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Phase I
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2PI INC.
SBIR Phase I: High-performance, ultra-compact 3D sensor enabled by metasurface flat optics
Contact
292 NEVADA ST
Newton, MA 02460-
NSF Award
2204825 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2022 – 11/30/2023 (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 the development of a lightweight, ultra-compact 3D sensor offering enhanced performance compared to the current state-of-the-art. Existing sensors on consumer electronic devices, such as those on augmented/virtual reality headsets, are limited in their perception accuracy and detection range resulting in a poor user experience, which has limited their implementation. The technology developed in this project seeks to address these issues to create a truly seamless and immersive interaction experience for users. The technology may also improve the adoption of augmented/virtual reality technologies in fields such as education, telecommuting, healthcare, industrial design, virtual meetings, entertainment, and many others. The technology has the potential to create new jobs in these fields, enhance human-to-machine interactions, and improve connections within and between communities. This effort also supports domestic photonics manufacturing and assembly industries.
This SBIR Phase I project will seeks to develop a novel 3D sensor design that promises performance enhancement over state-of-the-art devices. Building on a proprietary flat optics technology, the project may lead to a 3D sensor module featuring panoramic vision, significant spatial resolution improvements, enhanced signal-to-noise ratio, and a compact, lightweight architecture amenable to low-cost manufacturing and assembly. The project has two main goals: 1) demonstration of a 3D sensor prototype and experimental validation of its performance and 2) development of scalable manufacturing routes for fabrication of flat optics components leveraging standard microfabrication 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. -
ABBERIT LLC
SBIR Phase I: Harvesting strawberry using delta robots
Contact
8201 164TH AVE NE
Redmond, WA 98052--7615
NSF Award
2207897 – SBIR Phase I
Award amount to date
$256,000
Start / end date
10/01/2022 – 09/30/2023 (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 project is to enhance scientific and technological understanding in selective harvesting of high-value crops such as strawberry. The innovation proposed here will be a key component in creating a compact economically viable autonomous strawberry harvesting robot. The technology developed in this project will help address the farming labor shortage which is experienced by farmers more and more each year. Agricultural robotics market is estimated to be $11.9 billion by 2026. Providing autonomous harvesting robots will enable farmers to grow more crops with less business risks related to manual labor shortages and will ensure that US farmers remain competitive, while creating more skilled, highly paid jobs.
This Small Business Innovation Research (SBIR) Phase I project will develop critical technologies for delicate selective harvesting of fragile crops such as strawberries at a competitive pace. Recent advancements in computer vision object detection and three-dimensional scene reconstruction will be used to create near real-time operational scenes. Those scenes will be used to detect ripe berries, create a movement path and navigate the fast and precise robot arm for harvesting the berries without damaging fruits while avoiding obstacles.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ACTIVECHARGE LLC
STTR Phase I: Enhancing wind-energy industry competitiveness using self-powered blade monitoring sensors
Contact
1450 S ROLLING RD
Halethorpe, MD 21227--3863
NSF Award
2131373 – STTR Phase I
Award amount to date
$256,000
Start / end date
10/01/2022 – 09/30/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project seeks to provide an integrated monitoring solution for wind turbine blades. Continuous and reliable monitoring within the blade has been a challenge, primarily due to the lack of reliable energy for the wireless sensor (e.g., batteries need to be replaced and can be expensive and logistically difficult to replace inside the blade and power lines inside the blade are hard to install and require frequent maintenance). The proposed solution seeks to overcome current technical challenges by providing a long-lasting, maintenance-free, self-powered, integrated solution for wind turbine blade monitoring and analytics. If successfully commercialized, the solution can be deployed for autonomous sensing and smart maintenance scheduling based on big data analysis. This project may contribute to significantly and permanently reducing existing blade monitoring costs, decreasing downtime for manual monitoring and battery changes and reducing catastrophic failures with better monitoring information. By reducing the operational costs, the solution may make large-scale wind energy more competitive, reducing the world’s dependence on environmentally-harmful sources of energy. In addition, the technology may reduce the risk of injury to humans as compared to current operational processes, making wind energy safer to operate.
This STTR Phase I project proposes to develop an integrated, self-powering sensor node for wind turbine blade monitoring by overcoming the following technical hurdles: lack of reliable energy for the sensor/transmitter system deep inside the blade, logistical challenges to replacing batteries inside the blade for a large number of sensors at different intervals, and difficulites with long wire-runs inside the blade as those are hard to install and require frequent maintenance. To handle these technical hurdles, this project aims to prototype an integrated, self-powered, wireless sensor node and perform field tests. This project plans to: (1) develop a mechanism for the harvester module that reliably produces electrical voltage and power regardless of the blade rotational speed, (2) develop a power management circuit with autonomous sleep/wakeup and without impedance tracking to increase charging efficiency, and (3) perform indoor and in-field test for verification of power harvesting and data transmission performance. This technolology seeks to address the fundamental weaknesses of vibration energy harvesters while integrating various components (e.g., energy harvester, sensor, transmitter, receiver, and analytics software) for an optimized solution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADAXIUS CORP
SBIR Phase I: CNT-Enhanced carbon fiber structural composite with high performance and spec-tunability
Contact
41608 CLEMENS CIR
Novi, MI 48377--2863
NSF Award
2211884 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project will be materials that are lighter weight, tougher and more durable than existing carbon fiber reinforced polymer composites. This will allow companies incorporating these materials into their products to save energy by making products and vehicles that are lighter weight and also to improve range and fuel economy which will subsequently reduce greenhouse gas emissions. In aerospace applications payloads will be reduced saving both money and energy. In defense applications, tougher materials will improve reliability and reduce field repairs, which can be dangerous. In all these applications, the likelihood of catastrophic failures is reduced.
This Small Business Innovation Research Phase I project will enhance the strength of carbon fiber reinforced polymer composites (CFRPs) by improving the fiber/matrix integration and developing an interlayer (sizing layer) to protect CFRPs from being broken down by stress accumulated at the interface. This project will minimize or eliminate the interfacial weak points by using a patented surface engineering process. The process functionalizes the surface of the carbon fibers and dramatically promotes the wettability of the matrix resin on the fiber surface. The principal technical objective is to develop a surface engineering process that will improve the fiber/matrix wettability. Distinguished from the reported methods, the proposed surface engineering will process fibers larger than 100 mm in any dimension and more than five plies per load. Carbon nanotubes (CNTs) will be added to the sizing polymer to facilitate stress transfer between the carbon fiber reinforcements and the matrix.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADVANCED GROWING RESOURCES INC.
SBIR Phase I: Novel handheld spectroscopy for the early detection of crop afflictions
Contact
447 VOSBURG RD.
Webster, NY 14580--1040
NSF Award
2213137 – SBIR Phase I
Award amount to date
$255,786
Start / end date
02/01/2023 – 01/31/2024 (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 will focus on development of a handheld optical scanner that integrates precise imaging with optical spectroscopy. Although this technology has broad applications ranging from industrial quality control to education, the beachhead sector to be addressed is precision agriculture. To feed a growing population of 10 billion in 2050, agricultural production will need to increase by 70% over the next 30 years. Critical to this mission is the development of innovative tools and strategies for crop protection and health management to preserve the world’s food supply. The potential customers in this segment are crop growers, consultants, and field scouts aiming to act early while reducing the use of harmful and costly chemicals. The global crop monitoring market was estimated at $2 billion in 2019 and is anticipated to reach $6 billion by 2027, growing at 15.3% annually. The sensing and imaging segment accounted for 49.3% of the market in 2019. This technology has the potential to support the adoption of more sustainable agricultural practices as well as the economic viability of small- to medium-scale farm operations in the U.S. by providing an accessible and affordable tool for disease detection and crop health management.
The intellectual merit of this project is the commercial development of novel and affordable imaging spectroscopy technology in addition to application-specific analytics for the early detection of crop afflictions. Optical components of the scanning device that will be designed-for-manufacturing in this project bridge the current gap created by systems that trade the detection capabilities of spectral resolution for spatial resolution. The scanner will be deployed to collect data on grapes, a key, high-value crop that is susceptible to a number of afflictions that destroy yields before the human eye can detect them. Machine learning algorithms will be developed from this data to detect stressed and diseased states in the plant before they become apparent to visual inspection. These models will then be validated in the field with user feedback from horticultural experts and customers. Successful implementation of this technology will facilitate the detection of crop diseases before they spread. This detection capability can increase yields while reducing the use of costly and environmentally-harmful pesticides and fertilizers.
This award reflects 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 LINEAR INC.
SBIR Phase I: Low Noise Amplifier Running Fast At Ultra-low Currents (pp # 00035239)
Contact
15230 FRUITVALE AVE
Saratoga, CA 95070--6272
NSF Award
2208366 – SBIR Phase I
Award amount to date
$252,830
Start / end date
09/15/2022 – 08/31/2023 (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 project is the development of a fundamental electronic building block (i.e., smart amplifier) situated near sensors in Internet of Things (IoT) applications, thereby enabling ultra-portable, ultra-low power integrated circuit (IC) uses in medical (including wearables), industrial, defense, and environmental applications. Existing amplifier ICs (fabricated in low-cost conventional fabrication) are not smart and cannot simultaneously alter noise, power, gain, and speed performance in response to different input conditions. The proposed innovation enables new, commercially viable, impactful products at the intersection of machine learning, IoT, and sensors. Applications employing such a building block include: (1) battery operated necklaces with always-on sound sensors and smart amplifiers, plus localized machine learning to detect and warn of asthma attacks; (2) multiple always-on ultra-low power, low-noise smart amplifiers near denture or filling-implanted sensors that simultaneously read levels of sugar, salt, acidity, and temperature, with harvested energy from chewing; and (3) “always-on” toxicity sensors having thermo-resistors whose resistivity changes upon detecting toxic chemicals or gasses. The innovation enables fast response times by delivering sufficient output sink-source current to continuously drive the thermo-resistors between low and high toxicity conditions.
This Small Business Innovation Research (SBIR) Phase I project will develop an integrated circuit (IC) smart amplifier that intelligently alters its performance in response to input conditions. Anticipated technical results include: ultra-low-power, low-noise, high-speed, near-zero input-current, high-gain, high power-supply-rejection-ratio, high common-mode-rejection-ratio, unconditional stability, rail-to-rail input and output voltage swings, and an output buffer having source and sink load capability performance, all in one tiny silicon amplifier. The proposed smart amplifier is capable of providing all of these parameters in a single IC. In this Phase I project, the company will develop this IC amplifier based on a novel circuit design that intelligently alters its speed, noise, and gain in response to small signals and large signals applied to its inputs. As a fundamental building block, the resulting smart amplifier will be manufacturable using conventional, low cost, 65 nanometer IC fabrication processes, and will enable many emerging ultra-portable, ultra-low power “always-on” IoT, smart sensors, and localized tiny machine learning applications situated at the edge of the cloud, without the need for continuous internet connectivity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AIROMATIX INC.
SBIR Phase I: A Portable Oxygen Concentrator with High Flow Rates for In-home Therapy (COVID-19)
Contact
2828 SW CORBETT AVE STE 214A
Portland, OR 97201--4811
NSF Award
2136709 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/15/2022 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable easy oxygen delivery to patients with respiratory conditions. Currently, patients requiring high flow-rates of oxygen above 4 L/min require oxygen tanks that are large, heavy and can be hazardous, limiting mobility and transportation options. The proposed system produces breathable oxygen at higher flow rates and lower energy compared to current portable oxygen concentrators, enabling sustained patient use. This enables sustained oxygen production in a portable manner to manage medical conditions causing oxygen deprivation, including Chronic Obstructive Pulmonary Disease (COPD) and Coronavirus Disease (COVID-19).
This Small Business Innovation Research (SBIR) Phase I project will develop a portable system that utilizes a novel photocatalytic (light activated) reaction to separate oxygen from ambient air, trapped in a chemical solution, then released as needed through a temperature-controlled reaction. This project will monitor the capture and release reactions using absorption spectroscopy to determine the ideal conditions of oxygen production. Several photosensitizer chemical compounds (fullerene C70 and C60, rubrene, and methylene blue with urea) will be evaluated on system longevity by continuously cycling the systems under higher temperatures and light exposure, and monitoring their effects on oxygen production. A prototype will then be developed that generates targeted oxygen flow rates at the desired rate of energy consumption, and the oxygen produced validated as safe for inhalation using bench tests.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ANCILIA, INC.
STTR Phase I: Phage-resistant bacterial therapeutics
Contact
5776 PALISADE AVE
New York, NY 10014--4606
NSF Award
2126989 – STTR Phase I
Award amount to date
$255,717
Start / end date
07/15/2021 – 06/30/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will be a new approach to treat gastrointestinal (GI) diseases, metabolic disorders, and autoimmune disorders, with an initial application of inflammatory bowel disease, which affects approximately 1.5 million people in the US. The proposed technology will address the microbial population in the gut, which significantly affects GI health. This technology uses advanced techniques of microbiology to develop a new set of therapeutics geared toward sustaining a healthy microbial population in the GI system.
This Small Business Technology Transfer Phase I grant proposes to develop phage-resistant bacterial therapeutics to effectively alter the gut microbiome and treat disease. A key impediment to the use of live bacteria as therapeutics is their failure to reliably establish colonization in the gut. Although most focus to date has been on the bacterial components of the microbiome, bacteriophages, viruses which directly attack bacteria, make up at least half of the organisms in the human gut. Significantly, phages have been shown to influence the colonization dynamics of bacteria in every ecosystem studied thus far. Virulent populations of bacteriophages in the gut, which deplete commensal bacterial species, have been identified in patients with disease. Bacterial therapies with engineered immunity to gut phages will be developed to drive effective colonization in the gut. The endogenous immune system of bacteria, the CRISPR-Cas system, will be harnessed to engineer immune strains and develop targeted bacterial immunity against virulent phages. This work will enable development of a new class of bacterial therapeutics that overcome previous challenges and effectively colonize the gut. These therapies can be applied to treat the wide range of conditions associated with the microbiome.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ANGIOINSIGHT, INC.
STTR Phase I: Feasibility Study of a Reduced Order Model for Calculating Fractional Flow Reserve (FFR) Using Angiographic Data
Contact
330 EAST LIBERTY ST
Ann Arbor, MI 48104--2274
NSF Award
2151555 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2023 (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 the clinical care of patients suffering from coronary artery disease (CAD) and to reduce the associated costs. CAD remains the most common form of heart disease, afflicting more than 18 million adults and costing the U.S. healthcare system over $90 billion annually. Advances in diagnostics to improve treatment decisions have lagged behind advances in therapies. The proposed research will explore novel computational modeling methods within an artificial intelligence (AI) software platform to improve diagnosis and optimize patient-specific treatment decisions. Value propositions are to improve clinical outcomes, reduce healthcare costs, and save lives. The software will provide competitive advantages as a more user-friendly and non-invasive diagnostic method capable of faster and more accurate clinical assessment of CAD than existing alternatives.
This Small Business Technology Transfer (STTR) Phase I project will advance the diagnosis of coronary artery disease (CAD) to optimize patient-specific treatment decisions. CAD patients typically undergo an angiography procedure whereby coronary arteries are visualized to estimate stenosis severity and make subjective treatment decisions on whether to perform revascularization procedures (e.g., stenting or bypass graft surgeries). More recently Fractional Flow Reserve (FFR), a measure of the pressure gradient across the vessel stenosis, has demonstrated improved outcomes when guiding treatment decisions. However, adoption of FFR remains modest given shortcomings of available interventional devices and cost. Recently, commercial efforts have developed computer-based methods to estimate FFR non-invasively, although with limited accuracy in borderline values of FFR. The proposed research will develop and calibrate a Reduced Order Model (ROM) using novel machine learning and computational methods to provide FFR measures in a faster, more accurate, and more integrated manner with clinical workflows than existing solutions. The ROM will rely on recent advances in Graph Theory to enhance a 1D nonlinear formulation of blood flow. The method will be calibrated using synthetic data generated with ground truth 3D Navier-Stokes solutions and validated against clinical measurements of FFR from a cohort of 20 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. -
AQUA SCIENCE LLC
SBIR Phase I: Development of a new ELISA for detection of PFAS in soil and water
Contact
250 CORPORATE BLVD STE K
Newark, DE 19702--3329
NSF Award
2151512 – SBIR Phase I
Award amount to date
$255,751
Start / end date
04/15/2022 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I Project is to improve environmental testing. Once class of contaminants is PFAS (Per- And Polyfluoroalkyl Substances), associated with high cholesterol levels, thyroid disease, certain cancers, and pregnancy-related problems. Current testing costs $300 per sample and offers low throughput is low at 30 samples per day. The proposed project develops a test that would cost $50 per sample (6X reduction) and could test about 120 samples per day (4X increase). It could initially offer a rapid, low-cost qualitative screening tool, allowing users to determine areas of concern, hot spots, detection during emergency response and testing during mitigation efforts.
The proposed project will develop a novel immunoassay in the form of enzyme-linked immunosorbent assays (ELISAs) for the detection of PFOA (perfluorooctanoic acid) and PFOS (perfluorooctane sulfonic acid), two of the most abundant PFAS in soil and water. Currently, PFAS testing involves laboratory-based, costly LC-MS (Liquid chromatography–mass spectrometry) methods. An antibody test such as an ELISA has specificity to the target compound as well as any similarly structured compounds. Thus, the test will detect multiple species of the perfluorinated compounds. During the development of PFAS ELISA, verification testing will be done in an EPA lab using LC-MS to verify the species that can be detected by the ELISA test along with the accompanying levels of detection. The research will include determination of the appropriate immunogens and haptens for this application, antibody production, and screening of antibody for specificity and sensitivity. The goal is to improve PFAS detection sensitivity to 50 ppt. Once technical feasibility of detection is demonstrated, the antibodies can be used to develop more complete assays using test strips or magnetic particles.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AQUAPAO, INC.
STTR Phase I: Solar-driven, thermally responsive membranes for off-grid water purification
Contact
93 ELM RD
Princeton, NJ 08540--2523
NSF Award
2213218 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this STTR Phase I project will be the development of a solar-based water purification solution that has the potential to overcome the persistent barriers to safe drinking water access plaguing the more than 81 million Americans living in counties with elevated water quality issues. As the frequency of climate-related natural disasters and the prevalence of contaminated drinking water supplies (e.g., from detection of per-/poly-fluoroalkyl substances (PFAS) ‘forever chemicals’) increases, there is an urgent need for easily implementable water treatment options to maintain access to safe drinking water. Offering an off-grid, cost effective, energy-free approach, this technology is suited to provide a safe drinking water solution that can be cost-effectively deployed without requiring a water infrastructure overhaul. In contrast to existing water treatment approaches, which rely on energy inputs and infrastructure investment, the proposed technology is both sustainable and reliable, and has the flexibility, modularity, and scalability needed for facile deployment. Potential commercial impact of this disruptive technology is high, considering the number of communities currently seeking water treatment solutions that would be easily met with the technology, and the subsequent jobs created related to installation and maintenance.
The technical innovation of this project comes from the development of a solar absorber gel (SAG) membrane that passively purifies water using natural sunlight or a waste heat source. This system is designed to selectively capture clean water at low temperatures and release it under natural sunlight at higher temperatures. Compared to other passive solar water purification methods, which rely on the energy-intense evaporation and condensation processes, this technology does not rely on a phase transformation but instead absorbs and releases liquid water due to minor temperature swings and can achieve the critical temperature for water release within a matter of minutes. This system holds promise for both modular and stationary water purification in a sustainable manner. Phase I project will focus on demonstrating performance capabilities to meet drinking water standards, improving water collection rates, and enhancing the durability of the membranes. The objectives include: 1) investigating the properties and performance of SAG membranes with an open-cell membrane structure that dramatically improves the water purification rate; 2) performing detailed investigation on the SAG rejection rate to harmful mixed impurities and meeting National Sanitation Foundation standards; and 3) assessing the long-term reusability of the SAG membrane, including on accelerated degradation studies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AREN, INC.
SBIR Phase I: Automating Element-Level Inspection of Civil Infrastructures through Computer Vision
Contact
2 W LOOP RD
New York, NY 10044--1501
NSF Award
2151516 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (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 a damage detection analysis software platform to reduce the risk of failure for heavy civil infrastructure assets (e.g., bridges and dams) while optimizing the capital allocation for these vital systems using a unique combination of artificial intelligence (AI) and civil engineering. The public utilities responsible for civil infrastructure upkeep and assessment need fast, reliable solutions to collect massive amounts of data and rapidly assess the status of large amounts of heavy civil infrastructure. They also need to be able to make accurate and timely reports to stakeholders on the structural integrity of these assets. This project aims to facilitate data-driven decision making for civic leaders regarding infrastructure investments.
This Small Business Innovation Research (SBIR) Phase I project will develop and commercialize technologies to increase the automation of the infrastructure asset management process and reduce the costs of this process for asset owners. This increase in automation may also lead to improved conditions and temporal change assessment through AI-powered analytics. The resulting analytics would improve inspection practices by increasing accuracy and objectivity, leading to safer infrastructure systems and fewer infrastructure failures. The technical innovation of this Phase I project is a 3D computer vision pipeline designed to process remotely sensed data and automatically transform it into a format that meets the reporting needs of engineers. The technology addresses long-standing challenges associated with using 3D remote sensing data for infrastructure asset management by developing the foundational technical capabilities to automatically segment and transform 3D point clouds into high-resolution 2D orthomosaics of infrastructure components. Existing approaches are not flexible or generalizable, either employing highly constrained geometric approaches or statistical deep learning models, for which relevant infrastructure data sets do not exist. The proposed approach will utilize computational geometric analysis to isolate and segment point clouds into individual structural components. The process will be prototyped and revised through user pilot studies and ongoing customer discovery and validation activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASSISTANCE IN MOTION, INC.
SBIR Phase I: Development of the WeeBot, an Infant-controlled Powered Ride-on Device for Children with Motor Impairments
Contact
408 COLUMBIA ST
Ithaca, NY 14850--5906
NSF Award
2151611 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (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 project is its innovative and potentially transformative contribution to assistive technologies for infants with motor impairment. In the United States, over 40,000 infants per year are born with conditions, such as cerebral palsy, spina bifida, and Down syndrome, that often result in motor impairment. There is currently no device that provides independent movement to infants with motor limitations. Since children learn a great deal about their physical and social environments when they begin to crawl/walk, conditions that deny or delay independent movement can impact cognitive, language, and social development. A device that will let these infants move and explore at the same age as other children could mitigate these developmental delays and facilitate full integration into society. Lifetime cost of healthcare for these children has been estimated at $250,000. Providing early independent movement could result in a potential $50,000 lifetime reduction in additional interventions such, as behavioral and occupational therapy, special education, and the need for healthcare and educational aides. This amounts to over $200,000,000 in savings per year to the health and education systems.
This Small Business Innovation Research (SBIR) Phase I project addresses the need, expressed by parents and therapists, for a device that will allow infants with motor impairment to move independently at the same age as their typically developing peers. Currently, no such device is available. The intellectual merit of the proposed work is the development of a novel control method for a powered device that can be used by infants as young as 6 months old: The device moves in the direction that the infant leans (as when reaching toward a toy or parent) while preventing collisions and falls. Previous research has shown that infants as young as five months old can learn to use this control method to purposefully steer a powered device in all directions. The research objectives of this project are to build and validate a second-generation prototype that can be used by parents and clinicians outside of a research setting. Successful completion of these objectives will advance the device from a research testbed to a viable, if limited, prototype, enabling future work to evaluate the impact of the device on the development of cognitive, social, and communication skills for infants with disabilities.
This award reflects 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 – 08/31/2023 (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 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. -
ASTRABEAM LLC
STTR Phase I: A D-band, silicon-based, phased array radar front-end module for smart sensing applications
Contact
21 BERKELEY LN
Scarsdale, NY 10583--2403
NSF Award
2151190 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 millimeter-wave imaging radar sensor with significant advantages over current radar products including a smaller form factor, lower manufacturing cost, less signal processing and integration complexity, and improved detection performance such as range and resolution. The proposed miniature imaging radar sensor supports versatile deployment and can be ubiquitously applied to a wide range of short- and medium-distance wireless sensing use cases including industrial safety monitoring, building security, patient surveillance in medical and healthcare facilities, etc. The proposed research seeks to aligns with the Federal Communications Commission's (FCC’s) recent plan to develop new technologies for the global radar sensor market. The proposed technology requires close collaboration between the startup and a university team, which will enhance industry/academia partnerships in the United States.
This Small Business Technology Transfer (STTR) Phase I project seeks to study and demonstrate feasibility of a D-band, front-end phased array radar module design that enables an imaging radar sensor capable of operating beyond 100 GHz with a wide bandwidth. The radar module prototype under consideration consists of a scalable area-efficient front-end architecture, phased array transceiver circuits supported by a mass-producible silicon technology, and a low-cost antenna-in-package (AiP) compliant with standard manufacturing and assembly process. The proposed research includes detailed design analysis, modeling, and simulation verification of a front-end system and core circuit blocks. The project also includes antenna prototype designs and feasibility analysis for module-level integration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AXILEA LLC
STTR Phase I: Metabolite-based Polymer-loaded Chimeric Antigen Receptor Expressing Metabolically-Fit Immune Cells for Immunotherapy
Contact
9010 S PRIEST DR
Tempe, AZ 85284--2818
NSF Award
2151586 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to improve cancer treatment. This project advances a new therapy that targets cancer cells and addresses their malignancies. Following the initial application of lymphomas, the results obtained herein can be applied to several types of cancer.
The proposed project will generate Chimeric Antigen Receptor (CAR)-based cell therapies to improve treatment for lymphomas. Currently, these therapies show negative effects, such as cytokine release syndrome and metabolic exhaustion upon reaching the tumor microenvironment. Furthermore, low nutrient availability for CAR cells in the tumor microenvironment decreases the efficacy. Therefore, strategies utilizing CAR therapy to help target the tumors and keep these cells sufficiently metabolically fit to perform their functions are beneficial. The main goal of this project is to test the feasibility of generating biomaterials that maintain activation of immune cells in resource-poor environments. This project will generate CAR-macrophages and test the ability of our biomaterials to maintain metabolic fitness in these cells. Technical activities include: (1) Generate human CAR macrophages using non-viral electroporation, (2) Show proof-of-concept that human CAR macrophages can survive in a resource-poor environment, and (3) Show proof-of-concept that mouse CAR macrophages do not induce toxicity in vivo in mice.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AdvanceH2O Corp.
SBIR Phase I: Real-time Predictions During Water Treatment: An Intelligent and Proactive Pathway to Preventing Environmental/Health Hazards and Reducing Operational Costs
Contact
160 RIVERSIDE BLVD #22E
New York, NY 10069--0701
NSF Award
2126156 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 06/30/2023 (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 develop next-generation monitoring & data informatics for wastewater treatment plants (WWTPs). Industry standards to test WWTP performance typically measure the chemistry of the incoming wastewater (influent) and finished output (effluent), without insight into the intervening stages. This lack of data can result in significant environmental and human health hazards for end-users, as well as regulatory fines for WWTPs. This project advances advanced microbial analytics specifically for water treatment to proactively predict and prevent negative impacts at reduced energy, chemical, and financial cost. This project has global application.
This SBIR Phase I Project will combine: 1) Advanced microbial analytics tailor-made for water treatment, including global analysis of DNA, RNA, and profiles from the system microbiomes; and 2) Artificial Intelligence (AI)/Machine Learning (ML). This project identifies real-time WWTP performance predictions based on advanced microbial analytics (key drivers during treatment) to inform process control measures to optimize plant operations. For advanced microbial analytics, the objective is to prove reliable characterizations of microbial ecosystems in WWTP reactors, and to help maintain consistency and stability of the ecosystems over time. This project will propose and optimize a sampling, analysis, and reporting plan for infusion at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Alchemie Solutions, Inc.
SBIR Phase I: Re-envisioning alt text for education through concurrent authoring and diagram design
Contact
4735 WALNUT LAKE RD
Bloomfield Hills, MI 48301--1328
NSF Award
2221722 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2023 – 02/29/2024 (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 create a pathway to success in Science, Technology, Engineering and Mathematics (STEM) for all students, including those that are blind or have low vision (BLV), with a usable and effective description system for STEM diagrams. Only 3% of BLV individuals have been employed in a STEM field. The lack of accessible accommodations creates roadblocks for these students in STEM education throughout their academic journey, leading many students to give up, even though they have as much potential for academic success as the general population. All web-based, non-decorative diagrams are required to include alternative (alt) text descriptions for use with screen readers. Current methods for making STEM visualizations accessible through alt text are not scalable or amenable for use with dynamic digital media, nor is alt text standardized or proven usable by learners, resulting in lost learning opportunities for BLV students. The absence of reliable auto alt text generation is a roadblock for educational institutions and academic publishers to adopt new instructional technologies, as digital content and learning systems must include accommodations for accessibility.
This Small Business Innovation Research Phase I project will create a first-of-its kind system that generates descriptions of STEM diagrams as the educational resources are constructed. This project will go beyond current standards for accommodation, by creating an innovative layered approach to the alt text representation of STEM diagrams so that screen reader users can interact with the content in a manner that is best supported by their skills and prior knowledge. The technical objectives are to: 1) create a system that produces machine-readable configurations for the components of a diagram and spatial relationships between the components, and then generates a text-based description of the diagram and 2) devise a non-linear method for representing STEM content through a standardized system of representational layers within the description. Both the general description (objective 1) and layered description (objective 2) will be constructed by matching the diagram configuration to a context-driven lexicon.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BALLYDEL TECHNOLOGIES INC.
SBIR Phase I: Tagging and Authentication Technology for Vaccines (COVID-19)
Contact
204 SECRETARIAT DR UNIT B
Havre De Grace, MD 21078--2653
NSF Award
2111844 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/15/2021 – 04/30/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a state-of-the-art, counterfeit-proof security technology to enable vaccine manufacturers to tag, track, and authenticate vaccine products throughout the supply chain. The tagging process will be amenable to its integration into a scalable glass vial manufacturing process. Digital information such as product, lot number, expiry, etc. may be embedded into the tags, if desired. In light of the current global COVID-19 pandemic, security and authentication of vaccine dosages throughout the supply chain represents a significant public health and global logistics challenge. Industry concerns over vaccine theft and counterfeit products drive the market need for an effective ID security technology that enable manufacturers to authenticate vaccines in a safe, covert, and efficient manner. The tagging process developed in this program will add minimal expenses to the manufacturing cost of each vaccine dosage form, at an estimated cost of pennies per dose.
This Small Business Innovation Research (SBIR) Phase I project will require the completion of several tasks, including: 1) the computational design of the taggant patterns, 2) the development of a scalable tagging process, 3) the development of instrumentation and associated software for tag authentication, and 4) the encryption of tags with digital information such as lot number, expiry, manufacturing location, or any other desired product information. In summary, the specific design parameters of the tag will be elucidated and optimized during this Phase I effort. The design parameters will subsequently be demonstrated on flat glass and glass vaccine vial prototypes using a scalable process. Finally, newly developed “reading” instrumentation will be used to authenticate the tagged glass prototypes, demonstrating the overall utility of this anti-counterfeit 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. -
BEIROBOTICS LLC
SBIR Phase I: Unmanned Aerial Payload Systems for Live-line Access
Contact
1717 E CARY ST
Richmond, VA 23223-
NSF Award
2136680 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Phase I project is the potential use of Unmanned Aerial Systems (UAS) applications in performing inspections and repairs on a variety of live transmission equipment without the need for manned helicopter or bucket truck crews, reducing the time linemen are in harm’s way. The cost of transmission grid inspections and maintenance may decrease, leading to more frequent routine inspection and more timely and proactive inspections of infrastructure with potential for failure. Transmission grid operators may have a more resilient grids with lower losses thanks to increased and improved data from frequent inspections. The American people can potentially benefit from a more resilient grid with fewer outages and more consistent delivery of electricity. Fewer line losses conserve energy and reduce the amount of fossil fuels burned to generate electricity locally.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop Unmanned Aerial Systems (UAS) inspection capabilities enabling access to utility infrastructure unreachable and/or difficult to reach by current methods. Inspection, maintenance, repair, and auditing processes for electrical utility infrastructure are costly and hazardous to personnel. Current UAS-mounted payload technology has demonstrated initial success with inspecting connectors by approaching horizontally-arranged transmission conductor sets from above. Vertically-arranged conductors that cannot be approached from above represent a significant portion of transmission infrastructure. The project’s research seeks develop UAS payload system technology that delivers linemen’s tools to vertically-arranged, high voltage transmission infrastructure by approaching from the side and from below. To accomplish this research, new approach methods will be designed, engineered, constructed, and rigorously tested in de-energized and live environments to prove viability. Completing the research objectives of the project may establish commercial feasibility for the next generation of UAS payload technology in the electrical utility sector, paving the way for a safer and more efficient national electrical grid.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BESPOKE BIOTHERAPEUTICS LLC
SBIR Phase I: Engineered B-cell Therapeutics for the Early Detection and Treatment of High-risk Breast Cancer
Contact
904 BROMFIELD RD
San Mateo, CA 94402--1160
NSF Award
2206743 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2023 (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 involves creation of a new, immune-cell-based treatment to address the unmet physical and psychological health needs of women with locally advanced (Stage III) breast cancer at high risk for relapse following standard-of-care surgery and drug therapy. Called cancer sentinels, these “living drugs” are made from patient blood-derived B-cells that have been isolated, chemically activated, and genetically modified to selectively seek and destroy residual breast cancer cells before they form detectable tumors and spread to vital organs. Cure is dependent on early detection and cancer cell elimination prior to distant spread. These engineered therapeutics may promote the destruction of breast cancer cells in multiple ways, including activation of immune system and the secretion of cancer-killing antibodies. Additional solid tumor cancer types, such as colorectal cancer, lung cancer, and ovarian cancer may also be addressable by future cancer sentinel products. In total, greater than 200,000 American cancer patients each year may benefit.
This Small Business Innovation Research (SBIR) Phase I project addresses unmet needs of nearly 50,000 American women annually who are subjected to anxiety, fear, and lifestyle disruption because of newly diagnosed, locally advanced breast cancer. Emotional toxicity, beginning at cancer diagnosis, tends to peak during standard “watch and wait” cancer surveillance and the relapse uncertainty that follows initial surgical resection and post-surgery adjuvant therapy. This project combines the natural and unique antigen binding, lymph node-homing, antigen presentation, protein secretion, T-cell co-stimulation, and immune memory capabilities of human B-cells with large-cargo, non-viral, CRISPR/Cas9 and homology-mediated end joining-based genome editing techniques, to create cancer sentinels. Cancer sentinels are intended to destroy residual and relapsed breast cancer cells by locally secreting engineered anti-cancer antibodies and/or cytokines at the time of minimal residual cancer and prior to distant metastasis. To achieve such a multi-functional B-cell drug, autologous blood-derived B-cells will be genetically modified to express surface B-cell receptors (BCRs) with affinity for specific tumor-associated antigens (TAAs). Engineered BCR binding to TAAs may trigger local secretion of the engineered anti-cancer response molecules. Detection of these response molecules in the blood may also serve as a biomarker and alert physicians to the presence of residual cancer.
This award reflects 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 – 05/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop a synthetic lung surfactant product for the potential treatment of serious respiratory illnesses in neonatal patients. Bronchopulmonary dysplasia affects 10,000-15,000 pre-term infants per year and has a high mortality rate. Exposure of immature lung tissue to air results in inflammation and damages lungs and airways. Decreasing bronchopulmonary dysplasia is anticipated to reduce the number of days infants spend in the hospital, the need for supplemental oxygen, and other burdens on the healthcare system. The average length of stay in the neonatal intensive care unit for an infant with bronchopulmonary dysplasia is currently 103 days.
This Small Business Technology Transfer (STTR) Phase I project may result in the formulation of synthetic proteins for a bioengineered lung surfactant that contains full-length critical phospholipids and anti-inflammatory agents. Currently, bioengineered pulmonary surfactants are not as effective as animal-derived pulmonary surfactants for the treatment of illnesses related to bronchopulmonary dysplasia such as neonatal respiratory distress syndrome. The synthesis of full-length, native surfactant proteins has yet to be achieved. This research seeks to synthesize proteins which may add significant viscoelasticity to the pulmonary surfactant. The protein will be combined with major surfactant phospholipids and anti-inflammatory therapeutics at defined ratios to potentially generate fully-synthetic pulmonary surfactant preparations with anti-inflammatory properties. These surfactant formulations will be screened in vitro and in vivo using a neonatal rat hyperoxia model of bronchopulmonary dysplasia.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIRCH BIOSCIENCES, LLC
SBIR Phase I: Enzymes for Accelerated Plastic Recycling
Contact
4023 NE HANCOCK ST
Portland, OR 97212--5324
NSF Award
2151599 – SBIR Phase I
Award amount to date
$255,840
Start / end date
04/01/2022 – 03/31/2023
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enable a more efficient, profitable, and sustainable plastic recycling process. In the United States less than 10% of plastics are currently recycled, and the remainder are incinerated (15%) or placed in landfills (75%). Emissions from global plastics production and incineration could reach 56 billion tons of carbon between now and 2050, accounting for 15% of global greenhouse gas emissions. The economics of conventional plastic recycling are poor, because the high temperatures used in recycling cause quality degradation that greatly reduces the economic value. This project develops a low-temperature system for high quality, high-value plastic products in closed-loop recycling.
The proposed project will apply synthetic biology and related biotechnologies to identify, engineer, and optimize new enzymes and enzyme cocktails to break down polyethylene (PE) and polyethylene terephthalate (PET) plastics. These enzymes will enable closed-loop plastic recycling in an economically viable, low temperature, low CO2 emission process. The first objective is to sample plastic contaminated environments for naturally occurring enzymes that have evolved to depolymerize PE and PET synthetic polymers. Candidate PE and PET enzymes will be engineered to accelerate their ability to efficiently target and cut complex PE and PET polymers under scalable process conditions. Millions of enzyme variants will be constructed, tested, and analyzed using synthetic biology, high-throughput screening, and machine learning technologies. A primary goal of this effort is to demonstrate a 10-fold increase in PE and PET depolymerization rates compared to naturally occurring plastic degradation proteins.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BLOCKSYNOP, INC.
SBIR Phase I: Neural Blockade Monitor Technology for Precision Pain Management
Contact
7191 BROOKS RD
Highland, MD 20777--9542
NSF Award
2230879 – SBIR Phase I
Award amount to date
$274,686
Start / end date
02/01/2023 – 07/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is found in its ability to provide a novel tool for clinicians for perioperative, post-surgical, and chronic pain management. This technology supports enhanced patient safety, international standards for enhanced recovery after surgery, reduced addiction potential and opioid sparing, reduced loading on clinicians and healthcare resources, reduced cost of healthcare services, and advanced capability of clinicians through training. The commercial impact exists in all facets of healthcare, including perioperative procedures, in-hospital step-down and recovery, ambulatory surgery center procedures, and chronic pain management. The potential exists to expand into other clinical markets including the military and first responders. This technology can support the national defense of the country by providing advanced care capability for wounded troops on the front lines, in recovery, and through rehabilitation. The solution also applies to use during times of national, state, and local crisis, and, as the hospital-at-home trend increases, that market can be pursued. Ultimately, the commercial impact exists in both worldwide use and in contributing to the overall projected increase in use of regional blocks in the coming decade.
This Small Business Innovation Research (SBIR) Phase I project applies technology to a medical application that has not been addressed for over 130 years. Based on clinical needs, a minimally viable device (MVP) has been developed and prototyped that objectively quantifies neural blockades. This project advances the capability of the MVP and advances information about the real-time in vivo status of a neural blockade. The goal is to assure device robustness under challenging clinical conditions, for different neural blockade types, and for physiologically diverse patient populations. The plan to reach these goals is to apply human factors and design engineering standards to the MVP to assure that: a) the user displays are readily understood, provide the expected information in an appropriate form and format, and support the required clinical processes and procedures; b) the user controls perform the required functions, are complete, reflect the appropriate nomenclature for the clinical environment, and support the required clinical processes and procedures; and c) the monitor is reliable, well fabricated, safe for the patient and user, and completely supports the acquisition, processing, display, and recording of pertinent data. The resulting technology will be a robust patient monitoring device that assures patient safety and optimized 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. -
BLOCMOUNT LLC
SBIR Phase I: A Game-Theoretic Technology for Protecting ICS against Cyber-Attacks
Contact
25406 MESA CRST
San Antonio, TX 78258--4824
NSF Award
2150642 – SBIR Phase I
Award amount to date
$255,973
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to advance the state of cyber defense in Industrial Control Systems (ICS) that are widely deployed in various sectors such as manufacturing, healthcare, and utilities. This project will develop security cloud services that provide early detection of cyber-attacks and anomalous behaviors. Securing ICS will help guarantee their proper operation and consequently protect human life and equipment as well as conserve resources and materials. This directly benefits society and ensures economic competitiveness of the US through the development of trustworthy and resilient control systems.
This Small Business Innovation Research (SBIR) Phase I project will develop a technology solution that provides early detection of cyber-attacks that aim to take over Industrial Control Systems (ICS). The rise of cyber-attacks that use Artificial Intelligence and Machine Learning (AI/ML) techniques poses significant threats to such systems. The solution is composed of (1) an extensible and comprehensive library of check blocks that inspect signals at run-time using state-of-the-art methods from machine learning, statistics, control theory, and time-series analysis; (2) an AI-based defense agent that dynamically applies well-chosen subsets of checks to various signals at run-time; and (3) a cloud service that implements the defense agent. The expected results include game-theoretic models, approximation methods, and reinforcement learning algorithms incorporated in a cloud service that results in effective cyber defense strategies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BLOOMALO LLC
STTR Phase I: A pediatric care platform to enable personalized and coordinated developmental and behavioral care for children
Contact
218 PHILLIPS LN
Alpharetta, GA 30009--2600
NSF Award
2136460 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (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 targets the critical need and gap in developmental and behavioral care for children and families. Up to 1 in 5 children have some type of behavioral and/or developmental problem that requires diagnosis. Of these, 80% are likely to have insufficient behavioral or developmental care. There continues to be an overall shortage of qualified developmental and behavioral health clinicians, and specialists struggle to meet the current service demands which have increased dramatically during the current COVID-19 pandemic. The American Academy of Pediatrics recently declared a state of emergency in child and adolescent mental health. The proposed platform seeks to enable increased access to effective behavioral care and to allow families to get personalized information and support to address concerns in a timely fashion. The data-driven intelligence may allow for an approach that is scalable and that will serve as a gateway for comprehensive developmental and behavioral health care for children and families.
This Small Business Innovation Research (SBIR) Phase I project applies research in machine intelligence to the personalized developmental and behavioral care support for children and families and helps to address the critical need and current gaps in children’s behavioral health. The proposed research and development bring together a suite of capabilities to allow children and caregivers to get the support and access to care that they need in a timely fashion. The data collected will enable the expansion of the artificial intelligence-driven support. At its foundation, the platform seeks to provide evidence-based content, personalized data-driven behavioral assessments, and facilitated care navigation for families. The platform can use technology to increase the dissemination of behavioral health care information, to provide increased access and real-time support that is tailored to the families’ needs, and to establish a personal and long-lasting relationship with families as their children age and progress through various developmental stages.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BLUEWONDER CREATIVE, LLC
STTR Phase I: Digital Mental Health for Children and Adolescents
Contact
2849 STEAMBOAT DR
Nashville, TN 37214--1131
NSF Award
2110953 – STTR Phase I
Award amount to date
$255,932
Start / end date
07/15/2022 – 06/30/2023 (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 improved children’s mental and behavioral health via the creation of a platform that unifies the silos of healthcare and education to put children and families first. Due in part to the current pandemic, there is an increased need to support children’s mental and behavioral health. The end-users are the 28 million children between 8-12 years old in America. The team is advancing patient-centered care and personalized education. After the platform is tested for an initial age group of 8-12-year-olds, the plan is to expand the platform across the age-span, including early childhood through senior adults. The platform promises engaging, self-contained, adaptable, safe, and research-based support and learning. The team expects to grow their market share through strategic partnerships with healthcare, education, industry, and non-profit partners.
This Small Business Innovation Research Phase I project focuses on leveraging technology, including natural language processing, machine learning, and chatbots, to provide information to students, families, and educators about mental and behavioral health and to get feedback from these groups through their web-based computing devices. This project seeks to develop an online platform that will engage students and allow them to leverage personal care resources aimed at building resilience and providing them access to support and information customized to their individual needs. This Phase I project focuses on building a proof-of-concept platform that provides precision mental health solutions by combining interactive health and wellness methods with engaging content personalized and delivered by machine learning technologies and tools.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BOTELMOT RESEARCH LLC
SBIR Phase I: A wave attenuation technology for oyster reef restoration and small dock protection
Contact
48 HERNANDEZ AVE
Ormond Beach, FL 32174--5506
NSF Award
2223944 – SBIR Phase I
Award amount to date
$254,493
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercialization potential of this Small Business Innovation Research (SBIR) Phase I project is in advancing oyster reef restoration efforts by improving the understanding of oyster reef formation at the individual level and improving the resilience of waterfront infrastructure including small docks. This project will develop a technology that could improve ecosystem services and private dock protection. The socioeconomic importance of intact infrastructure and coastal protection includes maintaining property values, economic job opportunities, and supporting coastal infrastructure by minimizing erosion.
This project is focused on a shallow water wave attenuation system that does not restrict water flow behind it and does not create sediment accretion. This system is needed for both oyster reef restoration and the protection of small docks. Oyster reefs do not establish in areas that have been channelized and are then subjected to both boat waking and increased fetch due to the increased wave energy. The proposed system will be indexed to the water surface and will adapt to changes in water height but will necessarily be anchored to the bottom. What is unknown in this project is how rigidly the system has to encounter oncoming waves in order to both survive extreme events and not absorb too much wave energy as to limit water flow. The development of a nontoxic and biocompatible prototype would provide the data necessary to project both economic and hedonic valuation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BRADLEY, CARYN
STTR Phase I: An Integrated Biomedical Platform and Custom Algorithm to Optimize Feeding Protocols for Preterm Infants
Contact
827 10TH ST APT 5
Santa Monica, CA 90403--1616
NSF Award
2208383 – STTR Phase I
Award amount to date
$255,990
Start / end date
06/01/2022 – 05/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project improves outcomes for preterm infants in neonatal intensive care units (NICUs). On average 518,000 preterm infants are born in the US each year and 49% experience difficulty feeding after discharge. Preterm infants who cannot successfully feed are at increased risk of hospital readmission. In the US, there are 22,721 NICU beds and the average length of stay for an infant born less than 32 weeks gestation is 13.2 days. The current practice is for babies to remain longer in the NICU at an average cost of $7,000 per day and a national cost of more than $26 billion a year. This project advances a new feeding monitoring system. An estimated 2-day reduction in length of stay with this device will lower the financial cost of overall neonatal healthcare expenditure by $8.9 billion annually and will reduce the need for future medical interventions because infants are discharged with a stronger early-stage health baseline.
This Small Business Technology Transfer (STTR) Phase I project advances NICU care. For infants admitted to the NICU, successful oral feeding is a prerequisite for discharge home, but preterm infants often struggle with oral feeding skills, due to problems coordinating swallowing with breathing. Achieving safe and efficient oral feeding in preterm infants is challenging because of these neurodevelopmental immaturities. Feeding progress is therefore limited by difficulties in maintaining cardiorespiratory stability. The proposed biomedical platform and clinical algorithm interface uses big data describing breathing patterns to quantify the synchronization of breathing and swallowing. A precise method of measuring infant breathing patterns during feeding gives clinicians a diagnostic tool to better inform decisions related to feeding advancement. This device provides objective metrics of feeding success and discharge readiness. It will result in decreased readmissions for failure to thrive, substantially reducing healthcare utilizations and post-discharge expenditures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BRAINSOFT, LLC
SBIR Phase I: Using Brainwaves in Virtual Reality Applications
Contact
1444 BRECKINRIDGE CT
Ames, IA 50010--4224
NSF Award
2110883 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
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 make virtual reality (VR) applications more intuitive and thereby increase their adoption of immersive technologies. The VR market was estimated to be $6.1 billion in 2020 and is expected to reach $20.9 billion by 2025. This project addresses the VR developers’ challenge of creating interfaces that enable intuitive navigation. As envisioned, the technology resulting from this project may enable developers to write user-friendly human interfaces for VR software by removing the current constraints posed by the need to master the domain of brainwaves. The project seeks to provide capabilities for deriving the user’s mental and emotional states, thus facilitating objective user feedback. That new capability may impact other domains, including education and therapy. Acquiring capabilities to establish relationships between the mental and emotional states of the users and the VR and real-world environment stimuli could be developed and used to identify patterns that may answer important questions about human behavior and help people with limited mobility.
This Small Business Innovation Research (SBIR) Phase I project advances the use of brainwaves to control VR environments. This project will develop techniques for inferring users’ decisions while navigating a VR environment and for deriving insights into users’ reactions to stimuli in real-world and VR environments. For this Phase I proof-of-concept work, these innovative techniques will be evaluated in jury consulting and game therapy scenarios. The research addresses four technical hurdles: 1) inferring users’ decisions in virtual environments from brainwaves with reasonable accuracy, 2) deriving insights into users’ intellectual and emotional states as a result of exposure to stimuli, 3) designing an architecture for useable brainwaves-based applications, and 4) designing security and privacy solutions for this VR 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. -
BROWNBACK STUDIOS, LLC
SBIR Phase I: Coding the Affective Domain and Visuospatial Ability
Contact
1610 N SALEM AVENUE
Pueblo, CO 81001-
NSF Award
2129965 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 supports the development of a visuospatial educational assessment tool. Visuospatial aptitude is a facet of intelligence that underlies innovative thinking, i.e., how do new ideas emerge? and What are the physiological processes involved? Today, there is an overwhelming exposure within society to digital visual stimuli and national assessment authorities acknowledge visuospatial abstract reasoning as an accepted and sought after cognitive ability. Future curriculum designs must develop along with how people are changing and perceiving knowledge. This project seeks to set standards in education on visuospatial ability by introducing a novel assessment. This visuospatial assessment tool will utilize a software platform that allows customers to take the assessment online, and has commercial potential to improve industry, science, and educational programs for the advancement of human communication.
This Small Business Innovation Research (SBIR) Phase I project investigates the development of an information technology consisting of a visuospatial ability assessment for measuring the biological processes that are required for being creative. Humans are biologically predisposed both to perceive and to reproduce symmetry, mainly in visual form, but also aurally; This proposed visuospatial assessment tool measures some of the biological processes that are required for the perception and reproduction of symmetry. Specifically, this assessment measures a form of sensorimotor perceptual action referred to in this project as ‘affective symmetry gauging’ (ASG). ASG consists of a subject’s innate visual perception/identification of the division in extreme and mean ratio point (DEMR; i.e., the symmetry point) in a given pattern. Because this process measures the extent to which a subject can perceive/identify and reproduce the symmetry point in given patterns, the tool also suggests the degree to which a subject may be inclined to reproduce symmetry, marking this inclination as a natural human expression of creativity aligned to pleasingness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CACHE DNA LLC
SBIR Phase I: Massively scalable storage of nucleic acids using barcoded polymer packets
Contact
146 SANDY POND RD
Lincoln, MA 01773--2605
NSF Award
2136447 – SBIR Phase I
Award amount to date
$255,819
Start / end date
02/15/2022 – 04/30/2023
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 technology platform for storing biological materials that will improve public health outcomes and enable the storage of the ever-expanding digital data universe. Nucleic acids are the new bits of the 21st century; they encode our health and can be repurposed as alternative storage media for digital data. Harnessing the information encoded in these biological materials requires a scalable way to store and access nucleic acids. For decades, we have relied on energy-intensive low-temperature storage and expensive robotics to maintain the integrity of nucleic acids, which are not scalable. The successful outcome of this proposal is an alternative solution to store massive amounts of nucleic acids, obviating the need for freezers and enabling new products that leverage nucleic acid materials.
The proposed project will lay the foundation for developing a low-cost scalable solution for nucleic acid materials. Current approaches are limited by the requirement of low temperature to circumvent the degradation of nucleic acids, requiring a constant supply of electricity and expensive robotics. Instead, the proposed project focuses on maintaining the integrity of nucleic acids for decades at room temperature and simultaneously enabling search and retrieval functions akin to a computer or internet search engine by leveraging the rapid diffusion of molecules in solution. This ambitious goal will be achieved by using novel synthetic polymers that are made compatible with biological materials to enable rapid encapsulation of nucleic acids while providing long-term protection without the need for low temperature. The resulting synthetic polymers discovered through the project will be tested using purified nucleic acids, including animal, bacterial, or viral genomes, to demonstrate the capabilities and breadth of materials that can be used for the proposed 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. -
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 – 12/31/2024 (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. -
CANETIA ANALYTICS, INC.
SBIR Phase I: Development of an artificial iIntelligence (AI)-based, internet of things (IoT)-enabled system for structural health monitoring
Contact
444 SOMERVILLE AVE
Somerville, MA 02143-
NSF Award
2151388 – SBIR Phase I
Award amount to date
$255,999
Start / end date
09/01/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the low-cost assessment of the health of structures or buildings. Often property-owners and infrastructure managers do not have a true and fair view of the actual state of their building assets. Building health is assessed from infrequent inspections or monitoring that is often uneconomical for smaller structures. This project seeks to develop a technology that is able to discern structural anomalies to facilitate risk assessment and proper management. This technology seeks to disrupt the growing market of structural health monitoring, providing an affordable solution for the assessment of the current state of buildings and structures with benefit to cost ratios over 10, installation costs ranging between $10 to $1,000 per control point and Software as a Service (SaaS) costs ranging between $10 and $500 per month. Once on the market, the technology may help to avoid dramatic human, environmental, and economic losses caused by damaged or collapsed buildings and structures.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a proof of concept solution featuring Internet of Things (IoT) sensors and Artificial Intelligence (AI) to provide insights into the conditions of buildings remotely and automatically by analyzing natural structural vibrations. The solution targets structureal assets that currently are rarely assessed but entail risk of failure. The technology takes advantages of the fact that each structure has its own natural vibration signature, which depends on its design and materials, purpose, and environment. Hidden signals of anomalies, which can be associated with degradation, flaws, or failures, can be found encoded within this vibration signature. This novel technology uses AI to provide insight into these signals and translate them into valuable information about the health of structures. The project seeks to validate the degree to which anomalous data clusters obtained from buildings or structures can be associated with damage or defects and may help to establish the precision and accuracy in anomaly detection. The project comprises the monitoring of real buildings or structures and the manufacturing of the necessary IoT devices, the structural analyses through numerical modelling, laboratory experiments with physical models, and the use of AI to control hazard 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. -
CANOMIKS, INC.
SBIR Phase I: Genomics and AI-based biological effect benchmark development for functional ingredients
Contact
221 1ST AVE SW STE 202
Rochester, MN 55902--3125
NSF Award
2136163 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
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 improve the consistency of functional food and beverage and dietary supplements (FFBDS). Functional ingredients are ingredients that have benefits beyond normal nutrition, such as curcumin (turmeric), green tea, and cranberry extract. Currently FFBDS companies face challenges in sourcing functional ingredients that are consistent in their quality from batch-to-batch. The testing methods measure only the ingredient quantity and not quality. This project advances a technology to measure the effectiveness of these functional ingredients. This information enables FFBDS manufacturers to provide clarity, trust, and ease to the process of purchasing functional products. Furthermore, this can also be used to identify the specific health benefits and develop personalized nutrition products. In addition, the data can provide traceability and information for sustainable farming, harvesting, extracting, and manufacturing practices.
The proposed project will develop biological effect benchmarks for the pure form of functional ingredients, starting with turmeric, using commercially available human cells, genomics, and artificial intelligence technologies. The project will develop a test to measures a compound's biological effectiveness compared to that of the benchmark. The system will generate a biological effect score of the ingredient, a list of key genes affected, and a description of the relevance of these genes on human health. The system will be developed for high-throughput, cost-effective operation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CAPIENDA BIOTECH, LLC
SBIR Phase I: High-throughput drug discovery system
Contact
6076 CORTE DEL CEDRO
Carlsbad, CA 92011--1514
NSF Award
2127159 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 03/31/2023
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 help chemists find drug candidates that can stick persistently to the correct target and work better in patients. By coming off the target prematurely, a drug stops working and may be cleared rapidly from the body. Current state-of-the-art technologies find weak binders and are plagued by other limitations. The system proposed herein tests large numbers of compounds at high throughput during drug discovery and lead optimization, replacing current systems with low throughput. The identified effective drugs must be selective to the intended target. Furthermore, the proposed system will inform Artificial Intelligence and Molecular Dynamics simulations for optimized algorithms predicting drug performance.
The proposed project will solve an unmet analytical need in drug discovery and lead optimization by providing kinetic results at high throughput to refine drug designs. The proposed novel instrument and assay chemistry system measures how long chemical compounds stay on target. The solution will be benchmarked using FDA-approved drugs that use an allosteric mechanism of action to engage protein kinases AKT1 and AKT2. Inhibitors will be profiled for biochemical binding kinetics, thermodynamic analysis, and kinase selectivity in kinetic assays using novel reagents and commercial instrumentation. Dissociation rates for the allosteric drugs will be compared with literature reports. Analysis at several temperatures will measure the activation energy for the kinase to release the allosteric drug. The results will be a benchmark profile of kinetics and thermodynamics for kinase-inhibitor interactions of successful approved drugs. An advanced instrument will be built and tested in endpoint mode for sample handling, signal linearity, background and dynamic range using control reagents.
This award reflects 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 – 03/31/2023
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. -
CARBON SOLUTIONS LLC
SBIR Phase I: A Decision-Support Tool for Identifying Carbon Dioxide (CO2) Capture Opportunities for the Nation’s Energy Transition
Contact
398 E BELLEFONTAINE RD
Pleasant Lake, IN 46779--9577
NSF Award
2216541 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in providing much-needed decision-support tool to progress the United States towards a net-zero carbon dioxide (CO2) emissions economy. The Princeton Net Zero America study suggests that a of minimum 0.9 gigatons /year of CO2 sequestration is required to transition the country to a net-zero economy, which is 1.3 times larger than the country’s oil production on a volume-equivalent basis. One of the many substantial challenges to achieving this feat is identifying and profiling capturable CO2 streams from emitters across the United States. Software that could robustly address this challenge would provide benefits to society and the country. For example, climate change is recognized as the largest threat facing humanity and the security of the United States; Transitioning the US economy to net-zero CO2 emissions is one of the largest wealth creation opportunities of our generation.
The proposed CO2 National Capture Opportunities and Readiness Data software will enable users to identify sources of CO2 (e.g., cement manufacturers and ethanol refineries) that could be profitably turned into carbon capture and sequestration (CCS) projects. The database would provide the break-even CO2 capture cost, technology readiness level (TRL), and lifecycle CO2 emissions of any prospective CCS project across the country by integrating the latest public data and scientific research into a single end-user platform. A novel integration of advances in multiple disciplines is required for successful project completion: 1) big data fusion, 2) CO2 capture stream characterization, 3) lifecycle assessment, 4) advanced techno-economic assessments, and 5) software engineering. Additionally, this project will also advance the status-quo by creating dynamic results that can be easily re-generated as needed (e.g., with new technologies deployed or policies enacted).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARDIOPHI LLC
SBIR Phase I: Trustworthy and Automated Electrocardiogram Analysis
Contact
142 N MILPITAS BLVD
Milpitas, CA 95035--4401
NSF Award
2208759 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2023 (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 improve outcomes for patients with heart problems. This project will develop an AI solution for the automatic interpretation of electrocardiograms (ECG) to detect and predict irregular heartbeats. This will benefit patients with cardiac arrhythmias and will reduce spending on cardiovascular disease.
This Small Business Innovation Research Phase (SBIR) I project aims to refine existing deep learning-based detection algorithms, develop methods for the prediction of the onset of cardiac arrhythmias, develop interpretable and explainable tools for clinicians, and develop a web-based software tool for users to develop insights from ECG signals. This project leverages artificial intelligence technologies, including deep learning and natural language processing, as well as signal processing techniques for a trustworthy and automated ECG analysis tool for prediction and detection The techniques represent multimodal approaches derived from various data sources, including the ECG signals and electronic health record (EHR) documentation of clinician ECG interpretations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARE WEATHER TECHNOLOGIES, LLC
STTR Phase I:Constellation of Nanosatellite Radars for Near-Hourly, Global Ocean Surface Vector Winds
Contact
144 W 400 N
Provo, UT 84601--2855
NSF Award
2304609 – STTR Phase I
Award amount to date
$274,937
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a significant improvement in the accuracy of weather forecasts by increasing the refresh rate of sea wind measurements ten-fold. This forecast improvement will increase the economic competitiveness of the United States by improving efficiency in maritime, agriculture, and logistics industries. Improved weather forecasts will advance the health and welfare of the American public by enabling earlier storm warnings that save thousands of lives. Improved weather forecasts will support national defense, while also saving hundreds of millions of dollars in false-alarm hurricane evacuations. Sea wind data will also directly benefit maritime operators, including recreational sailors, ocean carriers and fishers. Wind map and forecast subscriptions from maritime customers represent a $3 billion commercial opportunity.
This STTR Phase I project proposes to study the feasibility of increasing the refresh rate of sea wind measurements ten-fold using a constellation of nanosatellite radars (scatterometers). Current satellites for measuring sea winds are prohibitively expensive and performance has not substantially improved since they were introduced decades ago. The objective of this research is to evaluate the measurement accuracy, cost, and refresh rate of the proposed nanosatellite scatterometers. Additional objectives study the regulatory feasibility, post-processing feasibility, and commercial feasibility. The research includes calculations of the radar signal, heat, data geolocation, cost, mass, data rate, latency, radio interference, and license feasibility. The research also includes simulations of the radar measurement geometry, the post-processing, the wind maps that will be generated by the scatterometer, as well as the constellation, its operations, and its replenishment requirements. The studies in this project answer key feasibility and performance questions posed by potential users. The results, such as data quality, availability, and simulated sample data, will be used in customer discovery to ensure the needs of potential users are met.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARIDIAN MEDICAL, INC.
SBIR Phase I: An extravascular bipolar catheter for targeted nerve ablation with minimal collateral damage to surrounding tissues
Contact
2450 HOLCOMBE BLVD STE X
Houston, TX 77021--2041
NSF Award
2213155 – SBIR Phase I
Award amount to date
$255,841
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel and emerging method for treating a subset of heart failure patients. Despite modern medical regimen and device therapies, heart failure affects 6 million Americans and remains a leading cause of death and hospitalization in the United States. The proposed system and approach aim to provide a novel procedure and treatment paradigm by leveraging an established clinical access procedure for performing Greater Splanchnic Ablation (GSN). The system would enable rapid and wider clinical adoption of the emerging therapy.
This Small Business Innovation Research Phase I project will develop a novel, minimally invasive, catheter-delivered, venous procedure for performing extravascular Greater Splanchnic Ablation (GSN). The proposed catheter system utilizes a clinically accepted venous approach in order to perform extravascular denervation, while minimizing collateral (off-target) damage to the other surrounding tissues. The objectives of this project include designing and prototyping new devices that will enable localized energy delivery and incorporate a detection system indicative of procedural success. Both benchtop testing and pre-clinical animal model studies will be used to access and ablate, verifying the function and performance of the device.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHROMATIR TECHNOLOGIES LLC
SBIR Phase I: Serially Customized Security Films Harnessing Color-shifting Microstructures
Contact
225 E MAIN ST
Boalsburg, PA 16827--1424
NSF Award
2222648 – SBIR Phase I
Award amount to date
$274,919
Start / end date
09/15/2022 – 08/31/2023 (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 1 project relates to the development and commercial utility of color-shifting security films. Such security films produce color from light reflections in three-dimensionally designed microstructure-arrays. Approximately 5% of the world trade is estimated to be impacted by counterfeit or pirated products, negatively affecting a broad range of markets while putting the safety of consumers at risk. There is a need and market opportunity to implement new, effective strategies and technologies to counteract counterfeiters and communicate authenticity to end users. The value of the technology developed in this project is based on a distinguished optical mechanism that enables the creation of tunable and visually distinctive color changing appearances that can not be imitated or copied. Outcomes include the development of roll-to-roll manufactured structural color film with colors that are serially customizable. The initial target market is focused on consumer brand protection and supply chain security. Target customers include security feature provider companies through joint-development, direct sales, and/or licensing. Potential annual revenue in year three is estimated between $1M-$3M.
This Small Business Innovation Research (SBIR) Phase 1 project will pursue two technical aims in the research development of microstructured color-shifting security films. The first technical objective is to increase total reflectivity without compromising color saturation. Overcoming this hurdle is necessary to ensure that the films are eye-catching under a range of non-optimal lighting conditions. A combination of simulations and experimentation will be used to design and optimize the reflective efficiency of the films. Roll-to-roll fabrication of the optimized structure geometries will be demonstrated. The second technical objective is the demonstration of serial color patterning for customized printing of iridescent films. Serial customization of color, for instance with bar codes or numbers, will enable integration of the films with digital security platforms. Evaluation of microstructure geometry and processing parameters will be conducted to determine color consistency and repeatability while achieving high spatial resolution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHS HEALTHCARE VENTURES, INC
STTR Phase I: Development of a lighted infusion line to optimize care and decrease complications of critically ill patients in infectious isolation (COVID-19)
Contact
690 SYCAMORE ST
Decatur, GA 30030--1958
NSF Award
2100995 – STTR Phase I
Award amount to date
$255,957
Start / end date
05/15/2021 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Technology Transfer Program (STTR) Phase I project is to make the intensive care unit (ICU) safer for patients and less burdensome for nurses through the development of an illuminated intravenous tubes (IVT) for easier and error-free delivery of medications, enabling better care generally as well as during the COVID-19 pandemic. IVT identification requires an inordinate amount of nurses’ time and confers an immense cognitive burden as it requires manual tracing of the line from pump to patient. The errors associated with manual IVT tracing are costly, contributing to increased ICU length of stay and hospital liability. The current pandemic has exacerbated these issues as ICU admissions are rising and the use of enhanced isolation requiring extended IVT. Successful completion of the proposed program will support the development of an extended illuminated IVT that allows for reliable identification of IVT from pump to patient through the use of a fiber optic cable that nurses can turn on and off as needed when identifying lines. In comparison to the manual tracing of lines, an illuminated line has the potential to provide more rapid and error-free identification of IVT lines, thus reducing the impact of errors on patients, decreasing associated medical costs, and improving nurse workload.
This Small Business Technology Transfer Program (STTR) Phase I Project will advance the development of a novel lighted intravenous tubing (IVT) device to allow nurses to quickly and accurately identify IVT through the use of a light-emitting fiber optic cable attached to the outer wall of the IVT. Management of IVT and medication delivery, requires nurses to manually trace lines from pump to patient, which is an error prone process and particular interest for ICU patients that require upwards of 10 or more IVT lines simultaneously. The proposed program will advance the development of the extended illuminated IVT through the execution of two objectives. The first objective is to engineer the device to ensure that illumination can be maintained over the length of an extended line used in isolation settings. The second objective is to assess the performance of the extended prototype in a simulated ICU setting with enhanced isolation. Successful completion of the Phase I program will demonstrate feasibility of the extended illuminated IVT device in an isolation critical care setting as defined by reduced nurse burden and time in motion.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CLAUDIUS LEGAL INTELLIGENCE INC
SBIR Phase I: Artificial Intelligence Tool for Analysis of Legal Documents
Contact
309 TRINITY CT APT 11
Princeton, NJ 08540--7029
NSF Award
2112315 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to establish an artificial intelligence (AI) system capable of providing data-driven insights for attorneys. The legal community currently lacks data analysis tools to help with civil case preparation, which can lead to suboptimal trial outcomes. The proposed technology can help lower costs through document analysis. The technology is designed to both automate and improve the decision-making process and enable attorneys to expand their case load, as well as enabling cost-effective representation.
This Small Business Innovation Research (SBIR) Phase I project will use federated learning techniques to train the technology’s algorithm across multiple decentralized databases without exchanging data samples, thus keeping information private and confidential. This approach overcomes the lack of access problem in applying AI to legal cases, without compromising data confidentiality. The proposed research will include two major objectives: 1) improve and verify the accuracy of the platform, and 2) create internal checks to ensure that the model does not propagate bias. Computational outputs will be assessed using data and records from randomly selected cases with known outcomes to demonstrate system accuracy; moreover, the model will explicitly account for potential sources of bias.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COLABS, INC.
SBIR Phase I: A CPR-integrated airway and ventilator system that eliminates human operator variability
Contact
17361 LAKEVIEW DR
Morgan Hill, CA 95037--6408
NSF Award
2136635 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (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 enabling automated cardiac resuscitation in emergency situations. Cardiopulmonary Resuscitation (CPR) is a manual process dependent on responder skills. Ventilation, the proper delivery of air into the patient’s airways, is the process during CPR that requires the most skill and, because it is manually accomplished, is the most variable - especially in high stress environments. The proposed automated system offers a convenient, reliable way of accessing the airway which automatically synchronizes ventilation with chest compressions to improve blood circulation during CPR. The system also introduces a defibrillation electrode in the airway tube to enable cardiac defibrillation at lower, safer voltages.
This SBIR Phase I project develops a novel, automated system to provide convenient, reliable patient ventilation and synchronization of compressions. The project’s technical milestones are to demonstrate: (A) reduced operator variability during airway placement and improved oxygen supply in swine models compared to current solutions, (B) reliable detection of cardiac contractions from pressure changes measured in the airway, and (C) feasibility of electric defibrillation with lower energy in cadaver models. The technical challenges are to: account for variations in human anatomy and detect errors with insertion into the airway, account for chest compressions not detected by the system, and ensure electrical contact between the defibrillation electrode and the esophagus during cardiac defibrillation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMMUNITY ENERGY LABS, LLC
SBIR Phase I: Smart Control Automation and Learning for Energy
Contact
401 NE 19TH AVE
Portland, OR 97232--4800
NSF Award
2221872 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2023 – 12/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a commercial building management system that uses model predictive control for small to mid-sized commercial building owners to help them flexibly manage increasingly complex energy codes and prices. This technology uses machine learning to automate costly aspects of advanced building control, and eliminating complexity, frustration, and expense for leanly staffed building owners who are attempting to save money, meet code, reduce carbon footprint and adapt to rapidly changing energy prices. The proposed approach significantly reduces the setup time, the amount of training data, and the compute time needed for the technology to converge on accurate models and predictions using building thermal dynamics. These improvements reduce the controller costs without sacrificing accuracy. This technology will simplify the setup and implementation process for under-represented segments in the building automation, efficiency and model-based controls market starting with K-12 schools. This simplification has several distinct societal and environmental benefits including: increased energy and demand charge savings, increased energy efficiency, improved environmental footprint, increased job creation for building controls technicians, improved resiliency, and additional educational opportunities for K-12 families and communities.
This SBIR Phase I project develops a technology capable of building efficiency control. The innovation employs a hybrid approach based on constrained deep learning tools that build on physical knowledge of building systems and architecture, thereby making use of sampling data while producing physics-consistent accuracy in modeling and control predictions. Specifically, the project team hopes to converge on an architecture that can more reliably and accurately manage energy use and occupant comfort compared to state of the art control approaches. The project team also aims to demonstrate a significant reduction in heating, ventilation and air-conditioning (HVAC)-driven peak system demand in target buildings while keeping instrumentation, labor, and data costs per building to an affordable cost for the target market.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CONNECT DYNAMICS, INC.
SBIR Phase I: Applying Machine Learning to Mitigate Disruptions in Novel Relay Trucking Model
Contact
409 SW A ST
Bentonville, AR 72712--5838
NSF Award
2213149 – SBIR Phase I
Award amount to date
$255,983
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impacts of this SBIR Phase I project include a more sustainable and profitable trucking industry, enhanced conditions for the trucking workforce, improved public road safety, reduced emissions, and a path to future advancements using alternative energy and autonomous technologies. This project centers on a patented technology that pools shipments and matches tractors and drivers with trailers and cargo in a relay fashion that ensures equipment and cargo keep moving while drivers return home daily. Research has established the theoretical viability of applying relay models in long-haul trucking to solve equipment and human capacity issues. Using relay trucking could potentially double asset utilization, cut delivery times in half, and decrease the high cost of truck driver turnover. To date, no company has created a technology to implement scalable relays in American trucking. Customer discovery and research suggests this is due to the complexity of predicting and mitigating real-world trucking disruption events (e.g. traffic accidents, equipment breakdown etc.). The project aims to assess the feasibility of developing a machine learning (ML) based predictive analytics tool to make our relay technology resilient to disruptions in the driver scheduling and truck route optimization problem. A successful project would extend a relay trucking model beyond largely theoretical studies to build the first real-world application in the U.S. It aligns with NSF’s mission by transforming the trucking industry while creating better jobs for new and existing truckers and reducing carbon emissions. We estimate that resolving the inefficiencies resulting in the loss of $110 billion per year.
This project aims to prove the feasibility of using machine learning (ML) techniques to build a predictive tool that integrates with our relay scheduling algorithms to effectively estimate the likelihood of occurrence of disruption events and provide actionable intelligence for deployment of mitigation strategies. A successful outcome will create resilient relay algorithms necessary to commercialize the first scalable relay trucking operations in the U.S. While the use of ML has been explored in predicting weather and traffic events in the recent past, no off-the-shelf ML tools are known to exist that can be utilized for this patented relay technology. This project leverages real-world proprietary operational data from large trucking companies, combined with public data sources and artificially populated datasets representing drivers and equipment informed by work with local partners at relay nodes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CONTROLPOINT INC.
SBIR Phase I: Rapid Single-Use, Point-Of-Care, Disposable Lateral Flow Device for Detection Of Kennel Cough
Contact
88 S 4TH ST
Campbell, CA 95008--2914
NSF Award
2205111 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (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 improve the health and well-being of animals, particularly respiratory infections in dogs commonly known as kennel cough. More than 5 million veterinarian visits a year in the United States alone are due to kennel cough. In 90% of those cases, dogs are treated based on empirical data, which means veterinarians take an educated guess, and fewer than 10% are tested. Dogs are more likely to develop clinical signs of kennel cough the longer they are in a group-housing environment. The 5 million cases in the United States are underestimated and do not typically include cases from kennels, shelters, and/or boarding facilities. With the current procedures, veterinarians may send samples to central laboratories that take many days to provide results. The proposed project will develop a diagnostic test that will provide veterinarians with a cost-effective, easy-to-use single test that can detect a wide range of organisms. The test will provide results within minutes of sample collection.
This Small Business Innovation Research (SBIR) Phase I will demonstrate the initial feasibility of detecting several pathogens in a single test device. The selected pathogens will be a combination of bacteria and viruses that have been identified to cause kennel cough in dogs, a common but debilitating ailment. The proposed work will allow test validation, prototype manufacturing, clinical sample evaluation, and procedures to report results to both veterinarians and pet owners. The innovation will help fill the extensive gaps in understanding the disease ecology, prevalence, incidence, and geographic distribution of kennel cough, facilitating faster and more efficient disease management decisions. The ability to rapidly identify the contagious pathogens involved in an occurrence will permit a rapid response to limit the dimensions of a possible outbreak.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CORAVIE MEDICAL, INC.
STTR Phase I: Highly Responsive Implantable Ultrasonic Sensor for Long-Term Hemodynamic Monitoring
Contact
6015 IDYLWOOD DR
Edina, MN 55436--1230
NSF Award
2213838 – STTR Phase I
Award amount to date
$275,000
Start / end date
08/01/2022 – 07/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to develop an early remote monitoring solution that notifies healthcare providers of risky blood pressure trends, enabling cost-effective interventions and preempting costly heart events or organ damage later. The clinical paradigm shift from infrequent point-in-time and manual blood pressure measurements to continuous and automatic monitoring and reporting may increase the understanding of circadian blood pressure trends and variability that could lead to more than $500 million in healthcare savings and promote the health of the American public. In the United States, there are 116 million people estimated to have high blood pressure, costing the economy $131 billion each year, and leading to stroke, heart disease, kidney disease, and death. A continuous and automatic long-term monitor that requires no patient action offers peace of mind for the nearly 3 million who struggle with monitoring blood pressure from home and who are taking multiple medications for high blood pressure; yet have not managed their blood pressure to a healthy range. The successful development and integration of technologies may offer significant opportunities for future implantable, closed-loop solutions for major chronic health conditions.
This Small Business Technology Transfer Phase I project will evaluate the ability of an implanted blood pressure monitor to address current, well-known challenges such as sensor drift and sensor failure due to tissue maturation and the encapsulation effect, sensor movement and migration, body movement and activity. This project will model, design, and develop ultrasonic sensors that have the technical capability to deliver accurate, long-term, continuous blood pressure measurement when hermetically packaged in biocompatible material for chronic subcutaneous implant. Three ultrasonic sensors will be modelled, designed, fabricated, and tested through a physiologic bench simulation for correlation to blood pressure meausrement over a range of clinical scenarios. The ultrasonic sensor’s miniaturized form factor will then be hermetically enclosed and further tested for power consumption, biocompatibility, and sensor performance during an accelerated test that simulates the biological process of encapsulation. The goal is to design and develop an ultrasonic sensor that possesses the functionality to continuously monitor blood pressure in a dynamic implant environment over a duration of at least one year.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CPR THERAPEUTICS INC.
STTR Phase I: A Multimodal Integrated System For Improved Cardiopulmonary Resuscitation
Contact
189 PUTNEY MOUNTAIN RD
Putney, VT 05346--8519
NSF Award
2151541 – STTR Phase I
Award amount to date
$256,000
Start / end date
07/01/2022 – 06/30/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This SBIR Phase I project aims to improve the outcomes of patients suffering sudden cardiac arrest. Approximately 650,000 cardiac arrests occur each year, representing the top reason for mortality and morbidity in the US and an estimated $33 billion a year for out-of-hospital costs. Overall survival remains generally below 10%, and patients are often left with significant neurological injury. Manual cardiopulmonary resuscitation (CPR) still remains one of the most effective treatments, resulting in better outcomes than current technologies. This project will develop a novel medical device that provides a novel superior automated CPR therapeutic system. It combines multiple methods of mechanical chest compression to improve patient blood flow during resuscitation.
This project will advance preclinical research for developing the first clinically effective noninvasive automated CPR device. The system integrates a multimodal approach for delivering mechanical CPR, and therefore represents a significant advancement to current systems that only deliver a single mode of CPR. The automated and programmable prototype will determine the optimal combination of methods and timing, to control multiple pump mechanisms for applying mechanical chest compressions to improve patient outcomes. This Phase I project will conduct optimization studies in a swine model of cardiac arrest and develop a proof-of-concept model. These results will provide the foundation for the next generation system suitable for human use, as well as advance research results on the hemodynamic interactions of pump mechanisms and cardiac electrophysiology during CPR.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CROOKES RESEARCH LLC
SBIR Phase I: Tele-Directed Artificially Intelligent Medical Robot
Contact
2952 HACKBERRY ST
Cincinnati, OH 45206--1441
NSF Award
2203203 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (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 project is to develop a novel artificial-intelligence (AI) robot-control paradigm to facilitate real-time tele-robotics and advance humankind’s robotic capability. This AI constantly interprets the intent of the operator in the context of the robot’s environment, and makes real-time adjustments to the motion of the robot to accomplish the intended task. Ultimately, this allows the operator to focus on the objective instead of operating the robot. This project will allow tele-robotics to become a viable solution in uncertain environments where traditional control schemes, with inherent latency and precision issues, currently prevent adoption of robotic solutions. This benefits applications in which a higher degree of expertise and decision-making is required to perform tasks in a dangerous or inaccessible location. The first application of this technology will allow nurses to provide patient care within hospital isolation environments to prevent exposure to the patient and care-providers. Additional applications include military, industrial maintenance, aerospace, public safety, energy, mining, and undersea solutions. Tele-robotics is a $62B market in 2019 growing by 13.5% annually.
This Small Business Innovation Research (SBIR) Phase I project proposes to address the nursing crisis with an AI-enhanced robotic in patient-isolation environments. Instead of delaying care to don and doff personal-protective equipment, nurses can instantly work through the eyes, ears, and arms of these robots. The key innovation in this Phase I project is novel AI which will intuit the intent of the operator to successfully complete tasks. The proposed research will develop a robot control policy which observes the robot’s current environment as well as the users control inputs, and actuates a robot to achieve the desired task. The robot will self-correct for errors made by the user through an understanding of the desired outcomes. At the end of this Phase I project, we expect the robot to perform a demonstration of accurate and timely object manipulation while controlled by a remote operator without line of sight to the work area. In a subsequent phase, the ultimate technical objective is for the solution to be as intuitive and invaluable as a modern smartphone. The business objective, developed in partnership with healthcare systems, is to provide better isolation-patient outcomes while improving productivity and reducing health risk for nurses.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CRYPTYX BIOSCIENCE, INC.
SBIR Phase I: A Natural Product Drug Discovery Platform Based on High-Throughput Elicitor Screening (HiTES)
Contact
WASHINGTON ROAD FRICK LAB RM 333
Princeton, NJ 08544--0001
NSF Award
2150951 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
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 the development of a novel, small-molecule drug discovery platform that triggers the production of cryptic microbial metabolites for use as new pharmaceuticals with the potential to target a range of diseases. This technology will address pain points associated with the development of new drugs, such as long timelines and high costs. By using a proprietary process and established collection of elicitor molecules, microorganisms can be compelled to generate natural products that offer biological activities that may be impossible with synthetic molecules. The proposed technology is the only screening platform that is free of genetics and cloning, focusing on bioactivity first, and enabling rapid and efficient biomolecule discovery. Initially the platform will be used to target the antibiotic/antiviral market, with future applications for anti-tumor and immunosuppressant drugs. This project has the potential to improve the health of the American public by providing a steady stream of novel drug candidates to address a range of unmet medical needs.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel, small-molecule drug discovery platform based on High-Throughput Elicitor Screening (HiTES), a rapid, simple method for triggering production of microbial cryptic metabolites and interrogating their activities without the need for genome sequencing, cloning, or genetics. There is a large untapped store of natural products in the form of ‘cryptic’ biosynthetic gene clusters encoded in microbial genomes that are not expressed under laboratory conditions. The technical objectives are to increase output/throughput of the platform, assess and optimize chemical diversity, and expand the platform to new antibiotic-resistant pathogens of public health concern. Silent genes across multiple bacterial species will be activated to generate cryptic metabolites with the goal of producing 5,000 induced metabolomes, which will be characterized using mass spectrometry. A workflow will be created that integrates bioactivity assays against multiple pathogens with HiTES screening. Finally, in-house software will be updated to include prioritization in terms of novel chemistry, desired bioactivity, and lack of cytotoxicity. Successful Phase I completion will demonstrate the ability to implement and use HiTES multiplexed with bioactivity studies and software to identify chemically-novel and unique compounds with promising bioactivities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CYBERSPARA, INC.
STTR Phase I: A simulation tool to teach cybersecurity and digital fluency practices
Contact
1883 COUNTY ROUTE 35
Potsdam, NY 13676--3538
NSF Award
2112181 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/15/2022 – 05/31/2023 (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 an effective, engaging education platform to teach cybersecurity awareness and best practices to protect against cyber threats. Identity theft affects millions of individuals every year, costing billions of dollars and severe personal difficulties to those affected. Privacy education is essential to address the potential dangers facing the billions of people using these platforms.
This Small Business Technology Transfer (STTR) Phase I project plans to develop an online simulation product that engages citizens to experience cybersecurity simulations that emulate various real-world cyberthreats while implementing evidence-based learning research in digital media and instructional systems technologies. For educational service providers, this solution will provide an effective standards-based computer science and digital fluency learning approach to cybersecurity for the school-age population. By using developmentally appropriate instructional and teaching strategies, the solution plans to address and measure effectiveness across a wide range of age groups, demographics and education levels.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DATASHAPES, LLC
SBIR Phase I: Study for a new design of child resistance packaging
Contact
735 E SHAW LN #501
East Lansing, MI 48825--3802
NSF Award
2136458 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/15/2022 – 03/31/2023
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 develop a novel medication safety cap capable of simultaneous child-resistance and adult-accessibility to reduce the morbidity and mortality associated with unintentional medication overdoses by young children. Every hour a young child under the age of 6 is hospitalized, and every 12 days a child dies in the United States due to unintentional medication ingestion. Studies have shown that improper use of safety caps by adults (only partially securing the cap or leaving it off entirely) contributes to unsupervised medication ingestions by young children. The proposed safety cap would prevent access by young children while also being easy to understand and operate by older senior adults, integrate with current high- speed manufacturing and distribution systems, and be cost-competitive.
This Small Business Innovation Research (SBIR) Phase I project leverages the ergonomic differences between child and adult hand sizes, with differences in human-product interaction behavior, to develop more effective child-resistant packaging for medications. Current state-of-the-art safety caps rely on strength and dexterity-based mechanisms to restrict access for young children, but these methods are also often difficult for adults to use properly. This project seeks to leverage the behavioral and mechanical product interaction differences into a safety cap and provide quantitative evidence of both senior adult accessibility and child- resistance. The expected outcomes of this Phase I project is a design that is (1) validated to function within the thresholds of child-resistance and senior adult accessibility, and (2) pass safety and regulatory 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. -
DCAN BIOSCIENCES LLC
SBIR Phase I: Advanced microfluidic systems enabling development of novel circulating tumor cell diagnostics
Contact
310 E 67TH STREET, SUITE 1-47
New York, NY 10065--6275
NSF Award
2234009 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2023 – 01/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the diagnosis, risk assessment, and monitoring of cancer. Nearly 40% of Americans will be diagnosed with cancer in their lifetime. Diagnosis of cancer in later stages dramatically reduces treatment options, leading to poor prognosis and low survival rates. In addition, the average cost of treatment for late-stage patients can be 3–5 times higher than that for early-stage patients due to the potential need for multiple rounds of expensive therapies. These multiple rounds of treatment contribute to the high economic burden of cancer. Thus, detecting cancer earlier will not only lead to improved patient outcomes but will likely reduce the overall costs of cancer treatment. Moreover, a minimally invasive and highly accurate diagnostic could be broadly administered to effectively identify those with various cancers, enhancing the commercial potential further.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop an advanced microfluidic system for the isolation and assessment of circulating tumor cells (CTCs) and CTC clusters (CTCCs) for cancer diagnosis and monitoring. Microfluidic devices in various forms have been developed to isolate the extremely rare CTC population from billions of blood cells, but these technologies suffer from three major problems: 1) low sample purity, 2) low numbers of isolated CTCs/CTCCs, and 3) CTC/CTCC heterogeneity. To overcome these limitations, this project will develop an innovative device for the simultaneous isolation and assessment of single and clustered CTCs and their molecular signatures, enabling the implementation of new, highly sensitive and accurate liquid biopsies for cancer. The key objectives for this project are: 1) Design and develop a hybrid microfluidic system for simultaneous isolation and concentration of CTCs and CTCCs with high purity, 2) Develop and optimize two devices for single CTC and CTCC analysis, and 3) Testing and validation using prostate cancer patient specimens. This research will lead to the development of a new cancer diagnostics platform that is minimally invasive and more sensitive and accurate than current methods, expanding treatment options and improving patient outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DIRECT KINETIC SOLUTIONS LLC
SBIR Phase I: Quantum Power Chip Component Development
Contact
1009 METATE PL
El Paso, TX 79912--7550
NSF Award
2136838 – SBIR Phase I
Award amount to date
$255,139
Start / end date
10/01/2022 – 03/31/2023
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 aiming to put a minute power plant in the motherboard of electronic devices. Every device with a battery in it has the potential to be enhanced with the proposed approach. This will take care of the idle and standby functions, preventing unnecessary battery drain. The benefits this provides are enormous, as an example, a potential customer was able to monitor a grain silo for a year transmitting once a day with its current setup, by adding one of the proposed power sources, they could monitor for five years while transmitting once an hour. The markets where such devices are expected to shine are IoT, especially for companies offering sensing as a service, particularly in remote, austere, and hostile environments where maintaining sensors is too costly, and in Space. In Space, we offer a third power alternative to the small satellite and below spacecraft. The proposed power sources can be used to continuously generate power for the entire system, or be used as a redundant power source to ensure critical systems are always alive. The company expects to commercialize the finished product by the end of 2023.
This SBIR Phase I project proposes to enhance the radioisotopic compound used in the power sources under development. The product is composed of three major components, the semiconductor (chip), the compound (the fuel and target for this engagement), and the encapsulation (putting them both together and ensuring they are producing power). The compound improvement is expected to enhance the power generation of our devices. From previous experiments, it was discovered that the area coverage of the previous version of the compound could be greatly improved. As coverage improves, the power output is expected to improve accordingly, the hypothesis is that it will be possible to at least double the previous power output results. Following such an anticipated significant improvement in the compound performance, the company will experiment with different chip combinations, this will allow for the creation of alternatives for potential customers, depending on their power and budget needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DIRECTED ANALYTICS INC.
STTR Phase I: Automating Employability Skills Development for Individuals with Autism Spectrum Disorder and Developmental Disabilities
Contact
7117 FLORIDA BLVD STE 200-1L
Baton Rouge, LA 70806--4549
NSF Award
2151654 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 seeks to increase the competitive employability of individuals with developmental disabilities. For individuals with developmental disabilities (autism spectrum disorder and other intellectual disabilities) employment disparities are far greater than their non-disabled peers; Approximately 20% of working-age adults supported by state developmental disability agencies are employed in a paid job and only 15% were employed competitively. The proposed project will develop a product for school districts and higher education establishments to address the needs of approximately 8 million intellectually disadvantaged individuals in the United States education system. The implementation of this innovation seeks to impact the rates of employment in this population, resulting in increases in personal income, reduction of poverty levels, and better health outcomes for individuals.
This Small Business Technology Transfer (STTR) Phase I project plans to create a scalable software framework which integrates, evaluates, and analyzes data from school districts and higher education programs in order to enable the use of machine learning to improve the relationship between transition intervention methods and employment outcomes. Using this innovation, school districts would be able accurately predetermine an individuals’ ability to successfully perform tasks associated with employment. Higher education programs which enroll adults with developmental disabilities may then effectively scale and develop an individual’s employability skills. The framework will provide structured data collection, data alignment, and data interlinking for roadmaps which will be implemented into the product, enabling educators and individuals to interact, learning how employability programmatic factors and educator corrective actions contribute to employability skills 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. -
DIVERSE EMERGENT ENGINEERING PROSPECTIVE -DEEP- DESIGNS LLC
SBIR Phase I:VIBES: An Intelligent Application for Emotional Support During the COVID-19 Crisis
Contact
4415 SW 34TH ST APT 301
Gainesville, FL 32607--1739
NSF Award
2034057 – SBIR Phase I
Award amount to date
$275,866
Start / end date
02/01/2021 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research Phase I project includes the need for 1) student engagement in social-emotional learning, 2) coordinated and consistent ways for counselors, teachers, and students to support the mental health of students, and 3) student connection during times of isolation. The transition from elementary to middle school demands new social skills in a larger and more intricate environment with an increased probability of peer conflicts. Paradoxically, this point also marks a need for more stable and intimate relationships with peers. In other words, the point of highest need with respect to relationships coincides with opportunities for the most turmoil. All of these challenges now exist in parallel with COVID-19, which has caused school closings, food scarcity, parental unemployment, social isolation, and destabilized support systems. The project will develop a scalable tool for supporting teachers, counselors and after school/out of school facilitators engaging students in social-emotional learning. Within the web-based system, students will be able to actively and consistently track and reflect upon their thoughts, feelings, and emotions; teachers/counselors will have a dashboard with a view of students’ challenges and customized suggestions for students to engage with social-emotional learning activities.
The proposed project will develop an intelligent online self-tracking system to support social-emotional growth for middle school students. The key technical challenges we must resolve include: defining and refining a user experience that teachers/counselors will find educationally compelling and with which learners will engage; designing a curating process for remote learning content that will ensure safety and security of all users; designing algorithms to support tracking of student social-emotional well-being; and creating a recommendation system that determines the best interventions to suggest to students based on previous 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. -
DRIVENDATA, INC.
SBIR Phase I: Open Machine Learning Competitions with Private Data
Contact
1644 PLATTE ST STE 400
Denver, CO 80204--4033
NSF Award
2038067 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 09/30/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to expand access to artificial intelligence (AI) talent and spur innovation to solve hard problems while protecting privacy. Machine learning and AI are bringing transformational change to governments, private companies, and social sector organizations. Yet in the coming years, innovation will be hamstrung by limited access to AI talent. Open innovation, such as machine learning (ML) competitions, provides governments and firms the ability to tap into a global talent pool to solve some of their most pressing and vexing challenges. Yet there is currently an immense barrier to running these competitions: the data must be made available to participants, which can preclude running a competition if the associated data are too sensitive to release due to concerns about privacy, security, or confidentiality. With data talent in increasingly high demand, government agencies, companies, and others have demonstrated a willingness to invest in this fashion. The proposed project develops a method to maintain data privacy at scale.
This Small Business Innovation Research (SBIR) Phase I project will develop an end-to-end competition system that provides privacy guarantees for data used to build crowdsourced algorithmic solutions. Open ML challenges typically work by providing participants with training data to learn underlying patterns, then evaluating resulting predictions on unlabeled test data. For many important problems, making training data available in this way violates concerns about privacy or enables abuse. The critical gap is preserving the privacy of training data while enabling participants to build models that can learn from it. This project will bring together recent advances in three of the most promising approaches in privacy-preserving data analysis: homomorphic encryption, federated learning, and differential privacy. Each technique will be developed and tested in a dedicated challenge structure with two core properties: 1) to preserve the privacy of sensitive data; and 2) to ensure competitors are able to get feedback on submitted models during the competition to inform algorithm improvements. Each competition system will result in a set of performance measures, including benchmarked algorithm performance and data privacy guarantees, to assess system 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. -
DYNAMAC MICROWAVE, INC.
SBIR Phase I: Environmentally Sustainable Manufacturing Technology for Fabrication of Radio Frequency (RF) Filter Products
Contact
1229 W CAPITOL DR
Addison, IL 60101--3116
NSF Award
2151757 – SBIR Phase I
Award amount to date
$254,214
Start / end date
04/15/2022 – 03/31/2023
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research Phase I project is to develop a radio frequency (RF) network miniaturization technology and manufacturing methodologies to dramatically reduce the size, weight, and cost of RF filters. This research will develop special filters for a broad range of wireless applications, including smartphones and their infrastructure, WiFi devices, broadcast systems, and satellite systems. The proposed technology may reduce landfill contributions by over 300 tons, scrap metal by 2200 tons, and general metal consumption by 4500 tons.
This SBIR Phase I project seeks to demonstrate the feasibility of the world’s first RF filter network miniaturization in air using an new network fractionalization algorithm via simulation and prototype fabrication. The fractionalization algorithm overcomes the high challenging wavelength barrier to RF filter miniaturization in air for development of miniature multilayer air filter structures. This project will develop: (1) methods of manufacture for single resonator circuit layer assemblies, the main building blocks for construction of multilayer air filter structures; (2) manufacturing methodologies for structures comprising multiple single resonator circuit layer assemblies to fabricate multi-resonator miniature multilayer air filter prototypes to demonstrate performance and key attributes of the multilayer air filter technology at various frequencies and power levels. The prototypes will be used to demonstrate the scalability, repeatability, and reproducibility of the miniature multilayer air filters for mass volume production, as well as to establish production unit cost models.
This award reflects 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 – 07/31/2023 (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. -
EARLY ALZHEIMER'S DIAGNOSTICS LLC
STTR Phase I: Saliva Screening Test for Alzheimer’s Disease
Contact
66 JEFFERSON RD
Glenmont, NY 12077--3318
NSF Award
2233317 – STTR Phase I
Award amount to date
$274,713
Start / end date
12/01/2022 – 11/30/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project entails the development of a simple and affordable saliva-based test that will enable the detection of early Alzheimer's disease. Today, there is no single test that can determine if a person has Alzheimer's disease. Because the diagnosis is complex, invasive, and expensive, these tests are only performed once symptoms, such as memory loss, begin to manifest. These symptoms of Alzheimer's disease only become apparent once the disease has already cause significant damage to the brain. The proposed test will be widely accessible and detect the disease before symptoms arise, enabling the patient to start active prevention strategies and even therapies to preserve brain health. As the American population ages — nearly 1 in 4 Americans will be 65 years of age or older by 2060 — Alzheimer’s disease and other dementias are becoming a great challenge for health and social care. As part of a broad approach to prevention, this technology can potentially extend early Alzheimer’s care to millions of Americans, allowing interventions, monitoring, and treatment initiation years earlier than what is currently possible.
This Small Business Technology Transfer (STTR) Phase I project is applying sophisticated chemical analysis methods to develop a novel test to detect signs of early Alzheimer’s disease using a person’s saliva. Diseases can cause changes in the biochemical composition of body fluids such as blood or saliva. Using a modern, highly sensitive type of spectroscopy based on light scattering, and combining it with advanced statistical approaches (i.e., machine learning), this project is developing a method that can reliably detect biochemical changes in saliva specific to Alzheimer’s disease. This project aims to demonstrate the feasibility of the approach by showing its ability to distinguish saliva donated by healthy individuals from saliva collected from Alzheimer's patients at both mild and moderate stages of the disease. The project will also investigate whether known biomarkers for Alzheimer’s disease are being identified by this method and develop statistical approaches to interpret spectroscopic 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. -
EARTHSHOT Labs PBC
SBIR Phase I: Smartphone-Based Machine Learning and Computer Vision for Cost-Effective Verification of Forest Carbon Offsets
Contact
25 N MOORE ST APT 7B
New York, NY 10013--2461
NSF Award
2212767 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project is to make the gathering of tree measurements and other field-based nature observations dramatically easier. The project involves building a mobile app that uses computer vision and augmented reality to make measuring trees much easier than using the tape measures of today, in fact it will be as simple as scanning a barcode. This will result in much more nature imagery and other training data for use with ecological models, which will yield a better understanding of how ecosystems will change in the coming years. One important prediction this project will help with is forest growth which is very useful for generating carbon offsets that can finance the regeneration of large amounts of land. Better ecological models can also help communities prepare for changes in climate, sea level, soil quality and other ecological shifts in the coming decades. Millions of people will be potentially affected by climate change and its accompanying shifts in ecosystems, so arming communities and governments with better insights about these impacts will be critical. Furthermore, catalyzing many millions of hectares of nature regeneration projects will help mitigate the worst effects of climate change and other ecological challenges.
This project involves the unique combination of computer vision with augmented reality in order to quickly and accurately measure trees. There are multiple computer vision neural networks being developed for the app. One of them uses bark and tree imagery in order to classify the tree species, an important feature needed for ecological models. Another model analyzes surrounding scenery and quickly identifies the closest tree trunk. The app then uses the phone’s augmented reality capabilities to gauge the distance and orientation of the phone from the trunk and combines these two to yield a diameter at breast height measurement. The research plan involves collecting data from specific regions in Panama and Brazil in conjunction with active nature restoration projects and gathering a critical mass of leaf and bark imagery so that species in those areas can be classified accurately. The scope will then increase to additional regions and later, measurements such as birdsong and other biodiversity markers. Over time the app could become a platform for many such nature observations, and it is expected to evolve to become more game-like to attract large numbers of people having fun experiences together and advancing the cause of nature science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECHO MIND AI CORP.
SBIR Phase I: Artificial intelligence (AI)-enabled ultrasound for imaging and diagnosing musculoskeletal injuries
Contact
9717 NEWCASTLE DR
Highlands Ranch, CO 80130--6811
NSF Award
2212911 – SBIR Phase I
Award amount to date
$249,978
Start / end date
08/01/2022 – 07/31/2023 (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 widespread adoption of ultrasound imaging for musculoskeletal (MSK) injuries. The ultrasound image analysis platform enabled by artificial intelligence (AI) developed during this SBIR may bring cost-effective diagnostic imaging to a broader patient population as the small form factor of the ultrasound instrument enables the technology to be used in a variety of settings, including doctors’ offices, physical therapy offices, and sports facilities. There are approximately 840,000 clinicians who see patients with MSK injuries. Each of these clinicians represents candidate customers for the platform, leading to a total addressable market in the U.S. of $1.7 billion.
This Small Business Innovation Research (SBIR) Phase I project seeks to advance artificial intelligence (AI)-enabled ultrasound imaging technology. Sonography is the most operator-dependent medical imaging modality in use today, limiting the use of ultrasound imaging in musculoskeletal (MSK) evaluation. The proposed approach seeks to enable the wider adoption of ultrasound for diagnosing MSK injuries. This project involves the development of rigorous mathematical models to determine whether a frame sequence is properly aligned and determine if tendon tears in shoulder scans are diagnosable. A guidance system will be developed to aid in ultrasound probe placement so that consistent identification of tendon tear presence or absence is achieved. The proposed AI-enabled approach to ultrasound imaging and diagnostics may help practitioners position the ultrasound probe without the need to maintain precise angular positioning. Once at the correct starting position, the practitioner will move the probe in a pre-prescribed motion using a guidance system as needed for accurate and efficient image capture. The goal of the technology is to enable novice practitioners to capture relevant analyses to assist in providing a diagnosis and a treatment plan.
This award reflects 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 β-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 – 01/31/2024 (Estimated)
Errata
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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 β-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. -
EDVISION CORP.
STTR Phase I: EdVision: AI-powered academic guidance for PhD programs
Contact
9408 AZALEA RIDGE CIR
Tampa, FL 33647--2557
NSF Award
2014338 – STTR Phase I
Award amount to date
$224,986
Start / end date
07/15/2020 – 05/31/2023 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to use artificial intelligence methods to help all PhD program stakeholders (students, alumni, faculty, administrators) maximize desired student placements by leveraging available courses and other resources on campus. PhD student placement is a great concern for universities. However, in the absence of data-driven tools that can help administrators track PhD student progress and market needs, there is little that university leaders or faculty can do to continually improve PhD programs and align these programs with the needs of the economy. The total addressable market for AI-driven academic guidance for higher education is estimated at over $1 billion annually. By improving the match between PhD academic preparation and the needs of organizations tackling contemporary challenges in knowledge and technology intensive industries, this project will help universities contribute to society’s grand challenges in areas such as energy, food, disease and transportation. The success of this project will demonstrate the feasibility of continuously gathering adequate data from students, alumni and job postings and using this data to make reliable predictions and actionable individualized recommendations to PhD students that support their academic preparation towards improved market readiness. Education is one of the most important applications of AI, and this project focuses on using AI to empower students, faculty and administrators to maximize the outcomes from the large investments by universities in PhD programs.
This Small Business Technology Transfer (STTR) Phase I project aims to collect highly granular data from PhD students, alumni and job market postings and use this data to build prediction and recommendation models to maximize the match between each student’s interests and market needs across long time horizons beyond graduation. While the market expectations for PhD graduate competencies are evolving rapidly and include high levels of multi-disciplinary excellence, PhD programs are evolving slowly, largely due to the lack of data-driven recommendations for appropriate interventions. The proposed R&D plan will develop semi-automated methods for data curation in higher education, then use this data to build novel algorithms using neural network architectures and techniques to predict career outcomes of PhD graduates. The company will also use this data and upstream models to build individualized recommendations using model-based reinforcement learning. The system will suggest the most suitable actions for students, faculty and administrators to maximize the impacts of PhD programs in all disciplines.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ELEKTRODA, LLC
SBIR Phase I: Low-Cost Bipolar Plate for a Proton-Exchange Membrane Fuel Cell
Contact
6901 LYNN WAY
Pittsburgh, PA 15208--2438
NSF Award
2208556 – SBIR Phase I
Award amount to date
$253,773
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the high cost of proton-exchange membrane (PEM) fuel cells. As the world transitions from internal combustion engine vehicles to electric vehicles, the market for fuel cells is expected to increase substantially. Fuel cell electric vehicles (FCEVs) have a number of advantages, such as high durability, long range, and fast refueling over battery electric vehicles (BEVs). Additionally, fuel cells are less susceptible to the supply chain issues that lithium-ion batteries are beginning to suffer from. However, FCEVs are currently at a significant disadvantage to BEVs in terms of cost. Reducing the cost of the fuel cell stack will help to make FCEVs cost competitive with BEVs and will accelerate their adoption into the marketplace.
This SBIR Phase I project proposes to reduce the cost of PEM fuel cells by reducing the cost of the bipolar plate component. Bipolar plates currently account for approximately 30% of the full fuel cell stack cost. Current bipolar plates are made from either metal foils or molded carbon composites. Metal plates can be produced by high-speed, low-cost forming techniques, but must be made from expensive, corrosion resistant materials. Carbon bipolar plates are made from inexpensive precursors but are manufactured by processes which scale poorly. This project aims to demonstrate that a bipolar plate can be produced from a novel, low-cost, carbon-based sheet utilizing forming techniques analogous to those used for producing metallic bipolar plates. The effort focuses on optimizing the carbon sheet for low hydrogen permeability, demonstrating that flow channels can be stamped into the sheets, and quantifying functionality and durability by testing in small scale fuel 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. -
ENCAPSULATE LLC
SBIR Phase I: Personalized Cancer Screening
Contact
400 FARMINGTON AVE
Farmington, CT 06032--1913
NSF Award
2208230 – SBIR Phase I
Award amount to date
$255,995
Start / end date
05/15/2022 – 04/30/2023
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to increase the success rates of cancer therapy, reduce the costs and duration of treatment, and to improve patients’ life quality. More than 70% of the 16 million Americans diagnosed with cancer will undergo ineffective chemotherapy cycles through trial-and-error methods. On average, a cycle of chemotherapy costs $30 k and takes 12 weeks to complete; cancer patients undergo 5-6 cycles at a cost of an estimated $180 k. This project advances a method to pre-screen response to chemotherapy drugs so that clinicians can select the most effective treatment, consequently shortening the duration, reducing complications, improving outcomes, and reducing the financial burden. The technology uses a quick, single-step, scalable, inexpensive, and automated process that tests a wide range of drugs in less than a week. With this technology, the oncologist will be able to select the most effective chemotherapy drug for a cancer patient, on an individualized basis and prior to initiating treatment. The proposed personalized approach would reduce the number of chemotherapy cycles to 1-2, and save up to $120 k per treatment, generating annual national savings of $18.2 B.
This Small Business Innovation Research (SBIR) Phase I project supports the development, proof-of-concept validation, and preclinical evaluation of an automated biochip platform that grows patients’ cancer cells outside the body to screen them against chemotherapeutic drugs. In the research described herein, tumor specimens from patient biopsies will be grown and maintained as microtumors in the biochips to recapitulate clinical tumor behavior. The biochips and process will be optimized to create microtumors that can be used toward evaluating the performance of cancer treatment. Research objectives are to I) evaluate, refine, and optimize the design of the biochips through simulation studies to ensure compatibility with native tumor microstructure and mass transfer behavior; II) evaluate the formation, growth, and behavior of patient-derived microtumors in the biochips; and III) investigate the response of patient-derived microtumors to anti-cancer drugs in comparison to longitudinal clinical 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. -
ENDEAVOR COMPOSITES, INC.
STTR Phase I: Innovative dispersion technology for the sustainable repurposing of off-spec and recycled carbon fiber into low-cost, defect-free, nonwoven fabrics
Contact
2370 CHERAHALA BLVD
Knoxville, TN 37932--1563
NSF Award
2212278 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 07/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The Broader impact of this Small Business Technology Transfer (STTR) Phase I project is to intercepting landfill-destined carbon fiber – designated as off-spec fibers - and repurpose it into sustainable nonwoven fabrics. Off-spec carbon fiber constitutes 30% of carbon fiber production. These sustainable fabrics will be categorized based on their performance characteristics into multiple tiers that are suitable for different scales of applications. In addition, this project will explore the hybridization of natural fiber and off-spec carbon fiber for increased sustainability. The results of this project may serve as a baseline for industry to adopt these fabrics into their composites to create lighter automotive vehicles with lower emissions. The advanced composites made from the resulting fabrics may introduce new, high-performance materials that can be used for the development of medical devices, lightweight unmanned aircrafts, and electronic enclosures with applications in the automotive, aerospace, sporting, and marine industries, and beyond.
The proposed innovation to produce nonwoven fabrics from off-spec carbon fiber is based on the fundamental studies of their physical and chemical properties and their responses to mechanical agitation and suspension in an aqueous solutions. This effort focuses on dispersing mechanisms for the wet laid process. This technology may lead to a mathematical model that can receive inputs about fibers properties and predict a mixing regime that will provide dispersion conditions for an optimal nonwoven fabric. Such models can be supported with thorough, standardized, quality control and mechanical testing. This project objectives are to establish process to fabricate mats using off-spec materials, including trims, and recycled fibers and to optimize operations for mats made from different combinations of blended carbon fiber tiers. Mixtures of different fractional percentages and types of on- and off-spec carbon fibers will be used, and models will be adjusted to reflect optimal operational settings. Finally, the team will compare the performance of tailored mixed-material carbon fiber mats against those produced using only carbon fibers to expand products 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. -
ENVONICS LLC
SBIR Phase I: A real-time precision nutrient analysis and management system for hydroponic farming operations
Contact
13499 BISCAYNE BLVD STE 709
North Miami, FL 33181--2027
NSF Award
2210046 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to promote the viability and sustainability of small-to-medium indoor, urban, and controlled environment agriculture (CEA) farms. As the global population grows to 10 billion by 2050, the agriculture industry will need to produce 70% more food using only 5% more land. Indoor farming can make a significant contribution to meet this demand sustainably. Indoor farmers are also seasonally and geographically independent, which means they can help meet demands for locally produced fresh foods and are protected from extreme weather events. These farms primarily use soilless growing methods, such as hydroponics, that currently suffer from critical needs for efficient and affordable methods to monitor and manage nutrients and water in order to be financially viable and environmentally sustainable. The proposed project provides an innovative solution for nutrient management in hydroponic farming, thereby lowering the costs, increasing the yield potential, and supporting the viability of such farms. By supporting the expansion of the national hydroponics industry, this project will increase the local production of and expand access to fresh produce.
This SBIR Phase I project will develop a nutrient management system to provide CEA farmers with real-time information about the nutrients in the growth solution of their crops. The proposed solution will utilize ion-selective electrode (ISE) technology and a decision support system powered by machine learning (ML). This project will focus on the critically needed engineering and data analytics research and development to de-risk major technical challenges in the development of the nutrient management system, providing proof-of-feasibility. The key objectives of this project are to: 1) design a special chamber for the sensors to minimize the interference and increase accuracy, 2) validate the feasibility and accuracy of this new design in a greenhouse setting, 3) develop a predictive algorithm to automatically calibrate the sensors, and 4) measure and predict deficiencies in leafy greens production: collecting empirical evidence of nutrient deficiency to train ML models to identify, and ultimately, predict a deficiency prior to when it is observable.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ERISYON INC
STTR Phase I: Single molecule sequencing of phosphorylated proteins for next-generation protein analyses and diagnostics
Contact
165 LUQUER ST APT 1
Brooklyn, NY 11231--4011
NSF Award
1938726 – STTR Phase I
Award amount to date
$225,000
Start / end date
07/01/2020 – 06/30/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will be to develop a highly sensitive assay that characterizes protein modifications for life science research applications. Proteins are life's nanomachines and serve as the targets for almost all drugs and the vast majority of diagnostic tests. One type of Modifications to proteins, such as addition of phosphate molecules (termed phosphorylation), are key triggers that alter protein activity. Subsequently, this can radically change cellular behaviour, such as affecting embryonic growth or development of tumors. The market for technologies studying proteins and their modifications range from clinical applications to fundamental research and is estimated at $17 B, and detecting these modifications is the fastest-growing application growing at an estimated 18% annually. The proposed protein-sequencing assay can characterize these protein modifications with 4-6 orders of magnitude greater sensitivity than current technologies. This sensitivity enables new classes of experiments in which only small samples are available (e.g. biopsies from living patients) or the target protein/modification is rare, and translates to substantial materials savings in all cases. The highly-sensitive characterization of proteins and their modifications will provide a new type of valuable quantitative data for scientists in industry and academic labs alike.
This Small Business Technology Transfer (STTR) Phase I project will be to develop the single-molecule protein sequencing assay (fluorosequencing) for use by proteomics scientists to precisely quantify multiple phosphorylated sites on protein molecules. The best analytical technology today, mass-spectrometers, has an inherent limitation in identifying multiple (>2) closely spaced protein modifications and cannot produce accurate quantitative data if fewer than 10% of the proteins are modified at the particular amino acid. Better characterization and quantification of phosphorylation is recognized as a need by proteomics researchers. The project will explore the competitive ability of fluorosequencing to distinguish and quantify closely spaced modifications in multiple proteins. The project will also provide evidence for the capability of the technology to detect and quantify a single phosphorylated protein amongst 100 total proteins.
This award reflects 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 – 08/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to accelerate the adoption of error correction technologies in the quantum computing industry. It is widely held that quantum error correction will be critical to realize the potential of universal quantum computing. An error-corrected quantum computer holds promise for making transformational discoveries in science and engineering that will have broad impact across traditional technology sectors. By developing resource-efficient quantum error correction design and decoding software tools, this Phase I project aims to hasten the era of error-corrected quantum computing.
This Small Business Innovation Research (SBIR) Phase I project will advance a new method for error syndrome extraction from a register of data qubits during the execution of an error-corrected quantum algorithm. In contrast to the standard approach to syndrome extraction, where each quantum codeword is treated independently, this new approach extracts error information from the entire quantum computer collectively. The algorithmic and cost advantage of the proposed approach is a reduction in the number of extra qubits required for error syndrome extraction. This project will focus on reducing the density of the quantum circuits used for syndrome extraction according to the new approach. Low-density quantum circuits are critical for robust quantum error correction since syndrome extraction is mediated by two-qubit entangling gates, which often have error rates higher than idling or memory errors occurring in the data qubits. Another objective of this Phase I project is to design low-density error correcting codes that promote locality in syndrome extraction. Local syndrome extraction is important for error correction in quantum processors that support limited connectivity between qubits. A final objective is to benchmark the proposed constructions and algorithms on simulated data and perform proof-of-concept experimental validation on cloud-based quantum computers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EXLATTICE, INC.
SBIR Phase I: Machine learning-powered simulation of additive manufacturing for real-time design and process optimization
Contact
201 W MAIN ST STE B22
Durham, NC 27701--3228
NSF Award
2151667 – SBIR Phase I
Award amount to date
$255,934
Start / end date
08/15/2022 – 07/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to accelerate larger-scale adoption of additive manufacturing (AM) through ultrafast engineering simulation software. The AM industry was worth $12.6 billion in 2020 and holds great potential in providing advanced designs and enabling distributed supply chains for the US aerospace, medical, and automotive industries. However, AM is facing slow adoption due to trial and error processes casued by the lack of an efficient and reliable engineering workflow. The proposed ultrafast simulation technology may provide real-time predictions of possible manufacturing issues for AM parts in the design phase, thereby reducing manufacturing failures and prototyping. The project also seeks to generate systematic knowledge of how machine learning can help overcome some long-lasting fundamental challenges in scientific computing and help advance engineering software used for digital manufacturing.
This Small Business Innovation Research (SBIR) Phase I project integrates machine learning with finite element methods (FEM) to develop a proof-of-concept for 3-5 orders of magnitude faster process simulation software for AM used to predict manufacturing failures due to high temperature, residual distortion, and residual stresses. The traditional computation method for part-scale AM simulation takes hours to days and relies on an iterative, layer-wise approach. The proposed project seeks to replace the most time-consuming steps in the traditional simulation method with deep learning and implement a one-step approach. The proposed hybrid data-driven plus physical simulation framework includes the development a feature-driven, deep learning model and a process parameter-based transfer learning model, and coupling these models with the finite element method. The project also aims to apply and benchmark hybrid datasets from AM physical modelling, three-dimentional (3D) scanning of manufactured parts, and in-situ monitoring for training and model scalability. The team seeks to demonstrate technological advantages through pilot testing with streamlined user interfaces and application programming interfaces (APIs) developed in this project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EZRABIO INC.
SBIR Phase I: An Easy RNA-Adenylation Method for Deep Sequencing of Picogram RNA Samples with High Resolution
Contact
135 HOLLY CREEK LN
Ithaca, NY 14850--8657
NSF Award
2151149 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research Phase I project is to advance personalized medicine for improved treatment and prevention. This project advances a technology to identify novel cancer-specific antigens and advances cancer immunotherapy. The proposed technology can be applied to cells in culture and solid tissues obtained by needle biopsy. Furthermore, it can be engineered into an easy-to-use system for a wide range of scientists and healthcare professionals.
The proposed project aims to develop a versatile and cost-effective library construction technology that enables protein translation monitoring on a variety of biological samples. High throughput sequencing of RNA molecules requires the preparation of libraries. Current methods for library construction utilize adaptor ligation to the 5'- and 3'- ends of the target RNA molecules. However, ligation of adaptors is time-consuming and low-efficiency, and the resulting cDNA libraries are contaminated with cross- and self-ligation adaptor byproducts and require additional purification steps. The proposed technology relies on a novel enzyme system capable of 5’ adenylation and 3’ polyadenylation of RNA fragments. To increase the efficiency of RNA adenylation at both ends, a fusion enzyme with high enzymatic efficiency is engineered. Moreover, to reduce ligation time and increase efficiency, pre-orientated oligonucleotide adaptors will be specially designed. This project focuses on the removal of the sucrose-based centrifugation and the automation of the proposed technology, which have not been conducted previously in ribosome profiling. The proposed technology can become a method of choice for broad ribosome profiling in both laboratory and clinical 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. -
FEMTOMAG, INC.
STTR Phase I: Low-Cost Quantitative Lateral Flow Assay for Cytokine Release Syndrome Detection in Point-of-Care/Point-of-Need Settings
Contact
1204 TALL PINES DR
Friendswood, TX 77546--4624
NSF Award
2224174 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2022 – 08/31/2023 (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 a biosensing technology that may enable highly sensitive, quantitative, point-of-care diagnostics. Once validated, the proposed biosensor, disposable sensor chips/cartridges, and electronic readout modules can be readily mass-produced using existing medical device manufacturing capacities. The technology may have an impact on the health and welfare of patients. The immediate goal is to examine interleukin protein monitoring for early detection of cytokine release syndrome, a potentially life-threatening health complication that develops in patients undergoing immunotherapy treatment, organ transplant, infectious disease, sepsis, etc. Additional applications include early detection of cancers or cancer recurrence, dry eye disease, existing and emerging infectious disease, biothreats, etc.
This Small Business Technology Transfer (STTR) Phase I project is a proof-of-concept demonstration of a low-cost, magnetic biosensor technology that may enable analytical laboratory capabilities for reliable biomarker detection and quantitation at the point of care. The proposed biosensor will be adapted for quantitative detection of interleukin proteins in blood for early diagnostics of cytokine release syndrome. The technology integrates magnetic sensing into the ubiquitous lateral flow assay (LFA) format (used in pregnancy tests) utilizing magnetic nanoparticles as reporters of biomolecular interactions. The tests are well-suited for point-of-care applications where rapid and convenient access to low-cost diagnostic tools helps improve patient care. The rationale for this project is that the proposed biosensors can provide clinically-relevant quantitative data rivaling those of state-of-the-art laboratories while preserving the advantages of LFA tests in terms of low cost and ease of use. The disposable chip with its clam-shell design builds upon the usual LFA cassette design. The disposable chip will be produced and assembled from low-cost printed circuit board (PCB) manufacturing and is expected to add only cents to the cost of an LFA test. A low-cost portable reader capable of ultrahigh sensitivity quantitative readings will be built from conventional off-the-shelve electronic components.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FERMI ENERGY, INC.
STTR Phase I: Manufacturing nickel and cobalt-free cathodes for high-energy and low-cost lithium-ion batteries
Contact
2200 KRAFT DR
Blacksburg, VA 24060--6704
NSF Award
2233272 – STTR Phase I
Award amount to date
$275,000
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to facilitate the adoption of battery electric vehicles in the US by securing the supply chain, reducing battery cathode cost, and enhancing US-innovated battery manufacturing. This project will address the several challenges facing the US battery industry. First, the state-of-the-art lithium-ion battery cathode materials use scarce and expensive elements, such as cobalt and nickel. Second, the US battery manufacturing capability needs to be improved in order to meet the rapidly growing demand, cathode materials production is especially important. Third, current lithium-ion battery cathode manufacturing involves costly liquid and gaseous waste management. The proposed technology will create fundamentally new ways to produce next-generation cathodes for American electric vehicles. This project can significantly impact the battery field since the proposed new cathode technology is expected to result in a major cost reduction per electric vehicle battery pack. Advances in novel cathode chemistries and manufacturing processes offer new opportunities for the US to establish the leadership in cathode innovation and manufacturing.
This project develops a fundamentally disruptive technology to enable the use of low-cost, cobalt- and nickel-free oxide cathodes in high-energy lithium-ion batteries. The dry manufacturing technology will be uniquely combined with new materials development to enable stable battery cycling with a 700 Wh/kg specific energy at the cathode materials level. The technology is compatible with mainstream lithium-ion electrolytes and anodes, which makes full-cell integration feasible and practical at the commercial scale. The research and development objectives include: (1) design, manufacturing, and characterization of new cobalt- and nickel-free oxide cathode chemistries with abundant and low-cost elements, (2) develop cathode electrodes with controllable physical properties based on an all-dry electrode preparation process, and (3) integrate the graphite anode and electrochemical measurements under various practical testing conditions. This project proposes to combine materials synthesis and electrode powder mixing and to avoid the costly materials storage and handling between cathode powder production and cathode electrode manufacturing. The successful development of the technology will enable low-cost, high-energy, dry-processed, and US-manufactured battery cathodes for more affordable and reliable electric vehicle batteries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FIELD PROPULSION TECHNONOGIES INC.
SBIR Phase I: Advanced Propellant-less propulsion system for spacecraft based on the Unresolved Longitudinal Ampere Tension Forces in Conductors
Contact
4824 S ELK ST
Aurora, CO 80016--5815
NSF Award
2213139 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 develop an advanced propellant-less propulsion system and compact ultra-high-energy storage devices using the unresolved Ampere Tension forces in composite conductors. Currently, there is no viable propulsion system for satellites and interplanetary spacecraft that only use the spacecraft power bus to generate propulsion. Plus, no energy storage devices can directly use Ampere Tension forces in solid non-elastic materials to store energy or strengthen the material. Currently, feasible methods for launching spacecraft into an orbit require large amounts of stored energy as combustible fuel to get spacecraft into space. These limitations have restricted the access to space to multi-billion-dollar corporations and nation-states. This technology that results from this research could transform how we get into space and store energy using compact, lightweight ceramic materials. This technology could open space to individuals, small companies, and small research groups that are now restricted from doing research in space due to the high cost of getting spacecraft into space and storing the energy for space travel.
This Small Business Innovation Research (SBIR) Phase I project proposes researching the conditions that allow the unresolved Ampere Tension forces to be observed and exploited to create propellant-less propulsion and energy devices with almost infinite energy storage capacity. The research proposed in this project is to determine under what condition Ampere Tension forces are present and how these forces can be used to create a spacecraft propellant-less propulsion and energy storage devices that are not limited by a chemical reaction in materials electrolytic. The project aims to determine the conditions that allow the unresolved forces to be observed and used to create an external force on a conductor directly from the electric current and the conditions that these same forces can store electrical energy directly into a ceramic material directly from an electric current. The innovation proposed here is to create a brand-new energy technology as a spacecraft propulsion device and energy storage device that operates only on electricity and does not need any fuel or chemical energy. In so doing, this innovation could transform current methods of launching into space and energy storage methods. Satellites using this technology would not need to include volume for fuel or chemical batteries and could use that extra space to increase the functionality of the spacecraft. Similarly, interplanetary spacecraft could maneuver using just the power bus and operate for decades without limiting the mission due to limited propellant supplies or energy storage limitations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FILTRAVATE, INC.
STTR Phase I: Developing antifouling viral clearance membranes to enable efficient monoclonal antibody (mAb) processing
Contact
3655 RESEARCH DR BLDG B RM 111
Las Cruces, NM 88003--1239
NSF Award
2212947 – STTR Phase I
Award amount to date
$255,982
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this small Business Innovation Research (SBIR) Phase I project is to enable a scalable, high-volume Tangential Flow Filtration (TFF) system for monoclonal antibody (mAb) manufacturing applications. The primary benefactor of this technology is the biomanufacturers and bioprocessing integrators. However, the cost of goods (COGs) savings provided to the collaborating industry partners could be far-reaching. This technology could enable efficient (and lower cost) production of lifesaving drugs and vaccines. Reducing overall cost will potentially make these life-saving therapeutics more accessible and affordable to all people regardless of socioeconomic status. The unique, sustainable, and cost-effective membrane fabrication approach offered in this proposal could improve the membrane manufacturing industry by producing membranes containing narrow pore size distribution and high fouling resistance. Many industries beyond bioprocessing stand to benefit from high-performance membranes, including food and beverage manufacturers, water treatment facilities, healthcare providers, and other manufacturing enterprises.
The proposed project is to develop a virus filtration membrane using a synthesis process that is more sustainable and cost-effective than the conventional process. Pharmaceutical manufacturers rely upon membrane ultrafiltration due to its advantages of scalability, replication, and user experience. However, membrane antifouling can hinder a full realization of continuous bioprocessing production efficiencies. Membrane fouling causes protein deformation and loss, limiting membrane applications for efficient virus/protein separation. The proposed membranes have a narrower pore size distribution and stronger fouling resistance without using any post-production processes. Additionally, the proposed membrane fabrication technology simplifies the membrane production process and reduces the manufacturing costs by eliminating the use of solvents, eliminating the need for solvent reclamation and recycling. The adoption of the novel membrane product into existing bioprocessing systems could advance manufacturers’ ability to adopt a more efficient continuous production method providing potential advantages such as smaller facility footprints, lower investment costs, increased flexibility, and lower processing 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. -
FIRST WATER TECHNOLOGY CO.
SBIR Phase I: Compact, low-maintenance water treatment plant
Contact
5321 S CHARITON AVE
Los Angeles, CA 90056--1354
NSF Award
2212882 – SBIR Phase I
Award amount to date
$255,849
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of a low footprint drinking water treatment plant (WTP) suited to facilitate much-needed upgrades to the nation’s water infrastructure. Today’s drinking water treatment systems are suffering from high volumes of generated waste (~100,000 tons sludge per typical plant per year) and high maintenance requirements and costs (4x/year week-long clarifier decommissioning for cleaning). The aging infrastructure of many of the nation’s water treatment plants has left millions of Americans with inadequate drinking water. This situation, paired with the aging and shrinking water operator workforce, translates into a growing threat of water supply interruptions and noncompliance. Owing to its small footprint and low energy and maintenance demands, the proposed technology would deliver an easily implementable solution that could be adopted by communities and water systems around the world, even in remote areas. Successfully developed, the WTP will offer a unique economic opportunity to meet critical global sustainable development goals and promote human health and welfare. This technology will lower the barriers to upgrading the nation’s water infrastructure, creating jobs through the introduction of long-delayed upgrades through plant implementation.
Elements of the innovation under development for the proposed water treatment plant include a self-modulating feedback/feedforward controller driving automated coagulant dosing, which is paired with a high-efficiency hydraulic flocculator that leverages turbulent flow to promote floc formation while remaining free of failure-prone moving parts; a self-cleaning clarifier fitted with settling plates and a sludge blanket system for efficient contaminant removal; a stacked sand filter that decreases the hydraulic loading rate for a given flow and bed volume, resulting in improved stability of the deposited particles (i.e., reduced shear and particle breakthrough); and a continuous sludge dewatering and treatment system that decreases the volume of produced sludge while also providing a continuous waste stream for further processing. While early efforts have established a proof-of-concept demonstrating operations at 50% less energy demand than conventional systems, continued research and development to improve system performance and autonomy are needed. In line with this effort, the Phase I effort will focus on: 1) development of an automated control system for precise coagulant dosing; 2) design modification to minimize waste stream volume; and 3) design and construction of a pilot plant with 15 gallons per minute capacity, suitable to meet the water treatment needs of communities of ~300 people.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FLOBIO LLC
SBIR Phase I: Automated DOAC assay to determine coagulation status in emergent care
Contact
3401 GRAYS FERRY AVE BLDG 176-1016
Philadelphia, PA 19146--2701
NSF Award
2035983 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2020 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial impact potential of this Small Business Innovation Research (SBIR) Phase 1 project is a diagnostic product that addresses patient safety and clinical decision-making for physicians managing patients taking Direct Oral Anticoagulants (DOACs). DOACs are becoming the preferred drugs to reduce the risk of blood clots that can lead to significant adverse events, such as stroke. However, DOACs are part of the leading class of drugs implicated in adverse event-related emergency department visits. These adverse events place a significant burden on the healthcare system in the form of transfusions, exposure to blood products, platelet repletion, reversal therapies, and additional complications (e.g. infection, sepsis, multiple organ failure) driving longer hospitalizations, higher mortality rates, and escalating healthcare costs. In emergency situations, the rapid detection of DOAC anticoagulation is needed when planning for urgent care for surgery, serious trauma, drug overdose, emergency procedures, or monitoring for drug accumulation in cases of renal and liver failure. This project proposes a diagnostic at the point of care. With an estimated 21 M patients globally taking DOACs, this technology could significantly reduce the $2.5 B in costs related to treating and correcting adverse events caused by the absence of DOAC information in emergency care situations.
This Small Business Innovation Research (SBIR) Phase I Project will demonstrate the feasibility of a point-of-care (POC) diagnostic chip for emergency room clinicians to manage bleeding risk and avoid overuse of drug reversal therapies, thereby improving patient outcomes while reducing healthcare costs. Currently there is no approved rapid diagnostic POC test that accurately identifies the type of DOAC drug a patient is using, nor how much of the drug is in the patient’s blood. An integrated microfluidic cartridge is proposed developed to manage blood distribution within the device, mix the blood with DOAC detection reagents, and provide an integrated assay result that evaluates the three important clotting factors in clot formation (fibrin/thrombin/platelets). The technology is unique in that, unlike other coagulation tests, it re-creates the blood clotting physiology, and characteristic blood flow, that happens within the body. With DOAC-reversing drugs, the diagnostic can determine DOAC type (Factor Xa or Factor IIa), and the level of DOAC in the blood, allowing emergency room physicians to make more informed care decisions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FLUIDION US Inc.
SBIR Phase I: Automated In-Situ High-Resolution COVID-19 Wastewater-Based Epidemiology
Contact
396 S SAN MARINO AVE
Pasadena, CA 91107--5050
NSF Award
2041400 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2021 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact of this SBIR Phase I project addresses the monitoring needs via wastewater-based epidemiology of current and emerging viruses that pose high risks to public health. With the rapidly evolving nature of the pandemic situation and the recent emergence of the coronavirus variants, one common concern is that the virus variants are more contagious than their predecessors, and will likely spread quickly within communities without early detection and warning. Other concerns are that future mutations may not be covered by existing vaccines, in which case early monitoring through high resolution wastewater-based epidemiology will become one of the only effective means of providing early alerts of the presence of such mutated virus variants within local communities. With a wide adaptation of the proposed instrumentation by municipalities, large and small communities such as college campuses and senior care facilities, the project enables the early detection and monitoring of the current coronavirus and its variants during the pandemic. The technology can also be extended to other emerging viruses with risks of community spread in the years to follow, not only in wastewater but also in widespread environmental and recreational water quality monitoring.
The proposed project is a highly-optimized reverse transcription quantitative polymerase chain reaction (RT-qPCR) approach for in-situ sampling and analysis, and the realization of a corresponding instrumentation platform that is applicable to the early detection and monitoring of different viruses, including the current coronavirus (SARS-CoV-2), its variants, and other emerging viruses. The proposed technology aims to reduce the time-to-result compared to current wastewater-based epidemiology approaches while minimizing cost and logistics. The effort will include the testing of several protocols that are amendable to adaption for automated in-situ SARS-CoV-2 measurement, followed by the selection and optimization of the most suitable one. The protocols will be subsequently tested and validated using spiked samples, along with appropriate positive and negative controls. The approach will implement, for the first time in an automated device, the latest advances in molecular biology protocols, such as extraction-free single-step RT-qPCR. The project strives to achieve the first in-situ RT-qPCR available, with the potential to completely revolutionize the fields of wastewater-based epidemiology, general environmental testing and source tracking.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FRESHKUBE INC.
SBIR Phase I: Adaptable Refrigeration Cycles for Smart Mini-Containers
Contact
2128 S PASEO LOMA
Mesa, AZ 85202--6485
NSF Award
2212910 – SBIR Phase I
Award amount to date
$255,981
Start / end date
12/01/2022 – 11/30/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project includes reductions in food waste, energy use, and carbon emissions by developing a highly efficient and adaptable system for refrigerated transport. Mini-containers, which are small, insulated boxes with environments controlled by a central driving unit that contains a refrigerator and other environmental controls are proposed. The technology may increase the economic feasibility of small farms by allowing them to target a more resilient, efficient, and potentially carbon-neutral cold supply chain. The potential impact of the research includes improved availability of nutritious food for the general population and mitigation of negative environmental effects of cold logistics. Additionally, mitigating food waste will create savings up and down the supply chain.
Two key technical challenges are addressed in this research. The first area has, as its main objective, the development of a volume-adaptable refrigeration system that allows for the efficient operation of several levels of control to best adapt to high levels of cooling capacity needs. The second area of research corresponds to the development of the methodology and solutions algorithms to exercise a hybrid control strategy for the optimal scheduling operation of the refrigeration system. The archetype refrigeration system would be subject to constraints imposed by the heterogeneous loads stored in the different special storage and transportation units known as mini-containers which receive cooling and other environmental services. This technology will allow for efficiently aggregating, storing, disaggregating, and distributing fresh products in the mini-containers. The mini-containers will allow the emergence of efficient cold logistics for small loads by enabling the capacity of large transportation containers to be split among multiple conveyances. The proposed solution will also make it possible to convert almost any truck into a refrigerated truck and any warehouse into a cold storage facility, supporting the emergence of sharing economies in cold 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. -
FRONTLINE BIOTECHNOLOGIES INC.
SBIR Phase I: A Versatile Nucleic Acid Collection and Purification Technology for Wastewater-Based Epidemiology
Contact
2143 FOLWELL AVE
Falcon Heights, MN 55108--1306
NSF Award
2224172 – SBIR Phase I
Award amount to date
$275,000
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide private and public stakeholders with new technological tools to better monitor and predict pandemics. This project is expected to modernize the tools used today by private and public laboratories to collect and purify pathogens, particularly human coronaviruses from community wastewater, for testing and diagnostic purposes. The new technological tools are expected to simplify the workflow, reduce costs and time, and enable the prediction of COVID-19 outbreaks and other pandemics several weeks before observing clinical cases. Such early prediction would provide the public and government agencies with important data and sufficient time to take preventive measures. The technological products of this project are expected to empower the growing number of companies and laboratories offering wastewater-based epidemiology (WBE) services and help establish WBE as a routine, cost-effective and reliable tool for public health monitoring.
This Small Business Innovation Research (SBIR) Phase I project will address a major technological barrier for the detection of viruses such as SARS-CoV-2 in wastewater. Commercially available nucleic acid collection and purification kits are designed for clinical samples with small volumes. These kits are not generally used for large wastewater volumes where the virus is present at low concentrations. As a result, current processes are time-consuming, and result in the recovery of less than 30% of viruses and nucleic acids, significantly reducing the sensitivity. The goal of this SBIR Phase I project is to demonstrate the feasibility of a novel virus and nucleic acid collection and purification technology from wastewater. Specifically, the project tasks aim at enhancing understanding of virus properties, particularly human coronaviruses in wastewater and their interactions with filter media. The project’s innovative approach is to design a streamlined workflow that includes all the steps from sample collection to detection, in a single disposable cartridge containing novel filters with high affinity to viruses. This development is expected to enhance viral and nucleic acid recovery in wastewater to over 90%, while reducing costs. The developed tools will be independently tested and evaluated by third-party laboratories to confirm their 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. -
GENCORES LLC
SBIR Phase I: Rapid and scalable production of high-performance 3-dimensional foam cores
Contact
1529 CAMBRIDGE ST APT 2
Cambridge, MA 02139--1012
NSF Award
2136727 – SBIR Phase I
Award amount to date
$256,000
Start / end date
11/15/2021 – 11/30/2023 (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 reduce the weight and increase the efficiency of today's ground vehicles. Replacing steel with structural composites, a foam core wrapped in carbon fiber and resin, is a key strategy to reduce vehicular structural weight and to increase efficiency and safety. Current foam cores often exhibit low performance and are costly to produce for non-planar designs. As a result, three-dimensional cored composites remain cost-prohibitive for mass-manufactured automobiles and relegated to niche, high-performance vehicles. Improving core performance and fabrication processes will unlock high volume manufacturing of structural composites and enable manufacturers to increase the efficiency of their fleet by up to 40% throughout the next decade. Such a step-improvement in manufacturability can also accelerate urban air mobility vehicles and electric aircraft development and deployment.
This Small Business Innovation Research (SBIR) Phase I project will support the development of a novel, high throughput additive manufacturing technology for three-dimensional, thermosetting polymer foam parts featuring unique, specific mechanical properties (strength-to-weight or stiffness-to-weight ratios). Combining a unique 3D printing nozzle for thermosetting polymers, material science, and robotics enables unlocking on-demand and the rapid production of net shape, complex foam parts to be incorporated into existing supply chains. The project will develop and test novel resin formulations, optimize material synthesis and deposition, and enable the control of foam microstructure in situ. Using this latter feature, coupled with topology-optimization software, the project will produce the first foam metamaterials. These unique metamaterials will be mechanically and thermally tested using American Society for Testing and Materials standards to ensure the processing meets industry standards.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GEOLABE LLC
SBIR Phase I: Autonomous Interferometric Synthetic Aperture Radar (InSAR) for surface deformation monitoring
Contact
1615 CENTRAL AVE
Los Alamos, NM 87544--3018
NSF Award
2213289 – SBIR Phase I
Award amount to date
$254,707
Start / end date
03/01/2023 – 02/29/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enable the global autonomous detection of surface deformation. Measuring Earth surface deformation is fundamental to detect and analyze surface and subsurface changes due to anthropogenic activity, with a myriad of industrial applications that includes the monitoring of oil and gas extraction fields and storage reservoirs, mining operations, carbon dioxide sequestration, and/or infrastructure integrity. Illustrating the economic and social impact of its uses, the market for analyzing Interferometric Synthetic Aperture Radar (InSAR) data is expected to double within 5 years. Beyond the dramatic economic growth of InSAR, its far-ranging applications have broad social and scientific impacts, in particular related to natural hazards and climate change. Advances in InSAR processing and improved signal-to-noise ratios will translate into improved monitoring of earthquake activity, landslides, water supplies, deforestation, floods, ice sheets, etc.
This Small Business Innovation Research (SBIR) Phase I project aims at tackling the lack of automation in InSAR processing and improving detection thresholds in InSAR time series analysis. While the technique can potentially measure millimeter-scale changes in deformation over periods of days to years, atmospheric effects can wreak havoc on repeat-pass InSAR interpretation by introducing errors that may mask small surface deformations. These effects, which are fundamentally due to pressure, temperature and relative humidity variations in the troposphere, can lead to errors that are larger than most of the deformation signals of interest. Current algorithms are not suited for automated, large-scale monitoring without a priori data because they require time-consuming manual intervention, and the final product requires exhaustive expert interpretation. Through the development of machine learning and artificial intelligence methods this project aims at: (i) further automating and accelerating the processing of InSAR time series, via the automation of some key sections of the processing pipeline that still rely on extensive and costly human intervention; and (ii) developing a new methodology to generate InSAR time series, that is robust to noise and allows for a finer temporal and spatial resolution compared to the state-of-the-art.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GODWIT KEY COMPANY
SBIR Phase I: Key 360 Species Survival Database (K3SS)
Contact
5015 CAPE MAY AVE UNIT 309
San Diego, CA 92107--2575
NSF Award
2125285 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 06/30/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase 1 project is to create a more collaborative and efficient way for scientists to combat species loss. The project proposes to create the a centralized database for a complete view of all of the issues affecting species survival which can be tracked in real-time. This project will allow scientists to expedite their research while offering the public more transparency about environmental data. The company aims to provide a high level of transparency about what factors are directly and indirectly affecting species survival and provide actionable steps that businesses, organizations, governments, and individuals can take to make a difference that they can see in real-time, and model well into the future. They seek to democratize conservation and bring new skills, people, and funding streams to the science and practice of conservation.
This SBIR Phase 1 project consists of the development of a comprehensive database, which exists in the cloud, that encapsulates all of the factors that affect biodiversity. The project will result in a robust data system that can host and pull environmental data from all over the world, track the populations of the world’s species, and measure conservation support and influence from the general public. The project will also allow users to query data in the cloud and use artificial intelligence (AI) capabilities to further their research. The project will track both scientific data and data about support efforts from conservation organizations and the general public. The tracking of these factors will inform decision-making bodies on what methods are most effective in preserving biodiversity. The core technical risk to be addressed through Phase I research and development is standardizing diverse qualitative and quantitative data so that they can be used together.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRAVEL CAPITAL LLC
SBIR Phase I: Development of an AI PCB Prototyping Service called FlashPCB
Contact
1019 CLINTON ST
Philadelphia, PA 19107--6016
NSF Award
2212989 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project is to create an artificial intelligence-powered printed circuit board assembly (PCBA) service that facilitates innovation and economic growth in the United States. Prototyping PCBAs is a key element in the innovation process for all electronics from consumer goods to medical devices, but current PCBA prototyping services are limited by manual steps and supply chain shortages. The artificial intelligence innovation of this project will save the customers time through strategic automation, shortening innovation timelines, and bringing new products to market faster. Currently, China and other Asian countries are still dominating the PCBA market share, serving many customers from the United States. There is an opportunity to provide high-quality, cost-competitive manufacturing in the United States to better serve the market and meet the rising demand for PCBAs. Additionally, investment in domestic manufacturing will strengthen electronic manufacturing capabilities, reduce dependence on foreign markets, and protect intellectual property.
The technical innovation of this project is the development of two artificial intelligence algorithms that work together to determine the optimal selection of components to be mounted on a customer’s printed circuit board. The first algorithm reads the design file and identifies the properties of the components that the user has specified for their design. The second algorithm takes these properties as its input and selects in stock parts for the components in the design which will then be mounted onto the printed circuit board. This is a cost and time saving innovation that uses state of the art artificial intelligence algorithms and encodes electrical engineering principles. The key objectives for this project are to understand the types and combinations of components that our customers are likely to use in their designs, to define and test the algorithm for component property identification, and to define and test the algorithm which will choose the optimal components used for the manufacture of PCBAs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRID MODERNIZATION SOLUTIONS, L.L.C.
SBIR Phase I: IoT-Enabled Intelligent Data Replication for Secure Redundant Monitoring
Contact
1960 S WASATCH DR
Salt Lake City, UT 84108--3326
NSF Award
2213221 – SBIR Phase I
Award amount to date
$248,975
Start / end date
09/15/2022 – 05/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Phase I project is to increase the visibility and availability of data used for control and automation of critical infrastructures. This research proposes the development of a novel technology that takes advantage of flexible, low cost, and low power internet of things (IoT) devices to replicate, transmit, and analyze relevant monitoring and control data. Blackouts in the U.S. cause tens of billions of dollars in outage cost annually. This technology will advance the nation's energy safety, security, and economy by improving the capabilities of critical infrastructure systems to respond to blackouts caused by anomalous events such as natural disasters (e.g., hurricanes, winter storms) and localized faults or cyberattacks. Therefore, the technology developed in this project will decrease restoration time and provide real-time defense against cyberattacks, reducing the loss of electricity to critical users such as hospitals and governmental facilities, and saving billions of dollars.
This Small Business Innovation Research (SBIR) Phase I project will advance the scientific knowledge required to enhance the resilience of critical infrastructures through the integration of IoT networks, monitoring and control technologies, and data analytics. Advances in the use of IoT devices for critical infrastructures integrated with security mechanisms will facilitate the technology transition of the current critical infrastructure. This project will explore and design novel mechanisms for data processing, light-weight encryption, and attack detection. The technology developed in this project will have widespread applications in monitoring and control, not only in the electricity sector, but also in many other critical infrastructures such as water, oil, and gas. A proof of concept will be developed to validate the feasibility of the proposed architecture and algorithms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRIDIRON ROBOTICS LLC
SBIR Phase I: Developing an Automated Outbound Packing System
Contact
31 OAK AVE
Chalfont, PA 18914--0001
NSF Award
2223089 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2023 – 01/31/2024 (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 the fast and efficient loading of parcels into shipping containers ranging from small delivery vans to maritime shipping containers. This project will focus on demonstrating the feasibility of an algorithmic approach and robotic development. The technology is a step towards creating a fully autonomous system with expanded robotics capability to further enhance the efficiency and speed of outbound shipping for customers. Over 3,000 parcels are shipped every second. However, in the U.S., one out of every four trucks is empty, two are less than 50% filled, and only one is filled over 50% capacity. Initial projections indicate that the technology under development could decrease trucking costs by 20%, reduce loading costs by 70-80%, and decrease loading time by 30%, all while meeting the demands of peak shipping seasons. Overall, increasing the density of parcel shipping will reduce greenhouse gas emissions (400 tons/per truck/per year), reduce traffic congestion, and enable smaller businesses to compete with large organizations by reducing their logistics and shipping operating costs.
This Small Business Innovation Research (SBIR) Phase I project will focus on advancing a bin packing algorithm to minimize void space in outbound shipping containers. The 3-Dimentional Bin Packing Problem (3D-BPP) is a classic Nonlinear Programming (NP)-hard problem that has been studied for decades. To solve the problem, an effective and easy-to-implement constrained, quantum accelerated, deep reinforcement learning model is being developed. Monte Carlo Tree Search is an unsupervised, heuristic search algorithm technique in which the learning agent learns to predict the expected value of a variable occurring at the end of a sequence of states. Deep reinforcement learning (DRL) extends this technique by allowing the learned state-values to guide actions which subsequently change the environment state. A proof-of-concept assessment showed that the learned strategy meaningfully outperforms the state-of-the-art methods. Outcome success metrics for this project are >90% utilization rate, sub 24 hours of model training time, and >2500 parcels/hour for any given data set. This foundation will be expanded by integrating many unique box sizes, exploring model performance in the face of broader circumstances (e.g., lookahead and stacking parameters, General Processing Unit (GPU) vs quantum training), and developing of a robotic gripper to enact algorithmic output.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GYROPALM, LLC
STTR Phase I: Virtual Interfaces using Multi-Protocol, Augmented-Reality Activation-Based Control Transfer
Contact
14429 CATALINA ST
San Leandro, CA 94577--5515
NSF Award
2151524 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (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 provides virtual interfaces that can be dynamically customized to address the challenge of user adoption in augmented reality (AR) products. This project overcomes previous limitations for AR such as the lack of interoperability, user-acceptance, scalability, and application-aware user intent recognition. While the AR market is projected to grow, wearable collaboration has unexplored potential. Users empowered by this project may be able to easily collaborate alongside skilled experts as well as robotic interfaces in the same medium. Through contextually-aware dynamic controls, manufacturing businesses can lower the risk of human-error while increasing fulfillment capabilities, as employees working from home can stay physically connected and remain engaged with minimal compromise. The AR innovation proposed in this project has application across multiple industries, including manufacturing, training, and emergency simulations.
This Small Business Technology Transfer (STTR) Phase I project aims to create a framework for scalable experimentation of virtual interfaces that empower users to search, tag, and store meaningful data using gesture interactions in a secure and private manner. This project seeks to provide context-based, hands-free interaction with wireless devices while minimizing the need to set up sensors (such as optical components or microphones) in controlled environments and providing visual feedback and accessibility to the end user. A wrist-worn wearable captures pre-trained gesture data, and a pair of augmented reality (AR) glasses identifies and analyzes an object within the context of said gestures to control a mechatronic device, such as a robot, to perform occupational tasks. This dynamic process uses factors such as the user’s gaze area, physical location, and computer application. The improvement upon gesture control may allow a separate visual unit, such as the AR glasses, to wirelessly receive and display the gesture intents and perform contextually-aware, meaningful interactions with a clear distinction across a plurality of devices or digitally tagged objects associated with a specific use-case.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HARPE BIOHERBICIDE SOLUTIONS, INC.
SBIR Phase I: Safe control of herbicide-resistant weeds with a novel natural bioherbicide platform
Contact
501 COLE ST
Raleigh, NC 27605--1207
NSF Award
2223639 – SBIR Phase I
Award amount to date
$274,927
Start / end date
02/15/2023 – 10/31/2023 (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 providing solutions to farmers who are facing the culmination of decades of herbicide resistant weed species evolving from applications of synthetic herbicides. Creation of herbicides which are effective, naturally produced, scalable, and deployed using the current agronomic practices could alter the foundations of crop production in the United States and around the world. In view of the projected 8% annual increase in global food and agriculture market, shrinking areas under cultivation that lead to the need for higher productivity per acre, and increasing demand for nutritional food items, the need for sustainable alternatives to current synthetic herbicides that do not promote herbicide resistant weeds is becoming clearer. Widespread adoption of the proposed technology is expected to benefit farmers and crop producers reducing societal strain, financial burden, and environmental stress from crop losses due to herbicide resistant weeds by eliminating these weeds through an environmentally safe method, without the use of excess fuel, time, equipment, and synthetic herbicides.
The intellectual merit of this project is in developing a novel natural herbicide product that, when applied to herbicide resistant weeds, will cause seed or plant cell's membranes to degrade and lose integrity. Thus, the novel product is intended to work both as pre-emergent weed prevention and post-emergent weed control herbicide. The product will be an environmentally safe blend of natural plant extracts and excipients. The herbicide formulations will be sprayable onto soil or onto plant leaves and stems. The cost and time needed to initially screen herbicide rates, outcomes, and best practices typically is many years. The greenhouse screening approach takes months and provides valuable information to ensure that field trials, which are more expensive and impacted by changes in weather, are efficient in cost and outcomes. This project will initially focus on greenhouse validation of weed control of the most resistant weeds known in different geographical locations in the U.S. Dose response data for 50%-to-90% inhibition control/efficacy of herbicide resistant weeds will provide the information to develop a herbicide use label, directions for best practices, and good stewardship by using only the amount of herbicide needed for control without overuse.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HELIOS POMPANO INC
SBIR Phase I: Extremely Low Frequency Characterization of High-Risk Lightning
Contact
2226 N CYPRESS BEND DR
Pompano Beach, FL 33069--4486
NSF Award
2223166 – SBIR Phase I
Award amount to date
$250,109
Start / end date
03/01/2023 – 08/31/2023 (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 includes a notable reduction in the area burned by lightning-initiated wildfires. Understanding which lightning strikes are capable of igniting wildfires is critical as in the Western U.S. lightning-initiated wildfires are responsible for over 70% of the area burned in these environmental catastrophes. Globally, wildfires are responsible for 6.45 gigatons of carbon dioxide (CO2) emissions annually (18% of total emissions). Detecting high risk lightning strikes (those capable of igniting wildfires) may also significantly reduce losses of life, wildlife, habitats, property, and forests as currently lightning-initiated wildfires in the US devastate 4-6 million acres per year. The reduction of wildfires can reduce large evacuations and smoke-related health conditions, thereby improving the health and welfare of the American public. Both people and businesses would benefit from lower insurance rates due to the decreased risk of wildfire damage. Large wildfires are a constant concern to more than half of the mission assurance priority military installations due to routine testing and training activities that are significant ignition sources. The proposed project may also address military ignition concerns.
Wildfires start when a long continuing current (LCC) strikes the ground at a location where the environmental conditions are conducive for fire ignition. LCCs are those that last for 40 ms or longer and are essentially responsible for excessive heating. The transformative aspect of this research lies in the ground-based characterization of Extremely Low Frequency (ELF) lightning emissions to identify LCC strikes, with a 95% target detection efficiency and with 40 m accuracy. While for most lightning strikes the current ceases to flow after tens of microseconds, a small portion of lightning strikes (less than 10%) contain a continuing current that lasts thousands of times longer, from tens to hundreds of milliseconds. This can be viewed as a quasi-stationary arc between the cloud charge source and the ground and is detectable through electrostatic field changes and ELF emissions. A secondary innovative feature lies in the use of machine learning algorithms to pinpoint high risk lightning ignitions by analyzing the environmental conditions at the LCC strike location. This technology can identify a fire in seconds, unlike the present heat or smoke identification systems that can take hours or days to identify a fire.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HEYKIDDO, LLC
SBIR Phase I: A Machine-Learning Tool for Social-Emotional Learning, Development, and Intervention for Remote or Hybrid Child Development Support (COVID-19)
Contact
123 BECK ST
Philadelphia, PA 19147--3417
NSF Award
2039090 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 04/30/2023
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to detect social-emotional issues in children (ages 5-12) for early intervention. A growing trend in juvenile mental health concerns was exacerbated by the recent COVID-19 pandemic and the associated disruption in child development. This project proposes a machine learning (ML) system that learns from interactions with the child and parent independently and can detect potential social-emotional concerns. The ML system enables personalized evaluation and monitoring outside a clinical setting in a remote or hybrid context.
This Small Business Innovation Research (SBIR) Phase I project advances algorithms for integration into a social-emotional skill building curriculum. The project proposes: 1) User segmentation based on a comprehensive assessment of social-emotional functioning, 2) Correlation of the relevancy and effectiveness of modules to segmented users, and 3) Collection of information to identify social emotional deficits (red flags). These activities enable a feedback loop to learn and deliver recommendations for each child-parent dyad, personalizing learning in real-time. These algorithms learn from behavioral, social, and emotional inputs from both the parent and child when they engage with the technology. The system will also detect red flags correlated with social and emotional deficits, promoting early intervention.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HYFI LLC
SBIR Phase I: City-scale flood mapping using real-time sensor data
Contact
3648 FREDERICK DR
Ann Arbor, MI 48105--2852
NSF Award
2223128 – SBIR Phase I
Award amount to date
$274,391
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project addresses major fundamental knowledge gaps underpinning the ability to create accurate flood maps. This proposal will advance new knowledge on the use of advanced analytics for the estimation of floods, thus transforming the tools available to respond and plan for flooding. The working hypothesis of this proposal is that building-scale flood detection will be achieved through a combination of existing sensors and advanced analytics. This SBIR project will research and develop data-driven flood maps to support targeted flood response and long-term infrastructure planning. Using advanced analytics, existing sensor data will be spatially distributed to create real-time flood maps. The method will be validated using a highly dense sensor network in the Great Lakes region. The technical results of this project will yield unprecedented insights and measurements of uncertainty related to flood estimation at urban scales. The resulting real-time flood maps will allow stormwater managers to stay ahead of resident complaints, while saving lives and property by sending their crews to the most important locations. Improved flood maps will also allow stormwater managers to maximize the impact of long-term infrastructure investments.
The project's goal is to make all communities resilient to floods and climate change. To that end, this proposal will show how advanced analytics, driven by wireless sensing, will transform the ability of first responders to save lives, while helping stormwater managers maximize long-term infrastructure investments. The key innovation of this proposal is a data methodology, which will convert raw, spatially distributed sensor data into actionable, real-time flood maps. This data-driven technique will enable the first of its kind tool to detect floods at the scale of individual buildings, without requiring a sensor at every location.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HYSA FILLERS L.L.C.
SBIR Phase I: Multi-principal element alloy fillers for toughness enhancement in repair of Ni-base superalloy components
Contact
3346 S NELSON ST
Lakewood, CO 80227--5657
NSF Award
2208777 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project will be to improve safety and reliability, and to reduce operating costs, for gas turbine engines, a technology that impacts the daily lives of Americans by providing electric power and aircraft propulsion. Moreover, the national defense and energy industries are particularly reliant upon this technology, making this project highly impactful to these aspects of American welfare. Gas turbine engines contain nickel alloy blades, which must be carefully inspected and repaired at regular intervals to ensure failure never occurs unexpectedly, as in-service failures inevitably result in catastrophic engine damage. The integrity of repairs is largely dependent upon mechanical performance of filler alloys designed to patch cracks and cavities in the engine blades, which this project aims to improve through novel metallurgical design grounded in fundamental science. The scientific community at large will benefit from this research, as it will pioneer applied development for alloys within an emerging material class only two decades in the making. Designed alloys will have a commercial advantage over existing repair products due to superior performance and similar cost. This advantage will form the core of a successful business opportunity, which will generate revenue and provide STEM jobs as the business expands.
When designing new alloys from the ground up, rather than making modifications to existing alloys, limitless possibilities arise in multi-principal element alloys regarding which metallic elements to include and in what concentrations, necessitating a careful design strategy to efficiently identify candidates for a particular application. This project employs, as its strong technical innovation, a rigorous alloy selection strategy grounded in fundamental physics-based calculations to achieve this outcome. Equilibrium and non-equilibrium metallurgical thermodynamics calculations form the core of the selection strategy, with the aim to identify alloy compositions in which phases detrimental to mechanical performance are most likely to be suppressed. The project will design and test alloys to address cross-cutting industrial challenges – first and foremost, filling cracks in complex nickel-base superalloys designed for use in the harsh operating environment of a gas turbine engine. Much of the scope of work in this project will involve a vetting process to test whether the filler alloys can withstand these harsh conditions after crack repairs are performed. It will be of critical industrial relevance to validate their long-term metallurgical and mechanical viability in a simulated environment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Harvest Moon Automation
SBIR Phase I: Precision Weeder
Contact
19 FRANKLIN RD
Winchester, MA 01890--4014
NSF Award
2151435 – SBIR Phase I
Award amount to date
$250,665
Start / end date
09/15/2022 – 08/31/2023 (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 that it will help address the major concerns of climate change and sustainability of arable lands. The two common methods of weed control in the agricultural industry, herbicides and soil tillage, have a negative impact on the environment and soil sustainability. The health of the microbial environment in the soil is degraded by the use of herbicides and soil tillage. In addition, soil tillage exposes the organic matter in the soil to oxidation releasing carbon dioxide into the atmosphere. The goal for reducing the impact of agricultural practices on the climate is to sequester the carbon in the soil and not release it. At this time, the only option for weed control of mid to late stage weeds without the use of herbicides or soil tillage is manual labor, which is more expensive. The successful development and testing of the precision weeder extraction tool will give the agricultural industry an automated and cost effective option for addressing weed control while helping to reduce the carbon emission from the soil and protect soil sustainability.
This Small Business Innovation Research (SBIR) Phase I project involves the development of a robotic end effector extraction tool that can remove weeds without using chemicals or soil tillage. Advances in machine vision have made it possible to identify the individual plants in a field and determine which plant is the crop and which one is the weed. Presently, the two predominant methods used by automated weeders to kill the weeds is either by a targeted herbicide spray or soil tillage. Both of these methods negatively impact the environment and soil health. The proposed precision weeder will extract and dispose of the weeds without damage to the soil or environment. The economics of weeding will require the device to be simple, cost effective, reliable, and field hardened. Design and development of the extraction tool will use a new and novel method for removing the weeds with advances in design and actuation. The extraction tool will be tested in the field to determine its feasibility. Successful field trials will convince the customer and investor that this is a viable option for commercial automated weeding.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IBALLISTIX, LLC
SBIR Phase I: Handheld Ballistics Imaging Device
Contact
769 ROLLING VIEW DR
Annapolis, MD 21409--4654
NSF Award
2131437 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/15/2022 – 03/31/2023
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 supports law enforcement in solving crimes committed with firearms. In 2020, gun crime in the U.S. reached an all-time high with over 300,000 crimes committed and 40,000 people killed by a firearm, resulting in a $280 billion impact on the economy. There are approximately 800,000 law enforcement officers and 18,000 agencies in the U.S., and many of them have little to no access to forensics technology due to its cost and complexity. The total addressable market for this technology is estimated at $360 million per year in the U.S. This project advances hardware and software for next-generation portable ballistic devices, matching a spent shell casing to the weapon that fired it.
The intellectual merit of this project is to advance the collection and analysis of forensic ballistics data. This project will develop: (1) a ruggedized scanner to allow detailed, microscopic, three-dimensional imagery to be captured in the field; (2) an optical system that addresses the inherent difficulties and scattering challenges of scanning metals; (3) a user interface to upload images and receive leads, while preserving chain of custody and security; and (4) a cloud-based analytical system capable of comparing digitized/pixelated imagery to provide a “match” back to investigators.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ILAMBDA, INC.
SBIR Phase I: Scaling Up Open Innovation with Crowd Wisdom and Artificial Intelligence (AI) for Smarter and More Sustainable Fashion
Contact
251 W GARFIELD RD
Aurora, OH 44202--6523
NSF Award
2223164 – SBIR Phase I
Award amount to date
$274,667
Start / end date
02/15/2023 – 07/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project will develop and leverage an innovative hybrid intelligence, i.e., a unique combination of Big Data and artificial intelligence (AI) technologies with the wisdom of crowds, to help connect and empower both independent designers and small-to-medium-sized retailers/fashion buyers (together with supply chain partners), to help bring the original, unique, trendy designs with great garment quality to fashion consumers. The project also aims to help the fashion industry to tackle some of its hardest, most critical, and most urgent challenges in overproduction and waste (resulting in environmental issues). The project will advance recommendation technology and fashion intelligence by developing novel deep learning-powered fashion recommendation models, and effectively combine and integrate human fashion experts’ input and deep learning predictions. These techniques will help match fashion retail buyers and design(er)s, with the consideration of uniqueness and exclusivity. The project will also help evaluate key aspects of the fashion designs, such as uniqueness and trendiness, and provide more accurate predictions on fashion demands and sales.
The key technology innovations are two-fold. First, a novel self-supervised and deep learning-powered fashion recommendation engine will effectively utilize the heterogeneous fashion data (images, text, behaviors, and sales) to help accurately match fashion buyers and manufacturers with the (new) design(er)s under style compatibility and other requirements. Second, a hybrid intelligence engine will effectively combine and integrate fashion buyers' input (votes and orders) with deep learning models to help measure fashion uniqueness, trendiness, and sales forecasts, etc., of the new designs. The project can help both designers and retailers track the trends and the demands and stay ahead of the fashion curve.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IM TECHNOLOGIES, LLC
SBIR Phase I: Rare Earth Element Extraction from End-of-Life Fluorescent Light Bulb Powder
Contact
24 ROBINSON ST
Shoreham, NY 11786--2128
NSF Award
2126763 – SBIR Phase I
Award amount to date
$255,999
Start / end date
04/01/2022 – 03/31/2023
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 enable new technologies, such as additive manufacturing and electronics, that require special natural materials known as Rare Earth Elements (REE). Current REE extraction methods produce large quantities of toxic materials requiring mitigation. The proposed solution advances an extraction method that is environmentally friendly and generates no toxic byproducts, can be used with broad material sources (including recycled goods), uses less energy, and is readily scalable to deliver at a significantly lower cost.
This SBIR Phase I project proposes a reactor system that incorporates precision ultra-high temperature heating to evaporate targeted material constituents and subsequently condense to separate REEs. The approach optimizes thermal energy to efficiently achieve tailorable temperatures for the extraction and separation of REEs from a broad range of source material, including recycled Fluorescent Light Bulb (FLB) powder that contains significant concentrations of Yttrium, Europium and Terbium. This project will engineer a fully integrated prototype system that ingests waste FLB powder, extracts the REE constituents via precision heating, and then separates them in high purity via controlled evaporation and condensation. Research tasks include development of a reliable calibration procedure that simultaneously sets reactor current, voltage, and temperature for optimal evaporation. The end goal is to demonstrate commercial viability that yields an alternative REE extraction and separation approach that is economically and environmentally superior to existing chemical-based processes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSU HEALTH DESIGN, INC.
SBIR Phase I: Insu Health Design: Temperature Control System
Contact
1250 JUAN PONCE DE LEON AVE STE 400
San Juan, PR 00907-
NSF Award
2201997 – SBIR Phase I
Award amount to date
$256,000
Start / end date
10/01/2022 – 04/30/2023
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Phase I project is to offer novel opportunities to substantially improve temperature-controlled storage and transportation systems. The technology has the potential to become the ideal temperature-sensitive medication storage solution available to advance the health and welfare of the American public and third world countries by enabling a reliable means to protect and long-term refrigerate temperature-sensitive biomaterials such as medicines, blood, organs, vaccines, chemicals, and hormones even in areas that lack or have an unstable power supply. This project within the wireless technology area involves the integration of wireless and Bluetooth communication technologies for data capture and transmission to further support a wide variety of applications and services while maintaining full mobility, and long battery life for the system. Currently, there are over 200 different temperature-sensitive medications used by over 100 million people worldwide that the proposed innovation could provide monetary savings for individuals as well as decrease the $35 billion annual loss in the global biopharmaceutical industry due to failures in temperature-controlled logistics.
This Small Business Innovation Research (SBIR) Phase I project tackles the problem of keeping a portable volume within a precise temperature range for extended periods regardless of ambient conditions and power grid availability. The objective of the proposed research focuses on innovating the heat transfer design in portable volumes where meaningful performance improvement can be achieved through building proofs-of-concept that will later inform and enable the production of advanced products that create better solutions in the healthcare industry and cold chain transportation sector. The research plan consists of developing multiple designs of specific components within the cooling system, testing their respective effects on performance using our platform, and quantifying the cold storage efficiency and temperature precision for long-term stability. The anticipated technical result is a tested system design with a robust proof of concept platform demonstrating the technology with data to support further development of this new technology for a product ready to bring to market. The company will have also gathered data for a broader understanding of the technology’s scalability in other potential markets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTERMIX PERFORMANCE MATERIALS, INC.
STTR Phase I: Advanced compatibilization for mixed plastic recycling
Contact
5709 FREDERICK AVENUE
Rockville, MD 20852-
NSF Award
2136645 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research Phase I project is to promote increased recycling and to enable the upcycling of two of the most common polymers found in mixed waste streams: polyethylene (PE) and isotactic polypropylene (iPP). While plastic recycling can assist in mitigating the vast and continuously growing volume of plastic waste, mixed plastic streams—notably those with PE and iPP—introduce many challenges. These polymers are immiscible but of similar density, making them unsuitable for simple melt-blending yet difficult to separate. Although additives have been developed to overcome the immiscibility issue, these additives typically need to be added at high loadings and produce resins with poor mechanical properties. This project focuses on the development of advanced additives (compatibilizers) that can be introduced in low concentrations to produce PE/iPP resins with superior durability, ductility, and industrial utility that rivals or outperforms homopolymers. Such a technology has the potential to bring superior efficiency to the mixed recycling process, advancing the field toward a more circular plastics economy. By delivering high-value products from waste streams, widespread adoption of this technology would drive improvements in plastic waste collection, recycling, and re-manufacturing, supporting jobs in these and adjacent fields.
This project involves the creation of non-reactive, multi-graft copolymers capable of supporting high-quality iPP/PE blends with superior tensile strength characteristics, impact resistance, and rigidity compared to current resins. The proposed approach leverages interlocked molecular entanglements and co-crystallization to provide stronger adhesion to iPP and PE. This technology seeks capability of up to 30% iPP contamination in PE using as little as 1 wt% additive to generate high-value blended materials. Phase I development will involve: 1) optimization of polyethylene-graft-iPP copolymer compatibilization additives, 2) scale-up of optimized polyethylene-graft-iPP copolymers, 3) testing of larger scale batches for end polymer qualities, and 4) testing of compatibilizers with combinations of different grades of actual post-consumer plastic waste. The technology may contribute to an enhanced understanding of how specific copolymer architectures influence compatibilization efficiency, while also meeting the need for technologies to support compatibilization of PE and iPP for blended recycling 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. -
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 – 09/30/2023 (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. -
IONICSCALE LLC
SBIR Phase I: Low cost, portable mass spectrometers based on a chip-scale ion trap mass analyzer
Contact
501 BOULEVARD PL NE
Atlanta, GA 30308--2886
NSF Award
2213033 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (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 greatly expand the power of mass spectrometry for chemical detection and analysis to a far broader user base. The ultimate goal is to produce a chip-scale device sufficiently affordable that it can be a user replaceable component in an ultra-compact instrument. This is enabled by a microfabricatable ion trap geometry that circumvents key shortcomings of previous chip-scale mass analyzer efforts. There is potential to bring this technology to the consumer market where it can inform household residents of harmful trace or odorless chemicals present in their homes. In addition, with advances in data science, the proposed technology might also be able to inform household residents of volatile organic compound signatures that may be indicative of the early onset of disease in a manner similar to dogs which have a demonstrated ability to smell certain types of cancer, Parkinson’s disease, spiking or dropping blood sugar levels in diabetics, and, most topically, CoVID-19, among other conditions. Prior to entry into the consumer market, these compact instruments can be leveraged for important in-situ analytics in fields such as defense, energy production, pharmaceutical research, environmental monitoring, and space exploration.
This Small Business Innovation Research (SBIR) Phase I project will enable the assessment of a novel, patent-pending ion trap mass analyzer in a compact physics package for handheld mass spectrometers. Mass spectrometers are the gold standard for chemical analysis and have wide ranging applications, however, widespread utilization of these powerful instruments is hindered by their high cost, size, weight, and power. Current portable instruments are ~$100k USD, roughly the size of a small suitcase, and operate for only a few hours on a single battery charge. The novel ion trap mass analyzer geometry explored as part of this work can be microfabricated, potentially lowering the cost per unit to the point where it can be incorporated in an instrument physics package that is a replaceable cartridge, thus eliminating the need for expert maintenance. Coupled with modern computational methods, processing power, and cloud computing architectures, these mass spectrometers could be utilized for chemical analysis applications for which mass spectrometry is currently not a cost-effective solution. This dream of ubiquitous, high specificity chemical analysis technology could generate massive amounts of new raw data informing and creating future collective research and advanced applications/solutions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ISEECHANGE, Inc.
SBIR Phase I: User-generated real time qualitative data processing for climate impacted model validation, integration, and augmentation
Contact
4532 BANCROFT DR
New Orleans, LA 70122--1206
NSF Award
2216888 – SBIR Phase I
Award amount to date
$274,381
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project is the development of an integrated methodology to use resident’s experiences about flood (and other climate change) events to validate modeling in real time, inform policy, and provide design insights for infrastructure development. It provides an integrated solution for capturing the valuable information captured by people’s direct experiences (photos, stories, and data) with climate change that are otherwise underutilized. The team will develop a community knowledge platform that can process a mix of text and photo data submitted by residents and process it into formats usable for understanding on-the-ground impacts, flood occurrence and severity, and deliver that data to planners and modelers developing ways to better manage floods. Data processing occurs behind the scenes and allows residents to engage with the planning processes impacting their communities in new ways, increase the access of underrepresented communities, and improve equity in decision-making. The project will stimulate research in data sciences, generate new types of jobs in civic data systems, and improve the efficiency of public infrastructure investments. User’s cell phones will become powerful local data collection tools allowing a direct line of communications and building trust between government decision makers, scientists, and residents.
Advances in data science allows the analysis of heterogeneous qualitative and image data to incorporate user generated posts into large scale infrastructure planning around climate resilience. Currently, descriptive data and photos submitted by users are manually analyzed for content. Through novel use of natural language processing (NLP), spatial data analysis, artificial intelligent (AI) and computer vision of flood event photos, and development of an application programming interface (API) to curate data for hydrological model developers, this project automates the process of extracting the full value of community generated posts of flood events. When successful, hyperlocal user generated posts will be processed in real time to deliver detailed on-the-ground data on flood events to planners, for model validation, and community members themselves. The product builds innovative technologies to permit processing at scale so that any community experiencing flood events can generate real time flood data and monitor the impact of infrastructure as hydrological baselines continue to shift. The project develops new machine learning NLP to automate the analysis of qualitative text data, keyword detection for sentiment analysis and impact, AI to extract flood characteristics from photos, and API for protecting model IP while allowing integration with external data for validation purposes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Integrated Medical Sensors
SBIR Phase I: A novel multianalyte microsensor platform for continuous wireless monitoring applications
Contact
121 ISLAND CORAL
Irvine, CA 92620--3561
NSF Award
2151738 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 05/31/2023 (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 an innovative and user-friendly continuous wireless sensing platform for simultaneously monitoring multiple analytes and physiological parameters. The wireless sensor market is worth > $13 Billion and is growing 10% annually. There is an under-penetration in the market due to the unmet need of an easy-to-use sensing platform that can provide users with quantitative and continuous data about their studies in real-time as compared to discrete sampling techniques used currently. This is because the current continuous sensors are either wired or bulky (discrete wireless), are disruptive to the studies, require special insertion procedures (e.g., complex surgeries for animal research), and do not easily integrate with the experimental workflow. Given our experience in wireless sensor development for diabetes, many researchers have asked us to develop a platform technology for biochemical sensing to enable research in materials science, pharmaceutical, in vitro diagnostics, protein engineering, and disease pathways. Such a platform can revolutionize biomedical researchers with a tool to study new drugs, cell cultures, artificially grown organs, bioinspired materials.
This Small Business Innovation Research Phase I project is intended to develop a unique monolithic semiconductor platform capable of wirelessly monitoring multiple biochemical and physiological markers simultaneously at a sub-mm3 footprint. This enables the device to be used in a variety of applications where conventional larger sensors can’t be used, including test tubes, multi-well plates, and cell cultures. Moreover, the platform can be injected under the skin using a needle-based insertion device, eliminating complicated surgical procedures currently used. The wireless miniature design results in a stable sensor-environment interface as opposed to the current wired and the bulky wireless devices that suffer from constant variation in response due to constant interface irritation. Furthermore, it’s extremely small size minimizes foreign body response, which is proportional to device size, and implantation injury, and hence minimizes calibration frequency. Micro/nano design is used to fabricate patterned electrodes on the top layer of a Complementary Metal Oxide Semiconductor (CMOS) Application Specific Integrated Circuit (ASIC) to form a fully integrated system without the need for discrete packaging used in current products. This enhances manufacturability and reduces unit cost in volume production. After successful feasibility in this Phase-I, we will optimize the system and develop a manufacturing plan to commercialize it in 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. -
KILELE HEALTH LLC
STTR Phase I: Aptamer Biosensors with the Longevity and Technology Compatibility Required for Continuous Biosensing Devices Beyond Glucose
Contact
201 E DIXON AVE
Oakwood, OH 45419--3545
NSF Award
2212221 – STTR Phase I
Award amount to date
$255,899
Start / end date
06/15/2022 – 05/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to improve clinical outcomes for patients with wearable biosensor needs. This project will develop wearable continuous glucose biosensor platforms to address a broad set of disease and wellness applications, such as measuring additional molecules relevant to diabetes management, improving management of cardiovascular diseases, and therapeutic drug monitoring to customize dosages. In addition to impacting human health (particularly for chronic diseases) in the United States, the commercial market is significant and valued at approximately $120 B/year. Furthermore, these biosensors will provide data directly to patients to inform their decisions.
This Small Business Technology Transfer (STTR) Phase I project will address the limitations which have prevented continuous diagnostic monitoring platforms from adding clinical utility beyond sensing glucose with enzymatic sensors. Unlike enzymatic glucose sensors, electrochemical aptamer sensors are rapidly adaptable to measuring other molecules in the body with high specificity and sensitivity. However, aptamer sensors currently degrade rapidly in live animals (<6-12 hours) and must be inserted through a highly-invasive incision. This STTR Phase I project will demonstrate robust and longer-lasting functioning of aptamer biosensors in a real biofluid environment. It will use a software-enabled method in which only one electrode is inserted, making the resulting device truly minimally invasive.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Kintsugi Mindful Wellness, Inc.
SBIR Phase I: Scaling Mental Healthcare in COVID-19 with Voice Biomarkers
Contact
2790 HARRISON ST
Berkeley, CA 94705--1346
NSF Award
2031310 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to use voice as a real-time measurement of mental health. Transforming voice intonations into biomarkers could enable disease diagnosis and progression, supporting the $13 B virtual health care sector that was growing 27% annually prior to COVID-19. Furthermore, peer support for mental health increases engagement in self-care decreases substance use and depression, particularly for vulnerable populations. The project will advance the use of machine learning for voice mental health biomarkers in a group setting.
This Small Business Innovation Research (SBIR) Phase I project will define voice biomarker features for a deep reinforcement learning based system. This project will advance a voice biomarker technology that can serve as fast behavioral health diagnostic, potentially superseding the current paper-based PHQ-9 and GAD-7 tests. The priority is to scale the optimal mix of individuals and activities for group therapy based on reward functions that maximize improvements in depression and anxiety scores. The major technical challenges include: (1) capturing nonverbal cues in a video; (2) interpreting multi-speaker audio processing; (3) creating deep reinforcement learning models to serve relevant group matches and follow-up exercises; and (4) building engaging visual feedback of progress from group meetings. The anticipated technical result of this innovation will be to define voice biomarker features and reward functions for a deep reinforcement learning based system in clinically relevant settings to improve depression and anxiety treatment 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. -
LABRADOR SYSTEMS, INC.
SBIR Phase I: Assistive Robots for Personal Care and COVID-19 Protection
Contact
5111 DOUGLAS FIR RD
Calabasas, CA 91302--1440
NSF Award
2036684 – SBIR Phase I
Award amount to date
$255,756
Start / end date
01/01/2021 – 03/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project advances the state-of-the art of an emerging class of vision-based, autonomous navigation technologies to open new possibilities for low-cost/high-performance personal assistive robots. The robotics solution enables mobility-impaired individuals to have more agency over their environment and enjoy a higher quality-of-life. This helps address the severe shortage of caregivers for the elderly and post-acute care patients by empowering individuals to maintain their independence, extending the impact of caregivers, and reducing the cost of care in both home and facility settings. Additionally, by providing affordable and reliable isolation support in COVID-19 care settings, the proposed solution can help decrease the financial burden and increase the public health outcomes associated with COVID-19 disease management. The core robotics solution has an immediate addressable market of 11 million high-needs users in the U.S. alone, with projected revenues of roughly $1.65 Billion five years after product launch. Further commercialization opportunities come from licensing parts of the developed navigation technology for other robotics applications and developing an ecosystem of complementary products around the core robotics solution.
This Small Business Innovation Research Phase I project seeks to enable a new generation of assistive service robots that are comparable to commercial robots in performance, but significantly more affordable for individual use and personal care applications. The innovation adopts emerging visual positioning technologies from Augmented Reality to enable robust navigation for mobile robots using low-cost, consumer-grade electronics, while addressing a key limitation of visual positioning systems namely, that external lighting conditions and other changes in an environment can dramatically impact their performance. The innovation addresses these challenges via a combination of hardware and software that learns and stabilizes the highest value visual elements of the environment to maintain persistency across lighting conditions and long periods of time — a development critical to making assistive robots cost-effective for adoption at a large scale. Research objectives include: fully developing and integrating the visual persistency system, to achieve accurate and replicable robot navigation performance across a representative range of lighting conditions and visual characteristics of the target operating environments and benchmarking the resulting solution against state-of-the art technologies, to demonstrate its superior performance (i.e., it can successfully localize in at least 90% of cases where other solutions fail).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LADON ROBOTICS LLC
SBIR Phase I: Autonomous Wind and Solar Powered Cargo Vessels
Contact
8006 213TH ST SW
Edmonds, WA 98026--7452
NSF Award
2130478 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 06/30/2023 (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 develop autonomous, ocean-going cargo vessels powered by a combination of wind and solar power. These vessels will enable the provision of cheaper and more frequent sea freight service to isolated communities, such as those in coastal Alaska. The technology seeks to the lower operating costs by removing liquid or solid fuels or onboard crew, enabling the vessels to be more readily right-sized to particular routes and markets. The project may also have positive impacts on the environment by eliminating fossil fuel emissions and reducing marine noise impacts on wildlife, such as marine mammals.
This Small Business Innovation Research (SBIR) Phase I project will integrate existing robotic and energy capture technologies with newly developed wind/solar combined energy optimization software and autonomous contingency management. A vessel using both the wind and sun for propulsion has a difficult energy optimization problem, both on a minute-to-minute basis but also on the scale of an entire voyage; This project will build a model for solving this intermitancy problem given specific vessel performance characteristics and weather predictions. Likewise, this project will build a framework for addressing the autonomous contingency management problem for uncrewed marine surface vehicles given a particular set of vehicle and system characteristics. The focus will be on ship-to-shore communications contingencies because those are the most serious for the contemplated target 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. -
LEARNING NETWORK, LLC, THE
SBIR Phase I: College Bound Video Game
Contact
1915 NATCHEZ TRCE
Allen, TX 75013--4873
NSF Award
2225635 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impacts of this Small Business Innovation Research (SBIR) project will result from the production of a useful game, called College Bound, that will entice youth to use their gaming time to learn how to navigate the college preparation, college-admissions, and financial-aid processes. This assistance could help in addressing the problem of an inadequate number of counselors in high schools that serve large minority populations. Studies have shown that underserved high school students see a counselor for less than 20 minutes a year. Since is also known that young people between the ages of 8-18 spend 7.5 hours a day engaged with media- either playing video games or watching television a game platform may enable minority students, who make up less than 4% of undergraduate enrollees in the national four-year colleges, to prepare for college attendence. The College Bound game seeks to recoup some of this screen time for positive benefits such as improving preparedness of the minority students to access higher education, and meeting future workforce demands in Science, Technology, Engineering, Mathematics, and Medicine (STEMM).
This Small Business Innovation Research Phase I project focuses on assisting underrepresented students in learning about what it takes to get college admission, how to prepare for it, and what financial aid is available to afford the education using a gaming environment. The project will focus on measuring students' knowledge about the college application process as the player navigates through different levels of the game. Knowledge about the college application process includes a) information about admission criteria and deadlines, b) the college acceptance and enrollment processes, and c) the ability to pay for college through scholarships, loans, work programs, and/or personal savings. Throughout the pilot phase, the project will develop reliable and valid evaluation tools to measure student learning in the game setting at each level of the College Bound game. These evaluation tools might reflect not only student learning performance but also boost college enrollment outcomes. These measures may also enable the school and other stakeholders to understand students' gaps and help strengthen students’ pathways into college.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEARNINGCLUES, LLC
SBIR Phase I: Scalable, on-demand, research-based, help-seeking innovation for learners in virtual and recorded training programs
Contact
2019 MARRA DR
Ann Arbor, MI 48103--6187
NSF Award
2151406 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/15/2023 – 12/31/2024 (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 develop a scalable, on-demand, research-based innovation for learners in virtual and recorded training programs. Research has shown that underrepresented populations arrive at an undergraduate institution less likely to have the advanced study skills or confident awareness to seek assistance when faced with uncertainty in the classroom. This project provides on-demand responses to in-lesson queries and helps develop deep study skills. Additionally, for the students who arrive at college without sufficient familial or academic support, the proposed product becomes a resource to participate successfully in an undergraduate environment.
This Small Business Innovation Research (SBIR) Phase I project will build an engine that automatically identifies the discipline of a course based on the extracted words and phrases spoken or visually presented in class, and then will identify terms important to the learning objectives of the course, garnered via categorical arrays of discipline specific keywords. Automatic creation of personalized study guides is initiated based on the learners' individual queries or class discussions. This innovation is applicable to the remote learning industries, where it may increase the value of their customers’ online content and enable teaching professionals to strive for higher levels of equity in the student population.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEXEL SYNERGETICS, INC.
SBIR Phase I: Handheld Devices for Practical Simultaneous Translation
Contact
5676 NW 132ND AVE
Portland, OR 97229--2420
NSF Award
2212978 – SBIR Phase I
Award amount to date
$255,994
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project on a handheld simultaneous translator advances the state-of-the-art technologies in natural language processing and machine learning acceleration. Beyond technical contributions, the novel translator will likely have a significant impact on a wide range of domains, such as military personnel deployed in foreign countries, businesspeople participating in multilingual meetings, medical service providers, law enforcement, customer support services, diplomats and political representatives, local governmental entities providing services to citizens in the preferred language, and international tourists. As such, the project will have broader impacts in increasing economic competitiveness, advancing health and welfare, and improving military capabilities of the United State. Furthermore, the project helps to enhance equity in education and STEM literacy by enabling better access to educational resources to people of diverse backgrounds, especially immigrants, women, and underrepresented minorities in some countries/regions, who were previously disadvantaged due to limited prior educational access or limited access to foreign language courses.
This Small Business Innovation Research (SBIR) Phase I project focuses on the research and development of innovative algorithmic optimizations and a purpose-built translation device to enable fast, accurate and low-power inference for simultaneous translation. The overall approach is to exploit the unspoken but implied connections among language elements at various levels to guide the learning model. Specific techniques are investigated at the phoneme-level, work-level, and sentence-level. Collectively, these innovations aim to reduce the computation complexity of simultaneous translation by orders of magnitude while increasing translation accuracy. A systematic and comprehensive methodology is also being established that allows fast implementation of the inference hardware via high-level synthesis and reports detailed statistics on translation accuracy, latency, power, and area to facilitate a thorough evaluation of the research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIFESPAN DIGITAL HEALTH, LLC
STTR Phase I: Peripheral Autonomic Regulation Training for Mental Health: Enabling Multimodal Peripheral Biofeedback in a Higher Education Setting
Contact
111 N DUPONT CIR UNIT 230
Phoenix, AZ 85034--1836
NSF Award
2208601 – STTR Phase I
Award amount to date
$255,409
Start / end date
09/01/2022 – 08/31/2023 (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 not limited to the higher education community, but has broader application at the elementary, middle and high school levels, especially in underserved and marginalized communities experiencing increased rates of suicide and mental health issues. This project's innovative technologies can assist in the mental health crisis in the country's youth, and specifically in the Native American health system as well as Juvenile Detainee/Juvenile Justice systems. This project's implementation of research based on the benefits of game-based intervention coupled with biometric sensing has the potential to provide the technologies necessary to equip the mental health profession to develop options that could replace pharmacological interventions with a path to delivering personalized and measurement-based mental health services.
This Small Business Innovation Research (SBIR) Phase I project uses predictive algorithms, wearable technology and peripheral autonomic biofeedback to provide timely and effective data to enable mental health professionals to enact treatments and therapeutic support for students. Challenges in the increase of adult mental illness, shortage of mental health professionals and shortage of child and adolescent psychiatrists require a move towards tele-psychiatry, collaborative care and innovative technology to bridge the gap between inadequate supply and increasing demand. The proposed approach involves the development of bio-behavioral technology that provides mental health professionals an interactive stress and anxiety evaluation to enable deep, transformative connections between young adults and mental health service providers.
This award reflects 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 AND CHARGE SOLUTIONS, LLC
STTR Phase I: Developing Thiazolothiazole Molecular Materials for Electronic and Photonic Applications
Contact
255 BURSON 9201 UNIVERSITY CITY BLVD
Charlotte, NC 28223--0001
NSF Award
2223042 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project includes the development of highly fluorescent, next generation dye compounds for a variety of optoelectronic applications. The new materials provide an easily synthesized and synthetically tunable platform to function in both solid-state panel lighting/signage and in organic light-emitting diodes (OLEDs). The fluorescent dye materials that are developed will enable low-cost printing processes and manufacturing for large scale lighting and luminescence industries. The technology will also enable OLED manufacturing to transition from thermal evaporation process to low-cost printing processes. The low-cost, high performance, printable dyes may increase panel lighting/OLED use, resulting in positive societal impacts through reduced energy usage, lower prices for existing lighting technologies, and new innovative lighting products.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop a series of highly fluorescent compounds that will be developed and tested for printed lighting panel/signage applications and as blue emitter for OLEDs. A primary barrier to large-scale, luminescent, organic materials devices for OLED lighting and the display/signage market is the limitations of currently available fluorescent molecular compounds in terms of cost, stability, and processability. The high structural tunability, photostability, and high fluorescence quantum yield of the new, high-performance materials make them an attractive option for luminescent molecular device applications. The new materials provide an easily synthesized and synthetically tunable platform to function both as a printable emissive layer for solid-state panel lighting/signage, and as the light emissive layer for solution processable organic light-emitting diodes (OLEDs). The goals of proposed research include the production of solution-processable, photostable dyes for stolid-state panel lighting with solubilities exceeding 1 wt.% in precursor formulations, external quantum efficiencies (EQEs) of greater than 30%, and photostabilities exceeding 10,000 hours. In addition, using these compounds, the team seeks to will demonstrate blue-emissive, printable light-emissive layers for OLEDs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIMINAL ESPORTS LLC
SBIR Phase I: Engaging citizens in environmental research to impact science literacy and STEM careers while ensuring data integrity
Contact
7850 MAYFIELD RD
Gates Mills, OH 44040--8601
NSF Award
2151476 – SBIR Phase I
Award amount to date
$255,945
Start / end date
09/01/2022 – 08/31/2023 (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 seeks to engage citizen in environmental research activities, potentially increasing the selection of science, technology, engineering, and mathematics (STEM) careers for youth. This project focuses on enhancing academic and industry partnerships around citizen science, improving science and environmental literacy, and increasing participation of underrepresented groups in STEM fields of study. In addition to improving the nation’s scientific and technical workforce pipeline, the project seeks to employ a unique commercialization model for interactive educational media that allows for both authentic learning and widespread use by general audiences. This model mixes digital and in-person experiences, digital distribution methods, and mobile experience commercialization strategies that can serve as a model for other educational and commercial interactive media companies.
This Small Business Innovation Research (SBIR) Phase I project addresses two critical issues: engaging more youth in environmental science and engineering education and increasing local environmental data for scientists. The project team will research and develop optimal methods and tools for creating educational and interactive media with rapid scientific data collection capabilities. For youth and educators, the project seeks to engage users in national standards-aligned scientific learning activities. The project will create hyperlocal networks that collect data and make results directly available to local communities so that they can actively track pressing environmental concerns such as migrations and changes in populations of species. The technical goals of the project include creating new processes for connecting local, crowdsourced user input to citizen science data repositories in a way that automates the categorization and validation of that data. The resulting project will actively engage youth in real scientific research and improve data collection for federal and university environmental science programs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIRA, INC.
SBIR Phase I: Video-to-speech software application to provide real-time, noninvasive, natural voice restoration for voiceless individuals
Contact
119 HOLLOW OAK DR
Durham, NC 27713--8643
NSF Award
2136629 – SBIR Phase I
Award amount to date
$255,997
Start / end date
09/01/2022 – 05/31/2023 (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 seeks to enable one million Americans that suffer with the loss of ability to speak through disease of or damage to the larynx or mouth (aphonia). The inability to fluently communicate with other people has severe consequences. Voiceless individuals are three times more likely to suffer a preventable adverse event in medical settings than speaking patients, and this can lead to health problems and even life-threatening situations. Up to 50% of these adverse events could be avoided with adequate communication between patients and clinicians. The proposed solution is a video-to-speech software application that provides voiceless people with real-time communication assistance, especially geared towards medical settings. The technology could help prevent hundreds of thousands of adverse health events each year (costing $6.8 billion annually), with benefits for the voiceless population and the healthcare system in general. The innovation may improve voice restoration by providing real-time translation with no training needed and allowing complex messages to be expressed while looking eye-to-eye (an important part of human communication). Moreover, the technology does not require invasive installations nor complex equipment, is readily accessible, and has maintenance requirements that are marginal.
This Small Business Innovation Research (SBIR) Phase I project aims to address the intellectual challenge of overcoming the ambiguity of visemes when trying to automate lip-reading. Visemes (the gestures made when talking) and phonemes (the sounds produced with these gestures) do not share a one-to-one correspondence. This makes accurately predicting the intended speech based on visual information challenging. Previous researchers have failed to reach acceptable accuracy levels in the interpretation of visemes, while other tools only work with a few dozen words that must be structured according to pre-defined, fixed rules that are impractical. The main goal of this effort is to develop a combination of convolutional neural networks and recurrent neural network transducers that is capable of accurately differentiating visemes and permits real-time, reliable voice assistance for voiceless people. Project objectives include: (1) pre-training an algorithm to detect phonemes using publicly available speech video, (2) optimizing the phoneme-trained algorithm against healthcare relevant vocabulary, and (3) alpha-testing of the lip-reading algorithm against real-time speech.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUMOSTECH, INC.
SBIR Phase I: Restoring natural sleep for adolescents: circadian clock advancement at night assisted with mobile application-delivered cognitive behavioral therapy
Contact
99 RAUSCH STREET
San Francisco, CA 94103--3902
NSF Award
2112403 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (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 chronic sleep deprivation among American teenagers, which has only been made worse by the recent pandemic. Adolescents' natural internal circadian clocks typically run 1-3 hours later than adults, leading to the tendency to stay up late, difficulty falling asleep, insufficient total sleep time, and morning grogginess. This project is designed to improve sleep for adolescents and young adults by advancing their circadian clocks leading to healthier sleep. Today, there are almost 42 million adolescents in the United States aged 11-19, and another 18.9 million young adults aged 20-24, making the commercial potential of this project to be a $10 Billion market opportunity in the United States alone.
This Small Business Innovation Research (SBIR) Phase I project is commercializing an innovation in sleep therapy. Approximately half of all American adolescents and young adults in the United States do not get enough sleep. Cognitive behavioral therapy (CBT) for insomnia has been somewhat effective when administered by a therapist in person, but the in-person model is not scalable. Lack of sleep can negatively impact physical and neurocognitive development, leading to inability to concentrate, poor grades, higher risk of diabetes and long-term cardiovascular problems, and increased risk of mental health issues, depression, and suicide. The proposed solution applies recent sleep research and innovates it into a product worn at night and plans to go to market with an integrated solution of both the product hardware and telehealth support. Healthier sleep brought by this solution may lead to better recovery, improved memories and concentration, and enhanced neurocognitive and physical development. It may also reduce the risks for depression and other mental health issues. The enhanced physical and mental health may have other positive impacts in society, for example, reducing healthcare costs and preventing accidents caused by sleep deprivation. Short light pulses may alter circadian phases of human subjects during sleep. Based on light flash technology, the team proposes creating a smart sleep mask that emits light flashes at night during sleep to effectively advance teenagers’ circadian phases without disrupting their daytime activities. This light flash technology will be assisted with cognitive behavioral therapy (CBT) delivered via a mobile application to promote earlier bedtime and better sleep hygiene.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
M3SIM, LLC
SBIR Phase I: A fractional-order computational platform for the multiscale and multiphysics analysis of failure-critical systems
Contact
2116 WAKE ROBIN DR
West Lafayette, IN 47906--5089
NSF Award
2212932 – SBIR Phase I
Award amount to date
$255,940
Start / end date
09/15/2022 – 08/31/2023 (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 develop the foundation of a fractional-calculus-based computational platform for the simulation of multiscale and multiphysics systems. This Phase I effort will focus on developing modeling capabilities for nonlinear thermomechanical fatigue and damage behavior of ductile materials and will provide important insights on both feasibility and performance of the fractional calculus approach for a class of nonlinear problems that is not only of extreme importance for scientific and industrial applications but it is also a prototypical example of multiscale and multiphysics systems.
By leveraging an advanced and generalized class of operators, namely the distributed and variable-order fractional operators, this project will develop fatigue and damage mechanics simulation software capable of continuum scale computational efficiency and microscale accuracy. The resulting formulation will offer an unprecedented combination of computational efficiency, a high degree of fidelity and accuracy, and a revolutionary adaptive mathematical structure that evolves in real-time based on the underlying physics controlling the deterioration and damage process.
The overarching innovation at the basis of the M3SIM software products is a one-of-its-kind computational platform based on cutting-edge distributed-variable order (DVO) fractional calculus (FC). The unique nature of DVO operators allows the new platform to perform multiscale and multiphysics analyses of complex systems at a level of accuracy and efficiency that is unattainable with traditional methods. This new approach will have profound practical implications for predictive science because it will enable a novel concept of an adaptive computational platform whose structure evolves with the underlying physics without a priori and ad hoc decisions from the user.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAGMA SPACE LLC
SBIR Phase I: Semi-active magnetic bearing for flywheel energy storage systems
Contact
80 M ST SE STE 100
Washington, DC 20003--3550
NSF Award
2222161 – SBIR Phase I
Award amount to date
$274,995
Start / end date
02/15/2023 – 01/31/2024 (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 implement a high-efficiency, low-power magnetic bearing that will enable the successful development of high-speed flywheel energy storage systems (FESS) both for space and terrestrial applications. FESS are mechanical batteries that overcome some of the limitations of lithium-ion batteries, such as the loss of energy capacity over time and the need for stringent temperature control. In space, FESS could reduce the overall mass associated with the battery pack and extend the mission life of Low Earth Orbit (LEO) satellites. On earth, FESS can take over some of the applications that are required to deliver high power for a short amount of time, such as electric vehicle charging stations or hospital back-up power units. Ultimately, FESS will help alleviate the demand for lithium-ion batteries while providing reliable, long-lasting energy storage.
This Small Business Innovation Research (SBIR) Phase I project will demonstrate the feasibility of integrating the proposed magnetic bearing into a carbon-fiber flywheel. The complexity of this task comes from having the three main parts of the flywheel (composite rim, metal core, and magnets) created using different manufacturing processes. The magnetic materials need to be protected as they will not withstand the high speeds of FESS. De-risking this manufacturing process is crucial in continuing the development of this technology and in scaling up. Another challenge is that the high speeds of FESS are expected to cause high gyroscopic torques during satellite maneuvers. Therefore, investigating ways to increase bearing stiffness (e.g., by changing magnet size and position, or modifying coil shape), while assessing the effect of gyroscopic torques through numerical models, will be paramount. Finally, the magnetic bearing has the distinctive feature of being able to tilt the flywheel (within its gap tolerances), without requiring an external gimbal actuator. This feature could possibly allow the technology to be used for dual purposes, and its implications will be investigated at a system level.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAXWELL COGNITIVE INC.
SBIR Phase I: Within-test measurement of learning progress: unbiased assessment towards bridging the educational opportunity gap
Contact
68 UPPER SHEEP PASTURE RD
East Setauket, NY 11733--1750
NSF Award
2136665 – SBIR Phase I
Award amount to date
$255,989
Start / end date
09/01/2022 – 08/31/2023 (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 help underprivileged students obtain higher education, leading to more than 150,000 highly-qualified specialists by 2035. In a rapidly changing civilization, one cannot predict which professions and skills will disappear in the next decades and which new ones will emerge. This makes an individual’s existing skill level less informative than their potential to acquire new skills. Unlike existing assessment methods, which focus on finding already skilled individuals, this project will help identify those better at obtaining new skills.
This Small Business Innovation Research (SBIR) Phase I project will create an assessment algorithm as well as an online testing platform to address the current lack of fairness and equity in high-stakes cognitive and educational assessments. This will be accomplished by combining two innovations: (i) measuring the growth of learning capabilities directly during an educational intervention without separation into pre-test, post-test, and training phases; and (ii) maximizing the rate of change of a student’s cognitive capabilities by applying adaptive item selection and personalized feedback. These two innovations will maximize both the effect of intervention and the accuracy of its measurement. As a result, learning capability can be measured in a single relatively short session comparable to the time typically allocated for standardized testing. The Phase I goals of this proposal are (i) demonstration of feasibility of extracting learning capabilities, (ii) increased signal-to-noise ratio, and (iii) elimination of the imbalance in initial proficiency levels.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MEALMATE INC.
SBIR Phase I: A Deep-learning-based Chatbot and Personalized Recommendations: Application to Nutrition
Contact
6516 W 87TH PL
Los Angeles, CA 90045--3726
NSF Award
2213316 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to advance the health and welfare of the American public. Obesity among American adults has risen from 12% in 1990 to over 40% today, leading to an estimated medical cost of $260 billion in 2016, according to the Center for Disease Control (CDC). According to the National Institute for Health (NIH), 70% of American adults were overweight or obese in 2014. In 2013, American adults were spending $60 billion annually on weight loss, according to US News & World Report. A 2008 American Journal of Preventive Medicine study showed that those who kept daily food journals lost twice as much weight as those who did not. However, existing diet tracking methods are often too time-consuming for maintaining long-term weight loss. A personalized artificial intelligence (AI) chatbot could make food logging fun and easy, benefitting millions of Americans who are trying to lose weight and furthering knowledge on spoken dialogue systems.
This Small Business Innovation Research (SBIR) Phase I project will advance knowledge in the field of spoken dialogue systems in several ways. First, the project establishes a new research area by noting that AI and spoken dialogue systems have yet to be applied to nutrition. Typically, conversational agents focus on factual question answering or tasks such as flight booking, but there is an opportunity to leverage big data for learning relationships between diet and health. Second, this project will develop a neural generative chatbot model with memory, demonstrating the benefit of personalized conversational interactions with intelligent agents that remember the history of conversations and personal details about the user. While manually writing chatbot responses ensures more control over the output, the drawback is that the responses are less interesting, diverse, and flexible. This work proposes generative Transformers in order to generate more realistic, human-like responses and knowledge graphs as a novel method for remembering the conversation and diet tracking history of each user for personalized feedback. Finally, this project proposes the application of causal inference, often used for medical diagnosis, to the new, challenging task of predicting which foods lead to outcomes such as gut symptoms, weight loss, or muscle building.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MED DIMENSIONS, LLC
SBIR Phase I: Novel Artificial Intelligence (AI)-Mediated Orthopedic Implant Design and Selection
Contact
318 TIMOTHY LN STE 2
Ontario, NY 14519--9022
NSF Award
2213118 – SBIR Phase I
Award amount to date
$254,580
Start / end date
02/15/2023 – 01/31/2024 (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 customized dental implant solutions for animals affected by traumatic jaw injury and disease. Current veterinary implants utilize platforms designed for human use, despite a greater variability in anatomy, bone strength, and procedural requirements. This approach has subsequent shortcomings accounting for anatomical and physiologic variations resulting in trauma, neovascular damage, incomplete healing, and failure to improve or restore functionality. The project proposes a software program and system for generating customized implant designs and criteria based on the specific anatomy and procedure. A successful project would improve veterinary care and the lives of pets and service dogs following injury.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a Machine Learning (ML) software to incorporate bone density screening with 2-dimensional to 3-dimensional reconstruction software to create anatomically derived implants and software guided implant placement. The proposed ML system will identify key anatomical considerations and animal classifications for optimizing implant designs and procedural criteria. By integrating a database of appropriate animal scans, the ML software will identify the optimal regions for implant and refine as needed. The result of this Phase 1 is a database-derived algorithm which generates implant shapes and sizes that avoid anatomical features that interfere with proper placement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MEMBRANEX, LLC
STTR Phase I: Three Dimensional (3D) Printed Mixed Matrix Membranes for Biogas Upgrading
Contact
119 LAWLOR RD
Tolland, CT 06084--3716
NSF Award
2223083 – STTR Phase I
Award amount to date
$275,000
Start / end date
01/01/2023 – 12/31/2024 (Estimated)
Errata
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Abstract
The broader impact /commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to derisk a new membrane manufacturing technology for biogas upgrading. Renewable natural gas (RNG) is attractive as a carbon neutral energy source as it is derived from organic wastes such as food waste, agricultural waste, and municipal biosolids. RNG is part of biogas and requires cost- and energy-effective separation from carbon dioxide. The company has developed an additive manufacturing technology that enables the fabrication of high performance membranes to enable lower cost biogas upgrading. These membranes offer energy and system design benefits over more traditional separations technologies for the production of RNG. The membrane printing approach may lead to the production of best-in-class membranes for RNG production and could enable carbon capture and utilization from biogas sources.
This Small Business Technology Transfer (STTR) Phase I project seeks to demonstrate the production of mixed matrix membranes (MMMs) comprised of polyether block amide polymer and zif8 zeolite. The proposed method uses electrospray based additive manufacturing to precisely control membrane thickness and zeolite loading, allowing customized membrane properties for biogas upgrading. Furthermore, the additive manufacturing, or printing, method enables increased loading of the zeolite over conventional casting techniques without the formation of defects that would lessen selectivity. The goals of the project include quantification of the maximum zeolite loading while avoiding loss of selectivity. The company will produce small membrane leaves up to 1 ft2 in area and demonstrate consistent performance across the leaf using mixed gas 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. -
MESPILUS INC.
STTR Phase I: Nano Functionalized Capacitive Deionization For Water Purification
Contact
1 PARKTON AVE
Worcester, MA 01605--3148
NSF Award
2222557 – STTR Phase I
Award amount to date
$274,995
Start / end date
09/01/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to further develop a technology that will unlock large new supplies of water. The technology can potentially provide a much-needed alternative to reverse osmosis (RO) for water purification, currently the most widely used technology applicable to total dissolved solids. The proposed technology seeks to address unmet needs in water reuse, water recycling, water purification, brackish desalination, and salt-less water softening. The solution may be applicable to water quality, including water supplies impaired with total dissolved solids, nitrate, arsenic, fluoride, and other contaminants. The technology may have applications in electric grid, commercial, and industrial processes for the use of low-quality grey water, wastewater, re-used water, ground water, and residential water. Success of this project would help in mitigating environmental, social, and economic threats related to water.
This STTR Phase I project seeks to enable optimization of third generation capacitive deionization electrodes for improved charge efficiency, energy usage, water recovery, lifetime and feed concentration. An initial target is to remove at least 2000 ppm from a mineral- or salt-contaminated feed and recover at least 70% at low cost. Higher concentrations of water impurities will be explored to determine the operational envelope. The planned experiments intend to help quantitate how surface functionalization with ionic groups increases charge efficiency and affects important electronic properties such as capacitance, resistance, and operating lifetime. These properties will be cross checked against different feed solution concentrations, the ability to purify a given concentration of feed solution, water recovery, and nanoscale electrode pore characteristics. Ionic molecules of different chain lengths will be tested for their ability to extend co-ion exclusion beyond mesopores into the macropore portion of capacitive electrodes. Adsorption studies will be performed to determine the number of ionic groups attached to the nanoscale electrode pore surfaces and to determine the robustness of their attachment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
METFORA LLC
SBIR Phase I: Detection of Chronic Diseases via Multiplex Analysis of Circulating Metabolites
Contact
13575 S SONOITA RANCH CIR
Vail, AZ 85641--8844
NSF Award
2212865 – SBIR Phase I
Award amount to date
$255,706
Start / end date
02/01/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel metabolite diagnostic blood test indicative of early-stage diseases including cancer, chronic heart and lung disorders, and diabetes. The technology analyzes specific panels of blood metabolites indicative of changes in cellular function that occur with disease. This technology reduces the diagnostic interval time from years to weeks or days, diminishes misdiagnosis resulting in improper therapy, and has the potential to alter the use of more invasive diagnostic methods such as biopsies, colonoscopies, and heart catheterizations from an exploratory to a confirmatory role.
This Small Business Innovation Research (SBIR) Phase I project aims to use specific panels of circulating metabolites measured using mass spectrometry (MS) and analyzed using artificial intelligence to detect chronic disease conditions. Pre-clinical models have demonstrated that alterations in metabolism occur at the stage of mild disease, before overt symptoms become evident. The first specific condition to be evaluated in this project is pulmonary arterial hypertension. The objective is to establish calibrated MS methods with quantified values of multiplexed metabolite panels in a reproducible manner as required for clinical use. Multi-label classifications will also be developed in order to detect and account for various co-morbidities that can affect overall metabolic changes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MICROPURE GENOMICS INC.
SBIR Phase I: Rapid, End-to-end Sample Preparation for Sequencing Applications
Contact
651 N BROAD ST
Middletown, DE 19709--6402
NSF Award
2222688 – SBIR Phase I
Award amount to date
$274,199
Start / end date
01/01/2023 – 12/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project consists of advancing methods for preparing deoxyribonucleic acid (DNA) for sequencing. Prior to sequencing a biological sample, DNA must be liberated from cells and separated from proteins and other unwanted debris, and then mixed with specialty buffers and chemical agents. This skilled task is currently carried out by trained scientists using largely manual manipulations of the samples and expensive equipment. The alternative method proposed in this project will speed-up diagnoses from genomic sequencing by significantly reducing preparation time while also making preparation more reliable through automation. Notably, the proposed approach is expected to prepare DNA without reducing its length; consequently, the process should be ideally suited for preparing samples for emerging long-read sequencing technologies. These improvements have the potential to decrease the burden and costs associated with DNA sequencing, hence expanding the benefits of DNA sequencing technology to wider segments of society.
This Small Business Innovation Research (SBIR) Phase I project relies upon a process for trapping genomic material in a small flow cell through which an electric field and pressure-driven flow are simultaneously applied. The process is highly selective towards strands of DNA or (ribonucleic acid) RNA; proteins and other, unwanted debris that enters the flow cell passes through. Also, the process is relatively gentle, so the length of sample should not be shortened as a result. This project will advance the technology to the marketplace by: (1) Completing cartridge design details and fabrication, including evaluation of material options; (2) Building a custom research and development platform for interfacing with the cartridges; (3) Developing methods for DNA sample extraction and transfer; (4) Developing the library preparation protocols using mixing and heating while toggling the Electro-Hydrodynamic Trapping; and, (5) Integrating the entirety of the preparation process into a single cartridge and validating the process 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. -
MINDTRACE TECHNOLOGIES, INC.
SBIR Phase I: A cognitive dashboard to support clinical decision making in neurosurgery
Contact
625 LIBERTY AVE
Pittsburgh, PA 15222--3110
NSF Award
2213231 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 07/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to support the ability of neurosurgeons to remove brain tumors or brain tissue that is causing seizures while protecting the patient’s mental function. As many as 4 in 5 neurosurgery patients self-report a cognitive difficulty after surgery that negatively impacts their quality of life. Neurosurgical interventions to remove brain tumors or treat medically refractory epilepsy try not to cause post-operative cognitive deficits in patients, but sometimes the pathological tissue that needs to be removed is involved with brain tissue that supports critical abilities, like the abilities to talk, remember, or move. Because there is inter-individual variability in the precise location of higher critical functions (e.g., language, memory, locomotion), each patient’s brain must be mapped in a personalized way. Ultimately, patients want confidence they will be the same person coming out of brain surgery as they were going into surgery, and clinical teams want tools that support quantitative pre-operative surgical planning and evidence-based projections of post-operative function.
This Small Business Innovation Research Phase I project seeks to support the development of a software product that enables neurosurgical teams to track patients’ mental function over the trajectory of their care, i.e., a type of cognitive dashboard. Current practice lacks a tool that identifies brain tissue that, if removed, would result in long-term cognitive deficits. This project’s core deliverable is a turn-key software platform that supports brain mapping protocols, as well as assessment, scoring, archiving and sharing of measures of mental function across the timeline of care of each patient. The software platform will integrate with critical existing systems already in place in all medical centers (e.g., cranial navigation, electroencephlogram (EEG), and magnetic resonance imaging (MRI) stimulus display systems). Follow-on work to this project’s core deliverable is based on the premise that data from prior studied patients can be used to train artificial intelligence/machinge learning (AI/ML) algorithms which can then be used to simulate the expected effect of a given surgical plan on a new patient’s future cognitive 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. -
MNT SMARTSOLUTIONS LLC
STTR Phase I: Superparamagnetic, antimicrobial nanocomposites and magnetic toothbrush for synergistic dental care
Contact
1451 INNOVATION PKWY SE
Albuquerque, NM 87123--0001
NSF Award
2151653 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (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 oral health. Although the conventional antimicrobial compounds in oral cleaning products can kill certain types of bacteria, others are harder to remove. The proposed technology advances a new oral cleaning device that uses magnetic nanoparticles to address this challenge. This project advances the research needed to make this solution effective.
The proposed project will develop a biofunctionalized magnetic nanoparticle ferropaste that can efficiently remove the oral bacterial biofilms under the control of an external magnetic field. The nanoparticles can significantly enhance antimicrobial activity. The core of the nanocomposites in this product have demonstrated strong magnetism and antibacterial characters in vitro. Under the external magnetic field provided by the magnetic toothbrush, the movement of the nanoparticles can be synchronized. Because of the nanoscale size, the nanoparticles can enter the oral biofilms through the pores on the surface and penetrate the cell wall of the bacteria. Therefore, these particles can disrupt the bacterial cell wall and break the dense biofilms to allow the released bacteria to be sufficiently eliminated by the antimicrobial compounds in the toothpaste. Additionally, the surface of the magnetic nanoparticles will be modified to increase the biocompatibility and favor incorporation into the biofilms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MODENDO INC.
SBIR Phase I: Ultrathin endomicroscope
Contact
1815 BLUEBELL AVE
Boulder, CO 80302--8021
NSF Award
2212906 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 04/30/2023
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 empower brain scientists with a high-resolution optical imaging instrument to reach currently inaccessible regions of the brain with minimal damage. The instrument contains thin fiber optics probes that enable access to very narrow cavities within the body or penetration of tissue. Deep brain imaging, photo-stimulation, and photo-ablation are possible applications, all of which could help understand brain function and potentially unlock treatments for brain diseases. The imaging instrument to be developed in this project may be amenable to scientific studies in animal models, addressing the need of neuroscientists and imaging facilities. The proposed technology could bring about innovations in biophotonics instrumentation as well as in the ensuing biomedical applications. The project seeks to advance novel imaging technologies with broad applicability addressing a new segment in the endoscopy market.
This Small Business Innovation Research (SBIR) Phase I project addresses a critical need in scientific brain imaging studies for endoscopes that are minimally invasive with a diameter in the order of 100 microns, which represents a cross-area about 10 times smaller than the thinnest existing endoscopes. While current endoscopes are appropriate for insertion in large cavities, their size produces excessive damage in brain imaging applications. The objective is to develop a new class of fundamentally less invasive techniques to investigate novel imaging probes, and to validate a prototype instrument in animal models. It is anticipated that in-vivo imaging of neurons with subcellular resolution at depth will become routine with minimal tissue damage. This novel imaging approach implements wavefront shaping in multimode fibers, using advanced machine learning and signal processing methods, to generate arbitrary digitally-reprogrammable light patterns and 3D images. The ultrathin endomicroscope (UTE) uses a spatial light modulator to first calibrate the fiber and then scan light at high speed, compensating for the inherent modal dispersion and intermodal coupling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MYCOLOGICS, LLC
SBIR Phase I: A novel biocontrol agent against fungal infection and fungal toxin contamination on food and feed crops
Contact
7551 FORDSON RD
Alexandria, VA 22306--2225
NSF Award
2208729 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (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 introduce a cost-effective way of crop protection from fungal spoilage. Every year, 25% of the food produced by the world is wasted due to fungal infections and contamination of crops with fungal toxins (mycotoxins). The combined social, environmental, and economic global annual cost of this food wastage is >$2T. The proposed innovation is centered on harnessing an untapped bacterium to bring a new line of affordable antifungals to a broad base of crop growers across the United States, which are designed to seamlessly integrate with existing preharvest postharvest treatment protocols. The products are quick and easy to manufacture without costly purification procedures. They should be safe for the environment and human health and have a defined mechanism of action. As a result, billions of dollars’ worth of crops, energy, and resources could be saved, leading to increased agricultural sustainability and economic competitiveness of the United States. It may also advance the health and welfare of the American public by enhancing food safety. Finally, it can pave the way for other innovations to combat fungal diseases in plants, animals, and humans.
The proposed project will demonstrate the feasibility of the innovation by developing the first product, safeguarding corn crops from fungal spoilage during both preharvest and postharvest. Corn is the most planted crop in the United States. Every year, the corn industry loses >$1B due to infection with a fungus (Aspergillus flavus), resulting in contamination of the crop with a carcinogenic mycotoxin called aflatoxin. The critical technical objectives during the project period will be to (1) identify the functional components of the product and demonstrate their mode of action; (2) assess the amounts of those components that can be produced per unit mass of bacterial biomass, (3) determine an optimal formulation of the minimal viable product that can be most effective in preventing fungal infection and aflatoxin contamination in the corn crop, and (4) conduct an optimal toxicity profiling of the minimal viable product. Upon completion, the knowledge obtained will provide valuable insights for effective intellectual protection and regulatory strategy for the products from the technology and identify any potential challenges related to scalability, consistency, and product shelf-life, which will determine the costs and logistics for large-scale manufacturing of the 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. -
Maine Shellfish Developers LLC
STTR Phase I: A cost-effective means of culturing large volumes of microalgae for land-based oyster farming.
Contact
193 CLARKS COVE R
Walpole, ME 04573--3307
NSF Award
2112253 – STTR Phase I
Award amount to date
$256,000
Start / end date
05/01/2022 – 04/30/2023
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 shellfish production at scale and in an environmentally sustainable fashion, using oyster farming as a launching pad. Today, most oysters are farmed nearshore under ecological stress. This project advances the culturing of microalgae using internal waste streams and those from other food industries. The focus of this project is to process one of the most abundant, sustainable, and freely available industrial food wastes, spent yeast from breweries, to facilitate algae production at scale onshore and indoors. Although currently used primarily by the food and chemical industries, the less costly algal product could also energize areas of food and feed, nutraceuticals, pharmaceuticals, biofuels, biomaterials, and bioremediation services.
The proposed project will advance the use of off-the-shelf bioreactors and a novel substrate which, along with CO2, form plant tissue heterotrophically in the dark as leaves do photosynthetically in the presence of sunlight. The proposed substrate enables production at scale of the single-celled microalgae that comprise much of the nearshore bivalve diet. The yeast is fermented with both agriculture-grade vitamins and plant-based commodities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NANO-PRODUCT ENGINEERING, LLC
STTR Phase I: Low Cost, Large Scale Production of Biocidal Micropowder by a Reversed Arc, Plasma-Fluidized Bed Reactor
Contact
705 SAN JUAN DR
Lafayette, CO 80026--1713
NSF Award
2136674 – STTR Phase I
Award amount to date
$255,966
Start / end date
09/15/2022 – 05/31/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is based on the improvement of respiratory equipment and personal protective equipment (PPE). Commercially available face masks, gowns, filter media and other PPE are contaminated through environmental exposure, posing a threat to healthcare personnel. The proposed solution is a high-surface-area antiviral/antimicrobial micropowder which can be applied to PPE surfaces. Improved protection from infections and reduced cross-contamination may result in fewer deaths, decreased healthcare costs, and increased economic productivity. The addressable global PPE market was $23 billion in 2020 and is expected to grow through 2028, while the global disposable face mask market was valued at $792 million in 2019, and the inclusion of other types of PPE increases this estimate further. The COVID-19 pandemic is driving the demand for these products, though the applicability of the proposed technology is not limited to COVID-19. The proposed product will be material that can modify the surfaces of fabrics with active antiviral properties, leading to improvements in health and safety. The customer base is expected to be healthcare personnel, pharmaceutical and food manufacturing facilities, the public, and manufacturers of PPE, medical devices, textiles, and filters.
This STTR Phase I project proposes to improve the antiviral/antimicrobial properties of respiratory equipment and PPE, which is typically only passively protective, is difficult to decontaminate and re-use, and can lead to worker exposure during changing and handling. The proposed solution is a high-surface-area micropowder, coated with an antiviral/antimicrobial coating, which can be applied to PPE surfaces. Unlike current technologies, the particle size, morphology, surface area, and topography can all be tailored for specific biocidal activity. Additionally, powder shape and surface quality can be customized to enhance adhesion. The proposed project is to develop a prototype powder product formulation that allows easy application of antiviral (copper alloy) coated particles to fabrics and other materials. This technology is based on a fluidized-bed, plasma-enhanced deposition process for synthesizing unique core-shell micropowders of metal, ceramic, or highly-shaped nanoforms of carbon, including proven biocidal materials. The synthesized microparticles will have high surface-to-weight ratios making them better suited for capturing micro-organisms while also having improved bonding to surfaces of filter media and PPE 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. -
NANODIAN, INC.
SBIR Phase I: A Drop-in Sustainable Cathode Replacement that can Allow Sub-$100/kWh Li-ion Battery Packs with Improved Safety and Performance
Contact
1329 COMSTOCK AVE
Los Angeles, CA 90024--5314
NSF Award
2126187 – SBIR Phase I
Award amount to date
$255,976
Start / end date
05/01/2022 – 04/30/2023
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project addresses the high cost and poor safety of Lithium-ion batteries in new energy applications. Low-cost and safe batteries will improve economic viability for solar energy storage, which is critical to increasing renewables penetration to above 30% of total power generation. This project advances a battery material to provide lower cost, higher safety and improved cyclability compared to currently used materials. This can support new batteries in applications including electric vehicles, grid-tied and solar storage, and consumer power tools, among others.
This SBIR project proposes a novel nanostructured LiMn2O4 cathode chemistry (ND-LMO) that offers ~30% lower $/kWh cost compared to incumbent nickel managanese cobalt oxides (NMC) materials. Furthermore, it will have iimproved performance parameters, such as cycle life, a safer heat generation profile, and a 10% greater amp-hour capacity between full state of charge and maximum depth of discharge. Many of these improvements stem from the “intercalation-pseudocapacitive” properties of finely nanostructured electrode materials. Technical challenges, such as inactive and deactivating surfaces, synthetic costs, and others, must be addressed for these systems to be commercially viable. The project’s proposed composition and methods used can be applied to other material 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. -
NEPTUNYA OCEAN POWER LLC
SBIR Phase I: Grid-Scale Marine Renewable Energy Technology Unlocked by Cost Reduction Innovations
Contact
901 NW 35TH ST
Boca Raton, FL 33431--6410
NSF Award
2208779 – SBIR Phase I
Award amount to date
$255,052
Start / end date
01/15/2023 – 12/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a novel mixed-mode (wind, wave, current) ocean energy converter that aims to be an improvement over the state-of-the-art offshore wind turbine design. This project will clarify design specifications to target a low-cost product with production scalability. Markets with the largest opportunity to benefit from this solution include US grid power, remote US islands (Puerto Rico, Guam, Hawaii, US Virgin Islands), other remote islands in the Pacific and Caribbean, and dispatchable power sources for emergency power generation like the Department of Defense. The environmental benefit of advancing the design of renewable energy converters and reducing the initial investments required by offshore clean energy may positively impact both the scope and the timeline for adoption of ocean renewables in the US.
This SBIR Phase I project will develop an efficient energy converter that drastically lowers the cost per installed unit through reduced weight of product components, onshore assembly, simplified installation, a lower center of gravity, and by achieving a storm rating. When coupled with offshore energy storage, this technology has the potential to unlock energy capture in ocean sites further offshore than is presently feasible. This project builds upon initial concept modeling and a 1/20 scale prototype construction, which validates the weight/power ratio, device stability, and comprehensive analytical evidence for commercial feasibility. Keeping the final cost-to-kilowatt low, while optimizing the overall design will be the major technical focus of the work plan, along with mitigating strategies for the risk of severe weather survivability. The proposed research will approach the design of each component individually with a focus on reducing cost and weight, while optimizing strength and output. Through the construction and testing of a proposed prototype, the team will conduct detailed analyses on scalability, performance, and cost factors that are critical for commercialization.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEUROENHANCEMENT LAB, LLC
SBIR Phase I: Neuromodulation device to promote healthy sleeping cycle
Contact
75 MONTEBELLO RD
Suffern, NY 10901--3746
NSF Award
2146931 – SBIR Phase I
Award amount to date
$255,851
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project aims to provide a safe, wearable device to to improve the quality of sleep. Sleep deprivation due to insomnia or other factors represents a significant health risk linked to various daily issues and later disorders in life. The lack of sleep costs the United States an estimated $411 billion in lost productivity and wages. This novel medical technology will provide an externally worn system which delivers a combination of low risk and reversible visual and auditory impulses, enabling patients to experience brainwaves associated with the desired restorative sleep stage. The product aims to capture a significant portion of the annual $80B global sleep aid market predominantly comprised of supplements and drugs.
This Small Business Innovation Research (SBIR) Phase I project will complete prototype engineering for a patient worn system which provides sensory stimulation in order to modulate brain waveforms during sleep. The system utilizes controlled and safe light and sound stimuli to transpose the brainwaves associated with the desired sleeping state into the recipient’s brain measured using non invasive electrical activity (EEG). The system is based on peer-reviewed evidence that normal brain wave patterns can be effectively transposed to a subject suffering from sleep disorders for restoring normative sleep. The phase I project will complete the data analysis of reference patient sleep patterns, and prototype design engineering to enable pilot studies and gaining evidence in subsequent stages.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEUROGENECES LLC
SBIR Phase I: Improved memory during sleep at home with a wearable EEG device for tailored stimulation of slow oscillations
Contact
1012 MARQUEZ PL UNIT 207A
Santa Fe, NM 87505--1832
NSF Award
2151469 – SBIR Phase I
Award amount to date
$255,732
Start / end date
06/01/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project improves memory for the elderly. Memory loss is a major concern of an aging population. The $29 B global memory enhancement market comprises supplements, training software, and drugs, although evidence of efficacy is limited. This project will create a user-friendly sleep headband with audio stimulation to improve memory. The solution will create a new category of non-invasive medical devices to benefit people in clinical, home, and professional settings.
This Small Business Innovation Research (SBIR) Phase I project demonstrates the feasibility of a wireless electroencephalogram (EEG) headband that increases memory consolidation during slow-wave sleep activity at home. Audio stimulation during slow-wave sleep activity using polysomnogram equipment has been previously demonstrated to enhance memory retention by facilitating memory consolidation. The envisioned headband acquires high quality EEG data to sense slow-wave brain wave activity and provide synchronous audio stimulation. The anticipated project outcomes are: a) a wireless sleep headband designed for comfort and usability, b) demonstration of enhanced slow-wave brain activity during sleep, and c) evidence of meaningful improvements to memory retention measured by standard clinical assessments.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEW HORIZON BIOTECH INC
SBIR Phase I: Determine Performance Characteristics During Cultivation of Living Organisms in a Novel Single-Use Horizontal Modular and Pressurizable Microbial Fermentor
Contact
500 HEMLOCK LANE
Nazareth, PA 18064--8500
NSF Award
2036270 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2021 – 05/31/2023 (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 significantly improve the ability to generate biological pharmaceuticals. The biopharmaceutical industry is working to grow specific genetically engineered microbial cells that will produce a vaccine, injectable protein, or other products. There is a pressing need to culture unique microbes, starting from small scale batches, that rapidly scale to commercially viable batch sizes with high product output. A pressurized horizontal fermentor supports the industry’s drive towards single-use bags for microbial fermentation, as single-use fermentors lower operating costs and reduce cross-contamination that can result in loss of an entire batch. This scalable, single-use fermentor should achieve higher yields and allow drug producers to produce kilogram quantities of protein in a more cost-effective manner. This innovative, flexible, pressurizable, horizontal modular design will decrease time-to-market for vaccines, therapeutic proteins or other microbially manufactured products, from both small and large biologics producers, to combat global infectious, and other diseases, at reduced operating costs, saving lives.
The proposed project will advance the knowledge of how microbial cells are cultivated in a horizontal, pressurized single-use bag fermentor. The knowledge gained will validate microbial production using a modular design that provides flexibility to adjust the capacity of the system, without significant facility modifications or cost. An initial prototype demonstrated highly encouraging results regarding fast mixing times, proper scalable power input, and excellent oxygen mass transfer. The design to be refined here has the potential to transform the biologics manufacturing industry by impacting the ability to generate high cell densities and reduce the cost of microbial manufacturing. Research objectives are to demonstrate: a fully developed design with the heat removal capacity required of high cell density fermentation (currently unachievable using existing industry vertical single-use fermentor designs); a pressurized bag system that can achieve oxygen transfer rates needed for high density cultures; and a scalable format that allows for rapid scaling to 3000 liters. A fully functioning test fermentor will be built and evaluated using both computational fluid dynamics analysis and laboratory testing of culture conditions. Experimental work will evaluate high agitation impellers, high gas flows, gas sparger designs, and system structural elements.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEW PAGE STRATEGIC CONSULTING, LLC
SBIR Phase I: Sustainable antioxidants for industrial process fluids
Contact
500 N TARRANT PKWY
Keller, TX 76248--5685
NSF Award
2222215 – SBIR Phase I
Award amount to date
$253,030
Start / end date
01/15/2023 – 12/31/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop bio-based antioxidant products for industrial processes. Commercial development of peptide antioxidants has been limited for use in consumer, food, or therapeutic applications. This project will develop peptide antioxidants derived from the enzymatic digestion of agricultural biomass as alternatives to synthetic antioxidants used in the processing and storage of industrial fluids. Although synthetic antioxidants are critical for the stabilization of many industrial processes, they are derived from petroleum and tend to have toxicity and/or environmental safety concerns. The products resulting from this effort will be first-in-class innovations; safer and more environmentally responsible than existing products. Project activities will validate peptide performance in the initial target application area: the stabilization of vinyl monomer fluids and processes. This research will initially focus on vinyl monomer processing as well as four additional industrial markets where sustainable antioxidants could have a high impact. The estimated consumption of synthetic antioxidants in the five combined markets in 2022 will be close to 1 million tons.
This SBIR Phase I project seeks to develop a bio-based antioxidant product derived from sustainable materials and suitable for industrial process fluids. Antioxidant peptides derived from the enzymatic digestion of plant-based proteins have the potential to replace synthetic antioxidants in industrial processes. This project focuses on process compatibility, product stability, and antioxidative performance as key technical hurdles. This project will create a library of antioxidative peptides generated by the enzymatic digestion of plant proteins. This library will then be tested for the solubility of peptides with representative fluids under process conditions, potential formulation design, and for thermal and storage stability of the designed formulations. This project will lower technical barriers to advancing the commercial development of peptide antioxidants for applications across many industries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NUMOOLA LLC
SBIR Phase I: Validating and Scaling a Financial and Entrepreneurial Aptitude Assessment
Contact
2818 SMALLMAN ST
Pittsburgh, PA 15222--4764
NSF Award
2151767 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of an intelligent and evolving tool that provides a framework to teach financial literacy skills to children. The literacy lessons are implemented at the child’s pace and stage of development. The product seeks to provide a family finance and entrepreneurism platform that combines real money, peer performance feedback, and artificial intelligence (AI)-driven education to teach youth how to responsibly use money and build businesses. By utilizing AI, the project will curate educational content into an immersive digital learning experience that is tailored to the individual regardless of wealth, demographics, or geographic location. Through this innovation, youth may be better positioned for success as they transition to financial independence. This project may also allow academia and industry to work together to validate an individual's financial preparedness and independence.
This Small Business Innovation Research (SBIR) Phase I project focusses on designing the principles and mechanics of a user performance feedback mechanism that promotes financial wellness. Financial literacy is important at every stage of life. The Phase I of this project is to develop a performance mechanism and uses deep AI techniques to baseline the goals for data collection and logical data organization, as well as to determine performance measurements and individual learner groupings. These metrics include static data, dynamic data, logical organization of data, calculation methods, and scoring principles. Once optimized, the outcome of the project may encourage individuals to achieve financial stability and success.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NUTHATCH ROBOTICS, INC.
SBIR Phase I: Three Dimentional (3D) Printing With Embedded, Layer-Crossing, Continuous Carbon Filament Reinforcement
Contact
63 BEDFORD RD
Lincoln, MA 01773--2031
NSF Award
2213040 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 04/30/2023
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to increase the all-around strength of three dimentional (3D)-printed polymer objects, which will make such objects more useful for structurally-stressed prototypes and manufactured products (including prototypes and products that are physically large). The prposed strength gains are expected from embedding continuous carbon-fiber filaments in multiple directions within the body of a 3D-print. Designers and engineers seek to tailor internal carbon-fiber arrangements to suit their specific needs. The resulting carbon-fiber-reinforced objects (as with 3D-printed objects in general) may be produced without the expensive and/or time-consuming use of molds, tooling, or specialized hand-labor. By facilitating the cost-effective production of strong, plastics-based custom and low-volume manufactured products, this project seeks accelerate product development, foster entrepreneurship, and encourage manufacturing endeavors within the United States by making it easier to turn imagined concepts into strong, functional objects in the physical world.
This SBIR Phase I project seeks to develop a process for embedding continuous, layer-crossing, carbon-fiber filaments within the body of a Fused Deposition Modeling (FDM) 3D print in order to provide tensile and shear reinforcement along planes orthogonal to the 3D printed layer. The goal of the research is to employ quasi-parallel filaments oriented orthogonal to 3D print layers, reducing the interlayer weakness and resultant structural anisotropy characteristic of FDM prints. The project will further examine the use of more complex filament arrangements to provide selective reinforcement in directions and along paths specified by a product designer. The overall strength, stiffness, and toughness will be assessed adn compared to conventionally-manufactured engineering plastics. The embedding process, which will take place simultaneously with the layer-by-layer creation of the print, will be achieved by combining the actions of FDM printer nozzles with those of automated robotic filament manipulators. The project will examine the geometric range of printed parts and components that incorporate reinforcing filaments, with initial goal of printing reinforced shell-like objects that continuously curve along multiple axes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Neptune Fluid Flow Systems LLC
SBIR Phase I: A Universal Connector for High-Density Microfluidic Chip Interfaces
Contact
11429 BANCROFT LN
Knoxville, TN 37934--1763
NSF Award
2151449 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (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 advance the lab-on-a-chip and other related life science platforms by the introduction of a new standardized microfluidic chip interface. The proposed project advances a novel interface to advance the applications and capabilities of microfluidic chips in both medical and non-medical fields, including dramatically increasing the rate at which doctors and medical researchers can prepare and perform diagnostic tests. The interface enables easy interoperability of devices as the chips can be freely switched out while the result of the hardware remains the same. The success of this project could lead to great breakthroughs in bioenergy, medical diagnostics, and drug therapeutics.
The proposed project undertakes the development of chip interfaces with reduced size and increased channel density by making use of novel interfacing and sealing methods, on a reusable micro-patterned surface. While the technology exists to fabricate microfluidic chips with much smaller dimensions, with more complex on-chip operations, and at a reduced cost, the current limitation is the size of the interfaces bridging the microscopic world of the fluid microchip with the macroscopic world of the laboratory. The work proposed herein could enable chips with 16x the density of sample channels, allowing for vastly more complex diagnostics to be performed and thereby vastly reducing the sample volume needed for accurate 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. -
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 – 12/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is 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. -
OAM PHOTONICS LLC
SBIR Phase I: Focal Plane Array for Active Coherent Imaging
Contact
10918 CAMINITO ALVAREZ
San Diego, CA 92126--5746
NSF Award
2015160 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2023
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 a cost-effective high-performance imaging technology with widespread commercial opportunities for industrial applications, such as autonomous navigation. The technology has the potential to greatly enhance the performance of autonomous navigation systems, enabling more precise detection of objects at further distances and enjoying greater robustness against environmental conditions. These capabilities help increase the safety of autonomous driving. The proposed technology is designed for manufacturability at low cost and high volume. Applications will benefit the defense, industrial, medical and scientific sectors, potentially bringing new opportunities in the areas of surveillance, security, remote sensing, machine vision, material surface characterization, biomedical imaging, as well as novel areas such as quantum imaging.
This Small Business Innovation Research (SBIR) Phase I project aims at developing a multi-pixel optical focal plane array (FPA) capable of coherent detection by leveraging photonic integrated circuit technology. Current conventional FPA technologies operate by direct photon detection wherein the incoming photons are converted into electron charges directly at each detection pixel. The measured signal is thus proportional to the intensity of the incident light. However, coherent detection measures both intensity and phase, with advantages including near-shot-noise-limited performance, background light rejection, and additional object information contained in the phase. The proposed technology will enable thousands to millions of coherent detection pixels to be fabricated monolithically on a photonic chip, enabling mass production. This research will result in a design of the coherent FPA with optimal detection performance and small form-factor.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OBJECTIVE ED, INC.
SBIR Phase I: Computer-based co-reading for students with reading disabilities
Contact
15355 TAKE OFF PL
Royal Palm Beach, FL 33414--8306
NSF Award
2150721 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2022 – 08/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide an out-of-school reading tool to complement and reinforce the in-school work of special education teachers. In the US, over 3.6 million students are assessed with reading difficulties, but school districts face challenges in providing appropriate services, specifically due to teacher shortages and budgetary constraints. Additionally, the number of students receiving special education every year is increasing. This research seeks to benefit school districts by enabling current teachers to become more effective in several ways: students will practice reading independently and receive appropriate feedback from the technology, the lesson plans will be customized by the teacher for the individual needs of the student, teachers will have additional time to concentrate on teaching new concepts or providing individualized attention to resolve specific problems, and teachers will have digital data on student progress tracking.
This Small Business Innovation Research (SBIR) seeks to produce a prototype that students can use at home to improve their oral reading. This prototype will use a cloud-based infrastructure and end-user application to perform computer-based co-reading with the student. The technology solution will: (1) validate the student’s reading accuracy and offer remediation when the student makes a mistake, (2) allow the students’ reading teacher to customize the reading experience and the remediation, and to monitor the student’s progress, (3) use engaging book content, (4) capture and analyze data including how the students’ eyes track as they read and this data will be displayed for the teacher, (5) capture audio of students’ oral reading, and (6) provide to the teacher with the captured audio, the corresponding text using automated speech recognition, and the students’ mistakes. This prototype will undergo efficacy testing and customer discovery, receiving feedback from Directors of special education and specialized reading teachers, in order to confirm the acceptable integration with current teaching 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. -
OCEAN MOTION TECHNOLOGIES, INC.
SBIR Phase I: Utilizing Reinforcement Learning to Optimize Ocean Wave Energy Capture
Contact
1627 JUNIPER RIDGE ST
Pomona, CA 91766--4113
NSF Award
2133700 – SBIR Phase I
Award amount to date
$255,558
Start / end date
08/01/2022 – 07/31/2023 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project seeks to facilitate the blue economy’s continued transition to a big-data paradigm. Currently, there is no cost-effective power solution for off-grid, small-scale, energy capture applications at sea. The project deliverables may benefit the commercial ocean sector as well as the Federal government and local municipalities by enabling cheaper and more reliable power at sea. This enabling technology may contribute to the ability for planners and decision-makers to anticipate and adapt to changing marine conditions, which will ultimately reduce costs and increase reliability for taxpayers. Additionally, to achieve its commercial objectives, the participating small business is committed to sustainability in its growth plan and aims to reduce carbon emission by working with local vendors and locally-sourced, recyclable materials. The small business will also continue its existing partnerships with local technical training/trade schools and workforce development programs to mentor underserved students and create jobs.
This Small Business Innovation Research (SBIR) Phase I project seeks to leverage advanced artificial intelligence for optimizing power output. The project seeks to demonstrate the application of advanced machine learning techniques to improve the efficiency and energy capture, and reduce the intermittency, of renewable ocean-based power generation. The project enables adaptability by using an advanced control model methodology which adjusts the device hardware based on ambient environmental conditions for optimized performance. Due to the deployment environment, this project will capture training data under a laboratory setting, train the control model offline, and apply it in the field by leveraging edge computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ONCOSTING LLC
STTR Phase I: Recombinant BCG as a novel immunoadjuvant for viral infections
Contact
17 S CHESTER ST
Baltimore, MD 21231--2008
NSF Award
2208609 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Technology Transfer (STTR) Phase I project improves treatment of viral conditions, starting with influenza. Each year seasonal influenza infects 9–35 million individuals, causes 56,000 deaths in the U.S., and costs $87.1 billion. The proposed technology has the potential to produce more rapid protection, expand pathogen/variant coverage, and extend the longevity of protection afforded by influenza vaccination and other vaccines. This added protection will reduce the high healthcare costs and productivity losses due to mortality/morbidity. This technology has the potential to serve as a rapidly deployable prophylactic or vaccine adjuvant to enhance protection and reduce the necessary vaccine dose, expanding access and providing a timelier response.
This Small Business Technology Transfer Phase I project advances a next-generation vaccine adjuvant platform. While vaccines represent a major medical success, several diseases have proven difficult to address, including seasonal and pandemic influenza, tuberculosis (TB), malaria, hepatitis C virus (HCV), and HIV. One way to improve the efficacy of vaccines for these diseases is to use an adjuvant to strengthen the immune response to the antigen presented via vaccination. The proposed technology has the potential to enhance the efficacy of vaccines against a wide range of infections directly and via heterologous immunity because the addition of “Stimulator of Interferon Genes” (STING) agonist overproduction to Bacillus Calmette-Guérin (BCG) serves a dual purpose: it enhances the elevated trained immunity of macrophages already known to be conferred by BCG and promotes critical antiviral IFN-I responses. The key objectives for this project are: 1) Optimize media and lyophilization for manufacturing of BCG-STING; 2) Evaluate the immunological effects of BCG-STING as an adjuvant for H1N1 influenza vaccination; and 3) Assess the protective effects of BCG-STING as an adjuvant for H1N1 vaccination. This will provide proof of concept for proceeding with the development of this novel recombinant BCG as an efficacy-boosting adjuvant that also offers intrinsic antiviral immunity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ONESEVENTEEN MEDIA, PBC
SBIR Phase I: An intelligent mental health care companion for kids
Contact
4012 BERKMAN DR
Austin, TX 78723--4543
NSF Award
2112093 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/15/2022 – 06/30/2023 (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 proactively identify and resolve mental health issues for children ages 10 - 18 before treatments and consequences become more acute and significantly more costly. This project innovation proposes bringing care to children at the onset of need using chatbot companions tailored deliberately and precisely to each child’s mental healthcare needs. Optionally, a child can be paired with live chat therapists and coaches no matter where the child is — at home, school, or when on their own. The system leverages proven mobile device-accessed Cognitive Behavioral Therapies in tandem with machine learning (ML)-enabled technologies that learn from a variety of interactions with the child to detect and digitally triage their experiences of loneliness, anger, anxiety, and depression and to alert adults when intervention and treatment are deemed necessary. Without appropriate care, these symptoms frequently increase in severity over time and become more difficult to treat. Intervening early can help slow or halt mental illness, reducing for parents, schools, and society the practical and financial burdens associated with reactive, generalized mental healthcare treatments while nurturing children into happier, healthier adults.
This Small Business Innovation Research (SBIR) Phase I project seeks to build a system to determine the nature and severity of a child’s mental health needs through real-time, early detection. Research reveals children face more barriers than adults when obtaining mental healthcare, especially in rural, marginalized, and low-socioeconomic-status communities. Due to a severe shortage of child behavioral health practitioners across the country, children frequently wait up to a decade between the onset of mental health symptoms and treatment. This project seeks to eliminate the delay between when children first experience mental or emotional needs and when they receive appropriate care, ensuring they flourish—not flounder—during those crucial developmental years. Leveraging ML algorithms and proprietary question weighting, the project focuses on: 1) algorithm development to determine the most effective combination of chatbot and live chat counselor engagements to understand a child’s immediate issues and provide resolutions for the child and their parent(s); 2) improvements to ensure the responses are fit for purpose, recognizing and flagging appropriate conversations for human interaction; and 3) refining the frequency and content of notifications; such as, adaptive motivational messages and recommendations to counselors for tailoring 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. -
ONYX AEROSPACE, INC.
STTR Phase I: Development of an Additively-Manufactured, Non-Toxic, Advanced Storable Hybrid Rocket Propulsion System
Contact
3414 GOVERNORS DR SW STE 210
Huntsville, AL 35805--3655
NSF Award
2127098 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 seeks to make orbital maneuvers affordable for large and small CubeSat operators. The proposed technology seeks to supply the market with an affordable, “green”, reliable, and easy to integrate modular propulsion system. Minimal integration requirements will allow CubeSat operators to focus on mission objectives and payload first, instead of the propulsion system integration. Today, integrating a propulsion system requires significant accommodations for thermal, electrical, and volume requirements and hazardous propellants limit available launch service. Both of these factors contribute to increasing cost and lenthening schedules. The goal of this project is to make advanced maneuvers, interplanetary trajectories, rapid end of life disposal, and accurate course corrections accessible capabilities for CubeSats. Accessible propulsion may also reduce orbital congestion as fewer maneuverable satellites can equal the capability of many statically-positioned satellites. CubeSats have already enabled rapid deployment of capabilities including low latency communication relays, defense purposes, and scientific research ranging from fundamental physics experiments to Earth observation. The proposed technology seeks to enhance CubeSat capabilities, opening new industries and discoveries for the next great generation of scientists, engineers, and entrepreneurs.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop the technology and produce a prototype spaceflight-ready design for a commercially-available, chemical-hybrid propulsion system. Conventional hybrid systems have shown significant downsides due to complex manufacturing, single use and/or toxic ignition systems, and low fuel regression rates. This technology seeks to solve these issues by utilizing a 3-D printed thermoplastic as the base fuel, which has electrical properties that allow for repeatable, rapid, and low power ignition. Some potential propellant combinations have a high theoretical performance, but are incompatible with the ignition method, have a low fuel regression rate, or are difficult to manufacture. After testing propellant combinations for compatibility with the ignition system, the system performance will be simulated. The performance data will be used to evaluate and design a prototype propulsion module. The fuel will be exposed to a simulated space environment and a lab weight scale test will be performed to verify the simulation results. The proposed research plan will identify the best option to produce a competitive and reliable integrated CubeSat propulsion system, with a test campaign constructed to provide confidence that a prototype system will perform as designed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPTAVE DIAGNOSTICS LLC
SBIR Phase I: Endoscopic Probe for Molecular Imaging and Diagnosis of Cancerous Prostate Pathologies
Contact
1100 WICOMICO ST
Baltimore, MD 21230--2043
NSF Award
2210021 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (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 outcomes for patients with prostate cancer, which affects about one in eight men and is the second deadliest cancer among men. The current process for diagnosing prostate cancer is imprecise and commonly involves multiple rounds of increasingly invasive, uncomfortable, and expensive diagnostic tests. The medical technology proposed in this project will reduce the number of unnecessary biopsies and expensive magnetic resonance imaging tests (MRIs) performed to confirm diagnosis, and enable improved ongoing monitoring of suspected or recovered prostate cancer patients. The proposed device will help hospitals save valuable time and decrease overall costs of care. The device will be designed to address the specific needs of clinicians to accurately diagnose prostate cancer cases at an earlier point in the diagnostic workflow, at a lower cost to health systems. Additionally, the technology will be developed with a focus on cost effectiveness, to ensure increased prostate cancer diagnostic capabilities are accessible even in low-resource settings, such as rural communities and low- and middle-income countries.
This Small Business Innovation Research Phase I project will result in a prototype of a new medical device that uses photoacoustic imaging (PAI) and novel acoustic lens technology to aid in detection and diagnosis of prostate cancer. Existing early testing options, such as digital rectal exams, prostate-specific antigen tests, and transrectal ultrasounds, are often inconclusive. The PAI endoscopic probe device proposed in this project will offer hospitals and clinicians a new method for visualizing potentially cancerous prostate tissues, with higher imaging contrast and resolution than existing diagnostics. It will also offer an alternative to other testing methods with known deficiencies that often result in misdiagnosis or missed cases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPTIC FRINGE CORP.
SBIR Phase I: Artificial Intelligence (AI)-Aided Part Identification for Coordinate Measuring Machines
Contact
8 COBBLESTONE WAY
North Billerica, MA 01862--2915
NSF Award
2222967 – SBIR Phase I
Award amount to date
$274,536
Start / end date
01/15/2023 – 10/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a new generation of smart machines used in the measurement of parts and assemblies. The team has demonstrated that this technology can convert existing coordinate measuring machines to self-driving autonomous machines. The ability to automatically measure parts is an important feedback link in the process chain that will enable fully automated manufacturing of the future. Specifically, this automation will reduce the specialized skill required to use a Coordinate Measuring Machine (CMM). The innovation will enable workers to operate a CMM and get a precise part measurement. This device is especially helpful as the skilled manufacturing/metrology workforce is retiring as it gives new employees the ability to provide accurate information with little/no training. This innovation also gives the manufacturing companies an option to buy a new machine or upgrade their existing coordinate measuring machine. While the focus of this proposal is part identification, this technology has ready applications in Computer Numerical Control (CNC) machining, robotics, and automated assembly lines. This capability will make the US manufacturing sector stronger and more technologically advanced.
The objective of this proposal is to develop a new technology to identify machined parts and assemblies. This technology will be implemented on coordinate measuring machines (CMM), which are used widely in the manufacturing sector to measure the shape and size of parts. The proposed technology will enable autonomous measurements of parts allowing a higher level of automation. In this identification technology, the team will use live images from a camera, multiple solid model/Computer Aided Design (CAD)-generated images, and advanced image processing. Applying Artificial Intelligence (AI)/Machine Learning (ML) to the image processing of part images will ensure correct part identification. Correct identification of parts as seen by the camera is the remaining unsolved challenge to achieving self-driven automatic measurements of parts. Most machined parts are textureless and most of the information is contained in the edges. Current image processing techniques work well with texture-rich parts but are unreliable with textureless machined parts. AI/ML enhanced image processing using edge and shape information is a promising approach, solving this problem will lead to the birth of a new generation of CMMs that can measure parts automatically.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OPTICAL METROLOGY SOLUTIONS LLC
SBIR Phase I: Novel Triangulation Gauge
Contact
2215 NOTT ST
Niskayuna, NY 12309--4336
NSF Award
2053336 – SBIR Phase I
Award amount to date
$255,981
Start / end date
08/01/2021 – 06/30/2023 (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 enable a critical tool for fast, high-performance measurement for precision parts manufacturing. High-precision parts are typically checked during manufacturing using fixed gauges based on 20-to-30-year-old technology costing several million dollars a year in maintenance and can take 2-3 hours using contact methods, out of a total of 20-24 hours of machine time. Improved measurements of parts in process will lead to better manufacturing practices and higher-quality parts. The proposed capability would reduce the time required for this step by a factor of 8 to 10, making in-process measurement more economically viable as well as improving machine utilization in a plant by as much as 20 percent, potentially driving savings of over $100 million per year industry-wide.
The intellectual merit of this project is the development of new techniques needed to create a long-range, high-precision laser triangulation gauge usable on a wide range of surfaces. Traditional laser triangulation gauges have changed little in the past 40 years, providing a reliable but limited point or profile measurement used widely in manufacturing today. Current laser gauge range-to-resolution is around 2000 to 1, achieving perhaps 4000 to 1 in special circumstances. A range-to-resolution capability of 50,000 to 1 would greatly expand the application potential of such gauges. The proposed project reimagines the basic mechanisms in triangulation gauges to separate the measurement process from the noise inherent in laser-based systems. Rather than imaging a laser spot from the part surface, the method will use a direct angular measurement of the light. This objective will be realized by adapting phase measurement methods not used in triangulation gauges today. The anticipated result will be a gauge with micron-level resolution over distance ranges of 300 millimeters and over variations in surface finish and texture. This capability will fill a critical void in measurement tool capability for 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. -
OPTIMIZING MIND
SBIR Phase I: Modular and Updatable Artificial Intelligence (AI) for Robotics
Contact
3168 SOUTH CT
Palo Alto, CA 94306--2949
NSF Award
2127085 – SBIR Phase I
Award amount to date
$254,746
Start / end date
02/01/2022 – 12/31/2024 (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 novel recognition architecture to computer vision in the robotics industry. The project seeks to enable computer learn without rehearsal, allowing corrections for details that are present in the real world environment. The aim of this project is a solution to be used by computer vision customers to solve their problems immediately (without sending data back to retrain the whole network), reducing machine and customer downtime and disruption while increasing productivity. The initial focus is on robotics with computer vision limitations though the technology may be useful to other industries. Success in improving computer vision-based learning could facilitate disaster responses, augment current physical abilities, and enable exploration beyond the boundaries of Earth.
This Small Business Innovation Research (SBIR) Phase I project will help create a framework to overcome rehearsal requirements that limit automated robots’ utility within life-like, dynamic environments. Artificial intelligence (AI) remains inflexible compared to humans at quickly accumulating knowledge without forgetting what they have previously learned. Robots using AI are currently only used in environments that are very limited and are very tightly controlled. Everything that might happen in the robot’s work environment must be included their training set. The proposed AI solution is suited for learning in dynamic environments without rehearsal while maintaining scalability as information is encountered. This technology may allow robots to be trained within their environment. This project may enable visual capabilities leading to a demonstration of flexible learning without rehearsal within dynamic robotic 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. -
ORALIVA, INC.
STTR Phase I: Portable single cell cytology and predictive analysis platform for the early detection of epithelial cancers
Contact
2135 ARIELLE DR APT 2403
Naples, FL 34109--0369
NSF Award
2233372 – STTR Phase I
Award amount to date
$275,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will address the need for an accessible method to identify early-stage epithelial cancers, with high accuracy, earlier and at lower cost than is currently available. In 2020, the total cost of cancer care was nearly $210 billion. Due to the nature of current cancer diagnostics, most cancers are diagnosed and treated during late-stages. This results in a large economic burden to patients, families, healthcare providers, and facilities. To advance the health and welfare of the public and reduce the nation’s healthcare burden, there is a need for cancer screening, diagnostic, and monitoring devices that are non-invasive, cost-effective, easy-to-use, and accurate. The proposed platform for the early detection of multiple types of epithelial cancers 1) addresses the lack of effective non-invasive portable screening devices; 2) provides faster, more discriminatory assessments in near real-time; 3) yields the most precise and accurate results to identify cancers earlier, when interventions are more impactful, less expensive, less invasive, and more likely to improve patient outcomes.
This Small Business Technology Transfer (STTR) Phase I project seeks to establish the feasibility of developing the first portable, programmable, single cell cytology platform for early detection of multiple types of epithelial cancers, suitable for use at the point-of-care. The proposed technology will uniquely combine microfluidics and artificial intelligence (AI) to act as a sensor and provide predictive analysis, allowing for the accurate classification of potentially cancerous tissue. The platform will support near real-time, multiparameter, single-cell cytology measurements and will provide a method for automated analysis of a plurality of key metrics. Proof of concept has been established for the application area of oral cavity cancers, with the approach demonstrating superior performance metrics compared to other diagnostics (tissue reflectance, tissue auto fluorescence, salivary testing, and cytology testing). It is the only adjunct that can distinguish between mild, moderate, and severe dysplasia. The key objectives for this project are to develop methodologies to link different clinical specimen types to the microfluidics environment, and a biomarker discovery process to identify biomarkers for different applications that are amenable to the platform. The successful completion of this project will enable the platform to recognize and assess various levels of dysplasia across multiple epithelial cancer types.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ORIGEN HYDROGEN, INC.
SBIR Phase I: Improving Anion Exchange Membrane Water Electrolyzers via Novel Electrode Geometry
Contact
733 INDUSTRIAL RD
San Carlos, CA 94070--3310
NSF Award
2223148 – SBIR Phase I
Award amount to date
$274,919
Start / end date
09/15/2022 – 06/30/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to enable very highly-efficient low-cost green hydrogen production by improving a key functional component of a promising water electrolysis technology. Green hydrogen is a chemical fuel and a feedstock with no associated CO2 emissions. In an effort to decarbonize our economy, green hydrogen can address sectors of our economy that are not easily electrified using clean electricity, for example steelmaking, chemicals, heating, and heavy transport such as shipping and aviation. However, the cost of green hydrogen is still too high to prompt large-scale adoption. The pure-water electrolyzers developed in this project can significantly reduce green hydrogen production costs compared to the current state-of-the-art: they require only water and electricity as inputs, and are entirely made of low-cost, non-toxic materials, utilizing domestic supply chains. They are modular, enabling the development of both large hydrogen production facilities and small decentralized systems, e.g., for on-site operations or refueling stations. This project will not only help the adoption of green hydrogen, it will also elucidate how the chemical and electrochemical modifications of active surfaces can more broadly be used to make electrochemical reactions, such as water splitting, more efficient.
This SBIR Phase I project proposes to drastically improve a key component of an anion exchange membrane water electrolyzer (AEMEL): the anode electrode. The anode is the site of the oxygen evolution reaction (OER), a required but inefficient step during electrolytic hydrogen production. Enhancement of the OER kinetics by improved anode design, if translated to commercial AEMEL systems, would directly lead to a lower cost of green hydrogen. This project aims to replace the conventional two-layer anode, in which a complex catalyst layer is coated on top of a porous transport layer (PTL), with a simpler “unified” anode, in which the PTL is functionalized such that the catalyst layer is no longer necessary and the reaction kinetics are improved. In this project, two approaches to functionalize the PTL surface will be combined: the increase of the electrochemically active surface area (via etching, dealloying, and deposition techniques) and the increase of the intrinsic catalytic OER activity (via alloying and deposition techniques). This effort is expected to result in significantly improved AEMEL performance and lifetime, which will be evaluated using electrochemical methods, both ex situ (3-electrode cell) and in situ (in an operating electrolyzer).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OT APP DESIGN LLC
SBIR Phase I: A mobile, device-based, screening tool for assessing K-6 students’ cognitive and motor skills via machine learning handwriting analysis
Contact
600 NE 36TH ST APT 1508
Miami, FL 33137--3941
NSF Award
2111898 – SBIR Phase I
Award amount to date
$255,993
Start / end date
04/01/2022 – 03/31/2023
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 1 project is to improve the assessment of cognitive and motor skills in K-6 students. More specifically, this project will develop and perform feasibility testing of a novel, objective, and machine learning-driven approach to analyzing student handwriting proficiency, a measure of cognitive and motor skills. Through the use of a smart device application, end-users (teachers, aides, and parents) will be able to take a photo of a student's handwriting and receive immediate results regarding proficiency, handwriting error types, and targeted intervention suggestions. Given the myriad of visual motor, fine motor, and higher-order cognitive skills needed to generate a handwriting sample and the fact that up to 30% of students have difficulties, there is a need for new and better detection schemes. The identification of cognitive and motor skill deficiencies is becoming especially important with the increased use of virtual learning environments due to the COVID-19 crisis. Students are interfacing more with computers, and teachers have decreased access to handwriting assignments.
This Small Business Innovation Research (SBIR) Phase 1 project focuses on developing machine learning (ML) algorithms to generate highly accurate, rapid, and objective predictions of handwriting proficiency. These algorithms seek to predict the handwriting error sub-type. ML analysis of handwriting images has never been done before. Through the use of data annotation schemes, highly sensitive and grade-specific algorithms will be created and accessed by a smart device application following the acquisition of a single photo of a single handwritten sentence. This technology is envisioned as a universal screening tool to be used at the beginning of each school year to identify students with subpar handwriting proficiency. The real-time analysis of handwriting proficiency will allow for earlier identification and earlier interventions to improve student outcomes and deliver cost savings to school districts.
This award reflects 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 – 11/30/2023 (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. -
PHAXTEC, INC.
SBIR Phase I: Production Pathways of Biopolymers for Barrier Paper Coatings
Contact
12324 HAMPTON WAY DR STE 201
Wake Forest, NC 27587--6543
NSF Award
2151428 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
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 new sustainable packaging materials. An important class of materials is polyhydroxyalkonoates (PHA). Production of PHA from carbon sources has generally been associated with high costs, precluding widespread adoption. Natural gas and biogas are cost-effective alternatives, however, and established PHA-producing microbes use only about half the carbon from methane, releasing the rest as carbon dioxide. This project will develop protocols to use newly discovered microbes for efficient PHA production. The newly discovered microbial platform would enable efficient utilization of biogas with high carbon conversion, allowing high efficiency and (near) zero emission PHA production. The produced PHA will be formulated into barrier paper coatings for food service packaging that is recyclable, compostable, and marine-biodegradable.
The proposed project will validate and develop the biological pathways for high-yield conversion of biogas using newly discovered microbes. Current PHA production remains noncompetitive to fossil-based polymers due to relatively high raw materials cost and low polymer yield with established microbial platforms, utilizing only a portion of the carbon from methane and emitting the rest as carbon dioxide. Breakthroughs in PHA production cost require high-efficiency carbon conversion. The microbes of interest have demonstrated improved carbon conversion, high polymer yield, and the promise for a (near) zero emission production. The goals of the project are to elucidate and optimize the cultivation parameters of the newly discovered cultures and build novel PHA copolymer pathways in the organisms by constructing synthetic biology framework(s). The project will also develop fermentation protocols that optimize yield for producing commercial PHA copolymers for further 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. -
PHOENIX WASTE SOLUTIONS INC.
SBIR Phase I: Advanced Scalable and Sustainable Waste Disposal System
Contact
7111 TOU LOU LOU ST
Chauvin, LA 70344--2427
NSF Award
2125671 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 03/31/2023
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 management of Municipal Solid Waste (MSW) in a sustainable fashion. The proposed system can manage MSW without generating toxic air emissions, reducing greenhouse gas emissions by 98% compared to landfills and incineration. An additional benefit is that waste does not need to be separated, thereby promoting recycling of glass and metal, as they are left untreated. In addition, the technology is envisioned to be affordable and easily deployed to enable on-site treatment, saving transportation costs and associated impact. Finally, the system has the potential to use excess heat to generate electricity and use the by-product effectively. This system promotes a circular economy and supports multiple benefits to the environment.
This project advances development of a novel system of applying gas plasma to create thermal degradation of MSW. Phase I objectives are to research, design, construct, and test a prototype and define an industrial-scale design. Tasks include testing functionality and emissions quality with a variety of waste feedstock and operational parameters, and conducting a life cycle analysis. Furthermore, the project will explore the co-generation of electricity and beneficial reuse of the ash by-product.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PIERSICA, INC.
STTR Phase I: A new class of highly conductive solid polymer separator membranes compatible with high voltage cathodes
Contact
2051 E PAUL DIRAC DR OFC 180A
Tallahassee, FL 32310--3760
NSF Award
2221874 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2022 – 08/31/2023 (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 transformational to multiple markets that require energy storage. High-energy densities will be enabled by the proposed advanced polymer separators. Potential customers for the new battery separator include battery manufacturers for a variety of applications including, but not limited to, space and military, small wearable devices, Radio Frequency Identification (RFID), drones, consumer electronics, as well as automotive manufacturers in the mass mobility market. Adoption will be driven by the huge demand for electric vehicle batteries that are cheaper, lighter, safer and allow for longer drive ranges and reduced charge time. There are multiple ways in which consumers and society will benefit from the batteries enabled by this novel solid-state separator; from electric cars, to flying taxis; from more efficient energy storage grids to more reliable space vehicles; from lighter wearable devices to long lasting medical implants. In the long-term, the successful development of low-cost, fast-charging, high-density, long-life, and safe batteries enabled by the company’s new separator will reduce fossil fuel dependency and drive the electrification of the transportation sector and the transition towards greener energy solutions.
This Small Business Technology Transfer (STTR) Phase I project will develop an advanced polymer separator for novel hybrid solid/liquid battery cells which will dramatically improve performance of state-of-the-art solid-state batteries, enabling higher energy density, faster charging rate and enhanced safety over commercial Lithium-ion batteries. The new separator will be constructed from a novel polymer material whose feasibility has been validated at laboratory level. Stability tests showed higher conductivity and stability than currently available options. Compatibility with high-voltage cathodes was also demonstrated in preliminary studies. The goals of the project are (1) to develop a solid electrolyte which has an ionic conductivity comparable to that of liquid electrolytes that are currently used in the Li-ion batteries and (2) a scalable solid separator (using the above electrolyte) that is compatible with high-voltage cathodes (4 – 6 V). Main technical hurdles to overcome for successful commercialization are developing blade-cast-worthy slurries and scaling up the separator to a cell-size free-standing sheet. The former will be achieved by tuning the composition of the slurry to improve solubility; the latter will be achieved by improving the molecular weight of the polymer and blending and mixing it with ceramic oxide.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
POWERSILO INC
SBIR Phase I: UpDraft Tower Technology for Geothermal Power Generation and Rankine Cogeneration
Contact
7250 REDWOOD BLVD
Novato, CA 94945--3269
NSF Award
2222965 – SBIR Phase I
Award amount to date
$255,966
Start / end date
01/15/2023 – 09/30/2023 (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 development of technology that unlocks the use of abundantly available geothermal hot dry rock energy for reliable renewable energy. This technology will be economically feasible and provide an optional zero emission cogeneration configuration for harnessing cooling loop waste heat from zero emissions thermal electric power plants. The additional benefits, broader impacts, and market opportunity for cogeneration applications create an increase in power generation efficiency and capacity. Increases in net zero emissions power will also be available at utility scale. This technology will reduce water use during wet cooling in power plants by replacing the iconic supplemental cooling towers for thermal electric power plants worldwide with cogeneration. Some larger and long-term societal impacts of this research include: a more stable power grid due to reliable geothermal renewable energy generation and a cleaner environment especially for populations living close to traditional power plants and industrial infrastructure. Global technology licensing applications include: grid flexing and resiliency, water desalination/filtration, green hydrogen production, and national security.
This SBIR Phase I project seeks to develop software that uses computation, measurement, observations, and computer models, based on sound theory to find operational boundaries, validate key performance metrics, and optimize functional parameters for more efficient power production. This research includes the examination of critical technology functions and elements that determine peak operational efficiencies. The goal of this research will be to produce analytical computer models to look specifically at: 1) air intake velocity for a given set of pressure differentials, 2) air intake impedance, 3) thermal/pressure gradients generated by heat exchange activity, 4) air flow impedance generated by heat exchangers, and 5) expected exhaust air flow given idealized intake, heat exchange configurations, and designs. Anticipated results will provide quantifiable and measurable data tables including system sizing, energy input requirements, and mechanical and organic inlet air flow with emphasis on modeling of data analysis and determining specific energy inputs and power outputs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRECIENT TECHNOLOGIES, LLC
STTR Phase I: Membrane Biofilm Reactor for Recovery of Valuable Metals
Contact
90 W COTTAGE LN
Tempe, AZ 85282--2100
NSF Award
2136392 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to use a biotechnology based Membrane Biofilm Reactor (MBfR) to recover valuable materials, including platinum group metals (PGM), Rare Earth Elements (REE), and other critical minerals and materials (CMM) using the natural metabolic processes of bacteria. These materials are used in battery and energy storage, semiconductor manufacturing and other industries. The demand for some of these valuable materials is likely to increase by as much as 4000% by 2040 and the USA is dependent on other countries for some of these products. Limited supply of PGM and REE is exacerbated by processing and recycling facilities losing ≥10% of the total market value of these materials in their wastewaters. The MBfR directly addresses this loss by recovering up to 99% of the lost PGM and REE as solid nanoparticles. Based on the concentration of valuable metals and co-contaminants in water samples provided by valuable-metals recyclers, a conservative 90% recovery of precious metals using the MBfR may generate more than six times the return on investment (ROI) for the customer in the first year. This project may help mitigate risks associated with materials shortages and moderate costs as demand continues to increase. The recovery of these materials from wastewaters may also avoid serious hazards to human and ecosystem health associated with their discharge.
This STTR Phase I project is organized into five objectives through which the company seeks to quantify the reduction and precipitation kinetics in relation to their hydrogen-delivery capacity. The company will also characterize the metal and mineral nanoparticles according to their chemical composition, purity, and size, as this affects how they can be used in industry. The objectives of the project include: continuous recovery of PGM and REE using the MBfRs, solid-state characterization of recovered PGM and REE in the MBfRs; characterization of PGM/REE-recovering biofilms in the MBfRs, and the development of a techno-economic analysis and technology-to-market strategy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRESAJ, INC.
SBIR Phase I: Combining Machine Learning with Clinical Expertise to Assess and Mitigate Risk in Healthcare
Contact
1950 44TH ST SE
Cedar Rapids, IA 52403--3983
NSF Award
2208120 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will improve health care outcomes associated with complex procedures. Approximately 1 in 7 major surgical procedures in the US is associated with a medical complication, totaling more than 4 million complications and $80 billion in costs per year. Many more complications occur in non-surgical settings. This project will use machine learning to combine proven engineering principles with clinical expertise to identify and address specific risks for each procedure, care facility, and patient (accounting for high-impact risk factors ranging from diabetes to social determinants of health). This technology will augment existing standardized, outcome-oriented quality-improvement tools with cost-effective customized, process-oriented tools in a novel way, with an envisioned initial application for the ~5,100 community hospitals in the US. A modest improvement of 1% of complications would annually reduce costs by nearly $1 billion and will save 4,500+ lives.
This Small Business Innovation Research (SBIR) Phase I project will use a systems-based approach to examine process-level risk in healthcare. Big data in healthcare is inconsistently structured and not optimized to directly improve patient outcomes. The large datasets for most procedures provide only high-level conclusions regarding risk; they do not pinpoint the specific steps in provider workflow with high risk or the role of external factors, such as comorbidities or facility age. This project will determine the feasibility of using machine learning supervised by experienced clinicians to assess risk using principles from Failure Modes and Effects Analysis. The project will develop a proof-of-concept machine-learning system that uses a proprietary risk taxonomy and modifiers to combine national, state, facility, and actuarial datasets to generate risk priority numbers for each step for a service line. This system will then be applied to coronary artery bypass graft surgery to assess its validity and clinical value. Monte Carlo simulations and clinician focus groups using a Likert scale will determine the significance of the results.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PRODUCTS FOR ANY LIFESTYLE, INC.
SBIR Phase I: Prototyping a Wearable Device that Continuously Monitors Biometrics using Machine Learning to Predict Meltdowns in Children with Autism
Contact
6629 TOWERING OAK PATH
Columbia, MD 21044--6037
NSF Award
2126364 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in its ability to use machine learning and wearable technology to reduce uncontrolled destructive episodees, known as meltdowns, in children with autism. Meltdowns are highly distressing events for these children and their families and may require intervention on behalf of emergency response personnel and healthcare providers. Treating individuals with autism by proactively detecting meltdowns will allow caregivers time to intervene, mitigate, and prevent the onset of destructive behavioral episodes. The ability to predict a meltdown, and then implement strategic intervention to prevent the meltdown, may have positive life-changing effects for the children, their families, and their caretakes by reducing social stigma, enabling more mainstreaming of school and family activities, and reducing significant financial healthcare burdens. This technology may also be used to mitigate panic attacks in individuals with post-traumatic stress disorders.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a wearable device that detects, predicts, and helps prevent meltdowns in children with autism. Wearable devices that measure physiological parameters are available in the market, but none of them are specific to autism, and none of them proactively predict behavior episodes. A unique feature of this wearable device is that it uses machine learning to predict meltdowns. Incorporating machine learning allows each device to learn the unique biometric signature of the wearer so it can predict meltdowns with high accuracy. When a child is at high risk for a meltdown, the device will detect the relevant physiology and alert caregivers and therapists in time to intervene. The objectives of this project are to create a prototype which includes the wearable product and the individualization enabled by machine learning to correlate a child’s biometric measures with behavioral states. The goal is to achieve decreased frequency and/or severity of meltdowns. By enabling caregivers of children with autism to take control of and prevent meltdowns, this project has the potential to eliminate the stigma these children face during a meltdown in public, and empowers the children to become more independent as they age.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PROMEDIX, INC.
STTR Phase I: Electronic Measurement of Capillary Refill Time to Improve Outcomes from Sepsis
Contact
4640 S MACADAM AVE
Portland, OR 97239--4232
NSF Award
2212728 – STTR Phase I
Award amount to date
$255,750
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is a novel external system for rapidly diagnosing sepsis by measuring capillary refill time (CRT). Independent clinical studies have demonstrated the utility of CRT for detecting sepsis. Current methods for monitoring capillary refill times rely on physical examinations that are both prone to human error and inconsistency. The company aims to develop an automated diagnostic and monitoring device for objectively and repeatably quantifying capillary refill time for use in a clinical setting. If successful, the technology may have widespread potential use in emergency departments, clinics, ambulances, or at home.
This Small Business Technology Transfer (STTR) Phase I project develops a new finger-sensor interface for monitoring CRT that ensures contact between the finger and sensor across a range of finger sizes and validate the system in human use. The objectives are to ensure human factors engineering to enable use in a broad range of patients by a wide range of caregivers. A novel algorithm to improve sensor performance and provide user feedback on noise or aberrant signals will also be integrated. The system will be tested in a group of patients at risk for sepsis to demonstrate the device reliably and accurately measures the CRT across a wide variety of patient demographics and the device is easily usable by a wide range of caregivers including physicians and family members without extensive training. A successful Phase I outcome is a system enabling the consistent ability to collect high-quality measures of CRT in patients at risk for sepsis and to provide the user with ongoing measures of signal quality.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 – 07/31/2023 (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. -
PROXIMAL, LLC
SBIR Phase I: An Easy-to-use Virtual Reality Development Toolkit for Education
Contact
1421 CAROLINA PINES AVE
Raleigh, NC 27603--2739
NSF Award
2126648 – SBIR Phase I
Award amount to date
$255,990
Start / end date
04/15/2022 – 03/31/2023
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 develop an easy-to-use virtual reality (VR) toolkit to enable rapid development and deployment of educational VR experiences. The COVID-19 pandemic made it clear that technology to enable remote learning is critical to education at all levels. However, instructors often do not use these technologies because they lack understanding of how to meaningfully deploy it in their courses. In order for VR to be useful in education, it must not just be easy for learners to use, but also must be easy for instructors to learn to use it. This project will create a user-friendly toolkit with which educators can create targeted, subject-specific, VR educational experiences. This learning tool may become an important part of future education as it will provide access for a diverse group of students of all ages and education levels who may be unable to be physically present (due to illness, location, or other social or socio-economic obstacles) to complete courses and curricula where on-site attendance is not possible.
This Small Business Innovation Research (SBIR) Phase I project fills an industry gap and unaddressed demand for educational simulations. Studies of students and instructors have shown that both want VR experiences as part of a broader demand for consumable instructional content. Developing this content, however, presents two interconnected technical hurdles: (1) developing pipelines by which existing digital resources can be used to create VR assets, and (2) creating a holistic user experience for non-technical users in the non-standardized computing environment of K-12 and higher education. Current state-of-the-art VR systems are often too complicated for non-technical users, requiring the user to have extensive programming skills, which many educators do not. This project seeks to develop methods to easily create VR assets from non-VR digital resources and a user experience (UX) structured around the “backward design” approach to instructional design. By building on the latest functionality for gestural interfaces to reflect interactions with physical spaces and objects, and developing templates to guide the instructional designer through the process, this project will enable instructional designers to develop realistic, compelling, and educationally valuable VR learning experiences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Precast Systems Engineering, LLC
STTR Phase I: Development of an Innovative Ultra High Performance Concrete Foundation System with Bio-inspired Surfaces to Support Renewable Offshore Wind Turbines
Contact
5320 CHESAWADOX DR
Exmore, VA 23350--4302
NSF Award
2222232 – STTR Phase I
Award amount to date
$274,956
Start / end date
01/15/2023 – 12/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to develop a marketable and cost-effective U.S. manufactured foundation system to support offshore wind turbines (OWTs). The planned offshore wind energy production in the U.S. has been growing rapidly and the industry is expected to be worth more than $1 trillion within the next two decades. Although only 42 megawatts (MW) of offshore wind energy were installed in the U.S. during the last 10 years, planned projects have been growing rapidly targeting 30 gigawatts (GW) by 2030 and 110 GW by 2050, with strong support from coastal states. Achieving the targets of offshore wind energy requires cost-effective and innovative components of these energy systems. One of the main costs for offshore wind energy systems is their foundations, with costs typically ranging from 14% to 34% of the overall project cost. OWTs are commonly supported on large-diameter foundations, which the U.S. does not have the capability to fabricate and instead relies on foundations fabricated abroad. Therefore, a U.S.-manufactured foundation system to support renewable offshore wind energy infrastructure, enhance domestic supply chains, and reduce dependency on foreign manufactured foundations is proposed. The result of this research is a U.S.-manufactured alternative with savings of over half the cost per meter, enabling wider adoption of alternative energy harnessing technologies.
The goal of the proposed project is to develop a U.S.-manufactured, bio-inspired, enhanced capacity foundation system to support offshore wind energy infrastructure that provides technical improvements and cost-saving to currently used systems. The proposed project also provides: (1) ease of adoption by providing similar weight and installation approaches to current means and methods; (2) better durability and longer service life than currently used OWT foundations; and (3) improved speed of construction promoting scalability. Furthermore, the proposed system will allow for optimized design, increasing the foundation capacity and improving the installation process. Preliminary tests show that the proposed design could improve the foundation capacity by up to 100% compared to that of the currently used foundation systems when subjected to long-term cyclic loading similar to those experienced by OWTs. The proposed concept could be used as a driven pile, suction caisson, anchors, or gravity base providing several options for the offshore wind energy industry in the U.S. To achieve the project goal, this research will focus on: (1) verification of key material properties for marine environmental conditions, (2) structural design of foundation cross-sections, (3) installation analyses on proposed foundations in marine environments; and (4) investigations of the effects of the bio-inspired design on foundation capacity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Pure Biomass Inc.
SBIR Phase I: Algae Cultivation Technology for Value Added Co-products from Waste Water Treatment Effluent
Contact
7776 ELM GROVE CT
Minneapolis, MN 55428--3873
NSF Award
2113705 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impacts of this Small Business Innovative Research (SBIR) Phase I project is to improve reuse of wastewater. This project advances a new algae reactor to reduce biological nutrient pollution. This will improve health, potential loss of commercial fishing resources, water tourism, and property value decline. The diversity of products that can be generated from algae cultivation improve the robustness of the global food chain and the security of domestic feedstocks, e.g. high nutrition feeds for livestock and aquaculture and a new source of chemicals and biofuels. The proposed design for maximum resource efficiency in water and energy enables value extraction from marginal lands.
The proposed project aims to reduce levels of biological nutrient pollutants in the effluent of wastewater treatment facilities—by the development of an industrial scale, algae photobioreactor, designed to operate in a high-volume, continuous flow process. Anticipated advantages of the new technology are a reduction in capital and operating expense compared to existing nutrient removal methods and the capacity to generate, high-purity, algae coproducts with commercial value. Research objectives include the following: (1) create a computational fluid dynamics (CFD) model of the reactor under various flow conditions; (2) perform dye tracer experiments in the reactor as validation of the modeling results; (3) install the reactor as part of an integrated nutrient removal system including ultrafiltration, product recycle stream, nutrient sensors and process feedback control; (4) evaluate the nutrient removal capabilities of the system using a live algae culture and effluent from an adjacent wastewater treatment facility; and (5) perform a technoeconomic analysis of the proposed process. Results of the project will provide a better understanding of the effect of reactor design and operating parameters on the hydraulic and solids residence time distributions, how these influence the waste removal performance of the system, and what design parameters exert the most control over economic 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. -
QUANTUM SIMULATION TECHNOLOGIES, INC.
SBIR Phase I: Matrix product state-based fermionic quantum emulator
Contact
20 GUEST ST STE 101
Boston, MA 02135--2040
NSF Award
2126857 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 05/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to enable the efficient emulation on classical computers of simulations carried out on quantum computing hardware. The proposed emulator technology is expected to address problems an order of magnitude larger than is possible at present using classical computing hardware. The emulator will be specifically designed for electronic structure calculations of molecules and materials. The successful completion of this project will disrupt the research and development associated with the use of quantum computing in the pharmaceutical and materials spaces by enabling faster assessment and development of quantum algorithms. Since it is widely accepted that these are impactful early applications of emerging quantum computing platforms, there is a paramount need for creating a user- and developer-friendly software stack specifically tailored for such simulations.
This Small Business Innovation Research (SBIR) Phase I project will support the development of a quantum emulator on the basis of the so-called matrix-product-state (MPS) representation of fermionic wave functions. The innovation results from the fact that the proposed emulator will be specifically designed for fermions and therefore can take advantage of the physical symmetries inherent in these systems. The first-principles MPS wavefunction ansatz has been developed in the quantum chemistry community in the context of the ab initio density matrix renormalization group (DMRG) over the past two decades, and will be generalized such that the same APIs as used for the standard quantum emulator will be exposed to users. The proposed new software is expected to allow for emulation of quantum simulations involving 100 spin orbitals/50 electrons, or more, on commodity classical computing hardware, which is an order of magnitude larger than is possible at present. In this SBIR Phase I project, a Python prototype and associated command-line tools will be completed to demonstrate the technology and commercial viability.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
QUIVER DENTAL, INC.
STTR Phase I: A Diagnostic Device to Measure Dental Implant Stability
Contact
4134 42ND AVE NE
Seattle, WA 98105--5125
NSF Award
2151367 – STTR Phase I
Award amount to date
$254,360
Start / end date
08/01/2022 – 07/31/2023 (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 aims to develop a novel method for monitoring dental implant stability. The system aims to provide a low cost temporary method for dentists to quantitatively assess the 27 million dental implants globally placed per year. These implants currently have a 10-15% failure rate. The proposed system provides mechanical feedback on the bond stability between the implant and the surrounding bone that serves as a foundation for the crown and receives bite loads. This bond stability provides direct, actionable information that may be superior to current subjective evaluations used by dentists including feel with their hands, X-Ray, or torqueing.
This Small Business Technology Transfer (STTR) Phase I project aims to complete a proof of concept demonstration of a reliable and accurate device to measure the stability of dental implants using vibrational technology. The proposed system seeks to provide controlled forces to the implant in order to sense the degree of motion and stability. This new technology has two critical concepts: the first is to quantify implant stability via angular stiffness at the gum line of the implant bone (i.e., the ability against rotation), and the second is the development of a clip-on sensor unit and a mechanics-based model to calculate implant stability. This project seeks to develop a prototype with a design validated on in vitro mandible models.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RADMANTIS LLC
SBIR Phase I: Adapting uncrewed aquaculture management to control sea lamprey and to protect wild salmonid fisheries of the Great Lakes
Contact
5470 LARCHWOOD LN
Toledo, OH 43614--1247
NSF Award
2212614 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/01/2023 – 07/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project focuses on improved methods for detecting and suppressing sea lampreys in the Great Lakes, a pest species that currently requires relentless, sustained, and costly control efforts at ecosystem scale. The project initiates the development of small, relocatable, field-deployed devices, capable of performing a range of assessment and selective control functions. Success in this effort will introduce an important new tool to bolster environmental health outcomes at an ecosystem level, and benefit commercial fisheries estimated at $7B annually. By replacing chemical and manual control of exotic invaders, the project contributes to the preservation of ecosystem integrity and function, biodiversity, and environmental quality of the Great Lakes, a vital natural resource providing water security for more than 35 million people in the region. With worldwide damage from aquatic invaders exceeding $300 billion annually, innovations driving advances in ecosystem protection and restoration will have wide appeal and application wherever habitats require protection. Broadening the available tool set empowers managers and local communities to act against exotic invaders at the level where causes and consequences are most acutely felt.
This project performs a feasibility study of existing technologies from aquaculture workflows for adaptation to the uncrewed control of sea lampreys in the field. The essential features of such a device are inherently similar to recently emerged solutions for automated fish management in robotic aquaculture systems. Existing models for detection and classification are expected to transfer well to a class as morphologically distinct as lampreys. The primary challenges to this project most likely arise from the unique biology and sensory ecology of a species whose responses to the physical device used here are completely unknown. A set of artificial stream experiments aims to entrain lampreys into devices placed into their path. How might lamprey react to a device optimized for the specific needs of imaging, classification, and selective removal? Informed by detailed knowledge of lamprey chemosensory ecology, the work also examines the efficacy of pheromonal cues for channeling lamprey movement through the device.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RAPIDECT INC
SBIR Phase I: A near real-time analyzer for MRSA screening and diagnosis of MRSA infections
Contact
32832 SPRINGSIDE LN
Solon, OH 44139--2067
NSF Award
2041861 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/15/2021 – 05/31/2023 (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 are significant. The prevalence of multi-drug resistant organisms (MDROs) or superbugs, which include S. aureus and methicillin-resistant S. aureus (MRSA), is one of the greatest threats to public health. Annually in the United States, over 2 million people acquire MDRO infections, leading to at least 23,000 deaths. Further, MDRO infections has been recognized as co-infections of COVID-19 that complicates the therapeutics of the pandemic disease in the healthcare environment. The analyzer will lead to fast containment and rapid diagnosis of MRSA and S. aureus infections. When its capacity is expanded to include other MDROs, the analyzer will allow clinicians to significantly enhanced treatment efficacy, leading to decreased morbidity and mortality, reduced costs of treatment and hospital stay, reduced prevalence of MDROs.
This Small Business Innovation Research Phase I project will address the long time-to-result of current MRSA testing technologies. The current culture-based diagnosis of bacterial infections requires 16-48 hours to produce results. The long diagnosis-time leads to overuse of broad-spectrum antibiotics (BSAs), resulting in under-treatment, severe side effects, morbidity and mortality as well as the development of MDROs. The culture-free analyzer will complete the diagnosis in 120 minutes. The analyzer will allow clinicians to limit the use of BSAs and start using narrow spectrum antibiotics in the early stage of treatment to enhance efficacy and reduce the prevalence of MDROs. The goals of the project are: (1) To construct a prototype analyzer, which will provide simultaneous diagnosis on multiple samples in 120 minutes, and (2) To conduct a small-scale characterization of the clinical performance of the prototype with clinical samples to establish its credibility as a clinical diagnostic technology. The prototype analyzer will consist of a multi-channel signal acquisition electronics console and detection plates. The detection plate will contain an array of bacteria-specific detection electrodes and will be inserted into the console and operated by the console for measurements. The analyzer will detect MRSA in clinical samples and distinguish MRSA from S. aureus.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RCE TECHNOLOGIES, INC.
SBIR Phase I: Development of novel artificial intelligence (AI)-enabled, non-invasive, heart attack diagnostics
Contact
233 ARNOLD MILL RD
Woodstock, GA 30188--7600
NSF Award
2208248 – SBIR Phase I
Award amount to date
$255,892
Start / end date
01/15/2023 – 06/30/2023 (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 a novel, portable, diagnostic device for non-invasively diagnosing myocardial infarctions (MI) and ischemia in real-time with a high level of sensitivity and specificity. The system aims to provide an accurate point-of-care clinical classification for the 805,000 heart attack cases occurring in the US each year with a real-time diagnostic and monitoring tool. The system aims to significantly reduce the time needed with current invasive sampling and blood analysis measures, thereby improving patient outcomes during the first critical hours of an MI while saving healthcare resources and improving efficiency. The portable nature of the technology enables other forms of integration including at home, in clinic, hospital bedside use, or field use applications.
This Small Business Innovation Research (SBIR) Phase I project will develop a proof-of-concept diagnostic-prognostic machine learning-based system for detecting MI. The scope of activities includes testing multiple techniques and models and producing distribution analyses and event plots of training data in order to optimize performance compared to clinically adjudicated events. Success measures include a data model which, when using their proprietary external noninvasive transdermal biomarker sensor with their wearable garment electrocardiograms (EKGs), are able to detect MI with > 85% accuracy. The device will also be able to detect clinically relevant ischemia with > 85% accuracy. These results will progress the company’s objective of completing a standalone, noninvasive, real-time diagnostic and remote monitoring tool.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RESBONDS INTERNATIONAL CORPORATION
SBIR Phase I: A Digital Platform to Assess Water Quality at Urban-Watershed Interfaces
Contact
12602 DENMARK DR
Herndon, VA 20171--2716
NSF Award
2152000 – SBIR Phase I
Award amount to date
$254,976
Start / end date
04/15/2022 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project is to help manage water quality at the boundaries of cities and watersheds. The proposed work develops a financial system to help cities and public utilities build infrastructure projects. This system integrates physical data with artificial intelligence and advanced monitoring systems. It will serve as a scalable analytics platform using environmental, economic, and social data for financing projects in water quality management.
The proposed project develops analytics and a financial instrument for environmental adaptation and water restoration projects. It uses open-source data management, sensors and interfaces, and mathematical models in a system with state-of-the-art artificial intelligence-enabled digital twin technology. The environmental data will be used in an integrated watershed model using principles of uncertainty analysis and neural network-based learning. The econometric model combines uncertainty analysis with reinforcement learning where accuracy in prognostics is incentivized.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RIFT VALLEY HEALTH COMPANY
SBIR Phase I: A personalized consumer health guidance platform
Contact
14 JAMES CIR
Longmont, CO 80501--6805
NSF Award
2129148 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses poor long-term public health outcomes stemming from lifestyle choices through an intuitive and effective tool to analyze and optimize their sleep, exercise, nutrition, and mental health. The technology will guide users through an individualized health and well-being analysis based on real-time data that presents an individualized baseline and heat map that helps individuals determine which lifestyle behaviors are most beneficial or detrimental towards their holistic health. This personalized approach seeks to establish new habits, interventions, medications, diets, etc. This tool may help people to live longer and more fulfilled lives with fewer health concerns and costs.
This Small Business Innovation Research (SBIR) Phase I project determines the viability of objective measurement of health metrics (heart rate, blood pressure, sleep cycles, and exercise) through the integration of already-existent technologies including, but not limited to, wearables and “smart” technologies such as Smart Scales and Smart Blood Pressure cuffs. Additionally, this project will determine the viability of using subjective inputs surrounding diet, mood, and exercise and the ability to draw meaningful correlations between both subjective and objective inputs. This project will develop and validate methods to integrate these two data streams into a health scoring system that may be used to improve physical and mental health and fitness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ROGUE SPACE SYSTEMS CORPORATION
STTR Phase I: Metal Fueled Hall Effect Thruster Using A Radioisotope Heater
Contact
84 UNION AVE
Laconia, NH 03246--3573
NSF Award
2222474 – STTR Phase I
Award amount to date
$271,381
Start / end date
08/01/2022 – 07/31/2023 (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 project is to significantly alter the current state of electric propulsion by providing a thruster platform with extended capabilities. Such a change would allow Hall thrusters to span a wider range of operating parameters with added benefits of increased efficiency, lower cost, exploration of deep space, and backup power via a radioisotope power system (RPS). By using a RPS, the thruster platform will produce one watt of electrical power for every nine watts of heating power. The heating power will enable the use of high-density metal propellants such as zinc. The electrical power will provide a backup for solar generation and can potentially power basic satellite systems. This work will provide scientific knowledge regarding nuclear fuel recycling, power generation, and related space technologies. Lastly, this work will be highly collaborative and will contribute to the training of a highly diverse workforce.
This Small Business Technology Transfer (STTR) Phase I project addresses a longstanding issue in space propulsion; the reliance on xenon as a fuel. The primary objective of the proposed work is to produce a prototype Hall Effect thruster utilizing zinc fuel and a RPS unit. A thermal management system will manage the heat produced by the RPS unit to deliver fuel to the thruster. Initial work will use an electrical module that will act as a placeholder for the RPS unit; the latter can be inserted when necessary. Design of the prototype will follow Hall Effect thruster scaling laws to reduce risk. The results of the tested prototype will provide information on the expelled ions, thruster efficiency, and divergence of the thruster plume. More broadly, the results will provide data on realizing an alternative to xenon fuel for space propulsion as part of an improved thruster platform.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RSTREAM RECYCLING LLC
SBIR Phase I: Autonomous waste sorting platform for decentralized pre-processing
Contact
76 HUDSON ST
Milton, MA 02186--1453
NSF Award
2223186 – SBIR Phase I
Award amount to date
$275,000
Start / end date
02/01/2023 – 01/31/2024 (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 Busisness Innovation Research (SBIR) Phase I project is in improving landfill diversion and recycling rates of non-industrial waste. This project targets high-traffic venues (HTVs) with controlled waste streams such as stadiums, universities, airports, and theme parks. Waste stream sorting to differentiate classes of materials for recycling and landfill is currently undertaken either using rudimentary, labor-intensive manual sorting, or expensive and technically complex robotic sorting, neither of which are feasible options for small- to mid-sized facilities (i.e., HTVs), which then shoulder heightened rates imposed by material recovery facilities due to contamination. These expenses have discouraged recycling, contributing to the mounting waste problem. This project seeks to develop an intelligent waste-sorting system that leverages computer vision and innovative hardware to enable on-site, decentralized sorting, facilitating the recapture of the 66 million tons and $200 billion worth of recyclable materials that currently go to waste each year. By mitigating waste accumulation in landfills and the greenhouse gas emissions associated with virgin resource mining, this technology supports United Nations sustainable development goals 11 (sustainable cities and communities) and 12 (responsible consumption and production) and aligns with the NSF’s mission of advancing national health, prosperity, and welfare.
The proposed technology consists of a hardware-software solution that uses the latest in computer vision to perform automated singulation (i.e., arranging objects in a 1-by-1 stream) and classification in cluttered environments, allowing for increasingly complex (or diverse) structures (shapes, sizes, and materials) to be accurately identified and subsequently sorted. This approach produces an ordered stream of objects, which can then be sorted according to any diversion scheme for efficient recycling. The software uses semi-supervised learning to allow for domain adaptation from a centralized training set, enabling rapid implementation of optimized sorting schemes of site-specific waste streams, requiring significantly less human intervention than traditionally needed. Successful development would result in a simplified sorting platform that is cheaper, more robust, and less resource intensive than existing waste sorting operations, thus offering a novel turnkey solution that could be feasibly adopted on-site. Research objectives include: 1) Developing and evaluating hardware assemblies using electromechanical processes for waste stream singulation; 2) Developing software for efficient dataset generation and waste stream classification, particularly using semi-supervised learning and data augmentation approaches; and 3) Validating the developed system for high precision singulation and classification of recyclables under noisy like conditions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
RUSH RIVER RESEARCH CORPORATION
STTR Phase I: Rapid Point-of-Care Sterilization of Personal Protective Equipment for Frontline Healthcare Workers (COVID-19)
Contact
W4272 455TH AVE
Ellsworth, WI 54011--5807
NSF Award
2112172 – STTR Phase I
Award amount to date
$255,961
Start / end date
04/15/2022 – 03/31/2023
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, Phase I project is to improve public health. During the COVID-19 pandemic, personal protective equipment (PPE), including filtering facepiece respirators (FFRs), have been critical to containing disease spread and protecting first responders and healthcare workers on the frontlines. Shortages of FFRs have led public health agencies to provide guidance in favor of FFR decontamination and re-use as a crisis capacity strategy. This project seeks to develop a cost-effective approach to support sterilization and re-use of personal protective equipment at the point-of-care. The technology seeks to develop and evaluate a simple, low-cost, sterilization receptacle for the effective, automated decontamination of FFRs. The aim is to enable first responders and healthcare workers to sterilize FFRs and prepare them at the point of care for re-use within minutes. This capability can be useful both in the current and potential future pandemics.
This STTR Phase I project seeks to harness high voltage pulsed electric fields (PEFs) for decontamination and re-use of FFRs. In addition to killing bacteria and fungi, PEF has been observed to rapidly inactivate enteric viruses within seconds of exposure. PEF can also be used to electrically recharge FFR mask fibers prior to re-use. The filtration efficiency of N-95 FFRs is improved by an intermediate layer of charged polypropylene electret fibers that trap small particles through electrostatic or electrophoretic effects. A prototype will be constructed and evaluated on FFRs inoculated with respiratory viruses, including SARS-CoV2, in a clinical virology lab to directly demonstrate sterilization and recharge efficacy. The project will establish whether such a system will allow multiple sterilizations and fiber recharging cycles without affecting FFR function or 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. -
SANGALI, INC.
STTR Phase I: Rapid Characterization of Wood-based Materials
Contact
18 MAPLEWOOD AVE
Albany, NY 12203-
NSF Award
2233237 – STTR Phase I
Award amount to date
$275,000
Start / end date
02/15/2023 – 01/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will enable the wood industry to certify materials along its entire supply chain, achieving reproducibility and reducing delays in the movement of goods, and supporting the economic competitiveness of American wood companies. The technology being developed by this project entails rapid and accurate wood species identification, which will bring transparency to the wood industry, helping to enable proper forest management that follows social, economic, and government standards. The technology will also promote quality control of products and characterization of residues leftover from wood processing, which in turn would facilitate their recovery and reutilization. By allowing manufacturers to achieve reproducibility in composite material manufacturing, the technology will encourage the recycling of wood waste and byproducts, supporting efforts to increase the sustainability and reduce the environmental impact of the wood industry. Lastly, this technology will empower organizations combating illegal logging by providing a new and powerful forensic tool, thus addressing deforestation and forest depletion with significant economic, societal, and ecological benefits.
This Small Business Technology Transfer (STTR) Phase I project is applying state-of-the-art chemical analysis methods to develop a novel wood identification technology capable of determining with accuracy the species, age, and geographical origin of uniform or composite products. With the increase in demand for transparency in the wood industry and more stringent regulations comes a demand for new technologies that support compliance. Despite being a critical step in this process, current methods for species identification are time consuming, require highly specialized training, and provide little information on age and origin. By combining a highly sensitive type of spectroscopy with advanced statistical approaches (i.e., machine learning), this project is developing a method that can reliably identify chemical fingerprints that inform about wood species, age, and origin when compared against a database. This Phase I project will develop and demonstrate this approach when applied to U.S. woods, including the creation of a wood species database, with these key objectives: 1) analyze domestic woods to develop statistical methods to identify the species; 2) test the method’s ability identify species within composite materials; 3) test the method’s ability to identify the geographical origin of samples; and 4) test the method’s ability to determine wood age.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SEASATELLITES, INC.
SBIR Phase I: Collision Regulations (COLREG) Aware Autonomy for Safe Interactions of Crewed and Uncrewed Vessels
Contact
2775 KURTZ ST
San Diego, CA 92110-
NSF Award
2151658 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2022 – 07/31/2023 (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 the productivity and safety of operations across the entire $1.3 trillion Blue Economy. Maritime operations routinely involve significant risks to human life and property and consequently bear extraordinarily high operating costs. Autonomous ocean vehicles (falling under the Robotics technology area) are being rapidly adopted by science, commercial, and defense organizations due to their potential to dramatically reduce cost and risk. The success of the proposed project will advance the state of the art for commercial autonomous vehicle compliance with international laws regulating interactions between maritime vessels at sea. Giving autonomous ocean vehicles the ability to interact with crewed vessels safely and predictably will accelerate the adoption of these tools and the missions they enable. Several specific market segments stand to benefit immediately from the proposed technology, including the $31B offshore wind market, the $2B port automation market, the $233B aquaculture market, and dozens of others. Beyond market impacts, humanity needs ocean data to understand the critical dangers of overfishing and climate change.
This Small Business Innovation Research (SBIR) Phase I project is focused on the design of systems and software needed for autonomous ocean vehicles to comply with the international collision regulations (COLREGS) for maritime vehicles. The difficulty the industry has faced in creating COLREGS compliant autonomy is the fact that the rules were developed with the expectation that experienced mariners would be able to make qualitative interpretations in unique situations. That led to a descriptive rather than prescriptive set of rules that is good for human mariners, but difficult to implement in software. The objectives of this Phase I project include the design and simulation of autonomous systems able to operate in compliance with the COLREGS. In addition to simulations, the software may be deployed to small autonomous surface vehicles for preliminary on-water testing. Anticipated results include a system able to maintain COLREGS compliance within a documented envelope of conditions. The effective implementation of safe system design, optimized control, and machine learning techniques can combine to produce the first autonomous ocean vehicles that can be trusted in congested waterway 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. -
SEETRUE TECHNOLOGY, LLC
STTR Phase I: Three-Dimensional Printing of Micro-Capillary Needle via Direct Laser Writing
Contact
26 HOLLYBERRY CT
Rockville, MD 20852--4222
NSF Award
1938527 – STTR Phase I
Award amount to date
$225,000
Start / end date
03/01/2020 – 04/30/2023
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase I project leverages recent advances in additive manufacturing to solve key technical hurdles and design deficits of current industry standard microcapillary needles. Microinjection is a well-established engineering technique and widely used in research and medical applications such as drug discovery and development, fertility treatments, and genetics research. The proposed technology will use additive (3D) manufacturing techniques for a new microcapillary needle to improve the quality, reproducibility, rigor, and efficacy of this method for a market estimated at $290 M. This technology will positively impact life sciences research and medical applications.
The proposed project will utilize state-of-the-art submicron-scale additive manufacturing technologies to revolutionize microinjection efficacy via substantive versatility in the design and fabrication of the needle-tip. In particular, two-photon direct laser writing (DLW) – wherein a focused laser is precisely positioned within a biocompatible photo material to produce 3D structures comprising cured material – provides an unparalleled level of geometric control with feature resolutions on the order of 100 nm. These capabilities enable new flexibility in re-architecting of the microneedle tip. In addition, due to recent enhancements in printing speed, DLW-based applications can now shift from niche demonstrations in the laboratory to fully functional commercial products that support rapid operation at scale. The project proposes multiple configurations for each proposed design change with respect to key performance metrics: the anti-clogging efficacy and fabrication repeatability. This project will: establish and characterize novel manufacturing protocols, simulate expected characteristics, experimentally assess (both in the lab and in vitro using the zebrafish embryo) the quantitative efficacy of these distinct and novel architectures, and qualitatively evaluate the user's 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. -
SEMERGYTECH, INC.
STTR Phase I: High Speed, High Power, Single Mode Photonic Crystal Lasers
Contact
1126 LONGFORD CIR
Southlake, TX 76092--8702
NSF Award
2223077 – STTR Phase I
Award amount to date
$275,000
Start / end date
09/15/2022 – 08/31/2023 (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 demonstrate the viability of a semiconductor laser technology based on laterally confined photonic crystal cavities. The proposed laser technology may ensure secure semiconductor and microelectronic supply chains within US for energy-efficient high-capacity data center link capabilities, Light Detection and Ranging (LiDAR) systems for autonomous driving/aerial vehicles, high performance communication and sensing systems, etc. The novel solution may accelerate technology development, address technical and market gaps, and foster entrepreneurship with important social impacts. The project will help prepare a diversified workforce skilled in semiconductor production, nanotechnology, photonics and optics, and advanced manufacturing.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop and commercialize high speed photonic crystal surface emitting lasers (PCSELs) with single-mode, high power output. PCSEL offers the combined attributes of conventional lasers with demonstrated high-power, single-mode operations from large apertures. To address the cavity scaling challenges in high speed PCSELs with aperture sizes down to a few micrometers, a novel lateral cavity confinement configuration is proposed. Such a lateral confinement configuration can offer both strong optical confinement and compact lateral charge confinement for increased intrinsic modulation speed and reduced parasitic effects. The trade-offs between the modulation speed and optical power will be investigated. Vertical cavity feedbacks will also be incorporated and optimized for photon lifetime management. The objective of this project is to investigate different optical feedback configurations in the PCSEL cavities to scale the cavity sizes down to a few micrometers with the goal of single-mode, high power, and high-speed operation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SENOGUARD, INC.
SBIR Phase I: Cryogenic probe development and testing for post-lumpectomy margin ablation treatment
Contact
1135 COASTLINE DR
Seal Beach, CA 90740--5816
NSF Award
2208433 – SBIR Phase I
Award amount to date
$255,731
Start / end date
01/15/2023 – 12/31/2024 (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 cryoablation treatment for improving the outcomes for patients undergoing a lumpectomy procedure. The system aims to provide a significantly more effective treatment for treating breast cancer following surgical intervention, enabling more rapid healing and fewer side effects than current radiation treatments. The technology aims to serve as a standard of care in the lumpectomy market projected to reach $7.5 billion in 2027 and address a leading cause of female morbidity and mortality.
This Small Business Innovation Research (SBIR) Phase I project seeks to explore the feasibility of the company’s proprietary cryoablation system to kill breast cancer cells with high (>99%) accuracy in preclinical testing. This project will validate the design using an accepted animal cellular model of tumors. The project aims to design and de-risk the probe design to ensure optimal contact and thermal transmissivity with the tumor cells in a fixed experimental setting in vitro. The project will be designed to ensure clinical usability in under an hour at the time of cancer removal. The results may serve as the foundation for furthering preclinical product research and development prior to 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. -
SENTIRE MEDICAL SYSTEMS, INC.
SBIR Phase I: Intraoperative monitoring device to detect bowel injuries during laparoscopic surgical procedures
Contact
10455 RIVERSIDE DR STE 210
Palm Beach Gardens, FL 33410--4332
NSF Award
2212402 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/15/2023 – 12/31/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to make laparoscopic and robotic assisted abdominal surgery safer for patients, and less costly for the healthcare system. Though a somewhat rare complication, inadvertent bowel injury during the more than 15 million laparoscopic procedures performed annually can be catastrophic for patients resulting in extended hospitalization, multiple corrective surgeries, lifelong medical complications, and, in more than 5% of cases, death. In addition, the direct costs associated with this complication can be substantial including intensive care convalescence and the potential for litigation given the nature of damages suffered by patients. Intraoperative detection of bowel injuries during surgery provides a simple, yet elegant solution enabling immediate repair and avoidance of negative outcomes. This project’s commercial potential includes availability in more than 49,000 operating suites and an addressable market of $750 million per annum. The proposed innovation will significantly enhance patient safety, reduce costs associated of corrective care, and generate revenue from U.S. based manufacturing.
This Small Business Innovation Research (SBIR) Phase I project aims to enable intraoperative detection of bowel injuries by identifying gases typically sequestered to the interior of the gastrointestinal tract. To accomplish this, these target gases must be sufficiently differentiable from background gases and other agents typically present during laparoscopic or robotic surgery. Such background agents present a meaningful technical challenge in that they present the potential for false positive detection results. Characterization of all potentially present agents will be completed such that they can be sufficiently differentiated from target gastrointestinal gases. A high precision gas chromatography system and custom fabricated chamber replicating surgical conditions including temperature, pressure, humidity and gas flow rate will be used to precisely identify and distinguish all potentially present gases. Once all potentially cross-reactive gases are characterized, a combination of physical filtration and algorithmic signal processing will be used to ensure proper differentiation/recognition of gas species and avoidance of potential false positive results.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SHERO LLP
SBIR Phase I: The Development of Biodegradable Hot Melt Pressure Sensitive Adhesives for Use in Hygiene Products
Contact
746 N 950 E
Bountiful, UT 84010--2721
NSF Award
2125908 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 05/31/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project is in development of fully-biodegradable disposable personal care products, particularly menstrual pads. In general, menstrual pads cannot be recycled or be composted by municipal facilities after use because of issues with the biodegradable hot-melt adhesives to construct and position them. Biodegradation may be the best way to reduce the environmental impact associated with them, particularly in geographies where municipal solid waste facilities are underdeveloped. Ultimately, non-toxic, safe and effective disposable menstrual pads could improve quality of life for menstruating women and the environment, and provide a new commercial opportunity for producers in the US and around the globe.
The proposed project addresses the technical challenge of synthesizing a combination of biodegradable thermoplastics and biological additives that will create a pressure sensitive adhesive (PSA). This PSA must performs well in commercial hot glue application machinery as well as in the intended products, completely and safely degrade within six months of use, and is commercially viable at scale. These parameters have yet to be met by biological-based adhesives. The research approach is as follows: First, develop and synthesize PSAs using a biological base polymer and biological-based biodegradable additives, including plasticizers, tackifiers, and compatibilizers to enhance the performance of the PSAs. Second, characterize PSAs based on established use and manufacturing requirements and optimize the composition to ensure the requirements are met. Third, test PSA compositions for degradation, including length of time required for complete biodegradation under landfill, soil, and water conditions, including marine environments. Identify intermediate chemical molecules and structures that form as a result of the biodegradation process, determine their potential hazards on both the environment and the health of biological organisms. This project will develop a biodegradable PSA that will meet manufacturing and performance standards in menstrual pads and show that the PSA can be fully biodegradable in less than six months under non-specialized environmental conditions, without the need of mechanochemical or photo degradation processes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SIEV TECHNOLOGIES LLC
SBIR Phase I: Novel Catalytic Membrane Reactor for the Production of Valuable Chemical Intermediates from Zero/Negative Value Feedstock and Waste
Contact
534 W RESEARCH CENTER BLVD STE 260I
Fayetteville, AR 72703--9302
NSF Award
2111756 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 03/31/2023
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 convert non-food cellulosic corn fiber, a low-value byproduct from corn ethanol plants, to fermentable sugars using a bolt-on catalytic membrane reactor without the need to construct new facilities. The successful completion of the project will enable corn ethanol producers to diversify revenue streams, maximize production efficiencies. The proposed technology operates with higher efficiency than naturally occurring systems and can complete the conversion in less than one day, 5-10 times less than the exiting enzyme technology. The catalyst can be used repeatedly and is environmentally friendly.
The proposed project relies on a catalytic membrane reactor with a patented enzyme replacement catalyst to simultaneously convert cellulosic biomass into fermentable sugars and separate the hydrolyzed sugars with high yield in one step. This catalyst consists of two adjacent polymeric nanostructures, a polystyrene sulfonic acid and poly (ionic liquid) chains grafted from a membrane support. Two types of grafted polymer chains will act cooperatively to bind and hydrolyze the biomass substrate, similar in nature to the functions of cellulase enzymes. The polystyrene sulfonic acid chain catalyzes the hydrolysis of the polysaccharides to soluble sugars whereas the poly (ionic liquid) chain enhances the catalytic activity and selectivity of the synthesized catalyst. The catalytic activity and selectivity of the designed catalyst can be tuned and optimized by ring substitution and by varying independently the properties of the grafted nanostructures. A porous membrane with an appropriate pore size will enable the separation of monomer sugars immediately after they are released, thus driving the forward reaction, minimizing acid-catalyzed sugar degradation, and improving sugar yields. In addition to fermentable sugars, the catalyst can be tuned to convert cellulosic biomass or other carbohydrates such as agricultural residues or food waste into platform chemicals for the production of bio-based 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. -
SIGN-SPEAK Inc
SBIR Phase I: Real-Time Artificial Intelligence (AI) Bidirectional American Sign Language (ASL) Communication System
Contact
7290 SHALLOW CREEK TRL APT F
Victor, NY 14564--9446
NSF Award
2213235 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2023 – 10/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve the communication between Deaf and Hard of Hearing (D/HH) individuals and the hearing community through automated sign language recognition. In the United States alone there are over 48 million D/HH individuals, who in total possess $87 billion in purchasing power. It appears businesses are not adequately serving this community, as is evidenced by the plethora of Americans with Disabilities Act (ADA) lawsuits against numerous companies. The proposed technology will provide plug-and-play software for organizations to improve their interactions with D/HH individuals. Businesses and governments will be able to interact with their D/HH employees, customers, or constituents when interpreters are unavailable. This technology can be integrated into a variety of platforms, from retail point-of-sale equipment to chatbots and video/teleconferencing systems.
This Small Business Innovation Research (SBIR) Phase 1 project aims to develop technology to perform unconstrained sign language recognition and natural sign language production. Specifically, current methods to train language translation models are ill-equipped to handle the sign language domain due to the lack of training data within this domain. Additionally, all currently established methods (apart from motion capture, which is unscalable) for producing American Sign Language (ASL) result in stilted, unnatural signing from an avatar. This project will develop solutions to these issues within the domain of ASL via semi-supervised expert-augmented models and data augmentation techniques. Technical hurdles include the lack of models to handle high-dimensional low-resource language domains, and lack of sufficiently large datasets. Technical milestones include creating semi-supervised datasets, engineering data augmentation techniques, generating a natural signing avatar, and performing extensive usability testing. This project aims to produce a method for automatically interpreting between a low-resource sign language and English to improve accessibility and increase equity for the Deaf and Hard of Hearing communities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SIMMBION LLC
STTR Phase I: Development of a novel system to manufacture therapies inside the human body
Contact
2410 W BELVEDERE AVE BLDG 312
Baltimore, MD 21215-
NSF Award
2123532 – STTR Phase I
Award amount to date
$255,136
Start / end date
04/15/2022 – 03/31/2023
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 drug delivery by developing a system to synthesize much needed drug therapies directly in patients. This advancement, if successful, would reduce the need for complex and expensive manufacturing, eliminate the reliance on refrigerated drug shipment and storage, and remove need for repeated injections. Development of such a system would be adaptable for different applications across human health and disease, would be resistant to supply chain disruptions caused by pandemics or natural disasters, and would result in the equitable delivery of medications to diverse patient populations across the globe.
The proposed project seeks to develop a dynamic living medicine capable of supporting the delivery of biological drugs directly in vivo. Over the last decade, many attempts have been made to deliver biologics safely and efficiently to humans using engineered bacteria and viruses as living medicines. The current system is fraught with problems, mostly stemming from the immunogenicity of these vectors. This critical technological and innovation gap - the manufacture biologics directly in vivo safely for extended periods of time - may be achieved through the genetic engineering of avirulent organism symbionts to express proteins of interest. In this study, blood symbionts will be genetically engineered to expresses either β-glucocerebrosidase or insulin, with the goal of generating living medicines to treat Gaucher’s disease and diabetes, respectively. The secretion, activity, and durability of the engineered compounds will be assessed in vitro and in vivo. The safety and efficacy of this therapeutic approach will be assessed in pre-clinical models.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SKUCHAIN, INC.
SBIR Phase I: Blockchain for Supply Chain
Contact
340 E MIDDLEFIELD RD
Mountain View, CA 94043--4004
NSF Award
2112262 – SBIR Phase I
Award amount to date
$255,780
Start / end date
06/01/2022 – 05/31/2023 (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 facilitate faster and safer transactions for manufactured goods. Current Enterprise Resource Planning (ERP) solutions are based on relatively old technology. The proposed project develops a new platform for the supply chain to operate efficiently using blockchain technology for a scalable, secure, and interoperable solution.
The SBIR Phase I project addresses three principal technical challenges of a blockchain commercial solution, namely scalability, security and interoperability. For scalability, the core technical requirement is to provision, maintain and periodically rotate hierarchical and deterministic public/ private key-pairs used to sign transactions and usable by non-technical users. Security research will focus on providing each organization/ participant the ability to provide granular access to field-level data to others in the ecosystem. The project will use an Elliptic-Curve Diffie-Hellman (ECDH) protocol to encrypt each field with its own key-pair. The system will use a blockchain smart contract to provide trustable decryption based on access control policies set by the submitter. The project’s interoperability will focus on the ability to share data between different blockchain networks as well as between traditional ERP systems and a blockchain network by developing an interoperability protocol that securely transfers the record and ensures that double-spend type attacks are not possible.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SLD PHOTONICS, LLC
SBIR Phase I: Single broadband detector from visible to near infrared using the spin Seebeck effect
Contact
1938 HARNEY ST STE 324
Laramie, WY 82072--3037
NSF Award
2213062 – SBIR Phase I
Award amount to date
$256,000
Start / end date
10/01/2022 – 09/30/2023 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I project will provide the medical field with a broad response detector capable of pairing with cheaper disease diagnostic tools for improved healthcare. Currently, there is not a commercially available broadband detector that can capture visible light and near infrared light. The Phase I SBIR effort will lead to an advanced detector capable of spanning this light range and fulfilling this unmet need. As a commercial product, this detector can be used in multiple commercial sectors including unmanned vehicles, the medical field, and for the defense and security of the nation. For example, in the medical field the ideal light for tissue penetration is between visible and near infrared. The detector developed in this project would permit optical scans of human bodies for disease diagnosis. The optical scan will provide a cheaper and safer alternative in comparison to expensive MRI technology and high-energy sources, such as x-rays, that result in radiological exposure. The size of the global medical imaging market is currently valued at $16 billion and the proposed work would help healthcare services in rural areas have access to optical diagnosing services.
Semiconductor-based detectors are limited to absorbing photons whose energy is equal to or slightly greater than the electronic band gap of the semiconductor. As a result, there is not a commercially available detector that can span 400-2200nm with fast detection. The expected outcome of this project is a single broadband detector, based off of the quantum spin Seebeck effect to generate a spin current, that can span 400-2200nm with a flat quantum efficiency and a high response time. The quantum efficiency (QE) of the patent-protected detector is almost three orders of magnitude lower than semiconductor-based detectors and the largest portion of the project is devoted to improving the QE to commercial levels. The project will accomplish the following goals: 1) prove the feasibility of increasing the quantum efficiency by two orders of magnitude, 2) make a readout circuit board, 3) show detector capabilities through building a benchtop-working prototype, and 4) design a compact prototype to be built during Phase II. As a commercial product, this detector can be used in unmanned vehicles, in the medical field, and for the defense and security of the nation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SMART HEAT CORP
SBIR Phase I: Innovative Latent Energy Exchanger for Effective Recovery of Industrial Wet Exhausts
Contact
9326 LOWELL AVE
Skokie, IL 60076-
NSF Award
2124735 – SBIR Phase I
Award amount to date
$255,642
Start / end date
04/01/2022 – 03/31/2023
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 save water and energy across a wide spectrum of industrial and commercial applications (i.e. boilers, baking ovens, furnaces, proofers, HVAC systems) that emit wet exhaust into the environment. For example, the U.S. bread baking market segment alone may save over 50 million therms of energy and over 400 million gallons of water annually with the proposed technology. The proposed project will create a new class of high-efficient and cost-effective equipment for energy recovery and energy efficiency improvement.
This SBIR Phase I project develops a unique energy transfer concept for high-efficient and cost-effective phase-change energy conversion. State-of-the-art heat exchange processes use linear heat transfer mechanisms. In contrast, the proposed approach accounts for the non-linear heat distribution during the condensation process. As a result, the mass of partially condensed mixture changes along the flow channel, and thus causes a corresponding change in local dew point. This approach defines a design configuration for efficient capture and maximal recovery of latent energy from the wet gas flow. The proposed concept successfully exploits the thermo-fluid advantages of spiral channels and thermosiphons. The project will resolve key technological gaps and address issues including condensation sustainability at variable channel geometry and changing flow parameters, and the thermosiphon’s optimal performance at unconventional conditions. The non-linear phase-change heat transfer mechanisms will be defined and simulated, followed by a sensitivity analysis and design optimization of the channel geometry and thermosiphons array for subsequent prototype design and performance 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. -
SOAR ANALYTICS LLC
SBIR Phase I: Artificial intelligence platform for secure, collaborative learning across medical institutions
Contact
2060 SAINT ANDREWS DR
Berwyn, PA 19312--1990
NSF Award
2136775 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2022 – 03/31/2023
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 develop a collaborative-learning platform that generates accurate population health models from secure access to patient records. The proposed system will overcome privacy concerns to enable AI methods to securely access hundreds of millions of patient records from multiple institutions across the US to learn high-performing predictive models. Models learned from this platform are differentiated due to their training data and help payors, providers, and pharma companies that benefit from early diagnosis and treatment of patients that may have remained undiagnosed. This system will improve patient outcomes and health care system performance.
This Small Business Innovation Research (SBIR) Phase I project will address fundamental limitations that can deter medical institutions from sharing patient data to support learning clinical-grade models. Unlike federated learning (FL), neither local data nor local model parameters are shared; rather, local classifiers predict labels for an unlabeled global dataset. Sharing model parameters in FL can violate privacy requirements and expose patient data used for local training. This novel platform is designed to be immune to the “white box” attacks of FL, and its main privacy risk for membership inference is significantly lower. This platform will accurately include information from all subpopulations and will support collaborative learning for multiple ML algorithms, including human-interpretable algorithms that cannot be learned with FL. Accuracy will be evaluated via sensitivity and specificity, privacy via membership vulnerability. Methods compared include federated learning and differential privacy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
SOLIOME LLC
SBIR Phase I: Development of biocompatible and biodegradable UV filters based on food-grade protein sources
Contact
479 JESSIE STREET
San Francisco, CA 94103-
NSF Award
2136707 – SBIR Phase I
Award amount to date
$255,899
Start / end date
09/15/2022 – 08/31/2023 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the development of novel sunscreens and UV-protective products that are safer for both humans and the environment. Sunscreen protects the skin by absorbing or reflecting the sun’s harmful UV rays,preventing premature skin aging, painful burns, and skin cancer, which is the most common form of cancer in the U.S., and results in treatment costs reaching $3.3 billion annually. UV-filtering active ingredients in sunscreens have been under scrutiny because of the safety risks they pose to humans and the environment. Current UV filters can be absorbed by the skin, cause hormone disruption, and persist and accumulate in the environment, where they can harm wildlife and disrupt marine ecosystems. This project will advance the development of novel sunscreens and UV filters composed of naturally occurring, food-safe peptides containing UV-absorbing amino acids. These compounds are photo-stable, biodegradable, non-absorbing, and safe for both humans and the environment, and they will have high impact in the fields of skin care and biosafe food packaging. Because they can be produced at relatively low cost, they also have the potential to take a considerable share of the $13 billion sunscreen industry.
This SBIR Phase I project proposes to complete the following objectives: 1) Develop sunscreen peptides from widely available food-grade sources and scale to 100 g to show cost-competitiveness with current xenobiotic sunscreen compounds and reproducibility; 2) Optimize peptides to improve their UV absorbance and investigate heterologous expression in bacteria; and 3) Evaluate peptide chemical
stability, photo-stability, and confirm non-absorption. This will achieve the overall Phase I goal of reproducibly generating safe and biodegradable UV-absorbing peptides at the 100 g scale, with initial stability studies conducted. This work will lay the foundation for future efforts including independent safety studies, kg-scale production, and clinical trials to result in the first new over-the-counter sunscreen active ingredient introduced in over 35 years.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
STARDUST LABS INC.
SBIR Phase I: Next-Generation Maximal Extractable Value (MEV) Proof Distributed Ledger Architecture
Contact
313 DUKES RD
Colonia, NJ 07067--1820
NSF Award
2213017 – SBIR Phase I
Award amount to date
$255,532
Start / end date
02/01/2023 – 08/31/2023 (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 ensure robust consumer protection for financial applications using distributed ledger technology (DLT). This project aims to improve upon existing global financial infrastructure by replacing it with a safe, open, accessible network powered by the proposed next-generation distributed ledger architecture. Accessing traditional financial networks is a major challenge, and often requires significant capital coupled with deep industry connections. As DLT stands today, there are still challenges for it to safely support financial applications. DLT vulnerabilities can cost users billions of dollars and is leading to the same monopolistic dynamics that are characteristic of traditional financial infrastructure. This project aims to advance the foundation of distributed ledger technology to address these issues, and deliver an accessible, safe, democratized financial infrastructure that can operate on a global scale and support the untold myriad of value-added use cases from companies that cannot sustain the high economic costs, or overcome the accessibility barriers, of traditional financial infrastructure.
This SBIR Phase I project seeks to advance distributed ledger technology to safely support financial primitives. Transaction information in modern distributed ledgers is public during origination, allowing validators to exploit this information and at times their privileged position to attack every financial primitive. As an example, there are issues with validators taking arbitrage opportunities and sequencing their own transactions first. Financial best practices are to silo transactions into distinct lifecycle stages to ensure consumer safety. This solution brings these best practices to DLT through a cryptographic commitment scheme. Cryptographic commitment schemes allow users to commit to an action without disclosing sensitive details, however, the traditional process requires centralization to coordinate the timing for disclosure. The primary research goal and objective for this Phase I project is proving the viability of a decentralized commitment scheme with real world latency and no centralized timekeeping or coordination mechanism. The proposed architecture will allow users to initiate transactions without including sensitive transaction details at origination. Without sensitive transaction details, validators can no longer exploit this information for their own gain, allowing this architecture to provide the security and privacy necessary for improved safety for financial 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. -
STEC TECHNOLOGY, INC.
SBIR Phase I: Reactive Cyclic Induction Marine Diesel Emissions Reduction Monitoring and Delivery System Project
Contact
19 BROADCOMMON RD STE 200
Bristol, RI 02809--2768
NSF Award
2208348 – SBIR Phase I
Award amount to date
$242,890
Start / end date
01/15/2023 – 12/31/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the potential reduction of toxic nitrogen oxides (NOx) and harmful carbon dioxide (CO2) emissions from marine diesel engines. There are approximately 4 million diesel-powered craft in use globally, emitting approximately one billion tons of CO2 and 100 million tons of NOx annually. This project seeks to remove at least 80% of the NOx and 30% of the CO2 from marine diesel exhaust, contributing to a reduction in both greenhouse gas emissions and in air pollution that creates health hazards in coastal cities. There is no alternative, commercially-viable product that reduces CO2 and NOx emissions from marine diesel engines. The proposed concept seeks to overcome the disadvantages of competing technologies that are unworkable due to heat and space restraints in a confined boat engine room. The project may enable boat manufacturers to meet new international maritime regulations on engine emissions and may contribute new knowledge related to the engineering of monitoring and delivery systems for marine and land/vehicle emissions reduction systems. In addition to environmental benefits, the technology meets a global commercial demand and creates good paying jobs for an export-oriented US industry.
The goal of this project is to develop a low thermal electro-emulsification solution to reduce emissions in marine diesel exhaust, specifically nitrogen oxides (NOx) by 80% to meet the new International Maritime Organization (IMO) regulations and carbon dioxide (CO2) by 30%. The technology will be incorporated into a fuel processing system that can be integrated into existing diesel engines on marine boats. This system will precisely inject reaction-altering chemicals at the proper time in the combustion cycle to reach the desired reduction of CO2 and NOx. The system will also monitor the exhaust stream to ensure no harmful byproducts are discharged into the marine environment. This work will further develop the understanding of diesel emissions reduction and may be transferable to other vehicle and land-based 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. -
STERILE GEEKS VR INC
SBIR Phase I: Mixed reality wearable technology to improve workflow, productivity, and training in medical sterilization environments
Contact
16258 TISONS BLUFF RD JACKSONVILLE
Jacksonville, FL 32218-
NSF Award
2144074 – SBIR Phase I
Award amount to date
$254,718
Start / end date
09/01/2022 – 08/31/2023 (Estimated)
NSF Program Director