The proposed technology is expected to impact a significant number of industries, including agriculture, insurance, logistics/supply chains, and the public sector, with an initial focus and market entry in the energy sector. This market is financed by large banks, carries large insurance policies that are priced based on risk, and needs to allocate resources in both the short and long term to meet customer needs and prevent service interruptions. Without these forecasting capabilities, there is a risk of drastic economic and societal costs. For example, the 2022 Pacific Northwest heat wave resulted in $8.9 billion in damages and cost the lives of 1,400 people. With 4 weeks of advanced notice, energy companies could have adequately prepared, saving lives and minimizing the damage to physical assets. The suboptimal management of weather events costs the US an average of 839 lives and $161 B/year for the last five years (cumulative >$750B), a 2.5x increase from the previous five years.
This Small Business Innovation Research (SBIR) Phase I project aims to establish the
feasibility of utilizing physics-informed machine learning to create probabilistic models of crucial climatological parameters and extreme weather events. A proof-of-concept demonstration
focused on a single forecast variable, temperature, capable of predicting temperature anomalies 2-4 weeks in advance with 30-50% higher accuracy than the leading physics-based forecast for North America. The climate prediction models operate by using unpublished, state-of-the-art physics-informed machine learning methods and data distillation to provide high-resolution subseasonal forecasts. This SBIR project aims to (1) increase the accuracy of the temperature predictions using cutting-edge transformer networks and AI-foundation models, (2) expand predictive capabilities to extreme weather such as severe convective storms, (3) and enhance the robustness of the product by leveraging improved Bayesian modeling to capture the uncertainty of forecasts.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VERPOND, INC.
SBIR Phase I: Proof -Of-Concept for Large-Scale and Low-Cost Biomass Production Using an Innovative Open Aquatic Algae Cultivation System (OAACS)
Contact
7904 VISTA GUYABA
Carlsbad, CA 92009--6977
NSF Award
2213114 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to establish the proof-of-concept of using an innovative open aquatic algae cultivation system (OAACS) to overcome scale and cost constraints of current large-scale algal biomass production systems like raceway ponds. Drop-in biofuels derived from OAACS? biomass have a projected minimum fuel selling price of $2.53/gasoline gallon equivalent, which is competitive with fossil fuels, and have potential production scales that exceed current global fossil fuel usage. Successful commercialization of OAACS can lead to new sustainable energy sources, significant displacement of fossil fuel use, and concomitant reductions in the future environmental and societal impacts of global climate change. If successful, OAACS can also pave the way for sustainable, competitive, and meaningfully large-scale production of other bioproducts like fertilizers and high protein feeds.
The proposed project aims to fabricate robust liners for OAACS using an innovative forced assembly co-extrusion and two-dimensional multiplication technique and then demonstrate their performance in OAACS scale-down laboratory photobioreactors. The minimum success criterion is production of liners that support sustained algal aerial yields >15 g ash free dry weight/m2/day for weeks or months without the need for liner cleaning or CO2 supplementation. This will establish feasibility that OAACS can meet production scale- and cost-targets. Tasks include: 1. Fabrication and physical characterization of base case liners using previously demonstrated techniques and then extending results to liners with pore size gradients and surface modified nanofibers; 2. Demonstrating high dissolved inorganic carbon transfer rates through the liners; and 3. Demonstrating robust performance of the liners during continuous culturing in laboratory photobioreactors.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VIADUCT TECHNOLOGIES LLC
STTR Phase I: Microwave-Enhanced Modular Ammonia Synthesis
Contact
720 MCKINLEY AVE
Morgantown, WV 26505--5722
NSF Award
2335104 – STTR Phase I
Award amount to date
$275,000
Start / end date
03/15/2024 – 11/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project lies in its exploration of Microwave Enhanced Ammonia Synthesis. Microwave research holds the promise of disruptive innovation and enables opportunities for substantial carbon emission reductions through reduced energy requirements, minimal direct emissions, and increased process selectivity. Applying microwave energy to chemical processes may transform how chemical reactions occur. This project targets the production of ammonia, which is the second most-produced chemical in the world. Ammonia is used as a fertilizer but also as a carbon-neutral liquid fuel; it allows power generation without carbon dioxide (CO2) emissions, making it crucial for sustainable energy. As a hydrogen carrier, ammonia?s role in hydrogen-powered systems is expected to increase with decarbonization efforts. Microwave-enhanced ammonia synthesis can transform the commercial landscape by meeting the increasing demand for ammonia, opening new market opportunities, and potentially increasing profitability.
This STTR Phase I project will address the Haber-Bosch process, which has been the standard method to produce ammonia in bulk for over a century. However, this process functions at high pressures and temperatures and requires a constant supply of energy, which equates to higher operational costs and increased emissions of CO2. Microwaves offer instantaneous, selective, and volumetric heating via interaction with electromagnetic radiation that targets the active sites, inducing electron transfer on the surface of a heterogeneous catalyst. This results in a fundamentally different reaction mechanism than conventional thermal heating, conductive, or convective heating. The goal of the Phase-1 project will be to directly test the feasibility of a specific microwave frequency, design, model, and test the optimization of an ammonia-specific microwave-enhanced applicator cavity that implements high flow rates, electric-field uniformity, catalyst temperature uniformity with high electrical efficiency. The research will involve electromagnetic numerical analysis, laboratory catalytic activity experiments, determining frequency effects, and the continued development of microwave-sensitive catalyst and catalyst support material. The anticipated technical results include the development of a more efficient, renewably powered, cost-effective method for ammonia synthesis, contributing to the decarbonization efforts of the energy sector.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VICTORY OVER CARBON, INC.
SBIR Phase I: CAS: A Novel Approach for Achieving Scale in Direct Air Carbon Capture
Contact
8 THE GREEN
Dover, DE 19901--3618
NSF Award
2322355 – SBIR Phase I
Award amount to date
$272,488
Start / end date
09/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in potentially contributing to the creation of a viable gigaton-scale Direct Air CO2 (carbon dioxide) Capture (DAC) technology. The technology could be a key pillar in preventing the worst effects of climate change. For over a century, humanity has emitted billions of tons of CO2 into the atmosphere each year. As more CO2 has accumulated in the atmosphere trapping the sun?s rays, Earth?s temperature has continued to rise. According to the Bipartisan Policy Center, gigaton-scale DAC stands to support the creation of a trillion-dollar industry in the United States and underpin the development of 3 million jobs.
This project is based on a novel DAC design addressing two key hurdles to achieving the scale needed to effectively offset CO2-caused climate change: cost to build infrastructure and energy to run processes. The system injects carbon capture fluid with a monoethanolamine (MEA) spray and removes that spray with an exhaust particle separating centrifuge. Through this hollow design, it not only saves on building costs, but may be poised to save on ongoing energy costs. Energy cost in a carbon capture contactor is a function of pressure drop or drag. The company's hypothesis is that a centrifuge is significantly more aerodynamic than the honeycomb-like filling currently used in contactors. The energy savings can translate into a system with significantly lower pressure drop and, therefore, lower ongoing energy costs to run. The program is organized into research objectives that investigate each area of technical risk. The first objective is calculating the optimal fluid particle size for capturing carbon dioxide from the air and optimizing the MEA operating range within the proposed system through Computational Fluid Dynamics (CFD) and lab testing. The second objective is determining the relationship between the fan and centrifuge through physical prototyping. The third objective is designing the facility shape itself though a mix of CFD and physical prototyping.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
VUEMEN, INC.
STTR Phase I: Innovating Micro-Light Emitting Diode (LED) Manufacturing with Novel Quantum Dot Micro-Patterning Technology
Contact
4712 48TH AVE NE
Seattle, WA 98105--3826
NSF Award
2335283 – STTR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase I project focusses on chip manufacturing to create micro-Light Emitting Diodes (LEDs). Micro-LEDs are semiconductor chips devices that emit light when an electric current passes through them. Micro-LEDs will benefit virtual- and augmented-reality (VR/AR) technologies. VR/AR are immersive technologies that have revolutionized the way we interact with digital information and the physical world. VR/AR displays are in dire need of innovative optical technologies to achieve widespread availability and accessibility across various platforms and locations. Applications where the displays are closer to the eyes are very expensive due to the need for high resolution images with sufficient brightness in a compact form. Micro-LED displays are a leading solution, but current chip manufacturing is low-yield and cost prohibitive for consumer-grade devices. This project will provide an innovative process to overcome many chip manufacturing obstacles through the use of micro-patterned quantum-dot (QD) color converters. The process is simpler, significantly cheaper, and compatible with standard semiconductor manufacturing already employed by industry.
This Small Business Technology Transfer (STTR) Phase I project will investigate the use of micro-patterned QD color converters to mitigate the need for pick-and-place assembly of red, green, and blue micro-LEDs. The current state of the art, a pick-and-place method, has severe limitations and insufficient yield. The goal is picking and placing millions of sub-pixels from epitaxial wafers with nearly zero defects. This problem is a top contributor to the overall cost for micro-LEDs today. This technology will take a different approach to achieve full color with high resolution. It will use color converters to reduce the number of steps by orders of magnitude, through only one lift-off process. For VR, the display resolution must be >1000 pixels-per-inch, which can be challenging to achieve via standard approaches. For AR, the requirements are even higher. The new process will achieve extremely high resolution and will be suitable for a wide range of color conversion materials, including most common QDs. The technology also has the essential benefit that unused QDs can be recycled and reused. The outcome from this STTR Phase I project will be a prototype demonstrating the viability of the method to produce high-resolution QD patterns on a static backplane.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WALIA, RAMPYARI
SBIR Phase I: Endogenously secreted bispecific natural killer cell engagers (BIKEs) for therapy of solid tumors
Contact
1453 NORTH CUYAMACA ST
El Cajon, CA 92020--1508
NSF Award
2322959 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project provides a novel, intramuscular gene delivery platform that supports sustained expression of any therapeutic protein, a capability yet to be commercially realized. The ability to provide sustained expression and endogenous secretion of bispecific natural killer cell engager (BiKE) therapeutics is expected to be paradigm shifting by providing a solution that bypasses current immunotherapy treatments for solid tumors. This approach, which is less invasive than the current state-of-the art, could eliminate the need for continuous/frequent repeated infusions of therapeutics and would circumvent the need for hospitalization during administration. The approach has a lower price point, potentially reducing the cost of therapy by tens to hundreds of thousands of dollars compared to other immunotherapies, and is amenable to low resource settings, significantly increasing the availability of treatment. The proof-of-concept therapeutic will target hepatocellular carcinoma, a solid tumor that accounts for 90% of liver cancers. The platform has broad applications, supporting delivery of any gene therapy application (e.g., monogenic disease) that can benefit from systemic expression of a secreted protein, including bi-specific antibody T cell engagers, therapeutic antibodies, and vaccine candidates (e.g., endogenous therapeutic antibody production, delivery of DNA vaccines, and expression of therapeutic proteins to treat monogenic rare diseases). Anticipated impacts of the platform include improved treatment efficacy and improved patient quality of life.
This project seeks to advance the development of a safe, efficient intramuscular gene delivery system for redosable gene delivery as well as the demonstration of the platform?s ability to express endogenously secreted bispecific natural killer cell engagers (BIKEs) in vivo for treatment of hepatocellular carcinoma (HCC), a solid tumor. To date, gene therapy approaches to cancer treatment have been costly, labor intensive, and limited in efficacy. This platform is expected to enhance gene delivery by over 1,000-fold compared to the injection of naked DNA and to enable efficient secretion of the gene product into the blood stream, thereby allowing for systemic expression. Specific aims are to establish a cell expression system for production, purification, and functional validation of the recombinant BiKE in vitro and to make bioluminescent hepatoma cell lines transduced with a commercialized lentivirus co-expressing RedFLuc and secreted GLuc for more sensitive detection of tumor survival. The project will also validate the efficacy of the BiKE expression construct in a humanized, orthotopic hepatocellular carcinoma (HCC) mouse model. Proof of concept will be established with the demonstration of sustained systemic expression of the secretable BiKE for ? 1 month at serum levels of ?100-500 ng/ml, as evaluated by enzyme-linked immunosorbent assay (ELISA) assays at days 3-60 post-intramuscular delivery.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WATER ILLUMINATION INC
SBIR Phase I: A Tunable Deep Ultraviolet (UV)-based Polyfluoroalkyl Substance (PFAS) Destruction Technology for Water Treatment
Contact
240 DESERT BLOOM
Irvine, CA 92618--8872
NSF Award
2335229 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project addresses the global contamination issues of per- and poly-fluoroalkyl substances (PFAS) ? also known as ?forever chemicals? ? in drinking water resources. The technology aims to develop a proof-of-concept, cost-effective technology that destroys PFAS chemicals even at very low levels and converts them to non-toxic. benign products in an ambient environment. Ultimately, the project team aims to provide improved water sustainability and safeguard public health. The project is aligned with the American Innovation and Competitiveness Act by advancing of the health and welfare of the American public. Initial demonstration of these impacts is expected to be felt in the water-scarce and economically fast-growing inland southern California region for both centralized and decentralized water treatment.
This effort focusses on the development of a highly efficient and cost-effective photochemical treatment system for the destruction of PFAS in drinking water resources. Using a novel tunable deep ultraviolet light (a.k.a. vacuum ultraviolet or VUV), the technology aims to achieve nearly complete destruction of PFAS without generating secondary waste streams or toxic byproducts in drinking water. VUV light is one of the most accessible and efficient water ionization photon sources because it takes advantage of abundant water molecules as photon sensitizers, can be readily generated from common UV lamps, and is easy to control and operate. Tuning this light source in conjunction with other benign chemicals creates a highly reactive environment for efficient destruction of PFAS, converting waterborne PFAS into non-toxic fluoride. The effort will involve combination of chemical kinetics investigation, advanced chemical analysis, and technology scale-up in collaboration with potential customers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WAVERLEY CREATIONS, INC.
SBIR Phase I: The Resilience Gym
Contact
3120 WAVERLEY ST
Palo Alto, CA 94306--2901
NSF Award
2322376 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 08/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the creation of a "Resilience Gym", where mid-career, college-educated employees can proactively develop their emotional health in the same way they do their physical health at a regular gym. The current pandemic and mental health crisis have affected society deeply. In a 2021 survey, McKinsey found that 85% of frontline employees and managers do not find meaning at work. The US Bureau of Labor Statistics reported 4.3 million people, or 2.9% of the entire workforce, quit their jobs in August 2021. These statistics demonstrate the urgent need to address the issue of workplace dissatisfaction and support individuals in finding meaning and purpose in their lives. Since 2017, the team has successfully taught over 150 adult students to achieve their potential by studying behavioral science research and applying it to their lives. Over 50% of these students, despite having accomplished careers, are dissatisfied with their lives and seek more meaning. The team has found that adopting an empowering mindset is the most effective resilient action for these students to achieve more and find deeper meaning in life. The Resilience Gym uses technology to provide a scalable solution to improve the emotional health and prosperity of working adults.
The team's innovation is a mobile and web app subscription service that delivers a step-by-step Resilience Gym process and guides users to adopt new, empowering mindsets. The product is based on decades of behavioral science research and uses virtual reality, artificial intelligence and mobile nudges to provide a scalable solution that is personalized the individual user. Based on real-time progress, users may adopt new mindsets. The team will also incorporate neuroscience research to enrich the solution. To develop the design, the team uses the 5-step Stanford d.school design thinking approach (empathize, define, ideate, prototype, and test) for which the team has deep expertise. The approach is complimented with the agile methodology to have short milestones, scrum meetings, and backlog tracking to ensure new learnings can be adapted from users and delivered on schedule and within the planned budget. Combining the expertise of technology startups and university researchers, the team develops scientifically driven products that achieve both significant impact and commercial success.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WEEL AUTONOMY INC.
SBIR Phase I: Developing a safer electric bicycle through a pedal-by-wire drivetrain, balance assist, and artificial intelligence
Contact
920 S HOLGATE ST STE 106
Seattle, WA 98134--1623
NSF Award
2335514 – SBIR Phase I
Award amount to date
$275,000
Start / end date
12/15/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project creates transformative electric bicycles, redefining urban mobility and enhancing environmental sustainability. Modern urban environments grapple with congested roads, car exhaust emissions, and pressing concerns about cyclist safety. This project introduces an electric bicycle equipped with innovative steering assistance and an all-electronic drivetrain. This design promises enhanced safety, user-friendliness, and versatility. Such a bicycle caters to a wide range of users, from children to seniors, especially those who might find cycling intimidating or challenging. The bicycle's advanced steering not only aids in maneuvering but also helps maintain balance. By electronically managing both braking and acceleration, the bicycle incorporates features of traction control, anti-lock brakes, and safeguards against over-the-handlebar crashes. These innovations are poised to decrease bicycling accidents, promote healthier lifestyles, mitigate environmental impacts, and stimulate domestic manufacturing. The end goal is a society where cycling is not just a sport or hobby, but a safer, greener mode of transport popular in daily life.
This project sets forth an innovative approach: blending robotics-inspired sensing, actuation, and control to engineer a revolutionary electric bicycle for daily use. At its core, the bicycle incorporates an electric motor in each wheel, a steering motor to control balance, and a pedal generator to capture the rider's exerted energy. The completely electric drivetrain provides meticulous control over braking and acceleration, improving safety with traction control and anti-lock brakes. An active steering mechanism, augmented by balance sensors, helps the rider balance, a particular concern for older users. The primary technical objectives of this research are to develop a balance assist system that complements human riders, a user-friendly interface for the pedal generator, and a robust electronic drivetrain. Through comprehensive simulations, bench tests, and real-world bicycle prototype testing, the project seeks to validate the transformative potential and technical feasibility of a software-defined bicycle.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WINDSCAPEAI LLC
SBIR Phase I: Proximate Wind Forecasts: A New Machine Learning Approach to Increasing Wind Energy Production
Contact
1718 STUART ST
Berkeley, CA 94703--2124
NSF Award
2309367 – SBIR Phase I
Award amount to date
$274,330
Start / end date
07/15/2023 – 06/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project will be to demonstrate the potential to increase (by 2%) wind-energy production from existing wind farms at very low cost. Combining networked, air-pressure sensors distributed on the landscape with artificial intelligence/machine learning (AI/ML), the technology will empower wind farm operators with advance alerts of oncoming winds and gusts to preemptively adjust settings like blade pitch and turbine yaw. These adjustments will result in more wind energy production and less turbine damage. This technology will significantly increase energy revenues and decrease costs. In 2022, US wind farms produced 380 terawatt hours (TWh) of energy. If serving just half of existing plants, this technology could yield an additional 3.8 TWh of renewable energy and over $150 million to US wind energy sales annually. In the competitive wind industry, these revenues can greatly increase operating margins and help accelerate the growth of the industry and clean energy jobs. Using government emissions figures, this deployment would also avert 2.4 gigatons of carbon dioxide (GTCO2) over 20 years. This wind alert technology could also benefit solar tracker safety and increase safety at aerial vehicle ports and lift-crane operations.
This Small Business Innovation Research (SBIR) Phase I project will show how wind can be measured and predicted 10?600 seconds in the future by combining a new sensor modality ? distributed pressure sensors ? with new machine learning (ML) models. Pressure sensors are far cheaper than wind sensors (e.g., Doppler LIDAR), but processing data from pressure sensors into predictions of the wind is complex. It is impossible to hand-code statistical models to predict turbine-height wind from ground-level pressure measurements. Instead, one may rely on learned ML models to make these predictions. Previous studies have used ML to model weather on regional or global scales, but this project is the first to create models for the much smaller and more demanding scales applicable to wind farm operation and to optimize for metrics important to wind farm operators. Because ML models have not yet been developed directly for combined pressure and wind data at this spatial and temporal scale, this project will combine advances in attention-based models (like Transformers) with advances in models that respect physical priors (like Hamiltonian Neural Networks) and will lead to a new form of sensing which will be far more accurate than was previously possible at this price point.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WINDWARD ENGINEERING, L.C.
SBIR Phase I: Development of an ultra-low-cost distributed wind turbine
Contact
10768 S COVERED BRIDGE CYN
Spanish Fork, UT 84660--9207
NSF Award
2225406 – SBIR Phase I
Award amount to date
$272,019
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to address the declining U.S. distributed wind turbine (DWT) market and support the transition to renewable energy sources. The DWT market has experienced a decline since 2012, mostly due to low reliability and high levelized cost of energy. However, the deployment of DWTs is crucial to meet ambitious green energy goals set by utilities and governmental agencies. This project addresses these challenges by increasing the ease of manufacturing and using readily available materials. The project will also improve an ultra-efficient load path that yields a uniquely low-cost and low-mass structure. Additionally, the proposed design achieves a larger rotor-swept-area and increases overall power extraction efficiency, making the wind turbine more efficient, lighter, and inexpensive compared to typical horizontal-axis and vertical-axis wind turbines. The value proposition for consumers is a cost savings of approximately 40% or more with respect to DWT competitors.
This SBIR Phase I project proposes to develop a new wind power technology and provide a proof-of-concept for its viability. The project team includes experts in structural dynamics, control system design, turbine design, computer-aided engineering, power electronics and power transfer, and prototype and certification testing. In Phase I, a complete full-scale design of the DWT will be created, including detailed aeroelastic modeling, control development, and structural evaluation of the components. The research pillar of Phase I involves the creation of a rigorous aero-servo-elastic model, a detailed 3D solid model, and finite element analyses of the key components. The control system will be developed based on analytical analyses, and the team will work toward proper control specifications and constraints to be met by the dynamic system. The anticipated technical results include a refined estimate of the power coefficient, an optimized strategy for independent blade control and load reduction, improved design driving load values for the key components, decreased potential for aero-elastic instabilities and resonances, and the improved refined levelized costs of energy estimates.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WORD OF MOUTH TECHNOLOGIES INC.
SBIR Phase I: A language learning app based on sound and mouth movements
Contact
3960 SPENCER ST
Las Vegas, NV 89119--5201
NSF Award
2323040 – SBIR Phase I
Award amount to date
$274,660
Start / end date
10/01/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is advancing new language learning by incorporating facial and lip recognition along with sound analysis. This visual aspect of creating sounds is vital for mastering pronunciation, one of the significant hurdles of learning a foreign language and even improving a native language. Current language learning methods often fall short in helping learners achieve speaking proficiency and fail to provide real-life language usage experiences. This language learning platform aims to change this by addressing the growing need for multi-language proficiency in workplaces and academic settings, providing an effective and engaging language learning experience.
Current language learning methods and apps often fail to develop speaking and writing proficiency, focusing instead on memorization and standardized tests. This language trainer addresses this gap by offering insights into the science of speech production. By combining visual cues of oral shapes with auditory input, learners can master pronunciation, a significant challenge in language acquisition. This research will include obtaining near-perfect voice files for machine learning model training, signal processing of the voice and video files, development and comparison of machine learning models, data visualization development, incorporation into the mobile test suite, and preliminary testing. The machine learning algorithms will use the insights extracted from students' voice data to provide learners with highly targeted, fine-tuned activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
WUI-GO, LLC
SBIR Phase I: Testing computational feasibility and effectiveness of real time traffic nearcast for wildfire evacuation at the wildland urban interface
Contact
16192 COASTAL HIGHWAY
Lewes, DE 19958--3608
NSF Award
2322210 – SBIR Phase I
Award amount to date
$274,963
Start / end date
12/15/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to reduce the time for residents to evacuate to safe destinations by providing personalized evacuation guidance, resulting in lower risk to life and smoother government operations during a wildfire. Wildfires are an increasingly prevalent disaster; 50 million U.S. homes are currently in the Wildland-Urban Interface (WUI) areas. This project aims to empower residents in WUI communities by developing services that provide real-time information and personalized evacuation guidance during wildfires. Such services also supplement the actions of emergency response agencies that are often overloaded during wildfires due to resource and workforce constraints. The lessons learned through this project can be applied to other natural or man-made disasters, benefiting many more U.S. citizens. This technology will create highly skilled jobs and increase partnerships between academia, industry, government, and wildland-urban interface communities.
This technology innovation searches for the best evacuation strategies on digital replicates of the Wildland Urban Interface (WUI) using real-time traffic nearcast simulations that are dynamic and adaptive. These strategies are then be provided to evacuees as real-time, individualized routing guidance to safe destinations. The technology will also provide communications abilities, situational awareness, and an optimization platform for emergency response agencies. The project adopts the latest digital twin (DT) technology to revolutionize static planning methods and evacuation plan information distributed in leaflets. Specifically, for wildfire evacuation, the DT framework involves versatile simulations of the fire, communications, and traffic flow; Is designed to incorporate infrastructural parameters such as the road network, environmental parameters, as well as behavioral parameters of both the evacuees and the emergency managing agencies. The technical scope of this project focuses on the development and demonstration of a real-time solution based on DT simulation technology that improves a series of emergency evacuation metrics, including the total evacuation times, fire exposure times, and traffic congestion. Numerical validation against observed data and computational speed testing will be carried out to quantify the effectiveness and computational efficiency in order to build a baseline understanding of the performance of the solution, and subsequently establish confidence in real-life implementation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
X-SIGHT INCORPORATED
SBIR Phase I: Electrostatic Design for Cold-Cathode, Miniature X-ray Sources
Contact
492B CAMBRIDGE ST
Cambridge, MA 02141--1113
NSF Award
2322146 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 04/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is improved access to 3D x-ray imaging in everyday life. Currently 3D x-ray imaging is used for applications where it is absolutely necessary to non-destructively image an object. One example is in healthcare, known as computed tomography, where imaging is performed 250,000 times per day in the US saving countless lives by enabling doctors to quickly identify and treat disease such as stroke, heart attack, and cancer. Airports are other locations where computed tomography is heavily used to quickly inspect millions of bags per day to catch threats that were once unable to be seen through conventional x-ray systems. The systems capable of 3D x-ray imaging for the applications mentioned above are large, expensive and immobile which prevent their use in more applications. This project enables a new architecture for 3D x-ray imaging which promises to make systems less expensive, smaller and more compact, require less power and demonstrate higher performance. This new architecture will enable access to 3D x-ray imaging for new applications by making it more affordable and available where and when it is needed, outside of key infrastructure locations like hospitals and airports.
This Small Business Innovation Research (SBIR) Phase I project is the first step in developing the most critical component to a new 3D x-ray imaging architecture: a miniature, high-performance, and inexpensive x-ray source. Modern 3D x-ray imaging systems are large, expensive and immobile due to the method of generating 3D images. A single x-ray source and detector arc pair are rotated at high speeds to generate 2D images at different angles which are used to reconstruct a 3D model. Modern x-ray sources and detectors are very bulky, weighing over 100 pounds each, and necessitate substantial structural reinforcement, resulting in systems that weigh over 1000 pounds. The proposed new architecture uses a stationary ring of x-ray sources and detectors. The x-ray sources are electrically turned on and off mimicking the rotation of modern 3D x-ray imaging systems without spinning, resulting in a system that is inexpensive and smaller, and uses lower power while demonstrating higher performance. For these aspirations to be realized, a miniature x-ray source that is smaller, high-performance and inexpensive must be developed. This project will take the first steps to characterize such an x-ray source by measuring key metrics such as the performance, resolution and reliability. The design will be iterated through simulations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
XHEME INC.
STTR Phase I: A Completely Non-Toxic Blood Bag That Keeps Blood Healthier, Longer
Contact
149 WISWALL RD
Newton Center, MA 02459--3530
NSF Award
2335363 – STTR Phase I
Award amount to date
$274,987
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
Errata
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Abstract
This Small Business Technology Transfer (STTR) Phase I project is to replace a 50+-year-old technology that uses toxic blood bags with a completely non-toxic blood bag that keeps blood healthier and longer. With the European Union (EU) banning the toxic plasticizer in the current polyvinyl chloride (PVC) blood bags and the disposal of PVC products releasing toxic, chlorine-based chemicals that build up in the water, air, and food chain, this is an urgent need. This technology replaces both PVC and the toxic plasticizer in addition to preventing a short supply of blood. The solution has the potential to save millions of lives yearly while avoiding waste by storing blood longer. The technology can seamlessly integrate into film manufacturing and blood storage infrastructure. The new technology can be expanded into non-toxic dialysis bags, intravenous (IV) bags, medical tubing, and bioprocessing industry applications. The technology's commercial potential in the global blood bag industry is expected to reach about $845 million by 2033.
This STTR Phase I project applies interdisciplinary tools, encompassing the chemistry of nanoporous macrostructure materials, polymer engineering, and blood biology, to advance the knowledge required to develop non-toxic composite bags while taking into consideration stringent requirements of physicochemical and mechanical properties for application as a blood bag. The technical challenge is to balance the competing needs of a blood storage container and manufacture using commercial blood bag machinery while ensuring sufficient active surfaces of the composite films without any leaching of the active ingredient during blood storage. The technology development addresses several technical challenges for storing whole blood longer than 28 days while keeping it healthy. Additionally, technical challenges in sealing the composite films while maintaining the required polymer integrity during steam sterilization are addressed. Solutions to the above-mentioned challenges are anticipated to achieve the primary goal of the Phase I project, which is to demonstrate that the non-toxic composite blood bags extend the shelf life of human whole blood by protecting against cold storage-induced oxidative injury and spontaneous hemolysis of red blood cells.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
XMD DIAGNOSTICS, INC.
SBIR Phase I: Microdissection Optimization for Molecular Profiling and Clinical Lab Use
Contact
415 4TH ST
Annapolis, MD 21403--2536
NSF Award
2322010 – SBIR Phase I
Award amount to date
$274,594
Start / end date
08/01/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to improve cancer diagnosis and treatment. Cancer affects millions of Americans and people worldwide. The National Cancer Institute (NCI) reports that the number of new cancer cases will reach 30 million by 2040, representing an enormous cost to American society and the economy. There is a dire need for innovative technologies such as molecular diagnostics and personalized medicine to combat cancer. Modern molecular testing methods such as polymerase chain reaction (PCR) and next-generation sequencing (NGS) often suffer from low tumor content and genetic contamination from non-cancer cells contained in their samples - resulting in an insufficient amount of DNA for accurate molecular testing. This research will focus on microdissection as a means of obtaining cancer cells for testing. The proposed tumor cell purification and extraction will enable the company to focus on modelling and optimalization of individualized cancer treatments rather than non-cancer cells. The solution combines mathematical modeling, mathematical optimization, and real-world experimental verification which will contribute significantly to successful commercialization of clinical lab instruments and complementary products.
This Small Business Innovation Research (SBIR) Phase I project aims to conduct scientific research to understand the optical, thermal, and mechanical interactions that occur during microdissection. The resulting modeling will be used to enable reliable extraction of cancer cells from patient biopsy samples, accounting for different sample types and cancer-cell stain intensities. Microdissection purifies cancer cells from human samples and enables molecular testing and genetic profiling. Current instruments for tumor cell purification and extraction are either arduous or unreliable. In this project, the aim is to conduct research to model and optimize the opto-thermal-mechanical interaction of microdissection by taking into consideration common tissue variations (i.e., tissue types, tissue thickness, and stain intensity). This technology will be used to determine the specific operating specifications for successfully micro-dissecting tissue specimens and developing an instrument for research and commercial clinical laboratory use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
XTRACT MEDICAL, INC.
SBIR Phase I: A novel clot removal system for improved Venous Thromboembolism (VTE) thrombectomy outcomes
Contact
349 SHORT ST
Louisville, CO 80027--1700
NSF Award
2233665 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 05/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel system for treating Venous Thromboembolism (VTE), a clot in the patient?s deep veins or pulmonary arteries which blocks blood flow, in a more effective manner. Each year 1.2 million Americans are affected by VTE resulting in 100,000 deaths, $10 billion of direct medical costs, and $69 billion of economic impact. Despite modern treatments and procedures over half of all patients diagnosed with VTE will suffer long-term complications including Post-Thrombotic Syndrome, resulting in functional disabilities and the inability to return to work within 10 years of diagnosis. The proposed system aims to improve the clinical effectiveness of mechanical thrombectomy procedures by removing clots and restoring circulation, thereby improving patient outcomes and reducing long term patient care costs.
This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate the feasibility of a novel catheter-based system for securing and removing clots during mechanical thrombectomies. The technology aims to effectively remove clots while being both atraumatic to the vessel with minimal blood loss, in order to significantly improve upon existing clot entrapment or removal approaches. The scope of activities includes developing a first-generation prototype and demonstrating the prototype enables the ingestion of large clot volumes without clogging nor causing damage to other vascular structures. The device will be designed and prototyped within the dimensions needed to fit within a clinically accepted catheter size and validated using preclinical bench-top and animal models across a wide variety of clot sizes, shapes and mechanical properties.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ZANET ANALYTICS CORPORATION
SBIR Phase I: A Technology-Enhanced Statistics Learning Software App
Contact
113 N WARREN ST
Easton, PA 18042--3326
NSF Award
2324068 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2023 – 04/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in the development of an immersive, game-based, learning app to help teach statistics in an engaging way to middle and high school students. Designed as a classroom resource, the app is aimed at providing a mechanism to promote statistical thinking. The app will integrate research activities into the teaching of statistical concepts and techniques to common core curriculum standards. The game design is expected to increase interest in statistics and also increasing the number of students going into STEM related fields.
This game-based app features artificial intelligence (AI) and augmented reality learning components tailored to meet students where they are academically and customize fit to each student?s individual interests. This app will be used as a classroom resource. Phase I research and development addresses technical feasibility hurdles such as the development of augmented reality and artificial intelligence features. Other challenges include the development of a user-friendly, seamless application that does not require internet access and a feasible system architecture to integrate the computational engine with the game user interface and ensure reasonable response times. To overcome the inherent technical hurdles, the team will use an agile development cycle that allows for faster development of the finished product, as well as flexibility to respond to changes and requirement updates as they occur.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ZEALOUS RESEARCH LLC
STTR Phase I: Single-Chip Microfluidic Platform for Finely Controlled In Vitro Fertilization Processes
Contact
409 TAUGHANNOCK BLVD.
Ithaca, NY 14850--3232
NSF Award
2304368 – STTR Phase I
Award amount to date
$275,000
Start / end date
08/15/2023 – 07/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that by improving the success rate of in vitro fertilization (IVF), this project will benefit assisted reproduction technology (ART) providers, infertile couples, and insurance companies. With infertility increasing globally, there is a huge potential market for ART services. However, current IVF technologies provide inadequate results and come with high costs that significantly impact both the minority of infertile couples who can afford IVF and the majority for whom the technology is priced out of reach. The successful development of a disposable, low-cost platform automating all steps of IVF is expected to produce a manifold increase in the productivity of ART clinics by reducing the processing time demands on andrologists and embryologists as well as reducing the labor requirements for sperm separation. This will, in turn, have the effect of increasing the efficiency, capacity and profitability of ART clinics, while lowering overall costs of IVF. Lower prices will reduce the burden on couples using ART and on their insurance companies, while increasing access to ART for lower-income populations. The technology is also expected to result in higher fertilization rates, enhancing successful IVF conception outcomes.
This Small Business Innovation Research (SBIR) Phase I project will develop an IVF-on-a-chip platform in response to the need for a cost-effective and highly controlled IVF process. Variance in operator skill levels and damage to gametes due to handling contribute to significant variability in IVF performance, with success rates averaging only around 37%. The new technology aims to remove this inconsistency by using a microfluidic platform to perform the entire IVF process in a single-chip workflow, automating and optimizing sperm selection, sperm capacitation, and egg fertilization. The proposed platform includes a region for sperm selection, a reservoir for sperm capacitation, and a segment for egg fertilization. This project will develop a single user-friendly commercial device and optimize conditions for each step of the IVF process with bovine gametes, through rigorous analysis and optimization of the timing, flow, incubation, and media conditions. The device will be tested in mice and bovine models as a precursor to human treatment and its performance compared to traditional IVF. If successful, the fully developed platform system will fulfill the need for a simple-to-use, affordable, robust, and high-throughput sperm sample preparation for medical treatments and clinical applications, resulting in higher fertilization rates and enhanced patient outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ZENOLEAP LLC
STTR Phase I: High-Sensitivity Flexible Quantum Dots/Graphene X-Ray Detectors and Imaging Systems
Contact
4517 WINGED FOOT CT
Lawrence, KS 66049--3837
NSF Award
2322053 – STTR Phase I
Award amount to date
$275,000
Start / end date
04/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel sensitive x-ray imaging platform based on a quantum approach to photo-detection. This project will leverage recent advancements in Quantum Dots/Graphene technology to demonstrate its suitability and superior performance for x-ray-based imaging medical capital equipment. This novel technological approach aims to provide an X-ray diagnostic imaging platform with superior performance and lower potential price points than semiconductor detector paradigms. The commercial impact is a novel detector array platform for the $16 billion annual x-ray imaging market, focusing on the $6.9 annual computed tomography (CT) scanner subset of the market.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a functional prototype for a novel Quantum Dots (QD)/graphene nanohybrid x-ray array detection platform for use in medical diagnostic capital equipment. This initiative aims to design and quantify the critical attributes of a novel quantum sensor platform for x-ray capture, down-conversion, and detection of down-converted low-energy photons. During this first phase, experimental tests will be completed. The results will be used to design and develop a prototype detector array with a QD-layer design onto rigid and flexible substrates for scalability onto large X-ray imaging systems. The completed prototype system will then be tested and validated for performance versus existing platforms. This Phase 1 project will quantitatively benchmark several critical attributes (cost, sensitivity, efficiency, preliminary safety) for a novel x-ray imaging nanohybrid platform versus current hybrids for future commercial integration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ZEPSOR TECHNOLOGIES, INC.
SBIR Phase I: Micro-Electromechanical Systems (MEMS)-Based Near-Zero Power Infrared Sensors for Proximity Detection
Contact
145 S BEDFORD ST STE 240
Burlington, MA 01803--5480
NSF Award
2304549 – SBIR Phase I
Award amount to date
$275,000
Start / end date
01/15/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project seeks the development of a first-of-its-kind proximity sensor that consumes near-zero power at standby for touchless interface applications. The proximity detector is based on a proprietary micro-electromechanical systems (MEMS) infrared detector technology that is more accurate, more compact, and 100 times more power efficient than any existing infrared detector technology. The innovation is a digitized, ultra-low power, uncooled infrared detector. The total addressable market for this proximity sensor is estimated to be ~$4.7 billion in 2023, with a serviceable obtainable market of hundreds of millions for the technology. Although the market for proximity and presence sensing is extremely broad, the team has chosen to target touchless faucets and auto sanitizer dispensers as the go-to-market applications due to the technology and market readiness. The product and its commercialization process are expected to create societal and economic impacts in four areas including conservation of resources, hygiene promotion, and enhanced partnerships between university and industry.
The intellectual merit of this project includes the first demonstration of a near-zero power proximity sensor with a wide field-of-view, tunable detection range, and temperature stability in a relevant indoor environment. State-of-the-art sensors drain battery power continuously regardless of the presence of target signal. The team recently broke the fundamental paradigm of wasting energy in standby mode with the invention of a completely passive sensor microsystem that can detect and discriminate events of interest by exploiting only the energy contained in their specific physical signatures. Remaining challenges for chip-scale hand detection include efficiently harvesting the tiny amount of thermal energy emitted by a hand to trigger a micromechanical photo-switch while achieving a high level of immunity to background temperature changes. A new plasmonically-enhanced, long-wave infrared absorber, a threshold tuning mechanism, and vacuum packaging are developed and expected to lead to the demonstration of a miniaturized prototype capable of reliably detecting a hand at 2-10 cm distance, while consuming less than 1 microamp current in standby mode.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ZQAI LLC
STTR Phase I: Machine Learning-Based Smart Data Compression Solutions for Structural Health Monitoring Sensors
Contact
4942 N WINCHESTER AVE APT 1
Chicago, IL 60640--3313
NSF Award
2321884 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 08/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to enable efficient monitoring of civil infrastructures and rapid decision-making on their structural safety. The conditions of aging structures are monitored using structural health monitoring (SHM) sensors. These sensors produce very large datasets. In this project, a data compression solution will be developed to reduce the size of such datasets by 90%, without losing important information. As an example, one sensor can fill up a 128 Gigabyte hard disk in about 6 hours, but with the data compression solutions, it will take at least 60 hours to fill the hard disk. Data compression is thus a critical factor for both storage (disk space) and efficient transmission of sensor data. A microchip with a built-in data compression algorithm will be developed. The sensors with microchips will need to be visited less often for data retrieval and dramatically less bandwidth and power will be required for data transmission over existing wireless networks. This will enable monitoring of structures in remote areas. The data compression will be applicable to various market segments, however the initial target market will be the SHM of aging structures within the oil and gas industry.
This Small Business Technology Transfer (STTR) Phase I project aims to develop sensor data compression schemes and encoder/decoder devices utilizing deep learning methods. The proposed system will consist of a data encoder and decoder, which will autonomously learn the characteristics of the sensor data, extract relevant features, and transmit these using low bit rates. Even users without prior experience in machine learning will be able to train the deep neural network with transform domain layers for different sensor types. The software version of the system will allow for data processing and transmission over the Internet when the sensor is connected to a computer, making it possible to handle stored data on-site. The embedded hardware version will be designed for "edge" usage, meaning it will be implemented next to the sensor itself. This approach will ensure computational efficiency, particularly for the feature extraction part of the network, which needs to be executed at the edge. The project's focus will be on detecting pipeline leakage using high-frequency acoustic emission data on the developed microchip system. By reducing the data transmission bitrate of SHM devices, this system will enable continuous transmission of SHM data to the cloud or data centers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Zaiput Flow Technologies LLC
SBIR Phase I: Continuous, Scalable Crystallizer for Pharmaceutical Manufacturing
Contact
101A 1ST AVE
Waltham, MA 02451--1130
NSF Award
2233759 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/15/2023 – 04/30/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve a key step used in the >$500-billion market of pharmaceutical manufacturing: purification of active pharmaceutical ingredients. Ninety percent of all active pharmaceutical ingredients are purified using crystallization, however, current approaches to crystallization have drawbacks from both the commercial and scientific points of view. These techniques are difficult to scale up, are expensive to maintain and manufacture, and are plagued by inconsistency and lack of uniformity in conditions and results. With the development and commercialization of the technology proposed here, this team will address the scalability, cost, and inconsistency issues in order to: 1) speed up the transition to advanced manufacturing approaches (continuous manufacturing), 2) facilitate the re-shoring of drug manufacturing, contributing to addressing the national security challenge of American dependence on foreign drug manufacturers, and 3) reduce drug production costs, which will eventually lead to cheaper drugs for the benefit of the entire population.
This SBIR Phase I project proposes to develop an innovative, continuous crystallization device that is scalable, provides adequate and effective movement of solids, and provides high-quality crystalline products, thus fulfilling an unmet need in the pharmaceutical market and in the technical community. The novel design aims to solve the problem of moving solids (crystals) effectively while providing well-controlled flow characteristics with an approach that is scalable from lab to production. This technology uses a combination of several original features to provide a new technological approach to address these transport challenges. This team will first provide a demonstration of the ability to transport slurries with plug flow characteristics. Then, the team will demonstrate the crystallization of a pharmaceutical, benchmarking it against standard batch crystallization methods. Once the technology has been shown to function well in these conditions, the device will be scaled up, in order to be tested and used at production scale. Once complete, the commercialized device is expected to be able to overcome problems with other technologies, including issues of transport, uniformity, consistency, reproducibility, and cost, making this novel device a key player in the future of pharmaceutical manufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Zeteo Tech, Inc.
SBIR Phase I: Automated Robotic Disinfection System (COVID-19)
Contact
6935 WARFIELD AVE
Sykesville, MD 21784--7454
NSF Award
2036162 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2021 – 03/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will improve infection control in public transportation. There is currently no high-speed, autonomous method capable of decontaminating commercial aircraft and public transit vehicles. The proposed technology rapidly inactivates viruses and other potential biothreats in an automated robotic disinfection system.
This SBIR Phase I project proposes development and scaling of a system using radiofrequency (RF) directed energy to activate a benign chemical, producing biocidal reactive oxygen on surfaces. Preliminary studies of MS2 bacteriophage viruses have demonstrated inactivation of 99.999999% of MS2, despite being 7-10x more difficult to inactivate than SARS-CoV-2. The proposed system consists of four subsystems: application sprayer, RF, robotics, and power. This project will optimize and integrate these subsystems. A key technical objective is identifying the power density threshold and appropriate frequency for virus inactivation without negative interactions with electronic equipment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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