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Phase I
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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
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. -
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. -
ADAVANCE NANOLYTICS INC
STTR Phase I: AAV QC using SANE Sensor
Contact
7223 ARBOR OAKS DR
Dallas, TX 75248--2201
NSF Award
2415309 – STTR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 it will demonstrate a plasmonic nanopore sensor device for all-in-one DNA loading characterization of adeno-associated viruses (AAVs) used for gene therapy. In the longer-term, the company anticipates that it will extend uses of this device to accurately test the drug or DNA/RNA loading consistency of soft nanoparticles such as exosomes, other viruses, and liposomes, to make this quality control (QC) technology applicable to all nanoparticles with biological applications and beyond. This project has inextricable interests in biochemistry, nanoengineering, photonics, and resistive pulse sensing which would be beneficial to encourage more students to pursue STEM degree through its outreach program. The PI will lead the company?s outreach in the Dallas County Community College District, whose mission is to build up the local workforce to today?s market needs, with nanosensor demonstrations and discussion of broad applications. The proposed technology also has the potential to drastically reduce the time and resource demands of AAV QC processes and increase success rates in early-phase gene therapy trials, accelerating FDA approvals for desperately needed treatments.
This Small Business Technology Transfer (STTR) Phase I project will demonstrate a plasmonic nanopore sensor device that will outperform existing analytical techniques by capturing multiple optical-electrical data types per AAV particle to enable, for the first time, unambiguous payload classification (single-stranded DNA versus double-stranded DNA, or empty) at low, pre-scale-up concentrations to optimize formulations in small batches, enabling significant savings in subsequent large-volume production. The proposed work will show feasibility of the proposed device to be nanofabricated in a scalable manner by electron beam lithography, namely optimize sensor nanofabrication protocol for accuracy and production reproducibility of the 3D plasmonic trap, and ensure accurate laser source alignment with bonded optics, and a photodetector collecting optical signals transmitted through the sensor. In addition, this work will optimize machine learning-based sensor discrimination between empty versus partly and fully loaded AAVs by optimizing the spectrum of AC pulse frequencies that scan each particle during trapping. Once successfully tested, the prototype?s nanofabrication and machine-learning workflows will be ready for further development into the company?s first commercial device after a subsequent Phase II.
This award reflects 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. -
AEPNUS TECHNOLOGY INC
SBIR Phase I: Novel electrolyzer architectures to enable electrified chemical manufacturing at industrial scales
Contact
2828 FILBERT ST
Emeryville, CA 94608--4513
NSF Award
2321842 – SBIR Phase I
Award amount to date
$274,986
Start / end date
09/15/2023 – 12/31/2025 (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 is the creation of an economical and climate-friendly method to produce valuable commodity chemicals from inexpensive feedstocks such as chemical waste streams. Chemical manufacturing accounts for 8% of global greenhouse gas emissions: waste produced from manufacturing battery chemicals and recycling Lithium batteries could be converted back into input chemicals. The technology focuses on developing new electrodes that use electricity to produce acid and base from sulfate-containing waste streams. This innovation will stimulate the US manufacturing sector by improving energy efficiency, competitiveness, and environmental sustainability. This technology could eliminate 3 billion tons of greenhouse gas emissions through electrification of chemical manufacturing, while recycling or eliminating the production of a hazardous waste. Moreover, the technology is more economical than current methods, increasing the likelihood of widespread adoption. Replacing outdated manufacturing plants with clean, efficient electrolysis systems would provide high-paying jobs and tax revenue for the region.
Conventional salt electrolysis systems rely on titanium electrodes coated with a precious metal catalyst (e.g., iridium oxide) to enable efficient operation. The metal catalysts used for these coatings are expensive, rare, and fragile. This means that the capital cost of existing salt splitting systems is high, while their operating conditions (e.g., temperature, current density, and operating efficiency) are fairly limited. This innovation will develop gas diffusion electrodes that can help produce acid and base electrolytically from sulfate waste streams at industrial cost parity. The unique microstructure and materials design of the electrodes minimizes the use of precious metal catalysts to lower costs, enhances lifetime for robust operation under corrosive environments, and achieves higher operating temperature (>75 C) and improved current density (5000 A/m2) for lower operating costs. In this project, Design-of-Experiment principles will be used to determine the best combinations of binder, catalyst, and filler/support materials to outperform conventional systems. Optimal chemical and electrochemical properties will be sought for high electrical conductivity, ability to withstand corrosion in highly acidic environments, and minimal oxidative dissolution of catalyst. The durability and efficiency of the new electrodes will be tested first at the lab scale (25 cm2) for 100 hours and then scaled up to 500 cm2 cells for pilot-scale analysis. In all studies, actual sodium sulfate waste obtained from industrial partners will be utilized. The effects of impurities ions in the feed stream on the electrode and membranes will be tracked via spectroscopy and electron microscopy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AERHART, LLC
STTR Phase I: Passive Actuation for Enhanced Urban Air Mobility (UAM) Capability
Contact
6461 KANAN DUME RD
Malibu, CA 90265--4039
NSF Award
2334180 – STTR Phase I
Award amount to date
$274,999
Start / end date
05/15/2024 – 10/31/2024 (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 provides increased efficiency and range for urban air mobility (UAM) air-taxi systems. This research allows aircraft to reconfigure in-flight, enabling the craft to land in cityscapes while still being able to fly significant distances. As UAM aircraft primarily use electric power, this technology will facilitate the transition to greener modes of transport in cities, while alleviating surface level congestion due to traffic. The primary focus of this project is on improving the safety of in-flight reconfiguration to promote the well-being of passengers and payload. The UAM sector is set to rapidly expand in the coming years, providing services and creating jobs. By laying the groundwork for improved performance while maintaining high safety standards, the sector, passengers, and public will benefit.
Aerodynamically-actuated wings on urban air mobility vehicles come with the risk of asymmetric deployment. This project aims to mitigate risks by producing a closed-loop aileron control method that promotes symmetric deployment while simultaneously ensuring that even an asymmetric deployment does not induce aircraft instability. Wind tunnel data will be generated for a number of static and dynamic fold conditions. Methods for governing when and how fast reconfiguration takes place will be tested to bridge the control gap between motorized and aerodynamic actuation. Implementation of these methods will allow for operations resembling motorized actuation, without the associated weight penalties and disadvantages. Wind tunnel data will be used to produce the closed-loop aileron control method which will then be tested in the wind tunnel to verify that the level of expected roll torque variance is observed throughout asymmetric reconfiguration. Success will show a marked decrease in roll torque variance compared to reconfiguration where no closed-loop corrective action is taken. Together these methods and risk mitigation techniques will overcome the need for a mechanical actuation device, reducing the complexity and barriers to entry of reconfigurable designs. Introducing such benefits to size constrained aircraft will translate to a better performing urban air mobility 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. -
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
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-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. -
AIKIDO TECHNOLOGIES INC
SBIR Phase I: Detailed Engineering of 100kW Self-Upending Floating Wind Platform
Contact
3101 20TH ST
San Francisco, CA 94110--2714
NSF Award
2346763 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 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 SBIR Phase I project is in the development of a next-generation floating wind platform that could dramatically reduce the time, cost, and equipment/vessel requirements of installing commercial-scale floating wind farms. It is estimated that by 2050, there will be over $1 trillion (T) invested in floating offshore wind projects around the world, totaling up to 250 gigawatts (GW) of capacity. A major challenge facing the floating wind industry is the massive size of turbines and floating platforms, prohibiting them from fitting in existing United States (US) port infrastructure. Furthermore, the supply chain is severely constrained as only a few shipyards and port facilities in the world, can build, assemble and load-out these massive structures. The proposed platform solves these challenges because it can be assembled and transported horizontally, significantly reducing the required depth, overhead clearance, and overall footprint.
The intellectual merit of the project relates to the development of the upending procedure for an offshore floating platform with a pre-installed turbine. The platform can be assembled and transported in a horizontal position, and then unfolded into its vertical position through an upending process that only uses ballast water. During this project, the upending procedure of the platform with a pre-installed turbine will be studied to determine the optimal design to ensure the turbine can withstand the mechanical forces associated with assembly, transportation, and upending, as well as the materials challenges associated with an offshore environment. In addition, the upending procedure will be modeled in a variety of conditions to determine the maximum weather conditions in which the upending procedure can safely 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. -
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
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. -
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
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. -
ARED LLC
SBIR Phase I: Portable Full-Recirculation Incubator for Salmon Incubation/Restoration
Contact
730 CASE AVE
Wrangell, AK 99929-
NSF Award
2403690 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2024 – 04/30/2025 (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 1 project is in creating a new salmon incubation system to restore the wild salmon population of natural streams. Food security continues to escalate as a global crisis, especially for healthy whole foods. The proposed technology impacts both wild salmon (affecting both commercial and subsistence economies) and farmed salmon by offering tools for wild salmon restoration and advanced economic/environmentally sound aquaculture practices in salmon farms, eliminating toxic chemical use and dramatically less freshwater use. This project brings a new, self-contained, portable, full-recirculation incubation system to rear salmon eggs to the emergent fry stage of salmon development without the use of toxic chemicals and decreasing the amount of freshwater used from millions to hundreds of gallons. Further, the societal value of community involvement (STEM) in reversing extinction trends in wild salmon is immeasurable.
Wild salmon requires embryonic development with water from their natal stream. Hence, it is now recognized that the conventional central multi-million-dollar hatchery facilities are no longer suitable as they cannot accomplish this. This SBIR Phase 1 project intends to develop an incubation technology that will preserve genetic integrity, use water from the wild salmon?s native watershed, eliminate toxic chemical use, afford the ability to track restoration progress and avoid million-dollar hatchery capital costs. It will create a new salmon egg/alevin incubator by re-engineering and combining two proven salmon incubation systems together in a compact portable size. Among other features, the system will be designed for tight temperature control, having almost no vibration, and the ability to withstand major earthquakes. The system is expected to increase the survival of young fry several-fold; using water from their indigenous source, otolith mark them with a natural mark and restock the fry back into their wild stream of origin.
This award reflects 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. -
ASTERION AI INC.
SBIR Phase I: Pre-Hospital Detection of Large Vessel Occlusion Strokes
Contact
12700 HILLCREST RD STE 147
Dallas, TX 75230--7105
NSF Award
2213156 – SBIR Phase I
Award amount to date
$255,999
Start / end date
09/15/2022 – 08/31/2024
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 arm emergency personnel with an objective tool for identifying large vessel occlusion (LVO) strokes while in route to the hospital. This rapid and accurate triage of stroke will enable routing of patients to the most appropriate care setting and reduce the time to intervention. LVOs require endovascular therapy which only comprehensive stroke centers have the capability to conduct. If a patient with an LVO is routed to a hospital without endovascular capabilities simply because it was closer, the time to intervention is extended drastically. When it comes to improving outcomes, time to optimal intervention is the most important factor with the best outcomes achieved under three hours and statistically significant improvements for each 15-minute window under that threshold. Stroke is the second leading cause of death and the primary cause of long-term disability worldwide costing the US $65B every year. Nearly 800,000 people suffer a stroke in the US annually and 40% are left with a permanent disability. The project will streamline stroke triage in the pre-hospital setting to reduce time to intervention and improve outcomes in stroke patients.
This Small Business Innovation Research (SBIR) Phase I project an EEG-based product for EMS workers to use in the pre-hospital setting for the fast and objective diagnosis of LVO in suspected stroke patients. In under five minutes, EMS workers will be able to deploy, collect data, and have the analyzed results presented in an intuitive dashboard identifying the probability of an LVO, enabling EMS workers to route patients to stroke centers with EVT capabilities. When a patient arrives at the hospital, the determination made within the ambulance will be conveyed to physicians who can then immediately start intervention, reducing the time from onset to intervention and improving short and long-term patient outcomes. Comprehensive historical datasets of EEG-data from stroke patients using a broad array of hardware will be used to develop a machine learning model that can classify patients into LVO vs non-LVO stroke and stroke vs non-stroke. Automation of data cleaning and feature extraction will enable a highly user-friendly experience and the required workflow integration for our end-users, emergency medical technicians. Lastly, this model will be validated with novel EEG data collected at two clinical sites, laying the foundation for regulatory interactions.
This award reflects 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
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. -
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. -
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. -
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
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 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
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 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. -
BERKM INC
SBIR Phase I: Transparent Clay-PET Nanocomposite for Lightweight Packaging with Extended Product Shelf Life
Contact
22 BOND ST APT 615
Watertown, MA 02472--3758
NSF Award
2408935 – SBIR Phase I
Award amount to date
$274,424
Start / end date
06/01/2024 – 05/31/2025 (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 includes reducing plastic pollution, food waste, and CO2 emissions. The project focuses on new and economical ways of manufacturing clay-polyethylene terephthalate(PET) nanocomposite. The nanocomposite displays significantly improved material properties. The improvement in properties enables the use of up to 20% less plastic per package and reduces food and beverage waste by extending product shelf-life 5X-6X. The end beneficiaries of the technology are consumer packaged goods companies. Using the proposed technology, they can save costs from raw materials and product shelf-life extension and meet their sustainability goals. The company has several patents and trade secrets that have been developed over 30 years and the chemistry concept behind the project can be used to develop multiple additive product lines for different polymers. The estimated total addressable market size for inorganic polymer additives is $33B. The company intends to commercialize initially in specialty packaging followed by carbonated drinks.
This Small Business Innovation Research Phase I project aims to make clear PET soda bottles with a 2-3X improvement in CO2 barrier that displays industry acceptable yellow index. The team can achieve 5-6X improvement in the CO2 barrier on lab-scale films and is working to convert lab-scale performance to the final soda bottle package. This project aims to understand the barrier performance and haziness of the packages made from our clay-PET composite. The team will use a variety of microscopy and characterization techniques to study the nanocomposite through the bottle making process to determine if particle agglomeration, rapid crystallization, and/or micro-voids are causes for haziness. Depending on the findings, the team will develop co-monomers, high-temperature injection processes, and different compatibilizers to manage haze while maintaining CO2 barrier 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. -
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 – 08/31/2024
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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 – 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 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
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. -
BRAINSTORM THERAPEUTICS, INC.
SBIR Phase I: Development and Validation of a Novel Parkinson's Disease Drug Discovery Platform Using Patient-Derived Midbrain Organoids
Contact
5370 TOSCANA WAY H208
San Diego, CA 92122--5656
NSF Award
2414877 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 06/30/2025 (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 spans several fronts, starting with advancements in public health and welfare. The project goal is to reduce risks in clinical translation and expedite the development of crucial therapies for Parkinson's disease. Additionally, the highly scalable nature of the proposed platform offers the long-term potential to extend its application to other complex brain disorders and therapeutic domains. The platform will guide therapeutic candidate discovery, stratify patient selection and refine clinical trial endpoints. Beyond health, the project impact extends to the economic competitiveness of the US. For example, by providing therapies that can help address the challenges people with neurological disorders face in the workforce, the developed product will contribute to operational efficiency, reduce healthcare costs, and boost workforce productivity. The commitment to accelerating therapeutic development also fuels innovation, attracting investments and creating high-value jobs, solidifying the US as a global leader in healthcare innovation. Furthermore, the project team actively promotes partnerships between patient foundations, academia, and drug developers in the biopharma industry.
The proposed project addresses the urgent need for effective disease-modifying therapies for Parkinson's disease. There are no approved disease-modifying therapies for Parkinson's disease due to challenges, including the lack of reliable animal models that accurately predict human efficacy, and a poor understanding of the genetic, environmental and lifestyle factors contributing to dopamine neuron degeneration. To overcome these hurdles, an all-in-human Parkinson's disease drug discovery platform will be developed. This approach utilizes familial Parkinson's disease patient-derived midbrain organoid disease models, biomarker-based screening endpoints, and advanced data analytics to identify disease-modifying therapeutics that halt, prevent, or reverse dopamine neuron degeneration. This platform is positioned as a game-changer in the discovery of impactful Parkinson's disease treatments. The core innovations of the approach include patient-derived stem cells capturing human disease biology at the earliest drug development stages, human-first drug discovery reducing reliance on animal models, scalability and reproducibility of organoid production, robust and reproducible quantification of disease-specific phenotypes, and screening compatible with various therapeutic modalities. The focus on genetically validated targets and converging pathways in sporadic Parkinson's disease aims to de-risk clinical translation, reduce costs, and accelerate the discovery of transformative Parkinson's disease 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. -
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
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 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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
CALM WATERS GROUP LLC
SBIR Phase I: A Stakeholder Management Platform for Environmental Justice
Contact
2778 GEORGIA ST
Vallejo, CA 94591--6502
NSF Award
2208725 – SBIR Phase I
Award amount to date
$255,937
Start / end date
01/15/2023 – 09/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial impact of this Small Business Innovation Research Phase I project is to break the negative feedback loop of multi-generation, multi-sector cascading impacts of environmental and social injustices by providing effective tools for engagement of underserved communities. The tide is turning as Environmental Justice policies are increasingly being adopted by governments at the federal, state, county, and regional levels - to explicitly and meaningfully engage underserved communities early and often in all regulatory and planning phases. This project addresses the initial challenges around automating the process of identifying, building trust with, and elevating community-based organizations and underserved communities with the goal of accelerating the implementation of equitable climate-smart infrastructure projects. The proposed innovation will help agencies scale up their reach, accuracy, and efficiency of community engagement, establish and build trust with underserved communities, and accelerate community participation in planning and infrastructure projects throughout the United States. The project helps community leaders raise their voice and visibility with agencies, gain access to timely information across different agencies, and gain access to funding opportunities. Successfully implementing this project has the potential to reduce cost burdens on communities, while also supporting economic empowerment in communities where the project is deployed.
This Small Business Innovation Research Phase I project will demonstrate feasibility of using TextAI (Natural Language Processing using Artificial Intelligence (AI)) and GeoAI (Geographic Information Systems using AI) to perform location-based stakeholder discovery of Community Based Organizations (CBOs). This goal poses technical challenges: high variation in unstructured data; quality of manual annotations; complexity and diversity of attributes; and disambiguation of location identification and social challenges. The communities of interest have low trust in the government and technology and need transparent data sharing and ethics. The key innovation is a workflow that combines deep technology development with participatory and inclusive co-design with community-based organizations and government. If the project succeeds, it will have substantial payback for underserved communities. The first use case is with the San Francisco Bay Conservation and Development Commission, which has the right size and scope of jurisdiction to capture variations in data type, stakeholders, and users - and includes a highly diverse set of demographics across urban and rural communities - while also being small enough to manage its data.
This award reflects 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 – 09/30/2024 (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. -
CARAVEL BIO, INC.
SBIR Phase I: Next generation enzyme engineering: high-throughput directed evolution of spore-displayed enzymes
Contact
4640 S MACADAM AVE STE 130D
Portland, OR 97239--4283
NSF Award
2409142 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 provide a novel synthetic biology platform that generates customizable enzyme solutions for industrial biocatalyst applications. The use of enzymes as industrial biocatalysts continues to expand, offering environmentally friendly and sustainable solutions to a wide range of industrial processes while driving innovation in fields such as pharmaceuticals, biofuels, and food production, and more recently biomining and carbon capture. Viewed as an alternative to conventional chemical catalysts, enzyme biocatalysts offer greater sustainability in their processes owing to their biodegradable nature, high selectivity, ability to operate under mild reaction conditions, and their ability to generate a low amount of byproduct during a reaction; they also negate the need for potentially toxic or energy intensive reagents typically needed for conventional chemical catalysis. These advantages confer downstream impacts on operational efficiency, costs, and energy requirements. With the proposed technology?s enhanced capabilities, there is potential to increase this impact by providing novel enzyme solutions that confer greater robustness and efficiency at lower costs and environmental impacts.
The proposed project aims to apply directed evolution and high-throughput screening technologies to spore-displayed enzymes, enabling rapid prototyping of spore-enzyme variants to improve important variables like enzyme activity, stability, and loading density. While enzyme catalysis is used in a wide range of industries, the ability to create enzymes with thermal and chemical stability that are also reusable remains a challenge. Using a process called spore-display immobilization, the platform uses bacteria to make and assemble enzymes on the surface of spores, a self-assembling and genetically encoded microparticle. The platform is based on key foundational research that resulted in the characterization of 37 proteins that make up the spore coat of Bacillus subtilis and their ability to act as fusion partners for enzymes. To further develop this technology, the following objectives are proposed: 1) Use the platform to implement directed evolution of a commercially relevant enzyme on the spore; establish feasibility of approach to yield improved biocatalytic properties and benchmark to industry standard; 2) Advance system screening capabilities to enable high throughput selection using a microfluidic encapsulation approach; demonstrate ability to screen >1 million enzyme variants per day, and 3) use machine learning to predict and learn from improved catalyst variants.
This award reflects 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
Please report errors in award information by writing to awardsearch@nsf.gov.
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
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 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. -
CASIMIR, INC
SBIR Phase I: Development of devices to manipulate the structure of quantum field energy for use in electric power generation
Contact
16441 SPACE CENTER BLVD STE D200
Houston, TX 77058--2015
NSF Award
2423233 – SBIR Phase I
Award amount to date
$274,920
Start / end date
05/01/2024 – 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 Phase I Small Business Innovation Research (SBIR) project is a paradigm shift in how electrical power is generated leading to compact, clean, and lightweight power sources able to provide consistent power no matter the environmental condition. The proposed product to be developed as part of this work offers the potential for broader societal and economic benefit. The proposed activity seeks to conduct research and development (R&D) to demonstrate technical feasibility of continuous power generation from the quantum field for terrestrial and space applications. The research activity will advance knowledge and understanding of quantum field theory and the nature of the quantum vacuum for the purpose of power generation and commercialization. This is expected to enable a continuous baseload renewable type power source in environments where other renewables are often not readily present. In so doing, the research will also enable new pathways for novel forms of radiation generation and detection, thereby enhancing space sensing and providing new communication capabilities making use of novel forms of radiation. This product may also benefit from high throughput scalable in-space manufacturing advances going forward, and serve as a reliable, light weight and abundant power source for the acceleration and growth of the large scale in-space economy. The technology is also expected to bring an array of advantages to national security and defense.
This SBIR Phase I project proposes to validate numerical analysis design tools that will enable optimization of custom power cells. The research objective is to commercialize the company?s power-generating nanotechnology. These custom Casimir cavities interact with fluctuations of the quantum field to generate continuous power. The innovation in the approach is the customization of the original Casimir cavity concept to incorporate an array of electrically connected and conducting pillars arranged along the midplane of the cavity. With this enhancement, the custom Casimir cavity structure establishes an electrostatic potential between the pillars along the midplane and the cavity walls. The goals and scope of the research are: prediction of tunneling current magnitude for given metal-insulator-metal combination; and optimal selection of combinations of materials and insulator thicknesses. The methods to accomplish validation of software analysis tools are as follows: fabricate numerous metal-insulator-metal samples; conduct laboratory tests to quantify tunneling current performance; update analysis tools with measured performance data. The anticipated technical result is validated software analysis tools to predict the tunneling current magnitude for a given metal-insulator-metal combination of 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. -
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
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 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. -
CHANGEAERIAL LLC
SBIR Phase I: Integrating deep learning algorithms for UAS-based infrastructure inspection: Path to fully automated, commercially viable and scalable monitoring
Contact
5022 ONSTAD ST
San Diego, CA 92110--1552
NSF Award
2420601 – SBIR Phase I
Award amount to date
$274,727
Start / end date
07/15/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research Phase I project will be improving the lives of US residents by increasing electric power grid resilience through increased effectiveness and efficiency with automated electric infrastructure monitoring based on imaging with uncrewed autonomous system (UAS) (i.e., drones). Automated UAS monitoring approaches incorporating novel AI algorithms will disrupt conventional approaches, increasing the spatial extent and temporal frequency of infrastructure inspections, and will accelerate identification of all types of defects and reduce operating expenses. Such tools and technology will also support programs for integration of large-scale renewable-based power projects and electric vehicles to help meet sustainability targets. They will also reduce wildfire risks and duration of weather-related power shutoffs. While electric utility infrastructure is the primary focus, inspection and monitoring of myriad infrastructure types such as telecommunication towers, pipelines, and bridges, both in construction and operational phases, will benefit from this technology. Step-change productivity gains through adoption of digital workflow automation will require workforce role evolution and drive new job creation. A diverse and skilled company team will be built by emulating the culture of diversity and inclusion of the co-founders? university roots.
This project will facilitate a major leap towards exploiting highly detailed imagery captured by uncrewed autonomous system (UAS) to achieve greater performance and automation for infrastructure inspection. The goal is to integrate time-sequential UAS imagery captured from the same location in the sky, with multiple AI algorithms to achieve both detection and identification of damage to overhead electric infrastructure (and ultimately many types of infrastructure). The centerpiece of the integrated AI model framework is a model that exploits temporal changes in conditions of electric utility apparatus to detect defects requiring maintenance. Another AI algorithm will simulate apparatus damages in images used to train AI routines, since actual damage is a relatively rare occurrence within the thousands of inspection images captured by UAS. A riskier but transformative research element will involve integrating the novel damage detection model with AI models that identify specific damage types from single-time images. This hybrid modeling approach will restrict the image domain for which damage is identified, to focus the attention of infrastructure inspectors on changes confirmed to be associated with damage. Temporal image sequences will ultimately feed predictive analytic models that forecast the likelihood of damage or failure and prioritize the timing of inspections.
This award reflects 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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
CLUE GENETICS INC.
SBIR Phase I: ClueGen: a fungi-focused metabologenomics platform for natural product discovery
Contact
2748 BETTE ST
Alameda, CA 94501--7858
NSF Award
2334278 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2024 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be on addressing current global problems concerning disease, pollution and climate change through the development of a new biological technology platform powered by fungi. Many natural product chemicals with broad potential uses have been discovered through traditional bioprospecting methods. However, the Achilles heel for commercial development of products based on these discoveries is that many of the compounds are difficult, expensive, or impossible to produce at scale. Further, many potent biochemicals are not typically produced under laboratory conditions, and therefore remain concealed within their host genomes. By associating known and new commercially-relevant metabolites with the genes responsible for their synthesis, this platform will open new opportunities for accessing the powerful chemistry found in fungi through modern synthetic biology and genomics.
The proposed project will enable discovery of biosynthetic gene clusters (BGCs) encoding bioactive metabolites from a large private collection of Ascomycetes. The mature platform will contain thousands of annotated genome sequences from this large group of relatively unstudied fungi that have high potential for producing new drugs and crop protection molecules, in addition to uncovering enzymes that can be applied to multiple industries. A set of specific targets encompassing anti-cancer molecules, insecticides, antibiotics, and novel enzymes will be used as validation guides on the route to fully developing the resources needed for novel discovery. The goals for this project are to fully annotate BGCs from 200 genomes selected from a diverse set of bioactive fungi, and design at least 15 heterologous expression constructs encoding verticillins, antimicrobials, and insecticidal compounds for a Phase 2 project. Additionally, it is anticipated that over 100 valuable enzyme candidates will be discovered for immediate value creation with customer-partners. Together, successful completion of this project will validate the tools needed for application of the platform to the remaining ~50,000 strains in the fungal library, and drive the investment needed to launch the company.
This award reflects 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. -
COSMIC EATS, INC.
SBIR Phase I: Innovative Solutions for Sustainable Agriculture: Enhancing Post-Harvest Quality, Reducing Contamination, and Easing Sterilization for Value Added Mushroom Producers
Contact
1941 EVANS RD
Cary, NC 27513--2041
NSF Award
2423642 – SBIR Phase I
Award amount to date
$274,885
Start / end date
08/01/2024 – 07/31/2025 (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 Phase I project is to develop a more efficient and sustainable way of producing mushrooms in a novel farming set-up. Currently consumer demand for mushrooms exceeds supply, and demand is growing very fast in the US and across the world. Some challenges faced by specialty mushroom growers in operating their businesses include the resource intensive requirements for growing the mushrooms as well as losses incurred due to the short shelf life of the harvested mushrooms. This proposal explores deep, transformative science questions with the goal to implement a novel technology to help mushroom growers overcome these challenges. Successful implementation will result in the growers operating more successful businesses, and will facilitate more novice growers to enter the market. The overall outcome will be an increase in supply to meet the unmet demand of the US consumer. Currently there is a great reliance on imported mushrooms to meet some of the demand. This project will enable an increase in domestic production capabilities thus improving national security, and will support the White House?s National Strategy on Food Insecurity and Better Health.
The innovative research proposed in this project is to define and implement a plasma treated water sterilization method that will impact multiple stages of mushroom cultivation and has the potential to transform production processes by reducing labor, water, and energy usage while enhancing product quality and extending shelf life. The application of plasma treated water in mushroom growing is relatively unexplored but seems promising as it has known antimicrobial activity due to reactive nitrogen and oxygen species. The reactive oxygen and nitrogen species also are known to boost post-harvest quality in mushrooms. However, there is risk that antimicrobial activity could also harm fungal mycelium and delay, inhibit, or otherwise disrupt growth resulting in yield loss. The project seek to understand the impacts of plasma activated water on mushroom production and seek to minimize the deleterious impact on fungal mycelium and mushrooms while maximizing its benefit. Successful applications of plasma activated water for mushroom production through this Phase I project will bring a significant efficiency gain for mushroom growers and reduced reliance on resources will enable production of mushroom in formerly inaccessible environments (such as in austere and isolated environments), thus opening new markets while providing more sources of nutrition to the local populations.
This award reflects 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. -
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. -
DEEPSEQAI LLC
SBIR Phase I: Development of an AI-Driven Humanized and Developable Single-Domain Library Design Platform for Accelerated Drug Discovery
Contact
3400 COTTAGE WAY
Sacramento, CA 95825--1474
NSF Award
2409105 – SBIR Phase I
Award amount to date
$274,797
Start / end date
07/15/2024 – 06/30/2025 (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 to address major technical and commercial limitations in protein drug discovery. Drug discovery is currently a slow and expensive process, taking an average of 10 years and $2.6B per drug. In 2021 the US pharma industry spent almost $100B on drug research and development (R&D) efforts, with ~10% dedicated to protein drugs. Although some artificial intelligence (AI) solutions exist to support this process, fundamental problems exist: no current system optimizes multiple protein functions simultaneously, existing models rely heavily on predicting protein structures, and there is a lack of transparency in the models. This proposal supports the development of an AI system to improve the identification of small, highly specialized antibodies. The proposed technology could enhance the speed of identifying lead molecules while also reducing the cost through technical innovations. Therefore, this work has enormous clinical and commercial potential.
This Small Business Innovation Research (SBIR) Phase I project is intended to support the creation of an AI model to improve the identification of highly developable single-domain antibodies. These molecules have accepted advantages for therapeutic use (strong binding affinity, good thermal stability and chemostability, and less steric hindrance than conventional antibodies). However, they are typically obtained through a time- and cost-intensive process that involves immunizing a camelid or screening a large synthetic library. This proposalwill support the development and validation of an AI model specifically intended to quickly identify effective and highly developable single-domain antibody leads against a given target. In order to accomplish this goal, the proposed work encompasses training a multimodal AI model that is able to ecognize key features and residues of single-domain antibodies, then produce libraries of sufficient depth and quality to generate stable, safe leads with strong binding affinities. After the study period, the model and developed workflows will be evaluated for their ability to rapidly identify lead molecules.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DEFINED BIOSCIENCE, INC.
SBIR Phase I: Protein isolate serum replacements for low-cost cultivated meat medium
Contact
6404 NANCY RIDGE DR
San Diego, CA 92121--2248
NSF Award
2412327 – SBIR Phase I
Award amount to date
$274,995
Start / end date
07/15/2024 – 06/30/2025 (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 is to enable a robust, scalable, and cost-effective means of cell expansion for cell-cultivated meat. Cell-cultivated meat offers an alternative source of animal meat products that may address issues of sustainability, conservation, and ethical sourcing. Current meat consumption is 30-40 kg per person per year in a population of nearly 9 billion people, presenting a major and growing annual demand for animal meat. Cell-cultivated meat, by bypassing animal slaughter through the growth of animal-derived cells in controlled environments, could help to meet this demand in a way that reduces greenhouse gas emissions, foodborne illnesses, and land and water usage. It also could offer more control in terms of metabolic profile, fat content, product sourcing, and food testing and analysis, a level of control from single cells to finished meat product. With concerns for animal meat sourcing over the next several decades, cell-cultivated meat may offer an opportunity for supplementing a shortening food supply and an alternative to traditional meat sourcing.
The proposed project expands on a low-cost and highly optimized cell culture medium formulation to enable scalable production of bovine cells for cell-cultivated meat. Cell-cultivated meat expects to use orders of magnitude more growth media than any previous market demand. Even pending the inevitable advancements in high-density cell culture, medium recycling and perfusion, scale-up bioreactor design, and limiting factor replacement that will all reduce this burden, there remains a profound need for lower-bulk, lower-cost media. A challenge is that cell culture has historically relied on blood serum to provide nutrients, growth factors and proteins?the most abundant and costly of which is albumin. The goal of this work is to replace high-cost recombinant albumins with plant-sourced albumin or albumin-like proteins, enabling the affordable production of cells for cultivated meat. Recombinant albumin improves on current formulations in the proliferation of bovine cells, and plant-derived fractions derived from US agricultural waste streams can similarly improve performance. This project aims to identify the highest-performing isolates among a defined set of candidates, followed by formula optimization. The resulting medium would be a low-cost solution for the growth of cells for cultivated meat?with the potential to serve other albumin 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. -
DENCODA LLC
SBIR Phase I: Development of a DNA-linked Kinase Assay
Contact
3203 ELKHART ST
West Lafayette, IN 47906--1152
NSF Award
2332861 – SBIR Phase I
Award amount to date
$274,990
Start / end date
05/01/2024 – 04/30/2025 (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 development of a highly specific and sensitive kinase assay that can be used as a research tool to discover new therapeutic targets or a clinical diagnostic test. Kinases are involved in the dysregulation of multiple cellular processes that drive the pathogenesis of various diseases, such as cancers, diabetes, and Alzheimer?s disease. Measuring kinase activities in the early stages of various kinase-driven diseases including cancers could improve patient outcomes and reduce healthcare costs. Herein, kinase activity assays will be developed in an innovative, low-cost, high-sensitivity, and multiplexed format to improve kinase activity detection and quantification for cancer-related kinases. This approach offers a critically needed innovation that could overcome multiple barriers facing existing kinase assays and better arm scientists and clinicians to understand kinase function and for personalized treatment. The development of this assay has the potential to drive new discoveries and improve clinical care across many disease areas by enabling researchers and clinicians to detect kinase activities precisely.
The proposed project addresses the unmet need for sensitive, accurate, and cost-effective methods to quantify kinase activity in disease. Current kinase assay systems lack key features required for precise measurement of disease-related kinase activities. This Phase I project aims to develop a novel DNA-based kinase assay platform that enables multiplexed quantification of kinase activities with superior sensitivity and specificity compared to existing assays. DNA-based activity assays offer advantages, including cost-effectiveness, high multiplexing ability, and sensitivity. The assay is estimated to be 10- to 100-fold cheaper than current assays due to the low cost of DNA synthesis and multiplexing capability. Successful completion of Phase I will demonstrate the feasibility of utilizing this DNA-based approach for measuring kinase activities in cancer cell lysates. Subsequent Phase II studies will validate the assay with clinical samples such as patient blood, urine, and tissues. Ultimately, this DNA-based kinase assay platform aims to enable highly sensitive kinase activity profiling that is currently unattainable. This will pave the way for assay-guided patient stratification and therapeutic development by overcoming the limitations of current kinase assays.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DINYA DNA LLC
STTR Phase I: Commercializing Architect-directed DNA Synthesis
Contact
505 DOUGLAS ST
Durham, NC 27705--3888
NSF Award
2350533 – STTR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 Technology Transfer (STTR) Phase I project is to expand innovation in the biotechnology sector through the development of a new DNA synthesis technology. DNA synthesis is a key enabling technology for synthetic biology and biotechnology.
Traditional DNA synthesis methods build DNA one nucleotide at a time and can only synthesize short strands of DNA due to fidelity limitations. These short strands of DNA can be assembled into larger DNA fragments but this process is sequence dependent and often fails. This results in high costs, delayed timelines, and even an inability to complete certain research goals. This project seeks to overcome these challenges by developing an entirely novel DNA synthesis technology that will significantly reduce costs and lead times, while also enabling the synthesis of long and complex DNA. These advances will significantly accelerate and enable innovation and development of new therapeutics, biomanufacturing, agriculture, and more.
The proposed project is focused on the commercial development of novel DNA synthesis technology. This technology is a hierarchical approach to DNA synthesis that relies on small 2-5 bp DNA precursors that can be enzymatically assembled into larger DNA sequences in an exponential fashion (eg, 2 bp to 4 bp to 8 bp to 16 bp, etc). Funding in this program will be used to i) develop new methods for ensuring higher fidelity DNA precursors, ii) reduce synthesis costs by streamlining synthesis reactions, as well as iii) characterize quality control approaches. If successful, this project will pave the way for high fidelity DNA synthesis at low costs and rapid turnaround 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. -
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
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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. -
DYNAMIC LOCOMOTION, INC.
STTR Phase I: Low-Cost Autonomous Sailboats for Long-Term Ocean Missions
Contact
107 CORONA AVE
Groton, NY 13073--1206
NSF Award
2213250 – STTR Phase I
Award amount to date
$248,418
Start / end date
08/15/2022 – 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 Technology Transfer (STTR) Phase I project is the development of new technologies to facilitate ocean data collection. Understanding the oceans is important for climate research, naval operations, maritime domain awareness, and ecosystem preservation, yet traditional data collection methods using research ships, commercial vessels, and buoys are cumbersome, expensive, and limited in their scope of discovery. While satellites have enabled remote data collection, they are affected by weather and limited in the types of data they collect. Uncrewed Surface Vessels (USVs) - robotic boats - are promising, but even today?s smallest oceangoing USVs are too costly for many applications. Thus, many regions of Earth?s oceans are rarely studied. The technology developed here aims to meet this need by enabling low-cost deployment of sensor-equipped robotic fleets. Better access to ocean data may improve understanding of the ocean and its resources, leading to better climate modeling, improved safety, economic gains, and more effective regulations. Further, ocean monitoring and surveillance is key to understanding ocean water quality, identifying contaminants, and devising strategies to prevent future contamination and pollution of the ocean?s waters. Ultimately, cost-effective oceanic data collection may help sustain and grow the ocean economy.
This Small Business Technology Transfer (STTR) Phase I project aims to develop a small, low-cost, autonomous robotic sailboat that uses an innovative sail arrangement and weather-optimized navigation system. With a combination of affordability and utility, the technology represents a new approach for widespread oceanic data collection. This technology can be deployed virtually anywhere in the ocean, can be small (2 meters or less), and is 100% wind- and solar-powered. The research in this project seeks to further this technology by advancing two innovations: passive directional stability and weather-optimized navigation. Unlike most other robotic sailboats, the proposed USV does not need active steering to hold a course, once set. Further, the proposed USV has a navigation system that exploits the spatial and temporal variance in the weather and uses local weather data to direct the boats to navigate more efficiently. This STTR proposal seeks to address areas of high technical risk including stability of the steering system under various wind and water conditions, resistance to traveling excessively downwind during storms, effectiveness of the optimized navigation system in both actual and simulated weather conditions at locations worldwide, construction and performance of prototypes in lakes and oceans, and long-term resistance to marine environments.
This award reflects 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
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 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. -
EARTHEN INC.
STTR Phase I: Packed Bed Thermal Energy Storage (PBTES) in sCO2-based thermo-mechanical energy storage for short and long durations
Contact
6401 W ORCHID LN
Chandler, AZ 85226--1140
NSF Award
2404520 – STTR Phase I
Award amount to date
$274,723
Start / end date
07/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this STTR Phase I project involves the development and deployment of an integrated energy storage solution designed to harness and store excess energy from renewable sources such as wind and solar. This project addresses the critical need for effective energy storage systems to manage the intermittency of renewable energy sources. The anticipated commercial impacts include significant advancements in grid stability and the potential reduction of reliance on fossil fuel-based peaker plants. The market for grid-scale energy storage is projected to reach billions of dollars globally, positioning the technology to capture a substantial share of this growing market. Additionally, the project is expected to contribute to environmental sustainability by facilitating a higher penetration of renewable energy sources into the grid, thus reducing carbon emissions and enhancing air quality. The successful development and implementation of this technology could also foster greater scientific understanding of advanced energy storage systems and promote further technological innovations within the renewable energy sector.
The intellectual merit of this project stems from its innovative approach to combining thermal and mechanical energy storage using supercritical carbon dioxide (sCO2) as the heat transfer fluid in a Packed-Bed Thermal Energy Storage (PB-TES) system. The research objectives focus on optimizing the heat transfer efficiency and minimizing mechanical losses in the system, aiming for a heat transfer efficiency greater than 90% and a levelized cost of storage (LCOS) below $60/megawatt hour (MWh). The research will involve detailed design, modeling, and testing of PB-TES configurations to handle the high pressures of sCO2 and achieve efficient thermal management. Anticipated technical results include the development of a scalable, cost-effective energy storage system that can be rapidly deployed and integrated with existing renewable energy infrastructures. This project not only aims to advance the state-of-the-art in energy storage solutions but also enhances the scalability and economic feasibility of renewable energy systems, contributing significantly to the field of energy engineering.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECATE LLC
STTR Phase I: High-resolution, spatially selective intraspinal stimulator to restore sensation in spinal cord injury patients.
Contact
3686 BARHAM BLVD APT H301
Los Angeles, CA 90068--1153
NSF Award
2403910 – STTR Phase I
Award amount to date
$274,976
Start / end date
06/15/2024 – 05/31/2025 (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 Technology Transfer (STTR) Phase I project is a novel custom-made micro-probe electrode system for restoring organ function in nervous paralysis and paralysis-related conditions such as neurogenic bladder or fecal incontinence. The electrode system aims to provide real-time, bi-directional, closed-loop spinal cord machine interface to restore both sensation and volitional motor control in spinal cord injury (SCI) patients. The system aims to provide restorative function for the 5.4M US paralysis victims, while providing smaller, more accurate, higher capacity implantable electrode platform for the $7.6 B neurorehabilitation and neurostimulation market.
This Small Business Technology Transfer (STTR) Phase I project aims to demonstrate the preclinical feasibility of a novel spinal cord neural interface as an effective scalable platform for rehabilitating paralysis-related conditions including neurogenic bladder and mobility. This project will develop a new type of neural interface that delivers selective stimulation to specific targeted regions of the patient?s spinal cord in order to evoke a target sensation. For example, bladder fullness will trigger the proposed intraspinal stimulator to deliver safe current pulses to the patient?s spinal cord to reenable the sensation of bladder fullness. The proposed probe will also sense the patient?s intention to urinate and relay the signal to a bladder stimulator to reenable patient?s control over their micturition. Nanopatterned stimulating electrodes will be fabricated and coupled with custom-designed complementary metal oxide semiconductor (CMOS) chips to deliver safe and spatially selective current pulses. The system aims to bypass the spinal cord injury to restore communication between the subject?s body and brain. The system will be validated in rodent nervous models and characterized 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. -
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
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 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. -
EDNA BIOTECH, INC
SBIR Phase I: Point-of-Care Diagnostic Tool for Identifying Extended Spectrum ?-Lactamase E. Coli in Urinary Tract Infection
Contact
2265 E FOOTHILL BLVD
Pasadena, CA 91107--3658
NSF Award
2233653 – SBIR Phase I
Award amount to date
$274,975
Start / end date
02/15/2023 – 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 Innovation Research (SBIR) Phase I project lies in demonstrating the commercial viability and clinical benefit of a point-of-care diagnostics device based on novel technologies for patients with urinary tract infections. There are 10 million primary care visits for urinary tract infections per year in the United States. More than 15% of these patients suffer antibiotic-resistant infections. Clinical studies have shown that accurate identification and early diagnosis of the antibiotic resistance of the infecting bacteria shorten the treatment period, eliminate antibiotic misuse, and reduce average patient costs. However, on-site diagnostic testing that returns molecular information about the bacterial identity and antibiotic resistance remains a significant challenge. Current laboratory-based tests are costly, have long turnaround times, and require skilled technicians and well-equipped laboratories. In most cases, this results in empirical antibiotic prescriptions before the information is returned from test results. Developing rapid, on-site, easy-to-implement, and frequently used antimicrobial resistance screening is essential to combat the ongoing threat of antimicrobial resistance and antibiotic misuse. This device will be suitable for outpatient clinics, home healthcare, and inpatient facilities. It will enable a shift from empirical to evidence-based treatment of bacterial infections.
This Small Business Innovation Research (SBIR) Phase I project will develop a point-of-care device for the on-site identification of E. coli and associated extended-spectrum ?-lactamase (ESBL) antibiotic resistance genes in urinary tract infections from unprocessed urine samples. The device uses novel, patent-pending electrochemical nucleic acid sensing techniques and a loop-mediated isothermal amplification assay to semi-quantitatively measure target bacterial genes. The device consists of a disposable microfluidic cartridge and a portable multifunctional reader. The self-contained microfluidic sensing cartridge supports sample preparation, isothermal amplification, and sequence-specific electrochemical detection. This novel combination of sensing technology and highly integrated sample handling microfluidics will enable the development of critically needed point-of-care diagnostic solutions. The project will demonstrate the specificity of bacterial detection, the ability to identify multiple genotypes, the ease of device operation, and the portability of this point-of-care 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. -
EMPALLO, INC.
SBIR Phase I: Developing Artificial intelligence Models to Predict In-hospital Clinical Trajectories for Heart Failure Patients
Contact
809 PEACHTREE BATTLE AVENUE NW
Atlanta, GA 30327--1313
NSF Award
2304358 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/01/2023 – 07/31/2025 (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 includes improving cardiovascular management, personalized medicine, inclusivity for historically underserved populations, and clinical trial design. The project could improve the health and wellbeing of heart failure (HF) patients while saving billions of dollars in HF hospitalization costs. If the technology proves feasible, it could shift the paradigm of HF management from reactive to proactive. The proposed machine learning model extracts latent features and detects subtle patterns from clinical data, which derives digital biomarkers that can potentially enable novel phenotype discovery and eventually personalized medicine. The digital biomarkers derived from the proposed innovation, when used in clinical trials, could also improve inclusivity and greater generalizability of novel therapies when applied to diverse populations. The proposed technology could enable clinical trial sponsors to achieve the desired statistical power with smaller patient populations. This, in turn, would enable faster, cheaper, and more effective clinical trials.
This Small Business Innovation Research (SBIR) Phase I project mitigates the burden of heart failure (HF), which afflicts over 6.5 million Americans. As the leading cause of hospitalization in the U.S., HF results in more than $29 billion in hospital charges and $11 billion in hospitalization costs, annually. A large portion of hospitalization costs are driven by readmissions, with about 20% of heart failure patients readmitted within 30 days of discharge. The fundamental challenge is the variability of this disease. A treatment regimen that works for one patient might not work for another, even if they show similar symptoms. Anticipating clinical trajectories, treatment response, and potential complications, and translating those insights into actionable interventions is key to improving outcomes for HF patients. To help clinicians anticipate a HF patient?s response to treatment and adverse events during hospitalization and enable personalized intervention planning, this project will develop explainable and generalizable multimodal artificial intelligence (AI) models that predict a HF patient?s clinical trajectory shortly after admission. This technology is a methodological innovation grounded in large-scale, multi-center, clinical data. The key milestone in Phase I is to yield a reasonably accurate predictive AI model, cross-validated between the data of two large healthcare 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. -
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
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. -
ENCHROMA INC.
SBIR Phase I: Contact lens for assisting color vision deficiency
Contact
2001 ADDISON ST
Berkeley, CA 94704--1192
NSF Award
2335248 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2024 – 04/30/2025 (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 biocompatible dye integrated into contact lenses for improving color recognition in people with various forms of color blindness. The technology aims to improve color recognition in patients with color vision deficiency (CVD), due to either hereditary (11.3 million anomalous trichromats) or acquired (33 million retinopathies and maculopathy affecting color vision) causes. Common reasons include macular degeneration, Type II diabetes retinopathy, and glaucoma. Classroom information is also nearly 80% color-coded, and the technology poses a more equitable learning environment for color vision deficient students who wear contact lenses and in a less externally obvious manner. The system thus poses the potential impact of improving learning, task performance, and quality of life as demonstrated through spectrally identical external eyewear studies for contact lens wearers. The total addressable domestic market exceeds 5 million patients with over 1 million patients suffering from hereditary causes and 4 million from acquired color deficiencies, resulting in an annual market of up to $326 million.
This Small Business Innovation Research Phase I project aims to embed narrow-band hydrophobic dyes into polyvinyl alcohol (PVA), a primary hydrophilic contact lens (CL) hydrogel, to create a contact lens that offers color vision deficiency assistance. Narrow-band absorber dyes provide spectral shaping, modifying light reaching the eye. The technical hurdles to be addressed is developing a fabrication method which ensures the dyes and PVA are embedded into a stable format such that they do not leach out during prolonged submersion and wear. A novel chemical process that combines dyes into a common solvent, when combined with the PVA-water solution will be integrated into a contact lens such that it permeates and impermeates the porous substrate without precipitating. Upon curing and cross-linking, this embeds less than a microgram of hydrophobic narrow-band dyes to create a thin and stable lens layer. The effects will quantified using optical spectroscopy and mass spectrometry to provide a basis for a human grade contact lens.
This award reflects 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
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. -
ENVISION HEALTH TECHNOLOGIES INC
SBIR Phase I: ADAPTIVE PERIMETRY FOR HEAD MOUNTED DEVICES
Contact
16 STURGIS RD
Bronxville, NY 10708--5003
NSF Award
2415015 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2024 – 04/30/2025 (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 the development of a novel tool for the diagnosis and monitoring of functional visual field (VF) defects due to glaucoma.?Glaucoma, a leading cause of blindness, is asymptomatic in its early stages and challenging to diagnose, often resulting in late detection.?3 million Americans have a diagnosis of glaucoma, and this number is expected to double by 2050 contributing to a market size for treatment exceeding $7 billion by 2028. Early identification of disease and disease progression is key in preventing vision loss. Using a novel testing method, this technology will capture VF changes with higher sensitivity and specificity than the current standard of care. If successful, the proposed solution will allow for earlier detection of glaucoma and glaucomatous progression and facilitate earlier clinical intervention by eye care providers, reducing the overall burden of disease and incidence of irreversible vision loss.???
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This Small Business Innovation Research Phase I project aims?to improve the early detection of vision loss due to glaucoma through the development of fully automated adaptive perimetry software. Conventional VF testing, known as static automated perimetry (SAP), lacks sensitivity, often leading to late diagnosis of glaucoma and irreversible vision loss. With SAP, defects can only be detected when they affect at least 3 degrees of the visual field, providing only a macro understanding of vision loss. This project aims to develop a fully automated adaptive perimetry test that combines the uniformity and standardization of SAP with greater precision and individualization of an adaptive test strategy. This novel testing algorithm will intelligently adjust stimuli based on individual responses, increasing the sensitivity and specificity of early defect detection, and mapping functional deficits to retinal anatomical defects. Objectives include mathematical modeling of the retinal pathophysiology of glaucoma, development of spatial analysis for real-time test location determination, development of methods for active correction of fixational errors using eye-tracking, and determination of suprathreshold contrasts.?
This award reflects 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
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. -
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. -
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
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
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. -
FIGURE 8, INC.
SBIR Phase I: Recovery of NH3 from Livestock Manure for Clean, Zero-Carbon Fuel
Contact
6094 MADBURY CT
San Luis Obispo, CA 93401--8244
NSF Award
2332849 – SBIR Phase I
Award amount to date
$274,922
Start / end date
05/01/2024 – 04/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase I project is to promote the swift decarbonization of industries, in particular the synthetic nitrogen (N) fertilizer industry which generates 33.8 Megatonnes (Mt)/year (y) of life cycle assessment (LCA) carbon dioxide equivalent (CO2eq) emissions in the U.S. The proposed technology provides an alternative to the current N fertilizer production by recovering N from livestock manure and producing renewable, low-carbon ammonia (NH3) as a fuel. Green NH3, on the other hand, is costly and still requires long-term development to be commercially viable. Until Green NH3 becomes affordable, the renewable NH3 produced by the proposed technology can serve as a bridge fuel to help the industries start energy transition now. This technology could replace half the current synthetic N fertilizers. Manure generates 180 Mt of CO2eq emissions by applications to the soil. This technology has a significant potential to reduce GHG emissions. The market value of the N fertilizers is about $10 billion in the U.S. The estimated dollar value of the target market would be half that amount. The proposed innovation will help advance a fundamental scientific and engineering understanding of a consecutive liquid-gas (LG) and gas-liquid (GL) multiphase and multi-component mass transfer coupled with chemical reactions, a common phenomenon in many chemical and biochemical processes.
This project's intellectual merit is in acquiring the knowledge involved in a complex, consecutive LG-to-GL mass transfer, which is essential to a wide range of industries. A new kinetic model for such a mass transfer of NH3 will be developed and applied to optimize the operating parameters to maximize the NH3 recovery efficiency, which has never been accomplished before. The Phase I objective is to increase the NH3 absorption mass transfer rate by an order of magnitude by applying the model. The model will be validated by comparing the model against experimental data to be collected in Phase I. The experiments will be conducted using two columns: one for the NH3 stripping and another for the NH3 absorption. The operating parameters will be explored to maximize the mass transfer kinetics based on the model for flushed manure samples. The anticipated result would be a new, validated consecutive LG-to-GL mass transfer model, establishing the relationship between the mass transfer rate and the operating parameters and optimizing parameters that would significantly increase the NH3 recovery efficiency, making the technology affordable to livestock farmers.
This award reflects 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)
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 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. -
FLAWLESS PHOTONICS, INC.
SBIR Phase I: Revolutionizing Optical Communications from Ground to Space with Novel ZBLAN Manufacturing
Contact
19345 BROOKTRAIL LN
Huntington Beach, CA 92648--5579
NSF Award
2423603 – SBIR Phase I
Award amount to date
$274,999
Start / end date
05/01/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Phase I Small Business Innovation Research (SBIR) project builds upon the unique properties of ZBLAN, short for Zirconium-Barium-Lanthanum-Aluminum-Sodium fluorides, which boast many advantageous properties, including a wide transparency window, superior optical transmission loss, and small phonon energy when compared to state-of-the-art silica. ZBLAN can unlock radical performance improvements for telecommunication products, fiber lasers, and remote sensors. However, commonplace manufacturing techniques cannot develop ZBLAN without light-scattering defects, rendering glass to applications but ineffective for many of the most important ones. Based on modern automation, robotics, and processing techniques, this project builds a path to manufacturing this fiber to limit the growth of light-scattering defects. Moreover, the manufacturing process is further enhanced when performed in space. Due to the exceptional characteristics of microgravity, it is possible to produce a ZBLAN product devoid of scattering defects, offering a transformational leap in optical transmission capabilities. After successful preliminary tests, this project will develop the necessary hardware to develop ZBLAN at scale, both on Earth and in microgravity. This project is expected to catalyze a high growth, high throughput, scalable and profitable in-space production process with meaningful societal impact.
This SBIR Phase I project proposes to develop an instrument capable of rapidly casting molten ZBLAN glass through minute-scale apertures, aiming to streamline manufacturing by eliminating bubbles and restricting defect growth. This project seeks to overcome the challenges historically hindering ZBLAN optical preform production. The approach will produce high-value products that can radically improve optical capabilities by identifying a method to create precise preform core dimensions. Currently, state-of-the-art manufacturing processes lack the accuracy and standardization required to meet ZBLAN's stringent tolerances. This project leverages extensive theoretical calculations to optimize the melting, casting, and annealing of ZBLAN, which is crucial for minimizing crystalline defects and maximizing transparency. By leveraging novel automation techniques, harnessing the unique properties of microgravity, and effectively managing heat loads, this project is pioneering the in-space manufacturing industry, as demonstrated by the company's recent ISS experiment where astronauts pulled ~10km of ZBLAN in space. The project will develop an automated ZBLAN manufacturing technology to enable scalable terrestrial and in-space ZBLAN production. It will allow the company to develop new optical products - starting with free-space mid-wave infrared optical links. This innovative approach is poised to pioneer in-space manufacturing and propel the development of high-value ZBLAN products.
This award reflects 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. -
FORCHUN LLC
SBIR Phase I: Universal Electric Propulsion System Gridded Hall Thruster For Satellite Life Extension And Space Debris Removal
Contact
6710 LOOKOUT BND
San Jose, CA 95120--4649
NSF Award
2335156 – SBIR Phase I
Award amount to date
$274,958
Start / end date
07/01/2024 – 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 Phase I Small Business Innovation Research (SBIR) project has far-reaching impacts that benefit the global community by offering crucial solutions to uncertain challenges encountered in space, both in Earth's orbits and deep space. The successful outcome of the project is an innovative electric propulsion (EP) system which will be a foundation for on-orbit servicing systems. The new EP technology will directly benefit satellite operators by potentially extending the operational lifespan of their satellite fleet with its high propellant utilization capability. It will also offer solutions for safely removing end-of-life space objects from orbit by utilizing its high thrust capabilities for de-orbiting. Furthermore, the innovative EP system opens opportunities for deep space applications, such as deflecting asteroids, which were previously only achievable using high-impulse systems like the gridded ion thruster (GIT). Overall, the new EP system holds immense potential for commercial and scientific advancements in the space industry.
This SBIR Phase I project proposes to demonstrate the concept and feasibility for an innovative EP system that enables various on-orbit service activities. The project aims to combine two distinct electric propulsion technologies, namely the GIT and the Hall thruster (HT), into a single ion thruster known as the Gridded Hall thruster (GHT). This integration will involve specific performance measurements and characterizations to evaluate the success of this novel combination. The GHT addresses the limitations associated with individual technologies. It overcomes the low thrust limitation of GIT and the low specific impulse of HT, as well as mitigates the inherent process instabilities like the ionization-induced instability found in HT. By doing so, the GHT achieves optimal performance and extends its usable lifetime. Additionally, the GHT offers another potential significant benefit. It enables neutralizer-free electron generation, which simplifies the ion thruster architecture and improves overall efficiency. This advancement in electron generation represents a simpler and more streamlined approach to ion thruster design. The successful completion of this project will contribute significantly to the advancement of electric propulsion technology and pave the way for critical applications in on-orbit servicing 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. -
FORSEE, LLC
SBIR Phase I: Fire-Resistant Polymer Composites Using Recycled Processed African-American Hair
Contact
1851 RIVERTON DR
Prattville, AL 36066--1918
NSF Award
2420037 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 Phase I project is in addressing an increasing need to develop more eco-friendly, non-toxic fire-resitant materials in applications ranging from protective gears for firefighters, for industrial workers working in hot environments, and in construction materials such as tiles, wall panels, and roofing. Creating improved fire-resistant materials for homes, buildings, and personnel will decrease costs to homeowners and insurance companies and can potentially save lives. The rise in global temperature, and the escalating frequency and severity of structural and wildfire incidents at scale, combined with need to use non-fossil fuel based materials in industry underscores this critical need. This project is likely to to introduce a brand new natural polymer - Afro hair- to develop as an additive to fire-resistant products. A successful development of this technology is also likely to create economic opportunities for a broader section of society that would participate in this novel endeavor.
Processed African-American hair possess notable characteristics such as a high nitrogen content, robust elliptic structure, and cross-linked cell membranes. When subjected to high heat levels, these cell membranes expand and create a protective barrier, hindering oxygen from reaching the substrate and thus preventing the spread of fire and heat. The processed material does not liquefy, merge, or melt and can act as insulation or a barrier, impeding or reducing fire spread. This remarkable discovery represents a significant advancement in creating lightweight, fire-resistant building materials, clothing, and reinforcing fire-resistant plastics. Phrase I R&D plan focuses on optimizing material compositions where African-American hair loading in the composite mix will adjusted through scientific experimentation for processing ease and improvement of desired properties. These compositions will be then used to develop prototype products that meet or surpass the industry performance standards set by existing fire-resistant products.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FOURIER LLC
SBIR Phase I: Thermoformable Technical Ceramics for Thermal Management Solutions
Contact
40 WEDGEWOOD ROAD
West Newton, MA 02465--1918
NSF Award
2415557 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2024 – 07/31/2025 (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 is to establish, understand, and improve a thermoformable ceramic technology that uniquely provides a scalable pathway to overcome significant thermal management limitations faced by next-generation electronic systems, including 5G cellular devices, high-performance vehicles, renewable energy, and consumer electronics. Thermal management limitations in electronics are a $26B dollar problem that spans industries and is the cause of 55% of all electronic system failures. Within this space, thermal management materials are considered the innovation bottleneck in electronic applications, especially for components with reduced size and weight requirements. The thermoformable ceramics and scalable manufacturing processes proposed in this project offer a new materials paradigm to deliver thermal management solutions with high production volumes, short lead times, and low prices. Further, this project provides a critical path to reestablish U.S. manufacturing of these next-generation technical ceramics enabling domestic economic benefits and supply chain resiliency.
This Small Business Innovation Research (SBIR) Phase I project aims to address and mitigate the remaining technical challenges for the commercial adoption of thermoformable ceramics in thermal management applications. Thermoformable ceramics are uniquely positioned to provide thermal management solutions for electronics due to their ability to conduct heat effectively while remaining electrically insulative, like diamond. However, unlike diamond, thermoformable ceramics can be manufactured at scale and with precise three-dimensional geometries, offering unprecedented thermal materials solutions for the electronic industry. The first technical challenge addressed in this project is to understand and improve the material's robustness against solvent attack. This enhancement will expand the target markets to include maritime technologies and fluid-based heat exchanger technologies. The second challenge is to establish the scalability of part sizes and feature complexity. Successfully addressing this will enable thermoformable ceramics to accommodate larger part sizes, higher production volumes, and entry into higher-value markets. The third challenge is to achieve best-in-class performance in application-based testing. Meeting this objective will facilitate faster customer adoption by reducing the technology's risk through market-relevant 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. -
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. -
FUM TECHNOLOGIES, INC
SBIR Phase I: Materials Science Digital Experts and AI-Powered Data Platform
Contact
178 HARVARD ST
Cambridge, MA 02139--2723
NSF Award
2423569 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/15/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase I project lies in its potential to significantly streamline the process of discovering and utilizing novel materials, vital for advancements in sectors like healthcare, energy, and national defense. A large portion of essential materials data is currently inaccessible, hidden within complex documents or known only to a handful of experts. This project aims to develop a technology that transforms this inaccessible data into useful information, drastically reducing the time needed for material selection from weeks to minutes, thereby accelerating scientific and technological advancement and enhancing national prosperity and security. The market for advanced materials is projected to grow to $2.1 trillion by 2025, and the business model for this initiative focuses on providing technological services to materials suppliers, ensuring a sustainable competitive advantage by improving access to and usability of critical data. Initially targeting the semiconductor industry and industries reliant on polymers, the strategy is to achieve significant market penetration, with anticipated substantial annual revenues by the third year of production, underlining its impact across multiple high-value industries.
This Small Business Innovation Research (SBIR) Phase I project addresses the critical challenge of "dark" data in materials science?valuable data that is unutilized because it is trapped in diverse formats or accessible only to a few experts. The primary research objective is to develop an artificial intelligence-driven platform capable of extracting and synthesizing this data into an accessible and interpretable format. The proposed research involves the creation of a customizable, conversational digital expert system that leverages advanced Large Language Models (LLMs) to interact with and learn from heterogeneous data sources, including natural language texts and inconsistent file formats. This system will enable the transformation of complex datasets into structured, actionable insights, facilitating rapid and accurate materials selection and application. The anticipated technical results include the successful demonstration of the platform's ability to interpret and organize large volumes of dark data, significantly reducing the time and expertise required to access this information. This breakthrough has the potential to catalyze discoveries and innovations in materials science by making decades of accumulated data readily available for research and commercial 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. -
FUNCTION THERAPEUTICS, INC.
SBIR Phase I: Structure-guided design of anti-inflammatory modulators of protease-activated receptor 1 (PAR1)
Contact
1626 N PROSPECT AVE APT 1901
Milwaukee, WI 53202--2437
NSF Award
2223225 – SBIR Phase I
Award amount to date
$274,710
Start / end date
03/15/2023 – 08/31/2024
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 that a deeper structural understanding will be developed of protease-activated receptor 1 (PAR1), an important target for promising new anti-thrombotic and anti-inflammatory drugs. The project will also support the development of new compounds targeting PAR1 with the potential for improved potency and safety profiles. Such compounds could represent a new drug class for the treatment of inflammation-related diseases, including kidney disease.
The proposed project involves the confirmation of the binding site on PAR1 of small molecule ligands called parmodulins. A detailed characterization of this binding site will support the rapid design, synthesis, and testing of new and improved parmodulins with superior properties as oral medications. A combination of computational, structural biology, and synthetic methods will be combined with PAR1 cell assays to confirm the binding site and develop more detailed structure-activity relationships of the parmodulins. It is also anticipated that novel parmodulins will be identified in this project with improved safety and stability profiles.
This award reflects 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. -
GEOFINANCIAL ANALYTICS, INC.
SBIR Phase I: Tiered multi-satellite observation scheme for methane quantification and attribution
Contact
141 BULKLEY AVE
Sausalito, CA 94965--2231
NSF Award
2405214 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 06/30/2025 (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 is in being able to assess and mitigate company-level methane emissions from oil & gas operations across the globe. Methane, with its global warming potential 85 times that of carbon dioxide over a 20-year period, represents a critical target in meeting the climate change goals. Specifically, the proposed intervention could help flatten the methane emissions curve ? cutting emissions of US oil & gas producers by 75% over five years. This 75% reduction in emissions from fossil fuels aligns with the International Energy Agency?s goal for 2030 that would enable limiting global warming to 1.5°C. Additionally, decreased global warming mitigates the frequency and severity of climate-related disasters such as wildfires, floods, and heatwaves. These changes have profound implications for biodiversity, ecosystems, and human livelihoods, particularly in vulnerable regions which includes much of the U.S.
The proposed technical innovation is a computationally efficient, tiered multi-satellite monitoring system that tracks daily-to-weekly methane emissions from oil & gas assets across the globe. These are then used to assess company-level emission performance and benchmark companies amongst their peers. The technology integrates satellite observations from multiple sensors, deep learning models, and statistical data aggregation. A crucial component is a deep learning model which automatically detects methane plumes in high-resolution imagery from satellites not designed to detect methane, like the Landsat suite and Sentinel-2. These plumes are used to refine TROPOMI baseline observations. Most quantification methods, and deep learning models in particular, are too computationally expensive to use at a global scale. Thus innovative, computationally efficient methods for emission quantification and statistical data aggregation must be developed. A significant technical risk is that these new computationally efficient methods may sacrifice some accuracy in methane quantification. Larger uncertainties using these methods could result in a data product that lacks meaningful insights. The intellectual merit of the proposed project is in developing computationally efficient new methods which strike the appropriate balance between efficiency and accuracy that meet real-world information needs of key stakeholders.
This award reflects 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. -
GLOBAL ENERGY CORPORATION
SBIR Phase I: A Fusion-Fast-Fission Reactor
Contact
5025B BACKLICK RD
Annandale, VA 22003--6044
NSF Award
2423343 – SBIR Phase I
Award amount to date
$274,936
Start / end date
05/01/2024 – 01/31/2025 (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 Phase I Small Business Innovation Research (SBIR) project is a safer, less expensive, proliferation-resistant hybrid nuclear technology. Previous experiments fissioned natural uranium without enrichment, thereby removing nuclear proliferation as one of the roadblocks to the use of nuclear power. The hybrid sub-critical reactor has no chain reaction and can't run away. The hybrid is cooled with helium gas which can't become radioactive. Without cooling water, a large pressure dome isn't required reducing plant cost and site size. The hybrid produces fusion neutrons without large lasers or enormous magnets while keeping its fuel at a billion times the fuel density of tokamaks. The fast fusion neutrons will fission thorium and spent reactor fuel. A good business case comes from being paid twice to fission existing nuclear waste while generating electricity. Hybrid fuel rods can be installed in existing reactors to "burn" nuclear waste on-site while reducing the time between refueling cycles. The hybrid reactor makes the best use of fusion's fast neutrons and fission's high energy density without the complications of either. A new, safer, cleaner nuclear technology can reduce carbon emissions and present environmental advantages.
This SBIR Phase I project proposes to characterize the Lattice Confinement Fusion-Fast Fission of depleted uranium through time-resolved neutron spectroscopy. Lattice Confinement Fusion holds deuterium fuel in a metal lattice as an electron-screened, cold plasma at a billion times the plasma density of a tokamak. Extended Electrodynamics may provide insight into the fusion driver. Earlier experiments measured the fast fission of deuterium-loaded natural uranium and thorium by high-resolution gamma (HPGe) spectroscopy, alpha/beta scintillator spectroscopy, and solid-state nuclear track detectors. Neutron energies were calculated to average 6.4 MeV. Phase I will use these diagnostics and measure the fast neutron spectrum with multiple neutron scintillator spectrometers with 500 MHz sampling rates and 200 keV energy resolution from 300 keV to 20 MeV. We expect to observe the 2.45 MeV Deuterium Deuterium (DD), 14.1 MeV Deuterium Tritium (DT) fusion neutrons and conventional neutron fission spectra peaking at 1 MeV, averaging 2 MeV with a Maxwellian tail past 10 MeV. Phase I control, and active experiments will be shielded against cosmogenic neutrons. Four sets of ten-day runs are planned with four simultaneous micro-reactors per run. The neutron flux, drive currents, and voltages will determine the scaling efficacy of a fusion-fast-fission sub-critical hybrid reactor 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. -
GNU COMPANY, LLC
SBIR Phase I: Safety Syringe Needle for Prevention of Unintended/Accidental Puncture (Needlestick Injury)
Contact
147 HIGHLAND AVE
Winchester, MA 01890--1435
NSF Award
2219892 – SBIR Phase I
Award amount to date
$249,369
Start / end date
05/01/2023 – 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 is a novel medical device for intramuscular injections that will reduce needlestick injury. Unintended or accidental puncture is the second most common occupational hazard for healthcare staff. An estimated 385,000 needlestick injuries occur in the United States each year impacting 5.6 million healthcare workers. Needlestick injury represents one of the largest risks, both financially ($258 million annually) and medically (e.g., bloodborne pathogen exposure), to healthcare providers. This project aims to develop a novel, flexible hypodermic needle with a safety syringe that enables rapid injections while replacing sharp needles and significantly reducing risks of unintended health care provider injury.
This Small Business Innovation Research Phase I project provides a novel, flexible, polymer needle-based safety syringe for health care providers to perform intramuscular injections in patients. A novel and variable stiffness shaft is integrated with an external safety lumen mechanism to create an integrated delivery system with the same delivery reliability and repeatability as standard needlesticks. The design will be prototyped and evaluated under a variety of human factors considerations. The device will be required to pass several mechanical tests for puncture, insertion, and lumen integrity in a consistent manner, as anticipated during routine clinical 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. -
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
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
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
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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. -
HENSUN INNOVATION LLC
STTR Phase I: Colleague: An AI-Enhanced Assistant Empowering K-12 Teachers with High-Quality Math Instruction
Contact
906 W 2ND AVE STE 100
Spokane, WA 99201--4540
NSF Award
2423365 – STTR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project will contribute to the development of the nation?s STEM workforce through enhancing K-12 students? mathematical proficiency beginning with support for educators. The artificial intelligence (AI)-enhanced platform augments K-12 teachers? capacity to develop high-quality and inclusive math instruction to meet diverse students? learning needs. The innovation leverages rapid advancement of AI in transforming both the workforce and educational landscapes, providing educators with a companion to significantly improve students' math performance, critical thinking skills, and readiness for a future AI-enhanced workforce. Importantly, this platform will democratize access to high-quality educational resources, particularly benefiting teachers in under-resourced schools by alleviating their workload stress and fostering a community of shared knowledge and practices. The adoption of this platform offers significant commercial opportunities within a $15bn market for educational technology in K12 education and offers a model of industry-university partnership in the development of educational technology, providing a robust and research-based solution to enhance scientific innovation and practical, classroom-based applications of AI while keeping humans in the loop through participatory co-design with educators. The project not only aligns with the national interest by promoting scientific progress and educational excellence but also holds substantial promise for economic returns.
This Small Business Technology Transfer (STTR) Phase I project aims to tackle the pressing challenges in K-12 math education in terms of widened achievement gaps among student demographics, by developing education-specific AI technology. Phase I research and development will integrate new AI models which assist teachers in their ability to retrieve or generate lesson materials, catered to teachers? instructional approaches and their students? learning needs, and meeting research-based math instructional quality criteria. Personalized instruction, including formative assessment, auto-scoring and generation of diagnostic reports, targeted materials for enhanced student mastery or remediation as well as student feedback will be infused into the platform through iterative, participatory co-design student with 30 math educators and A/B testing with thousands of educators. Utilizing retrieval and augmentation models, nudging algorithms, and domain specific generative AI models that work alongside teachers to inspire creativity, agency, and growth that works alongside teachers, acting as a trusted companion, to prompt teachers to refine parts of the drafty lesson plan. This platform aims to shift the nature of AI-powered instructional technology with research-based practices tailored to domains and provided to educators in real time to transform how educators develop lesson materials and amplifies their ability to provide learners with more effective, personalized, and engaging instruction.
This award reflects 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. -
HYPERKELP INC
SBIR Phase I: Feasibility of an L5 GPS-Based Tsunami Detection and Alerting System
Contact
1702 SWALLOWTAIL RD
Encinitas, CA 92024--1259
NSF Award
2345775 – SBIR Phase I
Award amount to date
$274,694
Start / end date
06/01/2024 – 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 is in the development and deployment of an effective, affordable, and globally accessible detection and alert system for tsunamis on coastlines worldwide. Tsunamis are among the most significant ways in which the ocean impacts human civilization. With the increasing population density along coastlines and the global rise in sea levels, the potential for tsunamis to cause unprecedented harm is higher than ever. The proposed product providing enhanced wave height and arrival time maps to its customers could provide significantly more timely alerts to at-risk populations, providing them with essential evacuation information and crucial hours to prepare for approaching waves. This could herald a major shift in tsunami preparedness and resilience. This technology offers wide-ranging benefits for various groups and industries such as small island economies, defense operations, and commercial port operators.
To develop these capabilities, this project proposes a buoy-deployable software product that takes advantage of new generations of Global Positioning System (GPS) to detect tsunamis at sea, hours before they make landfall. It will use revolutionary advancements in GPS technology, particularly in vertical accuracy, to detect, prepare for, and mitigate the formidable threat of tsunamis. For the first time, new generations of GPS provide sufficient resolution to detect the subtle vertical displacement of the ocean surface caused by passing tsunami waves with a single receiver even in open ocean. The project will focus on the development of novel methods of signal classification using Dense Neural Network (DNN) and optimize them with rapid Machine Learning (ML) methods. This is expected to help demonstrate that tsunami signatures can be perceived in real-time by low-cost and low-power on-edge processing capabilities. When this new on-edge technology is deployed on widespread ocean buoys, it would form a robust tsunami detection network. These buoys will serve as sentinels, capable of sensing distinct sea level changes that signal an impending tsunami.
This award reflects 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 – 07/31/2025 (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. -
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
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 – 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 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
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. -
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
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 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. -
INVERSAI, INC.
STTR Phase I: Integrating Vision-Guided Collaborative Robots for Postharvest Processing of Produce
Contact
111 RIVERBEND RD
Athens, GA 30602--1514
NSF Award
2208902 – STTR Phase I
Award amount to date
$212,153
Start / end date
01/15/2023 – 12/31/2025 (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 is to empower the processors of harvested fruits and vegetables with the flexibility to use robotic automation to meet their labor needs. The automation uses collaborative robots (cobots) guided by computer vision, which are potentially safe around humans. The technology will help assure consistent produce quality and processing rates. Through a robust cobot-based solution, the project will provide an affordable, sustainable, and safe means for farms of all sizes to keep up with their production goals, which will sustain competition and the nation?s food supply. This project has the added benefit of upskilling workers in farms by creating openings for more technically oriented positions, both in monitoring and maintaining the cobots. Instead of tediously programming the cobot for each use, the project is introducing a new way of translating the tasks performed by humans to the cobot by learning from camera recordings. It will also improve understanding of how cobots can safely be used alongside humans in a shared working space.
This Small Business Technology Transfer (STTR) Phase 1 project aims to make it possible to use cobots with human workers on tasks that go beyond the traditional pick-and-place. The proposed technology will automate processing line tasks that require computer vision, which is challenging because accurate and reliable perception must guide the robot?s motion. Research has coalesced the technical challenges on the path to a viable commercial product around five steps. These start with a formal description of the task domain followed by using robust implementations of noise-tolerant machine learning algorithms for automatically learning the task, and end with a solution that integrates the learned task behavior with a vision-guided cobot system. Phase 1 will support research toward addressing two problems. The first is to design an intuitive way to elicit a precise specification of the client?s task domain. A digital conversational assistant will utilize multiple modalities for the elicitation. The second is the inability of available implementations to generate coworker-aware and efficient cobot movements. The research will investigate and develop significant improvements to the cobot motion to improve coworker safety while reducing the processing time by an expected 50%.
This award reflects 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. -
KNOX NETWORKS, INC.
SBIR Phase I: File-Based Digital Assets
Contact
1840 CENTURY PARK E STE 1600
Los Angeles, CA 90067--2116
NSF Award
2341319 – SBIR Phase I
Award amount to date
$274,193
Start / end date
05/01/2024 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a novel technical approach to regulated forms of digital money and securities, including money and government securities, commercial bank money and corporate securities, and others via tokenization of File-Based Digital Assets (FBDAs). Tokenization represents a new frontier in finance that was originally pioneered in blockchain and cryptocurrency, and has many commercial applications to make payments and securities settlement faster, more transparent, and more reliable in the current regulatory environment. FBDAs are not blockchain based and can improve upon existing global payment solutions in making systems more scalable, easier to integrate with other payment systems, and more privacy-enhancing for institutions and consumers. The platform also allows for open sourcing and increased financial inclusion through the digital identity solution which gives the ability to move assets without friction globally. The commercial potential of FBDAs is significant, and tokenization products can be sold to domestic and international commercial and central banks, and allow third-party providers to build out their own financial products. This project will explore the technical market for FBDA-based tokenization and gain user feedback to improve the technology?s commercialization potential.
This SBIR Phase I project proposes to research and create a production-ready (99.999% availability with defined RPO/RTOs) File-Based Digital Assets (FBDAs) product, a novel tokenization scheme applicable to not only currencies and tokenized deposits, but also to securities and other assets. FBDAs improve upon many of the issues that Distributed Ledger Technology (DLT) and traditional database systems have, particularly in the realms of scalability, interoperability, privacy, and programmability. FBDAs utilize a flexible fixed-denomination asset design that is simpler and more robust than Unspent Transaction Output UTXO-based systems while beating the performance of Account-based systems. In addition, FBDAs allow for a disaggregation of the asset layer from the transaction layer, thereby allowing for easier separation of Personally Identifiable Information (PII) and from programmability rules for specific transactions. The Phase I project proposes to further explore different design choices of FBDAs and get technical and customer validation on achieving scalability, interoperability and privacy prior to large scale commercialization. The Phase I project will include a sandbox environment to test out different architectural setups, modeling of different financial instruments to expand tokenization potential, and to receive customer feedback from real-world financial institutions.
This award reflects 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
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. -
LATTICE THERAPEUTICS INC
SBIR Phase I: Proof-of-concept of a customizable, next-generation RNA delivery particle
Contact
7144 13TH PL NW
Washington, DC 20012--2358
NSF Award
2413714 – SBIR Phase I
Award amount to date
$274,947
Start / end date
07/15/2024 – 06/30/2025 (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 the creation of a novel RNA drug delivery platform with implications for treatment of cancer and other various diseases with unmet medical need. Current delivery technologies fail to realize the potential of nucleic acid drugs because of limitations like target specificity, toxicity, and administration. Next generation delivery technologies are ultimately required to achieve the full therapeutic potential of nucleic acid drugs. The technology being developed in this project is designed to address the limitations of existing delivery modalities, resulting in a flexible platform with target- and cargo-customization ready for progression to evaluate multiple clinical disease targets. This will expand treatment options, initially for oncology targets, with further applications in gene editing and vaccines, and continue to address existing patient needs. The technology developed in this project has the potential to expand the nucleic acid delivery market and result in improvements to length and quality of life for individuals facing life-threatening diseases in multiple therapeutic areas in both the United States and globally.
This Small Business Innovation Research (SBIR) Phase I project will address the proof-of-concept milestones required to validate delivery of RNA cargoes to target cells using an engineerable protein nanoparticle. The particle platform has several key attributes incorporated that enable efficient and targeted delivery, and which are required for full platform functionality: 1) the ability to package nucleic acid, 2) display of targeting moiety, and 3) the ability to disassemble within the intracellular environment and release nucleic acid cargoes. In this project, particles engineered to target specific cancer cell surface markers will be 1) in vitro loaded with mRNA cargoes, 2) evaluated in vitro for delivery of RNA cargoes to specific cancer cells, 3) evaluated in vivo for delivery of RNA cargoes to target tumors with exceptional specificity, and 4) evaluated in vivo for efficacy of therapeutic RNA delivery. The result of this project will be a validated customizable delivery platform positioned for clinical development against multiple targets.
This award reflects 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
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. -
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. -
LIFE SEAL VASCULAR, INC.
SBIR Phase I: Aneurysm Sealing Device (ASD) for Endovascular Applications
Contact
2744 GANNET DR
Costa Mesa, CA 92626--4755
NSF Award
2407378 – SBIR Phase I
Award amount to date
$274,547
Start / end date
07/01/2024 – 06/30/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project lies in its revolutionary approach to treating abdominal aortic aneurysms (AAA), a significant health concern especially prevalent among the elderly. This project aims to introduce a novel device that promises to significantly lower the rates of aneurysm related complications and reduce the need for repeat invasive procedures, which are common with current treatments. By potentially saving significant healthcare costs and reducing the frequency of medical interventions, the device presents a transformative solution that could ease the financial burden on healthcare systems and patients alike. Moreover, the project has the potential to expand access to life-saving treatments in underserved and remote areas, thus leveling the playing field in healthcare accessibility. The commercial and societal implications of this innovation could spur economic growth through intellectual property generation and job creation, thereby contributing to the advancement of the biomedical engineering sector.
This Small Business Innovation Research (SBIR) Phase I project seeks to address the limitations of current endovascular treatments for abdominal aortic aneurysms (AAA) by developing a new device that aims to completely seal the aneurysm sac, eliminating the risk of post-procedure endoleaks. The research objectives include validating the device's adaptability to different aneurysm profiles and its compatibility with various aortic locations, ensuring broad patient applicability. The technical approach involves a compressible body unit designed for precision deployment and a dual function that allows for drug delivery post-deployment. The anticipated technical results include demonstrating the device's effectiveness in sealing aneurysms in a benchtop flow model, thereby setting the stage for potential regulatory approval. This project represents a significant leap forward in the treatment of AAAs, offering a more reliable and versatile solution compared to existing methods.
This award reflects 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
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. -
LIMAR AI INC
SBIR Phase I: Semantic 3D for infrastructure asset modeling, maintenance, and predictive analysis
Contact
11569 PRAIRIE SHADOW PT
San Diego, CA 92126--8000
NSF Award
2344140 – SBIR Phase I
Award amount to date
$274,904
Start / end date
07/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the on the effective maintenance, construction, resilience and performance of large-scale infrastructure. The technology developed in this work will dramatically improve the productivity, accuracy, and quality of the information products generated by surveyors and engineers charged with assessing, designing, and maintaining infrastructure. For example, the roughly 200M utility poles in US should be surveyed and corresponding solutions engineered approximately every three years for weather robustness, fire mitigation, line capacity, and for future overhead and underground extensions. The technology has broad application in adjacent domains like water, natural gas, mining, oil and gas, power generation, transportation, mapping, and construction.
This Small Business Innovation Research (SBIR) Phase I project integrates geometric methods for constructing detailed three-dimensional (3D) models from photographs with semantic methods used to segment and classify features or objects in two-dimensional (2D) photographs. Key challenges include building 2D-3D correspondence across the geometric (3D) and semantic (2D) techniques, improving computational efficiency, and creating user interfaces to interact with and label data. The integrated computer vision capability will be validated on datasets for electric power distribution infrastructure to extract critical features like line attachment points, pole height and inclination, wire gauges, pole deterioration, vegetation intrusion, electrical component 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. -
LIMELIGHT STEEL INC.
SBIR Phase I: Laser furnace to thermally decompose iron oxides for cost-competitive green iron production
Contact
2431 PERALTA ST STE 2471A
Oakland, CA 94607--1700
NSF Award
2404156 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/01/2024 – 04/30/2025 (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 reduce emissions, energy consumption, and hydrogen demands associated with one of the world?s more carbon-intensive industries?steelmaking. The leading green steelmaking process, green hydrogen direct reduction and electric arc furnace (H2 DR-EAF) is expensive, energy-intensive, and requires high-grade iron ore as a starting material, which accounts for only 3% of global iron ore resources. This project develops on a sustainable, low emissions, and energy-efficient laser heating method to convert low-grade iron ore into molten iron metal and steel. This approach lowers costs by 1) enabling the use of the low-grade feedstocks that make up 97% of the world?s iron ore supply and 2) implementing an energy-efficient and thermo-kinetically optimized heating approach. The commercialization of this technology would deliver a sustainable steelmaking process that is more cost-efficient than current green steel technologies and has a lower carbon footprint than any existing steelmaking approach, helping the United States steel industry secure a competitive advantage over other global producers of green steel. This approach has the potential to yield a market-disrupting technology poised to supplant carbon-intense, resource-demanding iron and steel production processes, resulting in an economically viable pathway to green steelmaking.
This Small Business Innovation Research (SBIR) Phase I project will develop a laser furnace that thermally decomposes iron oxide while reducing the amount of hydrogen required to produce green iron and steel, using blue laser diodes to rapidly heat iron ore to temperatures needed for thermal decomposition. Phase I will establish the feasibility of the approach as economically favorable to leading sustainable steelmaking techniques and validate its potential to significantly reduce energy consumption. In Objective 1, decomposition of low-grade iron ore, which contains <67% iron and higher amounts of impurities, into wüstite will be pursued by exploring the relationship between ore composition, laser heating parameters, and purity of the partially reduced ore. The thermal decomposition reaction mechanism and degree of decomposition will be evaluated. Objective 2 focuses on reducing wüstite from low-grade ore to iron metal, leveraging unprecedented temperatures enabled by laser heating, and investigating methods and process conditions to minimize hydrogen demand. Reduction reaction mechanisms, degree of reduction, and impurity content will be characterized. This work will provide a novel opportunity to produce molten iron metal from low-grade iron ores and reduce hydrogen demands, avoiding the need for high-grade ores and hydrogen requirements that limit other fossil-free ironmaking techniques.
This award reflects 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
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 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. -
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
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 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. -
LUMONIQ INC
SBIR Phase I: Nanoscale Hybrid Optical Interconnect Platform
Contact
3175 HANOVER ST
Palo Alto, CA 94304--1130
NSF Award
2423362 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial impacts of this Small Business Innovation Research (SBIR) Phase I project will involve revolutionizing internal computer chip connections, called interconnects, by replacing materials like copper with light-based connections. The high-speed interconnects are the information highways of modern-day computing systems, and, unfortunately, these highways are hitting fundamental peak capacities and interconnects are now a critical limiter to computer system performance. This project will advance photonic integrated circuits and computer interconnects by researching commercialization pathways for a new photonic approach, called coupled hybrid plasmonics (CHP), that uses the interaction of light and metals to squeeze light and devices down to nanometer-scale sizes. Commercialized CHP will potentially enable durable interconnect product advantages in bandwidth, power, area, and cost. The ultimate go-to-market motivation for commercializing CHP is to enable short-distance (meters down to millimeters), all-optical interconnects and replace electronic interconnects in computer systems (e.g., in the multi-trillion-dollar Information Technology and Telecommunications markets). The first commercialization challenge for CHP is to develop a manufacturing flow that uses mainstream processing.
This Small Business Innovation Research (SBIR) Phase I project will bridge the gap between CHP principles and industrial manufacturing. The primary challenge this project faces is that the CHP effect requires a new multi-layer stack ? metals, dielectrics, and semiconductors ? that does not exist today in mainstream silicon-photonics/semiconductor chip manufacturing facilities. Industrial CHP manufacturing recipes and device architectures are the gateway to future proof-of-concept prototypes and then products. The project will employ industry-standard simulation and modeling tools to rapidly design and evaluate candidate CHP recipes, devices, and circuits. It will quantitatively benchmark CHP devices and transceivers against today?s state-of-the-art silicon photonic circuits (e.g., ring-resonator based) and assess candidates based on the bandwidth, area, and energy consumption they achieve. The overall project goal is to create preliminary industrial manufacturing recipes and a design-library of CHP-based devices and transceiver circuits.
This award reflects 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
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 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. -
MAGNIFY BIOSCIENCES INC.
SBIR Phase I: Unlocking the Full Potential of Next-Generation Expansion Microscopy through Automation
Contact
1632 NORMAN DR
Sewickley, PA 15143--8557
NSF Award
2415004 – SBIR Phase I
Award amount to date
$274,998
Start / end date
06/15/2024 – 05/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project stems from addressing critical barriers in nanoscale bioimaging?specifically, the prohibitive costs, technical complexities, and specialized expertise required for super-resolution and electron microscopes, which range from hundreds of thousands to several million dollars with sample preparation costs up to thousands and processing times exceeding a week. This project introduces a transformative solution by automating Magnify Expansion Microscopy into a cost-effective device, enabling conventional optical microscopes to achieve detailed biological insights at the nanoscale. By reducing sample preparation costs to under $10 and cutting processing times to less than a day, this technology will democratize nanoscale imaging, expanding research capabilities across various scientific domains. It enables researchers in labs without advanced microscopes to explore molecular and structural changes in diseases, discover new biomarkers, and develop diagnostic and prognostic tests. Societal benefits include pioneering discoveries in untapped territories, innovative diagnostic and prognostic tools, and significant healthcare cost reductions. Commercially, equipping existing microscopes with the AutoMagnify device is set to revolutionize the high-end microscopy market, potentially creating a billion-dollar industry by dramatically enhancing speed, cost-effectiveness, and ease of use, paralleling the transformative advancements seen in next-generation sequencing in genomics.
This Small Business Innovation Research (SBIR) Phase I project aims to develop an automated AutoMagnify device that physically expands biological specimens up to 1000 times in isotropically in 3-dimensions, while preserving their spatial and molecular integrity. This advancement will enable conventional light microscopes to achieve imaging resolutions down to 25 nm, capabilities typically reserved for super-resolution and electron microscopy. By shifting the focus from costly optical enhancements to physical specimen magnification, this project offers a practical, scalable solution for widespread nanoscale bioimaging. The AutoMagnify system reduces the sample preparation time from traditionally over a week to less than 24 hours, dramatically lowering both the financial and technical thresholds for super-resolution imaging. This project builds upon foundational Magnify Expansion Microscopy techniques to develop new rapid protocols and leverage durable gel compositions that address machine handling and reliability issues. The expected result is a fully functional prototype that standardizes sample preparation and staining protocols, enabling researchers in academia and pharmaceutical companies using conventional microscopes to access super-resolution quality images for their discovery needs. This pivotal innovation not only makes advanced imaging techniques more accessible but also significantly extends the research capabilities of scientific laboratories globally, potentially redefining the landscape of nanoscale imaging.
This award reflects 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
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
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. -
MANZANITA COOPERATIVE, INC.
SBIR Phase I: Domestication of Western Lupine - Manzanita Cooperative
Contact
44280 GORDON LN
Mendocino, CA 95460--9758
NSF Award
2414864 – SBIR Phase I
Award amount to date
$254,903
Start / end date
07/01/2024 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research Phase I project lies in generating a novel sustainable, climate-resilient food source through development of lupine hybrids. By focusing on US-native, drought-tolerant lupines, this project will introduce alternative high-protein, low-water, native-derived options to traditional protein crops? ecological footprint. This project will enhance food security while increasing productivity from marginal lands with native crops? reduced input needs- aligning with NSF priorities toward ecological and public health stewardship. Project outcomes will provide more sustainable options for farmers than traditional commodity crops- without sacrificing land profitability. By introducing a protein-rich, low-water-use alternative crop, the project will promote consumers? access to nutritional density. As demand for plant-based protein grows, commercialization of these cultivars could position them toward the lead of a burgeoning plant protein market. This will support one FT position and one researcher to screen hybrids for desired traits to enable Phase II hybrid selection and patent protection. Upon Phase II completion, the project will move toward commercialization. Following this, at least 3 FT and 3 PT employees in R/D, Product Manager, Business Development and other roles will be filled to support projected growth.
This project proposes rapid domestication and commercialization of novel, native-derived lupines to address the need for sustainable, climate-resilient crop protein sources. This initiative focuses on development of heterozygous F1 lupine hybrids, incorporating the pauper allele from the 'Amiga' cultivar of European White lupine (EWL, Lupinus albus) into four drought-tolerant, US-native species (Lupinus arizonicus, Lupinus stiversii, Lupinus succulentus, Lupinus arbustus). This allele confers reduced alkaloid content, enhancing lupines? palatability without sacrificing the drought and disease resistance of native lupines. Phase I of the project will generate these hybrids through genetic marker-accelerated introgression of the pauper allele while overcoming challenges, including potentially reduced fertility from aneuploidy among US-native and EWL parents. The project?s comprehensive approach includes PCR-based genetic analysis to confirm presence of the pauper allele, alkaloid profiling to ensure the trait's expression in various tissues, and evaluation of growth and yield. Intellectual property protection is a cornerstone of our strategy, ensuring novel cultivars' commercial viability while maintaining control over the seed-to-consumer cycle to safeguard company innovations. Resulting crops will bolster modern agricultural resilience with a focus on sustainability, reduced crop inputs, and improved nutritional value, aligning with our aim to utilize native biodiversity for food security.
This award reflects 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
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. -
MATHINVESTMENTS, INC.
STTR Phase I: A Technology for Learning to Infer from Unlabeled Financial Data
Contact
3120 LEEMAN FERRY RD SW
Huntsville, AL 35801--5325
NSF Award
2343777 – STTR Phase I
Award amount to date
$274,936
Start / end date
07/01/2024 – 06/30/2025 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to enable long-term, above-average profit returns from investing into the U.S. stock market. Currently, investors rely on the financial models that can forecast the future business performance of company only by looking through a rear-view mirror, and, consequently, create risks for the speculative stock trading that does not deliver any actual goods or services. If successful, this STTR project will make an important social impact that is controlling speculation by discouraging stock trading of company without material changes to its valuation. The research and educational impact of the current project is that selected results from the proposed studies beneficial to the fundamental research will be made available to the U.S research community for analysis, data mining, and search and will be also used to enhance contents of undergraduate and graduate courses. The economic impact is that the proposed efforts will create new financial technology related jobs in the North Alabama region.
This Small Business Technology Transfer Phase I project will develop and validate innovative technology capable of learning to infer from time series financial data in a resource-scarce environment. This technology will address the following technical hurdles: (a) well-documented deficiencies of machine reasoning of the qualitative parts of financial reports and earning call transcripts containing information that is much richer than just the financial ratios; (b) current reliance of the language-based models including ChatGPT on human annotation in resource-scarce environment, (c) difficulties with transfer learning for extensive, specialized documents, and (d) scarcity of labeled financial text. The technology will be based on innovative algorithms that use language-based models to augment original unlabeled data and utilize such augmented data for predicting the company valuation far ahead of the existing models. The feasibility of the proposed technology will be conducted in collaboration with academic and industrial partners.
This award reflects 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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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
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 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
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 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. -
MIMIC SYSTEMS INC
SBIR Phase I: Refrigerant-free heat pump using high-performance thermoelectric materials and methods
Contact
19 MORRIS AVE BLDG 128
Brooklyn, NY 11205--1095
NSF Award
2415650 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is through the development of a more efficient and cost-competitive solid-state heat pump technology for heating and cooling. Buildings are one of the largest contributors to carbon emissions, substantially associated with heating, cooling, and domestic hot water production. As an all- electric technology, solid-state heat pumps can easily be powered directly by renewable power, such as solar or wind. This would not only reduce reliance on fossil fuels but will also contribute to the sustainable electrification of the built environment that is necessary to mitigate the effects of climate change. This refrigerant-free technology may also avoid refrigerant leaks that contribute to climate change. As a retrofit, it would enable multifamily residential buildings to comply with the emerging more stringent carbon emission standards. In New York City alone, this represents a potential $2.2 B market.
This project aims to increase the efficiency and cost-effectiveness of traditional solid-state heat pumps based on thermoelectric energy conversion by leveraging new thermoelectric materials and modern manufacturing processes to surpass the performance of traditional vapor-compression heat pumps. The approach aims to integrate the active components of thermoelectric heat pumps, specifically the thermoelectric legs and electrodes, directly and in intimate thermal contact with active heat exchanger surfaces leveraging ink-based thermoelectric systems with high figure of merit. The proposed configuration and manufacturing process minimizes the deleterious interface and heat pump substrate thermal resistances, increasing the system performance. A multi-disciplinary team will integrate scalable fabrication processes for thermoelectric materials using sintering with printable electronics on metal core substrates. The goal of this project is to determine the feasibility of the approach by building and testing a representative assembly that can be easily scaled up to provide larger heating and cooling capacities. This approach constitutes a radical redesign to how thermoelectric systems are assembled, unlocking new opportunities toward delivering sustainable and scalable solutions for heating and cooling.
This award reflects 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. -
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
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 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. -
MYANIML
SBIR Phase I: Early Disease Prediction with Cattle Muzzles Using Artificial Intelligence, Facial Recognition, and Camera Capturing Technology
Contact
14305 OUTLOOK ST
Overland Park, KS 66223--1253
NSF Award
2330500 – SBIR Phase I
Award amount to date
$274,866
Start / end date
07/01/2024 – 06/30/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project addresses the need for technologies that can benefit the production, protection, and health of agricultural animals, like cattle. The profit margins for cattle owners are very thin. Treating a disease costs cattle owners on average about $80 per head. By the time an owner can tell their cattle are infected, it is typically too late to prevent infection and the spread of the disease in the pen and feedlot. With the successful implementation of the proposed technology, cattle owners will save on average about $80 per head. For an average 500-head owner, pinkeye can impact 90% of the individual cattle herd if one individual animal is infected, costing over $15k to treat in the case of an outbreak. The proposed technology aims to reduce the cost to only the cost of one vaccine since the proposed system should alert the owner about this risk early, allowing early isolation before the disease is able to spread. The proposed solution would enable early disease detection, help to secure the US food supply chain, reduce the emission of greenhouse gasses, and benefit the US economy by preventing cattle loss.
This Small Business Innovation Research (SBIR) Phase I project proposes to demonstrate the feasibility of a novel artificial intelligence (AI) technology to detect Bovine Respiratory Disease early on in a small pilot study. The company will develop an app (beta-version) that can automatically take pictures of cattle, use AI to analyze the muzzle, and then immediately send a notification of infected cattle to the cattle owner. When new calves that are sick enter a feedlot setting, they typically are not as active as healthy calves. There are also visible symptoms such as droopy ears, nasal discharge, and watery eyes. However, since the calves might be stressed due to travel, these symptoms do not necessarily mean the calf is sick, making it challenging to identify sick cattle. If successful, the proposed solution would reliably identify sick cattle and thereby enable early, targeted treatment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MYCONAUT LLC
SBIR Phase I: Unlocking the Potential of Mycoremediation: An Integrated Biological Approach to Combatting PFAS Contamination
Contact
7260 COUNTY ROAD 550
Marquette, MI 49855--9766
NSF Award
2337246 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/15/2024 – 04/30/2025 (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 its potential to revolutionize soil remediation techniques, addressing the lack of effective treatment options for soils contaminated by per- and polyfluoroalkyl substances (PFAS). The proposed remediation method utilizes the natural mutualistic relationship between plants and fungi to remediate contaminated sites, offering distinct advantages over traditional methods. This innovation not only preserves site ecology, but also allows for the reuse of remediated soils, distinguishing it from other solutions that have high environmental impact. By mitigating soil-based sources of PFAS contamination, the project contributes to public health by reducing exposure risks and safeguarding water and agricultural resources. Furthermore, the successful completion of this project will provide compelling evidence for field trials, paving the way for regulatory approval and commercialization. This advancement has significant economic implications, enhancing the competitiveness of the United States and stakeholders by allowing for the reallocation of resources through cost savings, and addressing pressing environmental concerns. This enhanced approach offers significant promise for furthering scientific knowledge and delivering tangible benefits to society by tackling a crucial environmental issue, yielding far-reaching benefits.
The proposed project focuses on developing a scalable and effective biological remediation method that utilizes synergistic interactions between fungi and plants to degrade and remove PFAS from contaminated environments. The project aims to expand on fungi that are able to efficiently degrade PFAS and evaluate their effectiveness in degrading six specific PFAS compounds recommended by the EPA. The research expands the understanding of fungal degradation of PFAS by identifying additional defluorinators and characterizing the resulting breakdown products. The impact of several environmental factors on degradation rates will be assessed to understand how site-specific challenges may impact remediation efforts. Additionally, various delivery methods for microbial inoculation, such as pelleting, soil drenching, and in-furrow application will be evaluated for consistent inoculum application to contaminated sites. Bench trials will assess the efficiency of this approach, combining fungi and hybrid poplars, for PFAS remediation. This research addresses a critical need for effective PFAS remediation methods, expanding the frontier of scientific knowledge in fungal bioremediation, offering a fresh perspective and innovative approach towards mitigating the impacts of PFAS on our ecosystems.
This award reflects 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
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 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
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 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
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
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 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 – 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 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
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 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. -
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
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 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. -
NONA TECHNOLOGIES
SBIR Phase I: Maintenance-Free Water Treatment using Ion Concentration Polarization
Contact
286 VASSAR ST APT F1
Cambridge, MA 02139--4957
NSF Award
2422906 – SBIR Phase I
Award amount to date
$274,994
Start / end date
08/01/2024 – 07/31/2025 (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 addressing the critical issue of water scarcity through an innovative membrane-free, chemical-free, more particle tolerant desalination technology. The project aims to make desalination more accessible and affordable, thereby providing communities facing water shortages with new water sources and enhanced water recycling. The technology is designed to be energy-efficient and environmentally sustainable, reducing the barriers to widespread adoption of desalination and water recycling. By advancing the field of water treatment, the project aligns with NSF?s mission to promote the progress of science and advance national health and welfare. The successful commercialization of this technology has the potential to generate significant economic benefits, including job creation and increased tax revenue, while also addressing a pressing environmental challenge.
This project proposes a groundbreaking innovation in desalination technology through the development of an Ion Concentration Polarization system. Unlike traditional methods, the ICP system requires significantly less energy and eliminates the need for harmful chemical pre-treatments. The primary innovation lies in the scalable design of the Ion Concentration Polarization system, which can effectively transition from small-scale to large-scale applications. The research aims to optimize the internal flow architecture and electric current distribution to achieve a production capacity of 1,000 liters per hour from an initial 10 liters per hour at bench scale. The methodology includes rigorous experimentation and prototype development to ensure the technology's efficiency and reliability at larger scales. This advancement holds the promise of revolutionizing the desalination process, making it more viable for widespread use and significantly impacting water treatment practices.
This award reflects 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
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. -
Nitrate Elimination Company, Inc
SBIR Phase I: Dual enzyme system to prevent food waste caused by oxygen
Contact
334 HECLA ST
Lake Linden, MI 49945--1323
NSF Award
2208721 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/15/2023 – 08/31/2024
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is development of new technology for safe, recyclable, and effective packaging. The system works by protecting packaged contents from damage from oxygen (technically termed oxidation). An estimated 25% of the world?s food supply is lost due to food spoilage, with oxidation a major contributor to the problem. Technology that contributes to food security is a compelling objective in the 21st century. Today?s methods of protection from oxygen require metals or complex and expensive barrier materials. These options inhibit efficient recycling. Reduction in packaging waste is an increasing goal. Industries agree that current products for oxygen protection are not meeting needs or consumer preferences. This proposal describes a solution based on a pair of enzymes that use minute quantities of sugar to consume oxygen by producing a modified sugar and water. Enzymes perform a specific function (catalyze a chemical reaction) and are inherently environmentally friendly. For many foods, the sugar in the food itself powers the system.
The proposed project seeks to determine the viability of a dual enzyme, oxygen removal system for preservation of food quality in real world packaging applications. Prototype materials have demonstrated sufficient performance to justify this research, and a series of technical objectives have been defined. Objectives include determining the oxygen removal activity in a variety of containers and designing optimal product configurations in different containers. A second objective is to determine system performance at various temperatures. Active shelf-life of the system ? activity over time ? needs to be evaluated. Defining these criteria is required in order to determine the commercial potential of the technology. Enzyme activity assays are key tasks for all objectives. Oxygen removal effectiveness will be determined by an industry standard for measuring oxygen incursion into sealed packages. The proprietary cell lines developed for expression of the enzymes in the system have been screened for production potential at commercial scale. All required enzymes will be produced in house under previously developed standard operating procedures for fermentation and purification. Interfacing with developers of new, environmentally benign packaging materials is ongoing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ONCOBLAZE LLC
STTR Phase I: Preventing Tumor Recurrence by Heat-Triggered Drug Delivery
Contact
8 FOREST CREEK CT
Charleston, SC 29414--7328
NSF Award
2415653 – STTR Phase I
Award amount to date
$275,000
Start / end date
08/01/2024 – 07/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project relates to a novel cancer therapy that addresses cancer regrowth after surgical therapy. Surgical removal of cancerous tumors is the first-line therapy for many cancers. In 30-40% of patients for certain cancers, cancerous cells remain after surgery that result in tumor recurrence. Such tumor recurrence is associated with worse prognosis and these patients often have limited treatment options. This project will develop technology that can deliver a large amount of chemotherapy precisely to the tissue where remnant cancer cells are anticipated after surgical tumor removal. The approach is based on heat-sensitive lipid particles that encapsulate the chemotherapy. When exposed to temperatures in the fever range, the lipid particles release the chemotherapy in the heated tissue regions. This approach enables the precisely targeted delivery of chemotherapy drugs to tissue with remnant cancer cells. If successful, this technology could cure many of those patients that would otherwise face tumor recurrence. Furthermore, the often-costly follow-up treatments will be avoided, making the approach cost-effective.
This Small Business Technology Transfer (STTR) Phase I project will develop a novel device for the targeted delivery of chemotherapy agents to tissue surrounding surgically removed tumors. The device is based on an infrared laser which can be precisely targeted to the intended tissue region. The laser will be computer controlled to heat the tissue indicated by a physician to accurately controlled temperatures, triggering drug release in this tissue region. Furthermore, drug release will be monitored by an imaging technology that will be developed as part of this project. This imaging technology will provide feedback on amount of chemotherapy delivered, and location of delivery. The research objectives are: (1) Build and test a device prototype. The testing procedures will ensure that a targeted region can be heated to accurate temperatures. The imaging system component will be evaluated in terms of accuracy and sensitivity. (2) Large animal studies. These studies will confirm prototype operation in living organisms, where mock surgeries will be performed. The animal studies will confirm that adequate chemotherapy amount can be delivered to tissue surrounding a surgically removed specimen. Furthermore, the animal studies will ensure that no unintended organ damage occurs before transition to studies in human 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. -
ONE SPOT LEARNING, INC.
SBIR Phase I: Holistic System for Comprehensive Student Assessment
Contact
741 CONESTOGA RD
Bryn Mawr, PA 19010--1039
NSF Award
2423635 – SBIR Phase I
Award amount to date
$256,800
Start / end date
07/01/2024 – 06/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to help educators meet the needs of all their students by leveraging AI and Natural Language Processing (NLP) tools to examine robust sets of student learning data including quantitative and qualitative samples such as essays, written assignments, lab reports, and reflections, to determine student progress based on specific standards and competencies for more holistic and comprehensive assessment of student learning. The real-time, detailed analysis of student learning through qualitative and quantitative data analysis enables educators and administrators to understand how each learner, class, grade, and school is progressing in their learning. By contrast to more summative, end-of-course or end-of-year assessments which offer limited or delayed insights on student learning, this project provides educators and learners with access to deep analysis of student learning to make systemic course corrections and enable teachers to identify which standards and skills student's have been mastered and which need additional support in support of a more holistic approach to assessment and learning in primary and secondary education.
This Small Business Innovation Research (SBIR) Phase I project will investigate the effects targeted large language model (LLM) fine-tuning using parameter-efficient fine-tuning (PEFT) and natural language processing (NLP) and infinite-context LLM based natural language generation (NLG) on qualitative and quantitative assessments of learners in grades 5-12. This research goal addresses, first, the problem that NLG is being used to generate feedback and content without targeted fine-tuning. There is an opportunity to use PEFT to allow for rapid, individualized NLG. Second, assessment relies on grades and tests that may not capture learning as robustly as necessary for a more holistic assessment mechanisms to make rapid and real-time shifts and provide comprehsive feedback. The technological innovation will use infinite context LLM pipelines and NLP techniques to allow teachers and administrators to gain a more complete view of students? learning over time. This technical innovation will be paired with discourse analysis of collaborating educators and administrators to investigate effects of these novel NLP and NLG technologies on student learning over time. It is anticipated the intervention will provide educators with much greater visibility into distinct learning paths and provide timely feedback to improve K12 education.
This award reflects 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
Errata
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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. -
OPTICALX, LLC
SBIR Phase I: Space-Time Projection Optical Tomography (SPOT)
Contact
20654 ALDER AVE
Tracy, CA 95304--8404
NSF Award
2404362 – SBIR Phase I
Award amount to date
$274,996
Start / end date
07/01/2024 – 12/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to understand how to harness the power of Graphical Processing Unit (GPU)-computing to detect and track small space debris. The last decade has seen rapid growth in satellite launches as well as space explosions which profoundly worsen the space debris environment, particularly in the Low Earth Orbit (LEO). Debris smaller than 5 cm is not detectable by current radar and optical techniques, remains in orbit for many years, travels at 5 miles per second and, therefore, poses serious collisional hazards to operational spacecraft and the inhabitants of the International Space Station (ISS). Ultimately, the concern is that the number of space objects beyond a certain threshold will trigger an unintended exponentially growing avalanche of fragments making LEO unusuable.The only option then is orbit maneuvering and it requires knowing the orbits of each of the debris pieces hours or days ahead of time. The proposed technology is a step toward a comprehensive space surveillance system to ensure sustainable use of the Earth?s orbits.
This SBIR Phase I project proposes to develop an optical solution for space debris detection using a small array of telescopes and algorithms implemented on GPU-based parallel computing platforms. If successful, the proposed technology transforms arrays of inexpensive small, wide field-of-view cameras into powerful computational telescopes with sensitivities enough to potentially detect objects smaller than 1 cm. Also known as synthetic tracking, the technology has been successfully utilized to detect large numbers of near-Earth asteroids for planetary protection. The same method is likely to benefit detection of small objects in LEO. However, it is computationally more challenging because the LEO objects move across the camera view much more rapidly. This requires taking 100x more picture frames per second, requiring the analysis of petabytes of data. More importantly, processing of these many frames is computationally more demanding. On the other hand, the sensitivity gain is significantly more, potentially allowing the detection of sub-cm objects. In contrast to building massive and expensive radar and optical telescopes, this project aims to provide a sustainable and low-cost solution to track millions of particles to provide protection for space assets now and eventually for human inhabitation of 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. -
ORBITAL SERVICES CORPORATION LLC
SBIR Phase I: Optimizing Safety and Fuel Efficiency in Autonomous Rendezvous and Proximity Operations (RPO) of Uncooperative Objects
Contact
A9 VILLA JAUCA
Santa Isabel, PR 00757--2703
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. -
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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
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
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 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 – 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 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
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 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. -
PATHFLOW INC.
SBIR Phase I: Enhancing Pathology Efficiency with On-Chip Optical Coherence Tomography (OCT) Imaging Technology
Contact
224 EAST ST
Lexington, MA 02420--1934
NSF Award
2423517 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2024 – 07/31/2025 (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 are to revolutionize pathology diagnostics through the development of an advanced imaging technology. This project aims to introduce a silicon chip based system that will provide fast, accurate, cellular-level resolution imaging. By improving diagnostic accuracy and reducing diagnosis times, this technology will enhance patient care, reduce the workload in pathology labs, and lower diagnostic costs. The project supports the NSF's mission to promote scientific progress and improve national health, prosperity, and welfare by providing a technological solution with substantial commercial and societal impact. The innovation will enhance scientific and technological understanding, address a significant market opportunity, and provide a durable competitive advantage. The proposed business model targets pathology laboratories as the initial market segment, with projected substantial annual revenues by the third year of production.
This Small Business Innovation Research (SBIR) Phase I project focuses on developing a silicon photonic optical coherence tomography (OCT) imager for pathology diagnostics. The primary objective is to create a high-performance, portable, and cost-effective imaging solution by integrating all optical components onto a single silicon chip. The research will address key technical challenges, such as achieving high resolution and speed while maintaining a compact size. The project involves designing, prototyping, and testing the OCT imager to ensure its effectiveness in accurately identifying diagnostic tissues. The anticipated technical results include demonstrating the imager's capability to provide real-time, 3D cellular-level visualization of tissues, thereby significantly improving the pathology grossing process. This technology is expected to set a new standard in pathology diagnostics and enable broader applications in medical imaging.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PERCEPT BIOSCIENCES INC.
SBIR Phase I: Percept Development Plan Agent: Accelerate drug repurposing research and development
Contact
1889 BACON ST STE 11
San Diego, CA 92107--3083
NSF Award
2410320 – SBIR Phase I
Award amount to date
$274,947
Start / end date
07/01/2024 – 06/30/2025 (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 allow companies to be able to efficiently lead drug repurposing initiatives by automating the formulation and writing of drug repurposing development plans. Addressing the needs of underserved disease communities presents both a societal imperative and a unique business opportunity. While repurposing allows companies to build off of existing safety and efficacy data for already approved drugs, companies frequently depend on external consultants to support such development, which can be slow, expensive, and error-prone. This project?s primary benefits would be: (1) enabling smaller, more streamlined teams to spearhead drug repurposing development, significantly reducing associated costs, and (2) catalyzing significant growth in the market for drugs targeting orphan diseases via the adoption of a more competitive cost structure. It could improve efficiency in the regulatory process by integrating knowledge across publicly available data sources, optimizing drug targets and candidates, and assembling this information into a coherent development plan with a high probability of scientific and regulatory success. Such increased efficiency may lead to a greater throughput of repurposing discovery, expansive growth of the market, and increased availability of repurposed drugs.
The proposed project addresses the problem that drug repurposing development plans mandated by the FDA require significant time and effort in searching multiple databases to mitigate biological, regulatory, and legal risks. Automating this process using software systems could accelerate drug discovery and reduce development costs but is complicated by the heterogeneity of the knowledge organization of data required to create such plans. This project proposes a tool which, given a drug target and the current list of FDA-approved drugs, will generate a repurposing development plan. The tools developed in this project are based on recent advances in automated reasoning and knowledge extraction using Natural Language Processing. The project will extend these advances in novel ways to make them radically more useful and trustworthy, and a natural fit to heterogeneous biological data. This includes ways to provide references in support of a given claim of knowledge made by the system across multiple knowledge sources and ways to create a cogent narrative from a list of claims and create a report from the narrative. The resulting tool will create referenced and cross-checked reports for drug candidates, ready for review and submission to the FDA.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PHYTOSTONE LLC
SBIR Phase I: A Novel Carbon-Sequestering Biomaterial for Dropped Ceiling Tiles
Contact
501 SILVERSIDE RD, STE 105
Wilmington, DE 19809--1376
NSF Award
2304384 – SBIR Phase I
Award amount to date
$273,652
Start / end date
08/15/2023 – 12/31/2025 (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 is to validate a new, biochar-enriched building material as a ceiling tile product. The plane of ceiling tiles represents a vast, untapped opportunity in combating climate change through carbon sequestration. With the innovation, a proprietary mineral matrix is enriched with 50-80% biochar. Biochar is the resulting charcoal-like residue from pyrolysis. This stabilized form of carbon is nearly crystalline and resistant to emissions-causing oxidation. Combined with a proprietary mineral binder, the resulting novel material is non-flammable, ultra lightweight, and biodegradable. As a ceiling tile, it can reduce a building?s embodied carbon in an easily quantifiable way, position the building for carbon sink remuneration, boost the green ratings of the building, help qualify a building for sustainability-linked financing - all without compromising on fire safety standards. This project capacitates an innovation that adds to the nation's toolkit in creating a climate-responsible built environment.
The project innovation is a novel, biogenic, cementitious chemistry composed of plant-based biochar, clay, binding minerals, proprietary catalysts, optional reinforcement fibers and optional pigments. The inclusion of biochar is a major characteristic of the innovation, comprising up to 80% of the material. Unlike carbon stored in plant matter, the ocean or in soil, the carbon atoms of biochar are more resistant to losing electrons and being converted into carbon dioxide, therefore making the innovation a novel solution towards converting the built environment into a "carbon bank". There are three major questions to resolve: how could varying biochar particle sizes impact tile integrity, can the innovation perform satisfactorily in standard tile dimensions amidst different ambient humidity levels, and can the tiles achieve the Class A fire standard of competing tiles. The iterative experimental protocols will utilize the classic American Society for Testing and Materials (ASTM) tests used to demonstrate building code compliance in all three of these research areas.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PIRVISION LENS LLC
STTR Phase I: ActiveLens: Enabling Stationary Occupancy Detection of Passive Infrared Motion Sensors
Contact
18842 MONTALVO OAKS CIR
Los Gatos, CA 95030--3091
NSF Award
2341560 – STTR Phase I
Award amount to date
$275,000
Start / end date
04/15/2024 – 03/31/2025 (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 is in developing innovative technologies that have the potential to improve indoor occupancy sensing devices significantly. It will enable new features and approaches in applications like occupancy-centered lighting, temperature control systems, surveillance, etc. To address challenges associated with standard passive infrared (PIR) sensors, the company has developed ActiveLens, a lens technology with advanced features overcoming issues related to mechanical shutters. ActiveLens sensors use artificial intelligence (AI) algorithms and processing to achieve improved detection capabilities. This project will expose fresh graduating students, particularly women, first-generation college students, and other underrepresented minorities, to valuable skills in areas like semiconductor chip design, data processing, and quality control. This project fosters collaboration between researchers, business leaders, and other organizations. The team has already refined prototypes and is now discussing with commercial users to develop customized solutions.
This Small Business Technology Transfer (STTR) Phase I project will support research activities for PIRvision Lens LLC to bring the proprietary solid-state ActiveLens technology to the market by overcoming technical challenges in optimizing infrared energy transmittance, differentiating human signals from other warm objects, and modularizing AI algorithms to enable minimum viable product development. Today, buildings are equipped with PIR sensors for occupancy detection, owing to their low cost, low energy consumption, wide field of view, and high reliability. Despite these advantages, PIR sensors only detect motion, not stationary occupancy. This long-standing limitation has hindered applications that demand high-accuracy occupancy detection. If successful, the proposed semiconductor modulator will enable novel capabilities for standard PIR sensors, including stationary occupancy detection, human infrared signal differentiation, occupancy counting, activity identification, and classification - representing the first true technological innovation in PIR sensing in over 40 years. It is a disruptive, innovative, efficient, and cost-effective solution that can be combined with any standard PIR component sensor to identify underutilized spaces and minimize operating costs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PITCH AERONAUTICS INC.
STTR Phase I: Drone Localization Near and Manipulation Control in Contact with Power Lines
Contact
6323 S FEDERAL WAY UNIT 17
Boise, ID 83716--9134
NSF Award
2414567 – STTR Phase I
Award amount to date
$274,853
Start / end date
07/01/2024 – 06/30/2025 (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 Phase I project is to alleviate the 2TW backlog of renewable energy projects desiring to connect to the power grid by installing and replacing dynamic-line rating (DLR) sensors on power lines with a novel cyclorotor drone. Currently, such (un)installation tasks are being performed manually with the help of helicopters, cranes, scaffolding, and/or rope access. Such manipulations are dangerous since, for example, a helicopter would be at low altitude where it would be impossible to recover from an engine failure and would have substantial risk of colliding with the line. On the other hand, conventional multicopter drones cannot perform heavy sensor installations. Specifically, they move by first pitching or rolling (underactuated motion), which hampers their ability to counter wind disturbances. This project will develop (i) techniques for localizing the drone with respect to power lines and (ii) control strategies that enable installation, removal, and maintenance of DLR sensors.
The work proposed in this project is to use innovative algorithms to navigate a cyclorotor-based drone to a power line based on the measurements of the electric and magnetic fields around power lines. This state-estimation technique around power lines is robust, using only the root-mean square (rms) electric/magnetic field that is present around the power lines naturally due to the flow of power through them. In parallel, a control system will be developed to bring the drone stably into contact with a power line to install and uninstall dynamic-line rating (DLR) sensors, bird-diverters, and other line products. This control system will be designed to seamlessly handle any abrupt transitions from free-flight to contact with a power line. Upon successful completion, the project will provide an efficient method of installing and replacing power line sensors, bird diverters, and other line components. The IoT line sensors can help alleviate transmission congestion, allow increased penetration of renewable energy, and decrease wildfire risk.
This award reflects 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
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 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. -
PLATFORM TECHNOLOGY VENTURES LLC
SBIR Phase I: Exploration and Development of Decentralized Autonomous Organizations (DAOs) for Diverse Industries
Contact
21 PINE PLAIN RD
Wellesley Hills, MA 02481--1143
NSF Award
2337771 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 to advance Decentralized Autonomous Organizations (DAOs) as a novel form of digital collaboration and governance systems that can be utilized to advance new commercial value propositions. DAOs, which leverage distributed ledger technologies, allow for democratic decision-making and coordination without a centralized authority, something that enables new business collaborations amongst trusted and untrusted entities alike. This innovative structure can potentially enhance various sectors of society, paving the way for novel commercial applications. DAOs offer a dynamic and adaptable approach that can benefit various sectors, including finance, healthcare, environmental sustainability, and more. This project aims to investigate the application of DAOs initially in the high-value field of voluntary carbon credits, which is anticipated to reach up to $40B in 2030, to enable enhanced environmental sustainability and accountability. It will rely on commercial transactions across a wide range of diverse participants of varying levels of trust who need to be able to verify the credits and their chain of custody and sustainability, integrated from a wide range of external data sources. Moreover, the DAO platform, a core product of this initiative, will be a versatile commercial "sandbox" adaptable to developing commercial products for various markets that demand decentralized participation. This will include input and transactability across varying DAO participants, including commercial partners, expert networks, customers, regulators, and broader stakeholders, such as water rights allocation, healthcare, carbon credit marketplaces, and more. By leveraging the power of DAOs, it may be possible to enhance operational efficiency, drive the growth of new technologies, and create more democratic and inclusive systems.
This SBIR Phase I project aims to pioneer the development of a Decentralized Autonomous Organization (DAO) as a platform for value creation in various sectors, starting with carbon credits. The research will investigate the innovative integration of off-chain data consensus protocols within DAOs, a largely unexplored and complex area. The proposed R&D involves deploying smart contracts for trustless verification of off-chain data via on-chain incentives, a process that demands a sophisticated blend of cryptographic techniques, game-theoretic mechanisms, and decentralized network design. This design has to be robust against malicious actors, ensuring fairness, incentive compatibility, and resilience to Sybil attacks. Crafting a decentralized smart contract for off-chain consensus requires balancing fairness, compensation, sufficient voting thresholds, and ground truth comparisons. This equilibrium mitigates malicious influences and encourages truth in adversarial environments. Despite these significant technical challenges, this work represents an innovative stride toward understanding the future potential of DAO technology across diverse sectors. In addition to exploring the benefits and successes of DAOs, it will also enable the identification of key risks and potential failure modes across various use cases to allow exploration and development of improved future alternatives and DAO 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. -
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
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 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. -
PRHOBE INC
SBIR Phase I: Solving the 4,023-year-old logistics control problem using modern IoT standards and a novel combination of passive RFID, UWB, cellular technology & their application
Contact
42850 CASTILLEJO CT
Fremont, CA 94539--5109
NSF Award
2404638 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/15/2024 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project aims to revolutionize logistics and transport management via real-time visibility at the unserved serial number level through integration of wireless technologies. This research will enhance scientific and technological understanding by providing unprecedented insights into the movement of goods, thereby optimizing transport methods and materials. The market opportunity addressed by the proposed technology is vast, with a value proposition centered around real-time tracking, digital control empowerment, and reduced tracking costs. By leveraging precise on- and off-premise technology with Radio Frequency Identification (RFID), the solution promises to provide a durable competitive advantage. The technology will be offered at a reasonable monthly pricing per unit, unlocking commercial opportunities both domestically and globally. This novel approach is projected to capture a significant portion of the market currently underserved by existing methods. Initially targeting pallets, containers, and commercial vehicles, potential annual revenues of $10M+ are projected in the third year of production, paving the way for expansion into wider domestic and global markets. Ultimately, the technology is poised to be a key factor in enabling commercial success while offering societal benefits such as minimized disruption of production and improved food quality.
This Small Business Innovation Research (SBIR) Phase I project seeks to provide technology for tracking reusable transports (e.g., pallets, containers, trailers, trucks) to reduce disruptions for manufacturers, movers, and package receivers by over 50%. Logistics operation inefficiencies in manufacturing, food distribution, and pharmaceutical delivery could be eliminated, reducing item journey monitoring costs and wasted time. The proposed devices will attach to pallets/containers, read passive RFIDs attached to serial numbered items, and communicate their location/state to a cloud based digital twin for each serial number. This will allow users to monitor products during shipping, updating product whereabouts, condition, and expected delivery timeline, boosting operational efficiency and product safety and creating the potential for circular logistics chains and goods that deliver themselves. This project will de-risk the device using evaluation hardware and demonstrate blink rate optimization feasibility, producing a prototype capable of transmitting and connecting to the monitoring software across various transportation types. The R&D will include reference design-based device testing focusing on battery longevity, chip power usage evaluation, and deployable antenna design for multi-item reads. The result will be an early prototype capable of being tested in an industrial pallet configuration for modular battery implementation in post-Phase I efforts.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PROMPT DIAGNOSTICS LLC
SBIR Phase I: Hybrid DNA-protein quantification platform for point-of-care diagnosis of syphilis and human immunodeficiency viruses (HIV)
Contact
301 W 29TH STREET, STE 2004
Baltimore, MD 21211-
NSF Award
2232930 – SBIR Phase I
Award amount to date
$255,667
Start / end date
02/01/2023 – 12/31/2025 (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 the creation of the first all-in-one automated syphilis test available at the point-of-care. The number of syphilis cases in the United States have doubled in the past 5 years with a five-fold increase in congenital syphilis passed from a pregnant mother to the fetus. Annual infections now account for $170 million in lifetime medical costs. This low-cost, portable test will enable care providers and outreach efforts to immediately diagnose and treat patients in a single visit to halt the spread of syphilis infections in the most vulnerable populations. Syphilis testing in this platform will be readily combined with hybrid detection of human immunodeficiency viruses (HIV) to streamline syphilis testing with existing programs for HIV diagnosis and further encourage uptake of this test solution into clinical practice.
This Small Business Innovation Research (SBIR) Phase I project addresses the need for easier syphilis testing solutions to provide comprehensive diagnosis on-site with the patient. Syphilis diagnosis relies on two separate antibody tests, of which one requires quantifying antibody levels with a tedious laboratory procedure called Rapid Plasma Reagin (RPR) to confirm if the patient has an active infection. The lack of resources and personnel to conduct RPR testing on-site severely limits the ability of public health clinics to effectively diagnosis syphilis in a timely manner. This project will combine both antibody tests including quantitative RPR into an automated cartridge for rapid and complete syphilis diagnosis at the point-of-care. The research proposed in this project will develop magnetic particle-enabled assays for each antibody test and integrate the assays into a multiplexed plastic cartridge. These cartridges, combined with a portable instrument, will enable all steps required for syphilis diagnosis to be completed within minutes in an affordable and easy-to-use format.
This award reflects 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
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. -
QUANTIREAL INC.
SBIR Phase I: Synthesizing large and diverse data-sets for training machine learning algorithms using physical modeling and simulation
Contact
3430 MONROE ST
Santa Clara, CA 95051--1418
NSF Award
2404821 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 03/31/2025 (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, would be to diminish the hurdles in building a synthetic data generator for robust automated detection technologies. Passenger and personal property screening is an essential component of Department of Homeland Security?s (DHS) strategy to combat terrorism and targeted violence. The synthetic data generated by the proposed technology can be used to train as well as characterize the advanced screening solutions deployed. This will boost understanding of expected field performance and hence confidence in systems used to protect people and critical infrastructure. At airports, fewer false alarms from people and baggage screening equipment would translate to shorter lines, smaller wait times and decreased stress levels. Better threat detection rates would boost confidence in the screening solutions and truly help in reducing anxiety surrounding air travel, large gatherings, and outdoor events. The apparatus for generating synthetic data can also benefit education and training of the budding STEM workforce in advanced technologies.
This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate that a novel radiation physics solver based on first principles can generate synthetic data that matches the realism of data obtained through manual acquisition on physical radiation-based scanners. In addition, the solver can grow/widen the sample probability distribution to more closely match the population probability distribution than manually acquired data and do so in a hitherto unrealized linear computational time. In an emerging world of machine learning based automated threat or anomaly detection, this cost-effective data synthesis fulfills an immediate need to address the problem of data paucity to both train and test such algorithms. The research and development effort in this Phase-I project will be focused on developing computational methods to estimate the residual energy post photon-matter interaction in a cost-efficient manner. Representative object assemblies will be constructed to virtually scan and generate realistic and precisely annotated imaging data. Appropriate metrics will also be developed to measure the quality of the created synthetic images. The challenge will be to match the resolving power of the relevant modality as it applies to specific application areas.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
QUARKSEN LLC
SBIR Phase I: eQuanta's Next-Gen STI Diagnostic Device: Unveiling the Power of Graphene-Based
Contact
241 FRANCIS AVE
Mansfield, MA 02048--1548
NSF Award
2409808 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 is to provide rapid, effective, affordable, non-invasive, and easy-to-use diagnosis of viral and non-viral sexually transmitted infections (STI), such as chlamydia, gonorrhea, syphilis, HIV, hepatitis C, and trichomoniasis. STI are estimated to be present in one out of five people in the U.S. and the estimated direct medical cost associated to their treatment is approximately $16B. While early diagnosis will ultimately contribute to better public health outcomes and economy, the principal barrier in seeking a diagnosis is the lack of available health services, cost, long clinic waiting times, invasive sample collection methods and the negative social stigma associated with looking for STI testing. This project will develop an affordable and point-of-care diagnostic device for STI, that will not only reduce diagnostic time but also lower healthcare costs.
This Small Business Innovation Research (SBIR) Phase I project advances an innovative STI diagnostic device. This project leverages self-assembled chemistry to form tailored cavities, which are sensitive and selective to the biomarkers of interest. The project aims to validate preliminary studies indicating the device's capability to detect viruses, opioids, and biomarkers for STI diseases, enabling early disease diagnosis and quantification of viral or bacterial loads in exhaled breath or urine. Phase I of this project will be focused on the fabrication of a device composed of an array of sensors to detect biomarkers of viral and non-viral STIs with high selectivity and sensitivity from day one of contagion. Detection of hepatitis C, HIV, chlamydia, gonorrhea, syphilis, trichomoniasis biomarkers from cervical mucus discharge/swabs will be evaluated. Additionally, user testing on a clinical research environment will be undertaken at Ragon Institute.
This award reflects 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
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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. -
RADIUS TECHNOLOGY SYSTEMS, INC
SBIR Phase I: Over One Million Transactions per Second - A Parallel Smart Contract Platform from Radius
Contact
153 5TH ST
Cambridge, MA 02141--2031
NSF Award
2423309 – SBIR Phase I
Award amount to date
$275,000
Start / end date
06/15/2024 – 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 Phase I Small Business Innovation Research (SBIR) project is to develop a platform which can process smart contract transactions at extreme scale for very low cost. Due to the antiquated technology of current payments systems infrastructure, many financial transactions are slower and more expensive than necessary. With modern computing power and cryptography, smart contract-based platforms can automatically execute transactions of various levels of complexity atomically and with real-time settlement. Improved transaction efficiency and instant settlement have the potential to revolutionize our payment systems, particularly in the areas of micropayments and cross-border payments. A high-volume and very low fee platform can support micropayments priced out of the market by the fee schedules associated with current payment methods. The feasibility of micropayments has the potential to substantially change the business model of the internet. For example, users could pay a minimal amount to view a website ad-free instead of using ad-blockers, and content creators could charge small amounts for users to view individual articles or web posts. Smart contracts can also be used to more efficiently process a wide range of transactions.
This SBIR Phase I project proposes to achieve throughput over 1 million transactions per second through parallel execution and horizontal scalability. While public blockchain systems have led to significant technical advancement and inspire aspects of our design, they face scalability challenges due to routing all transactions through the bottleneck of a single unparallelizable consensus mechanism. This project?s key innovation and line of research is the ability to execute smart contract transactions in parallel without needing to serialize a global order for all transactions on the platform. Crucially, this design enables horizontal scalability. Platform data is stored as a key-value database stored across multiple geographically replicated shards. When users initiate transactions, they are handled and processed by one of numerous transaction processors operating in parallel. Notably, the platform is compatible a range of smart contracts and other blockchain platforms as well as alternative runtimes. A key aspect of this research will involve on-demand scaling - the ability to bring additional database shards online and distribute keys and transaction activity across the new shards in accordance with transaction volume demands, all while the platform remains online and operational.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
REFIBERED, INC.
SBIR Phase I: Automatic Sorting of Prominent and Contaminant Fibers in Textile Wastes
Contact
10235 BYRNE AVE
Cupertino, CA 95014--2809
NSF Award
2423377 – SBIR Phase I
Award amount to date
$274,955
Start / end date
07/15/2024 – 04/30/2025 (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 enabling textile circularity. Today, over 92 million tons of textile waste are generated each year, and less than 1% is recycled into new clothing. While textile recycling technologies have been slowly scaling over the last decade, recyclers are facing a large challenge with a lack of recycling infrastructure. Specifically, recyclers are missing a method to accurately sort textile waste by material. All recyclers need to have access to well-sorted feedstock for the input of their process, but textile waste is notoriously difficult to sort due to the numerous blends, dyes, and contaminants present in each garment. This project is focused on developing an artificial intelligence-based material detection system that will accurately detect the presence of key materials for recyclers, as well as any contaminant materials that could interfere with recycling. If the proposed technology development is successful, textile recyclers could begin to recycle post-consumer waste at scale, which comprises >85% of the global textile waste stream.
The proposed activity involves using hyperspectral cameras and artificial intelligence to develop a methodology for contaminant detection in textile waste. A lack of accurate sorting capabilities is primarily the reason less than 1% of the textile waste is recycled into new textile. This project will focus on developing a textile waste detection system that can detect the presence of common fiber recycling contaminants, specifically a) elastane fibers, b) nylon 6 and nylon 6,6 fibers, and c) man-made cellulosic fibers (MMCFs). The biggest technical hurdle that this proposed project involves is the development of a regression-based machine learning algorithm which will provide a quantitative estimate of each potential contaminant and material present in each textile sample. The methodology for developing this system will involve 1) compiling a dataset of textile samples that represent the target contaminants and performing a complete spectral analysis of each sample, 2) experimenting with different machine learning algorithms and model refinement to optimize for contaminant detection, and 3) validate contaminant model accuracy on customer-provided textile 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. -
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
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. -
RESONANCE SIGNATURES LLC
SBIR Phase I: iNQR: A Low-cost, Smart, Portable Spectroscopy Device for Material Authentication
Contact
2649 NW 136TH TER
Gainesville, FL 32606--4750
NSF Award
2335565 – SBIR Phase I
Award amount to date
$274,997
Start / end date
05/01/2024 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research Phase I project aims to develop and commercialize a handheld authentication device, based on the principle of nuclear quadrupole resonance (NQR) spectroscopy, that can help improve the health and safety of the general public. The portable form factor and low cost of the device will make it accessible for everyone to utilize without any restrictions. The powerful analytical capability of this device to provide accurate and reliable results quickly and non-invasively can be used in different stages of the modern supply chain. Specific use cases of the device will include the law-enforcement agencies and postal systems, where it can be used to rapidly identify and isolate illegal drugs, thereby mitigating the illegal drug epidemic. In addition to its use in law enforcement and forensics, this spectroscopy technology has potential applications in the medical field for drug screening and monitoring. Its applicability in drug and pharmaceutical products detection alone will impact a multi-billion-dollar market. Overall, this innovation will greatly enhance our scientific and technical understanding of the capabilities and limitations of the NQR spectroscopy technology for chemical analysis and create a pathway for its widespread deployment in diverse fields.
The intellectual merit of this project lies in utilizing NQR spectroscopy to provide a highly specific and sensitive method at low cost for detecting drugs based on their unique chemical identifiers (UCIs). The project will focus on developing a portable NQR spectrometer device for general consumer use to detect and identify various compounds based on their unique chemical and structural properties in the solid state. NQR spectroscopy can detect drugs that may be difficult to identify using other techniques, such as those that are highly pure or are concealed in complex mixtures or disguised as other substances. The project will explore new approaches to improving the sensitivity based on pre-polarization methods, as well as size, cost, and selectivity of NQR spectroscopy for drug detection, as well as developing new portable instrumentation. Major hardware components, including the broadband tuner and backend signal processing unit, will be custom designed to minimize the footprint and improve sensitivity. The device will be extensively evaluated for wide range of drugs and other substances (e.g., dietary supplements, which often include unregulated harmful chemicals) for its efficacy in commercial 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. -
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)
NSF Program Director
Errata
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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. -
ROOTWORDS INC
SBIR Phase I: Asset-Based Latin Morpheme Approach to Language Learning
Contact
1651 LAKESIDE CIR
Park City, UT 84060--7730
NSF Award
2423673 – SBIR Phase I
Award amount to date
$271,780
Start / end date
08/01/2024 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this SBIR Phase I project is an innovative approach to language acquisition leveraging a tumbler-style mechanism. This method capitalizes on cognates from Latin-based languages to expedite vocabulary development and enhance literacy skills across diverse age groups. The application's design, rooted in morphological principles, offers a robust framework for learners ranging from novices to advanced practitioners preparing for standardized tests. By emphasizing Latin roots, the tool unlocks access to a vast array of STEM fields, as the professional lexicon in these areas is predominantly Latin-derived. The versatility of this approach enables its adaptation to multiple languages sharing Latin origins, significantly broadening its potential impact. The unique root-based learning methodology provides a distinct pedagogical advantage, facilitating cross-linguistic connections and deepening overall language comprehension. This technology's potential to revolutionize language education lies in its scalability and wide-ranging applicability. By making complex vocabulary more accessible, the tool has the capacity to enhance scientific literacy and foster greater engagement with technical subjects among the general population.
This Small Business Innovation Research (SBIR) Phase I project aims to address the inefficiencies in vocabulary acquisition by investigating the efficacy of morpheme-based learning strategies. The research objectives encompass demonstrating that learning lexical components accelerates vocabulary development, enhances decoding abilities for complex unfamiliar words, and improves long-term retention of lexical items. The proposed research methodology involves the development of a digital application that employs a tumbler game mechanic to teach vocabulary through morphological analysis. A randomized controlled trial will be conducted, stratifying subjects into three cohorts: a control group utilizing traditional whole-word definition methods, and two experimental groups engaging with the application for 30 and 60 days, respectively. Assessment will be conducted via standardized multiple-choice and matching instruments at baseline, 30, 60, and 90 days. Anticipated technical outcomes include: 1) inferior long-term retention and novel word decoding capabilities in the control group; 2) enhanced interpolation/decoding skills and 90-day retention for the 30-day experimental group; and 3) a 50% increase in interpolation/decoding proficiency and superior long-term retention for the 60-day experimental group compared to both other cohorts.
This award reflects 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
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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
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
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. -
SAVIMBO INC.
SBIR Phase I: Biodiversity credits for Indigenous and local communities
Contact
37 LOST VALLEY DR
Orinda, CA 94563--3928
NSF Award
2423048 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 is in addressing the need for innovative financing mechanisms to meet Global Biodiversity Framework targets, the aims of the Convention on Biological Diversity, and the Kunming-Montreal Accords. The global biodiversity market is projected to value $180 billion by 2050. But the market is in its infancy, lacking clear rigorous science that is market-tested and acceptable to all stakeholders who work in biodiverse regions. This project aims to deliver market-tested public protocols, peer-reviewed scientific methodologies, transparent tracking, clear unitized accountability for biodiversity gains and losses (conservation, restoration, and impact accounting), and provide fair, direct, funding mechanisms to Indigenous Peoples and local communities for their global contributions to planet health. Gains in these components of a fair and functional biodiversity credit market will not only benefit biodiversity frameworks but all nature-based accounting frameworks and broader human health, generating tax revenue, jobs, and sustainable commerce both for US citizens and for global citizens.
This project provides a breakthrough approach to biodiversity crediting based on a combination of Indigenous knowledge, high-tech efficiency, and modern scientific understanding of complex adaptive systems. The methodology monitors impact via ex-post crediting of indicator species observations done by locals themselves (game cameras, audio recordings, photos). The novel unit equates to one hectare, over one month, of intact ecosystem where all ecological niches are available to, and filled by, native species. Observations are typically rare, threatened, endangered animals on conserved land which have no other source of conservation funding. Biodiversity credits are then auto-calculated with open-source computer code and released for certification as biodiversity credit commodities to the international market. A highly qualified interdisciplinary team of biodiversity scientists, Indigenous rights experts, and economists are collaborating to commercialize this solution. They address the planet-wide dual-need to: 1) Reward the populations who are actually preserving biodiversity on the ground, and 2) Target high-biodiverse zones without conservation funding. This proposal aims to bring this solution across the rocky terrain of an international frontier market for biodiversity credits, for the benefit of Indigenous Peoples and the continued protection of 80% of the world?s biodiversity and 30% of the intact planet.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SCHNACKEL ENGINEERS, INC
SBIR Phase I: Automated and Optimized Three Dimensional Routing
Contact
3035 S 72ND ST
Omaha, NE 68124--3569
NSF Award
2404228 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2024 – 01/31/2025 (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 includes the development of new automated routing optimization methodologies, as well as advanced 3D data compression techniques, which will benefit a wide range of industries and applications beyond the initial focus on building construction systems, including civil and infrastructure design, data center design, robotics, path planning, military applications and the semi-conductor industry. Any industry requiring 3D spatial analysis and/or routing will benefit from the work of this project. The project will have broader economic and societal impacts due to a substantial reduction in construction materials and labor necessary for new and remodeled buildings. Carbon reduction, including embodied carbon and operational carbon, is a critical part of all climate change initiatives. This AI software will result in a meaningful reduction in emissions due to the ability to optimize the use of materials and labor in the construction and operation of buildings. The proposed technology will address many forms of design coordination and construction waste, dramatically reducing the amount of raw material, labor and construction waste required to construct a building, while simultaneously reducing the cost and time to occupancy of the construction project.
This Small Business Innovation Research (SBIR) Phase 1 project aims develop a suite of software that automatically routes building services systems through 3D obstructed space achieving a near optimal, clash-free solution. This involves developing a hyper-efficient 3D modeling environment using a process called ?low-resolution surface tessellation? (LRST). In lieu of trying to achieve a high-resolution surface, the project will create as rudimentary of a surface representation as possible to minimize the number of data points stored, thereby reducing the size and complexity of the data set necessary in which to compute routes. The project will develop new 3D optimized routing algorithms in the new 3D environment using a combination of mixed integer linear programming, visibility graphs, non-linear reduction, and variable relaxation among other techniques. The resulting technology, if successful, will find the most efficient path from Point A to Point B through a 3D space filled with any nature of obstructions in polynomial time, or better with no conflicts or clashes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SCRIPT BIOSCIENCES INC
SBIR Phase I: CasPlus: A safer, more efficient, and targeted method of deploying CRISPR in vivo
Contact
29 LUDLOW ROAD
Yardley, PA 19067--2751
NSF Award
2335124 – SBIR Phase I
Award amount to date
$274,438
Start / end date
06/01/2024 – 05/31/2025 (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 will be to decrease the risks associated with current gene editing practices. Gene editing offers significant promise for a wide variety of difficult to treat and currently untreatable conditions. Examples include cancers such as leukemia and multiple myeloma, muscular dystrophy, and cystic fibrosis. Last year, the FDA approved the first gene editing treatment for sickle cell anemia. Progress in gene editing has been slow due to unwanted side effects, which can delete the incorrect gene, insert a gene in the wrong location, etc., leading to undesirable impacts and ineffective treatment. The innovation is a platform technology that significantly reduces the potential inaccuracy of current gene editing technology. This leap forward in gene editing targets the desired gene, increasing the safety of gene editing, which is critical to the success of the technology. The innovation is a platform that could be used to advance promising therapies that are, in their current form, unsafe for patients and develop new therapies for disease unmet treatment needs.
The proposed project will examine the feasibility of the platform technology by targeting the use of the technology in myotonic dystrophy type 1. The disease affects skeletal and smooth muscle, heart, endocrine system, and central nervous system in a progressive, age-dependent manner, with death resulting from pulmonary or cardiac complications. There are no current treatments for this disease. A potential cause for the disease is misfiring by genes that repair DNA. When this gene is not present, there is no known associated loss of function in the biological species. This project will deploy the innovation to: 1) Optimize the formulation in vitro to target the problem gene. This task requires using the formulations in the target cell, sequencing the cells after editing to determine editing efficiency and understand if there are unwanted effects; 2) Determine the delivery dose required for testing in a mouse model using the optimized formulation from first task; 3) Use an in vivo study to determine the feasibility of using the innovation in a mouse model. This study will use the optimal formulation and dose to study the impact on the target genes and potential 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. -
SEMEN AND EMBRYO ADVANCED REPRODUCTIVE TECHNOLOGIES (SMART), LLC
SBIR Phase I: Improving Domestic Small Ruminant Reproduction Through Computer Assisted Embryo Analysis
Contact
2208 DUNCAN ROAD
Jonesboro, AR 72401--0477
NSF Award
2415628 – SBIR Phase I
Award amount to date
$274,996
Start / end date
07/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (or Small Business Technology Transfer) Phase I project will be to accelerate the quality and growth of U.S. sheep and goat production through improved embryo transfer rates. The United States is forced to import 1.5 billion USD yearly of small ruminant protein to fulfill national demand. Embryo transfer use to improve domestic herds is currently limited due to low success rates and almost exclusively used in a small margin of elite herds. By improving the success of this technology and lowering the cost, it will democratize it for wider industry use. Accelerating national sheep and inventory numbers through more productive and prolific animals will significantly bolster the health, safety, and welfare of the American populace through increased access to economical, lean protein. More animals entering the food supply means job creation and an expansion of tax revenue through increased demand for animal feedstuffs, routine animal care, veterinarian services, transportation, animal processing, and distribution of value-added products. Fulfilling U.S. consumer needs with U.S. grown sheep and goats means job creation and internal food security.
In this project, machine learning models with computer vision and multifactorial herd qualities will be studied to significantly improve sheep and goat breeding success rates. Key identified features in the embryo will be used as a baseline that will enable evaluation of a variety of intrinsic and extrinsic factors related to the ewe during the gestational period to better understand environmental factors related to pregnancy failure and success. This analysis will produce a comprehensive embryo and animal health analysis that can be used in sheep and goat embryology laboratories to enable veterinarians, embryologists, and producers to improve breeding success rates. The resulting user interface incorporates the data collection and processing with herd breeding management to serve as a minimum viable product for immediate wider industry adoption.
This award reflects 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. -
SHAMRCK SOCIAL IMPACT CORP
SBIR Phase I: Solving Minority Equity in Science, Technology, Engineering, and Mathematics (STEM) with Artificial Intelligence (AI)-Driven Workforce Development
Contact
925 LANEY WALKER BLVD
Augusta, GA 30901--2951
NSF Award
2304546 – SBIR Phase I
Award amount to date
$275,000
Start / end date
08/01/2023 – 12/31/2025 (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 to enhance Science, Technology, Engineering and Mathematics (STEM) career awareness in minorities by engaging their interests and correlating those interests with real career aspirations. The research aligns with diversity, equity, and inclusion goals in STEM fields, exposing students in secondary schools and providing support for career exploration that may need to be more equitably available to students. With the help of machine learning and artificial intelligence, the research is designed to evaluate the social impact involved in the misalignment of minorities in STEM fields and use technology to correct the alignment for larger, more prepared talent pools. This practice should help increase diversity in fields like biological sciences, data science, and engineering, to name a few. Additionally, upskilling talent before they enter the workforce helps to create a more robust workforce that can push the boundaries of STEM fields much faster, leading to new innovations, socioeconomic balance, and societal growth.
This SBIR Phase I project combines the use of Holland occupational themes with natural language processing in machine learning to recommend and create pathways for secondary school students to gain knowledge and experience in anticipated career paths, especially STEM careers. Based on statistical data about underperforming schools and the workforce of an area, the system can nudge students through pathways to help them be more employable as well as to provide school resources more equitably. By using real-time data to train the models, students are able to gain career readiness skills and immediately apply those skills to complete project-based internships with small to medium businesses. This process ensures that information provided by the model is industry relevant and can pivot quickly to align with changes in an industry such as hiring patterns, technology, industrial-organizational psychology, and other trends that increase the applicability of a talent pool.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SIGNAL-WISE LLC
STTR Phase I: AI- and Laser- Assisted Targeted Noise Control
Contact
1797 NEW CASTLE DR
Troy, MI 48098--6548
NSF Award
2348512 – STTR Phase I
Award amount to date
$275,000
Start / end date
05/01/2024 – 04/30/2025 (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 enables engineers to identify the root cause and weak spots of noise within a structure and apply local fixes rather than global treatments to mitigate noise emission. Employing the proposed AI and laser-assisted targeted noise control technology will enable the design and implementation of quieter and lighter metal structures. Studies have exhibited a direct correlation between weight reduction and CO2 emission. Statistics have revealed that for every 1 kg of steel used, 2.75 kg of CO2 will be emitted, and every 1 kg of aluminum used, 8.25 kg of CO2 will be released. In general, reducing 1% material weight in an automobile will decrease 1.25% CO2 emission. Our preliminary test results showed that using the proposed technology, sound transmission loss through a steel panel was increased, but its overall weight reduced by 38%. Therefore, this technology is not only cost-effective in mitigating noise issues, but also ideal for sustainability by simultaneously reducing structural weight and CO2 emissions.
This Small Business Technology Transfer (STTR) Phase I project is expected to produce a disruptive tool for engineers to perform targeted suppression of structure-borne sound radiation and transmission with higher precision, flexibility, and control than conventional sound characterization techniques. Specifically, the proposed technologies will enable engineers to see and determine: 1) where and how much acoustic energy is radiating from a complex vibrating machine; 2) where and how much sound is transmitting through a panel structure; and 3) where and how much to suppress acoustic radiation or sound transmission to meet noise mitigation requirements. Most importantly, it enables engineer to reveal the most critical components of structural vibrations that are responsible for sound radiation and uncover the root causes of noise issues. Accordingly, engineers will be able to enhance local stiffness, viscous damping, and mass without re-engineering the entire structure or increasing its weight. These targeted treatments can greatly shorten production cycle, cut production costs, enhance competitiveness, and increase profitability for U.S. manufacturing 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. -
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
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
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. -
SKILLSGAPP LLC
SBIR Phase I: Place-Based Platform for STEM Career Discovery
Contact
102 E SHALLOWSTONE RD
Greer, SC 29650--3311
NSF Award
2423615 – SBIR Phase I
Award amount to date
$274,428
Start / end date
07/15/2024 – 06/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase I project aims to address the persistent global skilled workforce shortage in STEM-based careers by facilitating corresponding career discovery in priority youth populations, outside of traditional K12 settings, using mobile gamification with a personalized, AI-generated career recommendation engine. Building on the foundation of game-based pedagogy that inspires and engages a diverse population, the AI-enhanced gaming platform will educate and guide youth toward local, meaningful career paths in advanced manufacturing relevant to their in-game proficiencies, personal preferences, and location. This geo-specificity is imperative in breaking cycles of poverty and keeping communities thriving. The core of this innovation lies in a synergistic combination of key AI technologies to provide unbiased, personally relevant learning experiences with actionable career guidance and mentorship through engaging and adaptive game mechanics. The insights gleaned from this endeavor will extend the project?s impact beyond advanced manufacturing careers to additional STEM industries in an effort to close social equity and knowledge gaps and foster a more diverse workforce around the world.
This Small Business Innovation Research (SBIR) Phase I project utilizes the integration of an LLM (Large Language Model) and RAG (Retrieval Augmented Generation) framework into a career gaming platform that carefully selects and provides context from controlled sources of information that the AI uses to generate personalized career guidance. Included in this innovation is the development of benchmarks where an AI-Judge, fine-tuned on the relevant data from a vector database, is leveraged to determine efficacy of the LLM to utilize knowledge in the RAG pipeline. The development of benchmarks and analytics layers around this environment creates a performance-driven closed loop system that allows for continuous improvement. Additionally, by controlling the datasets from which the AI retrieves information, this approach mitigates the risk of replicating biases and stereotypes and ensures diverse perspectives and data specifically relevant to the target. This method will also reduce computational demands, accelerate content updates, and is significantly less costly than fine-tuning a pre-trained LLM, allowing for easy adaptations of the knowledge it has access to. The combination of these adaptive technologies is poised to scale early career discovery across all STEM industries, for all youth, no matter where they live or what they look like.
This award reflects 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
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. -
SLUICEBOX, INC.
SBIR Phase I: Generative AI Toolbox for Interactive Life Cycle Assessments
Contact
11801 DOMAIN BLVD FL 3
Austin, TX 78758--3430
NSF Award
2423700 – SBIR Phase I
Award amount to date
$274,192
Start / end date
07/15/2024 – 03/31/2025 (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 is in shifting the way industries manage and mitigate their environmental impact through the development of an advanced generative AI toolbox for life cycle assessments (LCA). The project addresses the critical challenge of reducing Scope 3 emissions, which are often the most complex and significant part of a company?s carbon footprint. By providing real-time, explainable, and privacy-preserving insights into these emissions, the project aims to significantly enhance sustainability practices across various sectors. The innovative AI tool will empower businesses to make informed decisions that reduce their supply chain based environmental impact. This project aligns with NSF?s mission to promote the progress of science and advance national health, prosperity, and welfare. By facilitating better environmental management, the project is expected to create new jobs, stimulate economic growth, and generate income through increased efficiency and compliance with regulatory standards.
This project proposes the development of a generative AI toolbox for interactive life cycle assessments (LCA), which represents a significant technical innovation in the field of sustainability. The primary innovation lies in the integration of state-of-the-art generative AI with environmental data from various sources, including environmental databases, satellite imagery, and scientific literature. This high-risk effort involves creating a domain-specific large language model (LLM) that can process complex, multi-modal data and provide real-time insights into Scope 3 emissions. The goal of the project is to develop a robust, scalable, and privacy-preserving tool that can accurately predict and analyse the environmental impact of industrial activities. Methods include the development and validation of machine learning models, the standardization of heterogeneous data, and the implementation of advanced confidentiality and IP protection mechanisms. The successful completion of this project will result in a powerful tool that enhances decision-making capabilities for sustainability and drives significant reductions in 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. -
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. -
SOARCE, INC.
SBIR Phase I: Multifunctional, low carbon nanocomposite fibers derived from seaweed
Contact
6555 SANGER RD
Orlando, FL 32827--7584
NSF Award
2409680 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 seeks to phase-out fossil fuel-based textiles with sustainable, non-toxic fabric alternatives with enhanced properties. Currently, fabrics for high performance applications require toxic additives or coatings that may pollute air and water systems; additionally, most of them come from fossil fuels, contributing to global warming. If successful, the proposed project will produce novel seaweed-based textiles with enhanced properties like fire and ultraviolet blocking and infrared shielding properties. These properties are inherent to the material; thus, no further treatment will be needed, simplifying the manufacturing process. The material will be attractive to US work apparel and outdoor activewear manufacturers seeking to increase the sustainability of their products. The business model will be commercialization of the raw material and licensing the technology so manufacturers can fabricate the textiles to their needs. By doing so, the company requires less operational investment, easing its introduction to the market.
This Small Business Innovation Research (SBIR) Phase I project uses seaweed biopolymers combined with nanomaterials to create fibers and fabrics. The enhanced properties like fire resistance, ultraviolet protection and heat shielding, as well as the mechanical properties of the fibers, can be finetuned depending on the formulation and the production method. The aim is to develop a formula that will produce flexible fibers capable of being woven into fabrics with high performance characteristics. The team will vary the formulation chemistry, the spinning process and will test how it affects the mechanical and chemical characteristics. The project will focus on obtaining a fully plastic-free knitted yarn where UV protection, heat shielding, and fire resistance are achieved without adding plastic binders, coatings, or films.
This award reflects 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
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. -
SONOGEN MEDICAL, INC.
STTR Phase I: Ultrasonic Fracture Healing Assessment
Contact
3710 WILLIAMS LN
Chevy Chase, MD 20815--4950
NSF Award
2335462 – STTR Phase I
Award amount to date
$275,000
Start / end date
06/01/2024 – 05/31/2025 (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 Technology Transfer (STTR) Phase I project is a novel medical device algorithm for assessing the status of bone fracture healing using ultrasound measures. The system aims to provide advantages to current X-ray based paradigms by reducing cost and radiation exposure, and by enabling portability. An estimated 130 million X-Ray procedures are performed in the US each year, at a cost of $16 billion with as much as 25% redone due to quality issues. Furthermore, 2.8 million patients are considered at risk for delayed/non-union fractures. The combined market potential is $1.3B/year as a software solution to ultrasound equipment vendors and $1.4B/year for at home monitoring.
This Small Business Technology Transfer (STTR) Phase I project aims to develop the company?s proprietary fracture healing algorithm utilizing ultrasound data. During the first phase the company will acquire, analyze, and compare in-vivo ultrasound, X-ray, and micro-CT data in a lapine model across the healing cycle of surgically induced tibial diaphysis fractures. The company aims to de-risk their fracture healing to monitor the stage of orthopedic healing versus X-rays with 90% statistical confidence. The risks to be addressed include signal characterization versus noise ratio, back-scattering, and fracture healing classification. The results of the Phase 1 study will provide a working algorithm suitable to begin human feasibility 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. -
SONOVANCE, INC.
STTR Phase I: Novel signal estimation methods for low-cost diagnostic ultrasound acquisition by non-expert operators.
Contact
4203 SOMERSET PLACE
Baltimore, MD 21210--2708
NSF Award
2409639 – STTR Phase I
Award amount to date
$275,000
Start / end date
06/15/2024 – 05/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project can shape advances in health and welfare, national defense, and in science. The overall product simplifies image acquisition. It is an application for remote tele-health and enables any ultrasound device to take images without the operator needing to see the images acquired. Any physician, any nurse, and/or novice can acquire images, which can then be made available for experts, human or artificial, to examine. This opens up the bottleneck of high-cost trained sonographers to enable more rapid growth of the market, and can scale rapidly on any of the devices of large ultrasound device manufacturers. The technology can reduce costs associated with training and reduce variability in hospitals and health systems, reach patients in their homes, in primary care or retail clinics, and in urgent and remote care centers. Other needs that can be met include the Veterans Administration in its community-based outpatient clinics currently lacking imaging facilities; and in the Army in battlefield situations where ultrasound in the front lines can now be used due to obviating lengthy training requirements. Scientifically, other coherent imaging methods such as optical, photoacoustic, and thermoacoustic would also benefit.
This Small Business Technology Transfer (STTR) Phase I project develops low-cost
hardware and software for the acquisition of ultrasound images so that no anatomic training is needed, instead guiding even a lay operator with easily learned graphical clues until data acquisition is complete and can be passed, for example, to an examining physician in a format familiar to her from other radiological images. The central innovation is in signal and image processing that will allow accurate image reconstruction from freehand 2D ultrasound signal data with imperfect information on the position of the probe that comes from low-cost sensors. This is an essential element that enables the low-cost solution envisaged. Instead of the conventional approach of registering two image sets by comparing overlapping images, new methods are proposed so that different scan planes which do not have overlapping sets of images can be co-registered accurately. The key objectives of the research are to implement and test the algorithms for improved localization of an ultrasonic echo return, and then to determine whether these improvements are sufficient to obtain images of clinical quality as deemed by a qualified radiologist. Success allows a prototype satisfying the overall goal of the first sentence above.
This award reflects 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. -
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
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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
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 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
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 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. -
SPECTACULAR LABS, INC.
SBIR Phase I: Automated AI-supported sample preparation and enrichment technology for rapid detection of food pathogens
Contact
79 HARBOR VIEW DR
Richmond, CA 94804--7496
NSF Award
2402679 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 06/30/2025 (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 to provide the food industry with a fully automated platform for rapid detection of food pathogens. In the U.S., foodborne diseases cost ~$60.9B in medical care, lost productivity, and lives lost, rising to $90.2B when taking quality of life losses into account. Food pathogens also lead to greatly increased costs for food producers, both due to food safety testing itself and recalls caused by contaminated food, which average $10M in direct costs. The proposed food pathogen detection system will meet the food industry?s large unaddressed need for portable, affordable, accurate and time-sensitive testing that can be performed by non-specialists. Critically, an affordable onsite system will lower direct costs and increase testing capacity?the increased volume of testing will reduce the risk of contaminated food entering the marketplace with the associated costs to both businesses and the U.S. economy. Further, data collected by the proposed system will provide insights into the food safety landscape resulting in a safer food supply chain and reduced food producer liability.
This Small Business Innovation Research (SBIR) Phase I project aims to develop an end-to-end, affordable, fully automated, easy-to-operate, portable system for accurate and rapid detection of food pathogens across a broad range of food types. The system uses adaptive design of experiments to optimize the platform hardware and protocols, enabling rapid testing and allowing for earlier detection of food pathogens than currently possible. The proposed technology will provide the same value as traditional third-party laboratories, yet faster and at a fraction of the cost with the ability to test in-house, thus meeting the needs of small to medium-sized food producers and food processing plants. In Phase I, the company aims to 1) Build an automatic sample preparation module and explore its ability to enhance enrichment across food groups; 2) Develop an automated experimental design workflow to speed up the optimization of enrichment time; and 3) Using experimental data, develop an algorithm to quantify the microbial concentrations in food samples. Successful completion of this work will lay a foundation for future Phase II commercialization activities where the platform will be scaled to additional use cases.
This award reflects 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. -
SUBTIDAL, INC.
SBIR Phase I: A Scalable Ocean Carbon Sensing Grid
Contact
62 TERRENCE AVE
East Falmouth, MA 02536--5406
NSF Award
2404712 – SBIR Phase I
Award amount to date
$274,916
Start / end date
07/01/2024 – 12/31/2025 (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 to enhance the capabilities for precise measurement, reporting, and verification (MRV) of ocean carbon dioxide removal (CDR). By developing an innovative volumetric carbon flux approach, this technology aims to provide a scalable and accurate method for quantifying the effectiveness of various ocean-based CDR strategies. Ocean carbon dioxide removal, capable of extracting up to 5 gigatons of CO2 annually from the atmosphere, is crucial for achieving the global imperative of removing 10 gigatons of atmospheric CO2 annually to limit warming to 1.5-2°C. By introducing an accurate, scalable solution for measuring ocean carbon removals, the proposed technology has the potential to accelerate the expansion of the ocean CDR market to $25 billion by 2030 and up to $500 billion annually by mid-century. The successful implementation of this technology would significantly advance our scientific and technological understanding of carbon cycles, support environmental sustainability, and foster substantial economic growth in a sector critical for global climate mitigation strategies.
This Small Business Innovation Research (SBIR) Phase I project aims to tackles the critical challenge inhibiting the ocean carbon dioxide removal (CDR) industry from achieving its potential to remove up to 5 gigatons of CO2 annually: the absence of precise measurement tools to accurately quantify ocean CO2 removal. The research objectives for this phase include developing and validating a mooring-based sensing grid capable of delivering three-dimensional carbonate chemistry data with the sensitivity necessary for continuous and direct measurement of net carbon removal in various ocean CDR projects. The proposed research entails designing, implementing, and testing the sensing grid to ensure it meets the stringent requirements necessary for effective deployment in ocean carbon dioxide removal environments. Anticipated technical results include achieving measurement sensitivity, accuracy, and reliability, necessary to continuously measure net carbon removals for a wide variety of ocean CDR methods. Successful completion of this phase will lay the groundwork for subsequent phases aimed at piloting and refining this technology with ocean CDR developers, potentially establishing the first direct measurement system for carbon removal efficacy in the ocean CDR 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. -
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
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 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
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 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
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. -
SYNSORYBIO, INC.
SBIR Phase I: Engineering drugs that sense and respond to disease
Contact
24 WESLEY PARK APT 1
Somerville, MA 02143--1803
NSF Award
2404668 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 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 is to create cancer medicines that turn on only at the site of disease and remain inactive in healthy tissues. An estimated 90% of drugs fail to gain FDA approval, in large part due to off-target side effects and dose-limiting toxicities. This is because drugs are typically active all throughout the body, where the drug can act on disease tissue and healthy tissue. This is especially problematic when deploying potent cancer immunotherapies. Cancer immunotherapies are designed to stimulate the immune system to fight cancer and have been a revolutionary approach in the last decade. The discovery of immune checkpoint inhibitors garnered the Nobel Prize in Chemistry, and now many patients are commonly prescribed treatments such as Keytruda and Yervoy. However, indiscriminate immune activation can be lethal to patients, cause long-term complications, and limit the full potential these treatments. This project aims to develop a method to turn on these drugs only at the site of disease to create drugs that are safer and more effective to treat cancer.
The proposed project focuses on creation of protein switches that ?turn on? when they see a pre-defined disease signal at the site of disease. Specifically, this project aims to control the activity of a previously approved immunotherapy. This immunotherapy increases immune responses toward many types of cancer, but it is underutilized due to off-target side-effects and toxicity. To overcome this issue, a new version must be engineered to act locally at the site of disease, akin to how the body naturally mounts an immune response. This problem is being addressed by engineering protein therapeutics that sense-and-respond to disease. This protein therapeutic will be modified to only turn on when it sees a disease signal associated with many cancers. Locally acting therapeutics remain a long-standing goal in medicine, but current technologies used to locally deliver protein therapeutics lack versatility and truly local activity. In contrast, the proposed approach uses a versatile mechanism to control a protein?s activity following engineering principles. This phase I proposal may create proof of concept data to show that this novel technology can conditionally trigger a therapeutic response by a pre-defined disease signal. This platform technology may also be adapted to extend to other protein-based drugs and impact many other areas of therapeutic 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. -
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 – 12/31/2025 (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. -
TANDA BIOTECH CORPORATION
SBIR Phase I: High-capacity reusable filter technologies for large scale perfusion applications
Contact
1410 WINSTON DR
Buffalo Grove, IL 60089--6833
NSF Award
2413512 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will drive advancements in tubular membrane filter design, effectively tackling the critical bottleneck associated with capacity limitations. By doing so, it will contribute to reducing operational costs and minimizing plastic waste associated with polymer filters used in bioproduction, particularly in cell separations.
This SBIR Phase I project aims to validate an innovative filter flow channel design, enhancing resource efficiency, expediting cleaning and regeneration processes, and significantly boosting filtration system capacities by one or two orders of magnitude. Tubular membranes with rigid walls, such as ceramic membranes, offer higher flux rates and proven reusability but require high recirculation pump rates in tangential flow filtration systems, leading to bulkiness and substantial consumption of cleaning reagents. Through a combination of mathematical modeling and lab testing, the project will develop and validate innovative flow channel designs for tubular membrane filters. Upon completion, the project aims to reduce the cross-flow rate of tubular membrane filters, improve transmembrane pressure across all membrane surfaces, and mitigate membrane fouling while enhancing flux rates. These advancements in flow channel design are expected to extend processing time and capacity between regenerations, thus optimizing system 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. -
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
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. -
TECTARIA BIO LLC
SBIR Phase I: Engineered Cell Lines with Activated Proteasomes for Increased Biomanufacturing Efficiency
Contact
4300 LAZYRIVER DR
Durham, NC 27712--9543
NSF Award
2415545 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/01/2024 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to reduce the costs associated with the biomanufacturer of advanced therapies by making their manufacture more efficient. This project seeks to test the feasibility and application of a novel technology to significantly increase the protein production capabilities of cell lines currently used in the manufacture of biologics, gene therapies, and vaccines. Achievement of this project?s objectives could enhance the health and welfare of Americans by making advanced therapies more economically accessible. As the population ages, the prevalence of debilitating diseases like Alzheimer's and cancer is on the rise. This project could make the solutions to these issues more affordable and effective, significantly impacting the quality of life of Americans. In addition, this project could help revolutionize treatment for rare genetic disorders by overcoming the current hurdles of high manufacturing costs, thereby broadening access to these vital treatments.
The proposed project seeks to build on initial data showing that enhancement of the cellular proteasome has an unexpected and counterintuitive effect on protein production in cells. The aims will be to demonstrate that this technology can be applied to cells commonly used in the manufacture of advanced therapies and that it can enhance the production of protein types relevant to human health such as gene therapy vectors and biologic drugs. Successful completion of this project will also provide new insights into the function of cells used in biomanufacturing and potentially enable further innovation in this area to ease this bottleneck on the production of advanced 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. -
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
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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. -
TERASPATIAL INC
SBIR Phase I: Simultaneous Transmit-Receive and Full-Duplex Millimeter-Wave Massive Multiple-Input and Multiple-Output (MIMO) Systems
Contact
2164 WEBSTER ST
Palo Alto, CA 94301--4051
NSF Award
2322297 – SBIR Phase I
Award amount to date
$274,959
Start / end date
09/15/2023 – 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 addresses the demand for high-speed, secure, reliable, ubiquitous wireless connectivity, driven by digital transformation in the commercial and defense sectors. The widespread use of the millimeter-wave (mmWave) spectrum is essential to meet this demand, despite the release of new spectrum below 10 GHz (which will help in the short term, but not by itself be able to satisfy overall demand). The last few years have seen first-generation deployments of mmWave systems mainly for mobile access applications to smartphones. However, mmWave networks have not become widespread, due to significant pain points and challenges that remain in terms of coverage, capacity, reliability, ease of deployment, and total cost of ownership. Moreover, the high energy consumption of current 5G systems is estimated to have a significant impact on global carbon emissions and network operators? energy costs. This project comprises three elements: enabling high-speed broadband access for all Americans; deploying a reliable, high-speed, low-latency wireless connectivity in the manufacturing, industrial and energy infrastructure sectors, and building partnerships with academia to enhance the American STEM workforce. Optimized solutions have an annual market estimate of $10 billion.
This Small Business Innovation Research (SBIR) Phase I project will develop technologies for efficient, practical and low-cost Multiple-Input and Multiple-Output (MIMO) full-duplex radios operating in high frequency spectral bands and will pave the way for their eventual commercial implementation in future wireless networks. This project will adopt a holistic, inter-disciplinary approach to develop hardware-software system solutions encompassing novel silicon and novel algorithms to enable better use of spatial, temporal and frequency resources. If successful, the developed solutions can eventually lead to greater coverage, higher reliability, lower latency, more efficient spectrum usage, and also higher performance, lower power and cost. The team is building mmWave system (software + silicon) solutions that efficiently form and intelligently steer beams to enable better use of the spatial domain. The solutions can lead to greater coverage, higher reliability, lower latency, more efficient spectrum usage, and also higher performance, lower power and cost. To this end, the mmWave MIMO radios are based on two core principles: ?digitalized? hardware created by designing advanced digital/hybrid MIMO radios and integrated artificial intelligence (AI)/ machine learning (ML)-based algorithms tightly into the radio/physical layer. While the above goals are by themselves a significant advance over the state-of-the-art, the aim in Phase I is to specifically focus on solving technical challenges to implement mmWave full-duplex MIMO communication in wireless networks of the future, and to eventually drive this technology towards commercial adoption.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
TERRAFORMA CARBON LLC
SBIR Phase I: Geologic Biosolid Sequestration using Preexisting Wastewater Disposal Wells
Contact
119 S BURROWES ST
State College, PA 16801--3864
NSF Award
2423575 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 06/30/2025 (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 is in creating a new carbon sequestration method that requires significantly less energy, water, land use, and cost per ton of carbon removed. By addressing technical challenges posed by geologically sequestering biowastes such as human biosolids and agricultural manure, this project attempts to turn a waste problem into a revenue opportunity that also mitigates climate change. It is not yet known if geologic biowaste sequestration can be performed safely, and this lack of known feasibility keeps regulation from being introduced to allow it to be generally permitted. The commercial impact of the project, however, is significant. Current carbon removal credits cost over $800/ton. The proposed project could pave the way to removal of as much as 7 billion tons of CO2e in biowastes alone each year at costs as low as $10 - $20/ton. The technology has the potential to create about 400,000 high-quality jobs in the US and save local governments almost $1 billion in wastewater treatment costs per year that could be reallocated for additional social benefits.
This project aims to overcome the high-risk technical challenges associated with commissioning new injection well classes, or modifying existing ones, that are focused on geologic sequestration of biowastes. The goal is to demonstrate that biowastes can be injected into the subsurface safely without inducing earthquakes, clogging reservoirs, or creating unsafe pressure buildup. Critically, it will also determine that over long periods, microbially produced greenhouse gases (CO2, methane, and nitrous oxides) emitted from the biosolids do not migrate out of the reservoir and into overlying freshwater aquifers. Other contaminants including bacteria, toxins, and other harmful chemicals will also be monitored to show that they remain permanently sequestered. Furthermore, there is currently no credible protocol for generating carbon removal credits for biowaste sequestration. This project could develop scientific basis for carbon accounting?including CO2e from methane and nitrous oxides?that generates accurate removal and offsetting credits. Thus, the project will attempt to address the unknowns associated with storing solid carbon in the subsurface and the associated carbon accounting.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
THERAFLUOR, INC.
SBIR Phase I: Research and Development of a Multi-mode Instrument for Cancer Diagnosis and Treatment in Companion Animals
Contact
4023 NE HANCOCK ST
Portland, OR 97212--5324
NSF Award
2335292 – SBIR Phase I
Award amount to date
$274,999
Start / end date
07/15/2024 – 06/30/2025 (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 a novel therapeutic approach for detecting and treating cancer in companion animals. The project aims to develop a medical instrument when utilized with a novel proprietary molecular therapeutic compound, will visualize, target and effectively eliminate cancerous cells. The system aims to become a standard approach for the $3B companion pet cancer diagnostics and treatment annual market and create a new diagnostic and therapeutic approach.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a low-cost instrument for use in standard veterinary clinics that will visualize and monitor the delivery and effectiveness of the photosensitive compound molecule silicon naphthalocyanine nanoparticle (SiNc-NP), for targeting and eliminating cancer cells in an animal model. Preliminary invitro evidence indicates SiNc-NP differentiates cancerous tissue from non-cancerous, and can identify and kill the cancerous tissue upon an evoked response. This project proposes to yield a cost effective, manufacturable and robust multimodal instrument enabling veterinarians to utilize SiNc-NP as a cancer treatment in a standard clinic. The technology development to be completed during this phase includes integration of light optics, mechanical and electronics design, and software engineering to develop an instrument capable of imaging both the visible spectrum (400-700nm) and near infrared (~800nm) and present the user with an integrated and aligned single video stream that differentiates cancerous and non-cancerous tissues. The instrument also directs high intensity radiation onto the SiNc-enabled cancerous tissue and measure the tissue temperature to indicate when the temperature and exceeded the targeted temperature (5-50C) for the minimum duration (~>10 minutes) sufficient for killing the cancerous 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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
UBIQUITX, INC.
SBIR Phase I: Chimeric Ligands for Induced Proximity (CLIPs) for Targeted Proteome Editing
Contact
160 W 87TH ST
New York, NY 10024--2934
NSF Award
2405853 – SBIR Phase I
Award amount to date
$275,000
Start / end date
07/15/2024 – 06/30/2025 (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 will be to foster the economic competitiveness of the United States, advance the health and welfare of the American pubic and enhance partnerships between academia and industry. Drug discovery is hindered by high costs and lengthy development time, with costs often passed onto consumers. To alleviate these burdens, the private sector has invested in new research to discover faster, more cost-effective drug development methods. The platform in this Phase I effort may offer an answer to drug discovery challenges through rapid and inexpensive development of post-translational protein-editing therapeutics. The commercialization of the technology detailed here also may support the drug discovery field and advance America?s influence in the pharmaceutical production space, specifically for the generation of a novel therapy promoting liver regeneration in alcoholic hepatitis. The platform may also advance the health of Americans by offering a method to program the localization and activation of disease-relevant proteins currently considered undruggable and advancing therapeutics for alcoholic hepatitis as an initial focus. Further, the protein-editing platform was developed by members with pharmaceutical industry background as well as academic professions, thus demonstrating the importance of partnerships across these sectors.
The proposed project will advance a programmable, modular therapeutic platform for the direct modification of proteins of interest (POIs) via artificial intelligence, protein engineering and mRNA as a therapeutic entity. Proteins are a logical avenue for the development of novel therapies, but the current drug discovery pipeline requires targeting proteins with drug binding pockets and involves extensive, time-consuming screening to identify lead candidates. The platform described here leverages engineered enzymes to recognize and edit POIs by removing/installing post-translational modifications rapidly and precisely. The protein editors, chimeric ligands for induced proximity (CLIPs), feature a targeted recognition domain and protein modification enzyme component tailored to the POI. Following successful demonstration of targeted degradation of specific CLIPs in previous studies, the platform has also successfully achieved target POI stabilization, demonstrating platform modularity. This Phase I project seeks to expand the applications of the platform by designing and implementing CLIPs for other post-translational modifications by conjugating computationally derived peptides to various enzymes targeted to the POI. In vivo target engagement studies will also be conducted on CLIPs generated to extend the platform and demonstrate applicability in stabilizing ?-catenin and subsequently initiating liver regeneration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
URL TO IRL INC.
SBIR Phase I: Automated Digital Accessibility Testing and Remediation Compliance Platform for Web Content Accessibility Guidelines
Contact
15932 60TH AVE SE
Snohomish, WA 98296--4646
NSF Award
2408875 – SBIR Phase I
Award amount to date
$274,990
Start / end date
05/01/2024 – 10/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase I project is to make the Internet more accessible for those with physical, mental, or cognitive disabilities. Over the last three decades every sector has experienced a digital transformation. Despite federal regulation requiring digital assets such as websites, kiosks, or mobile apps to be compliant with the Americans with Disabilities Act (ADA), over 96% of the million most-visited websites are not ADA compliant. For the 17% of Americans with a disability the Internet is unusable. This innovation applies novel breakthroughs in generative artificial intelligence to automatically identify and remediate ADA violations in digital assets. Thus, ensuring that any platform from healthcare to public transportation to voting platforms are universally accessible. Consider the implications: an elderly citizen with deteriorating vision can seamlessly navigate an online prescription platform; a veteran with motor disabilities can effortlessly book transportation to a voting center; a K-12 STEM student with auditory challenges can access vital educational information or public service announcements without impediments. Automation of accessibility testing, and remediation leads to significant cost savings for companies, governments, and small- to medium-sized businesses that want to access the $17 trillion of spending power that disabled Americans and their families hold.
This Small Business Innovation Research (SBIR) Phase I project replaces the manual testing, manual remediation, manual training, and manual auditing that software engineers or consultants use to make digital assets compliant with the Americans with Disabilities Act (ADA). The aim is to leverage artificial intelligence, computer vision, and novel production code reassociation techniques to accurately identify 65% of Web Content Accessibility Guidelines (WCAG) compliance issues, significantly higher than industry leaders, and provide solutions that are both context-aware and developer-friendly directly within Integrated Development Environments (IDEs), something no industry-leader today does. The research will refine a novel approach which allows frontend software to be retraceable for automated testing and fixing at the source code level, enabling engineers to pinpoint exactly where an accessibility violation is located. Existing solutions completely lose track of the relationship between production software and the original source code that generated it. Instead, resorting to screenshots or inaccurate approximations to give developers context. The core technical innovation not only detects non-compliant elements, but also provides real-time contextual developer solutions in the immediate line of code or component where the error occurs. This research pushes the digital accessibility industry to full automation, resulting in a more usable Internet.
This award reflects 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
$275,000
Start / end date
03/15/2024 – 08/31/2024
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) project is in advanced semiconductor technologies that are of critical need for emerging autonomous systems, networked sensing technologies, artificial intelligence enabled systems, aerospace, and defense surveillance systems. In-Space manufacturing under microgravity conditions enable unique materials characteristics and advanced semiconductor device designs with significantly higher performances, thus providing the most appropriate platform for meeting the technological and market demands. A novel class of semiconductor based composite materials with unique characteristics for numerous large scale emerging applications including, magnetic sensing, thermoelectrics, photovoltaic power generation, quantum computing devices, etc. will be developed. The proposed manufacturing plans will benefit the US national defense and civilian industry. The In-Space manufacturing platform will boost the yield and reliability for high performance device technologies, meeting the demand of the multi-billion US$ 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. -
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 – 09/30/2024 (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 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)
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 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. -
VORTEX SPACE SYSTEMS LLC
STTR Phase I: Hyper Transfer Vehicle Concept Demonstration
Contact
24225 WELSH RD
Gaithersburg, MD 20882--3929
NSF Award
2233424 – STTR Phase I
Award amount to date
$274,454
Start / end date
04/15/2023 – 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 Technology Transfer (STTR) project is to develop a new, non-rocket based thrust technology capable of removing debris from space. This project will provide two separate business models including hardware fabrication and testing, and active orbital debris removal services. Six Department of Defense (DoD) and National Oceanic Atmospheric Administration (NOAA) Sun Synchronous Orbits (SSO)SSO spacecraft have broken up in high-value low earth orbits since 2000, and the US Space Force tracks over 550 pieces of NOAA-16 and NOAA-17 debris objects (>10cm). This technology provides solutions to help remove such problematic debris from space. The technology will be designed for beneficial use by both US Government agencies and commercial space companies. The proposed vehicle fleet production is expected to enable efficient deorbit services for removal from space.
This STTR Phase I project proposes to develop an innovative method for Earth orbit transfer, called a Hyper Transfer Vehicle (HTV). HTV is a non-rocket technology that solves performance limitations of in-space rocket thrusters. HTV offers reusable and economically sustainable orbital space debris removal solutions across all earth operational orbits. This proposal addresses the space debris problem not caused by operational satellites, but from non-maneuverable objects and debris in the highly populated Sun Synchronous Orbits (SSO). Historically, SSO space objects have contributed to technical, societal, and scientific advancements. The potential outcome of HTV research is a viable and reusable technology for cost-effective orbit object disposal in high value SSO with clean Solar Electric Propulsion (SEP). Instead of expelling propellant, HTV rotates a working fluid gas inside a toroidal cavity to generate a usable force. HTV torus structure draws in the gas while mounted inside an ambient pressure enclosure, which is separate from the vacuum of space. HTV generates a reactive force by employing the Conservation of Angular Momentum (CAM). CAM is preserved when HTV fluid angular momentum (H) and rotational energy (Trot) change. This project will demonstrate with experimental measurements an external force by using air as the working fluid gas, while satisfying CAM.
This award reflects 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. -
Virolock Technologies Limited Liability Company
SBIR Phase I: A novel platform for virus enrichment and isolation
Contact
200 INNOVATION BLVD
State College, PA 16803--6602
NSF Award
2222991 – SBIR Phase I
Award amount to date
$274,459
Start / end date
07/01/2023 – 12/31/2025 (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 will be the creation of a virus capture technology that may improve the reliability of diagnostic tools needed to detect viral infection in humans, animals, and plants. The proposed device will be designed to be easy to use, portable, and cost-effective, and could accelerate virus detection, providing superior analytical and clinical performance. Early and accurate diagnosis of infectious diseases is critical to curbing the spread of viral infections, improving health outcomes, and reducing economic losses. This technology is a platform potentially applicable to a wide range of target viruses and could be functional in different scenarios like virus surveillance, identification of emerging viruses, and detection of virus mutations.
The proposed project seeks to validate the technical feasibility of this technology for direct virus detection methods such as polymerase chain reaction (PCR), immunoassay, and next generation sequencing (NGS), to improve the virus to host ratio and allow for faster results. The project aims to develop a portable sample processing platform that enables high-efficiency virus trapping and purification from field samples (from cotton swabs or tissue biopsy) without using antibodies. This technology uses carbon nanotube arrays to trap virus particles by size discrimination while segregating host contaminants. This technology could be integrated into standard virus diagnostic protocols to achieve a faster, simpler, and more accurate diagnostics compared to traditional processes for virus sample preparation, such as ultracentrifugation and membrane filtration. Currently available state-of-the-art technologies present limitations in extracting pure virus particles from the host material, especially when the viral content is low, usually leading to false negative 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. -
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. -
WATERUS LLC
SBIR Phase I: Flow-cell Assisted Softening Technology (FAST) for Whole Home Water Treatment
Contact
201 ASCOT RIDGE RD
Irmo, SC 29063--7923
NSF Award
2345601 – SBIR Phase I
Award amount to date
$275,000
Start / end date
05/15/2024 – 04/30/2025 (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 is rooted in addressing the pervasive challenge of hard water?a condition affecting over 85% of households in the United States, leading to significant economic and environmental burdens. Hard water, characterized by high concentrations of calcium and magnesium, contributes to the inefficiency of water-using appliances, increases maintenance costs, and necessitates the use of environmentally harmful water softening methods. This project proposes an innovative, environmentally friendly solution to softening hard water without the use of salts, which are traditionally discharged into water systems, causing pollution and exacerbating regulatory challenges. The significance of this research lies in its potential to provide millions of U.S. citizens with access to soft water, thereby improving quality of life, reducing household expenses, and contributing to the preservation of natural water resources. Additionally, by offering an eco-friendly alternative to current water softening methods, this project aligns with the National Science Foundation?s mission of advancing the health, prosperity, and welfare of the nation, while also possessing the commercial potential to create jobs and generate tax revenue.
This project introduces a significant technical innovation in the field of water treatment through the development of a novel electrochemical process for softening hard water without the addition of salts. Unlike existing technologies that rely on ion-exchange resins or chemical conditioners, this project employs a unique method based on redox flow cell technology to selectively remove calcium and magnesium ions from water. This high-risk effort is characterized by its attempt to overcome the limitations of current water softening systems, including high operational costs, environmental impacts, and maintenance challenges. The goals of this research include achieving a softening capacity suitable for the average American household, ensuring water safety standards, and demonstrating the system's long-term durability and cost-effectiveness. The research will employ a combination of electrochemical engineering, material science, and fluid dynamics to optimize the design and operation of the softening system. By addressing the technical hurdles associated with membrane durability, electrode stability, and system efficiency, this project aims to bring a groundbreaking solution to the market, setting a new standard for sustainable water treatment 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. -
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
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 "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. -
WEKA BIOSCIENCES LLC
SBIR Phase I: Developing a Microbial Process for Creating a New Type of Natural Polymer
Contact
322 PASEO DE PERALTA
Santa Fe, NM 87501--1861
NSF Award
2406036 – SBIR Phase I
Award amount to date
$274,727
Start / end date
08/01/2024 – 07/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project involves the development of a novel sugar polymer designed specifically to improve chromatography, a technique used by scientists to separate and analyze mixtures. This project focuses on chiral chromatography, which is crucial for distinguishing between molecules that are mirror images of each other but behave differently in the body. This capability is especially important in pharmaceutical manufacturing, where the safety and effectiveness of drugs often depend on these molecular distinctions. By creating a stable, synthetic sugar polymer through a microbial process, this project aims to provide a more reliable and efficient alternative for chiral chromatography. This innovation will not only enhance the precision of drug manufacturing but also contribute to safer and more effective medications, aligning with broader public health goals.
The proposed project will focus on engineering a microbial process to produce a novel sugar polymer that meets the specific demands of chiral chromatography. By optimizing the production of this polymer in microorganisms, the project seeks to enhance the properties of chromatography materials, such as increased durability and improved ability to separate molecular mirror images. The research will involve refining genetic pathways for maximum yield, scaling up fermentation processes, and establishing purification protocols to ensure that the polymer adheres to high 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. -
WESTWOOD AEROGEL CO.
SBIR Phase I: Advanced Manufacturing for Aerogels for Low and Zero-Emission Applications
Contact
555 PIERCE ST APT 1531
Albany, CA 94706--1010
NSF Award
2401627 – SBIR Phase I
Award amount to date
$274,855
Start / end date
07/01/2024 – 06/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project will be to develop and optimize an advanced manufacturing process for aerogel insulation materials. Aerogels are a class of lightweight thermal super-insulators that are challenging and costly to manufacture due to a high-heat, high-pressure drying process in the final stages of production. To address this, a new method for drying aerogels using ambient pressure and ambient temperature has been developed. This process enables low-cost, high volume production and reduces aerogel production costs by up to 90%. This process will first be used to develop thermal insulation for batteries in electric vehicles, where aerogels are critical as a lightweight, high-temperature material for maintaining stable temperatures. The market for aerogels in EV batteries is rapidly growing, and has a balance of price sensitivity and demand that makes it suitable as a first market using this new production process. Once this process is scaled and optimized, aerogels may become viable for other critical markets including building insulation, energy storage and aviation.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a low-cost, scalable manufacturing process for aerogel insulation materials. Aerogels are a class of super-insulating materials known for their light weight and superior insulating properties, but are extremely expensive and scarce due to inefficiencies in the production process. The current manufacturing involves using specialized pressure chambers to dry aerogels under high heat and pressure, resulting in high energy costs and low production volumes. This project proposes a novel aerogel production process that dries the aerogels under ambient pressures and temperatures in a continuous process that resembles window glass manufacturing. This ambient drying process dries aerogels by saturating wet gels in a gas atmosphere, slowly drying the gels without causing stresses that can crack the gel. This reduces costs and energy consumption, and allows for a continuous, linear production process without the use of specialized pressure chambers. By enabling scalable production of high-quality aerogel insulation, this innovation could make aerogels more accessible and affordable, transforming insulation across a variety of modern industries. The project aims to use this manufacturing method to develop thermal separators for electric vehicle battery insulation to enhance safety and performance in extreme temperatures.
This award reflects 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
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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
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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
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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. -
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. -
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
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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
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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
Errata
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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. -
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)
NSF Program Director
Errata
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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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