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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
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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
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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
Please report errors in award information by writing to awardsearch@nsf.gov.
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