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Phase I
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2KR SYSTEMS, LLC
SBIR Phase I: Remote IoT Monitoring Network for Early Warning and Measurement of Structural Movements
Contact
217 MCDANIEL SHORE DR
Barrington, NH 03825--5052
NSF Award
2127727 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 injury, property damage, operating costs, and liability in the built and natural environments. Excessive snow, rain, wind and seismic activity create high structural loads that can lead to the collapse of buildings, bridges, and other infrastructure. These loads can also destabilize geographical features such as water impoundments and hillsides. Increasingly extreme climate impacts and aging infrastructure make these situations more common and unpredictable. Weather events affect 5.9 million commercial buildings and 137,000 schools in the US. Of the 600,000 highway bridges in the US, 45,000 are structurally deficient. Landslides result in $3.5 billion in repair costs due to physical damage and result in 25 to 50 deaths annually. Since small structural movements often precede damage and even catastrophic failure, the ability to detect and monitor these motions at key locations and deliver warnings to any user with a cell phone or computer is of great societal benefit. This project will lead to the development of a low cost, rapidly installed, and intuitive wireless system to measure and record movements within broad categories of infrastructure and geographic features. Early warning of structural movements helps mitigate risk, prevent unnecessary damage, initiate evacuations, and keep occupants safe.
This Small Business Innovation Research (SBIR) Phase I team will construct a series of sensors that measure commercial rooftop movement like that seen from high snow and wind loading. Existing disaster forecasting systems are expensive, operationally complex, and/or provide limited data. The sensors in this project will use precision radio receivers to create 3 axis centimeter-accurate movement data. Sensors report movements to an application server where an algorithm will be created to analyze and display geo-located data. When necessary, alerts are sent to users via Short Message System (SMS, i.e., text) and email, indicating the location and severity of the problem. A key metric to success will be the ability for the sensors to operate accurately on structures such as metal-decked rooftops which can create challenges for radio frequency devices. A compact design is necessary for commercial viability and to create a stable enclosure with low aerodynamic drag. Therefore, a novel hybrid energy supply will perform additional system functions and will be evaluated for output efficiency. To reduce battery demands, algorithms will be developed instructing units to remain in “power saving mode” during periods of low activity then switch into “high fidelity mode” when motion is detected or expected, such as during storms or geological events.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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. -
4-D AVIONIC SYSTEMS, LLC
SBIR Phase I: 4D Flightpath-Based Autonomous Separation Assurance Systems (ASAS)
Contact
800 BRIERWOOD DR
Manhattan, KS 66502--3120
NSF Award
2111827 – SBIR Phase I
Award amount to date
$255,994
Start / end date
01/01/2022 – 12/31/2022
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable the safe and autonomous management and control of airspace. The Unmanned Aerial Vehicle (UAV) and Advanced Air Mobility (AAM) sectors are expected to grow but that will only be economically viable if the UAV and AAM operations are highly automated. The technology developed in this project uses a new trajectory-based approach to aircraft and airspace operations to support that level of automation. The immediate focus of the project is on the emerging AAM aircraft and airspace, but the technology has an even broader potential impact for application to the commercial Air Traffic Control (ATC) system. In the United States, over a period of one year, over 1800 operational errors (breaches of minimum required separation) were officially attributed to airspace controller error. The commercial ATC is largely a manual system and and there is a limit to the number of flights air traffic controllers can manage with incremental improvements of the present system. Expansions in the number of airborne vehicles (of all sorts) requires that air traffic control systems be more automated to maintain their safety record.
This Small Business Innovation Research (SBIR) Phase I project seeks to produce a functioning proof-of-concept demonstration of an autonomous aircraft and airspace management and control system for AAM class vehicles. These aviation sectors are expected to see a rapid expansion but the highly manual implementation of airspace control will not be practical or economically viable. The objective of this research is to support a much higher level of automation, enabling the growth of the sectors. Aircraft missions are defined by 4D analytic flightpath models; Aircraft are must precisely follow the flightpaths set by the models. Deterministic and certain algorithms autonomously detect and resolve potential loss of separation events between flightpath models of all aircraft in the airspace. The autopilots allow the aircraft to operate autonomously and the deconfliction ensures safe operation of the airspace. Development of the proposed demonstration system will identify and resolve communication and integration issues. The demonstration system seeks to provide a test case to evaluate the viability, scalability, and robustness of the technology and to explore the responses to nonstandard and unforeseen operating 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. -
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)
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. -
AEROSENS, LLC
SBIR Phase I: Research on an energy harvesting system for the development of a self-sustainable, blue-tooth, low energy tracking and monitoring sensor for aircraft
Contact
7120 SW 47TH ST
Miami, FL 33155--4630
NSF Award
2136567 – SBIR Phase I
Award amount to date
$255,743
Start / end date
02/01/2022 – 01/31/2023
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) Phase I project is to develop a novel, self-sustaining, real-time asset tracking technology that addresses the aviation industry’s need for efficiency and safety. This technology will provide automated safety and emergency equipment compliance and security seal checks, significantly reducing the time required for audits, while increasing their accuracy and avoiding potential liability claims from undetected failure or tampering with safety equipment. Based on in-flight compliant Bluetooth Low Energy (BLE) communication, equipment can be monitored continuously, during flight and on the ground, using a compact communication hub or mobile devices. Self-sustainability is achieved by harvesting energy from mechanical vibrations present in-flight and during taxiing, without requiring time-consuming battery change cycles and avoiding regulatory challenges for hazardous battery chemistries such as lithium-ion. The proposed research will also enable in-flight monitoring applications and automate new tasks such as ensuring compliance with in-flight seatbelt regulations. The proposed system will help passenger airlines stay profitable in a highly competitive market, realizing significant cost-savings through efficient operations, reduced turnaround times, and lower maintenance overheads.
This Small Business Innovation Research (SBIR) Phase I project aims to evaluate a mechanical energy harvesting design regarding its technical feasibility and effectiveness as a power source for asset tracking devices onboard an aircraft. To this end, new technologies for mechanical energy harvesting will be tested: (1) a novel stacked piezoelectric device with tunable resonance frequencies and output enhanced by superposition among different piezo-elements vibrating in phase and (2) a mechanical vibration amplifier which extracts large-amplitude linear motions from vibrations to enhance the amplitude of mechanical movements. The two new technologies may enable the first mechanical vibration harvester which is compact enough to permit effective use in asset tracking in the aviation industry, resulting in an energy harvesting module miniaturized to comply with aviation applications and to efficiently harvest the extremely low frequencies (<10 Hz) dominating cabin vibrations. The energy harvesting circuit prototype will be evaluated under realistic deployment conditions within the scope of this project and integrated in BLE-sensor prototypes to further evaluate its 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. -
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. -
AI-RIS, LLC
SBIR Phase I: Novel machine learning framework for the classification of non-mydriatic retinal images
Contact
11403 SHADOW WAY ST
Houston, TX 77024--5234
NSF Award
2151393 – SBIR Phase I
Award amount to date
$255,945
Start / end date
03/15/2022 – 12/31/2022
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is an artificial intelligence (AI)-based method to screen diabetic retinopathy (DR), the leading cause of vision impairment and blindness in the US. DR affects almost 4 million people in the US and is associated with direct annual costs of almost $500 M. If diagnosed early, clinical treatment and lifestyle changes can halt the progression of the disease, preventing blindness. However, retinal exams currently require expensive equipment and invasive eye dilation that restrict screenings to ophthalmology or optometry practices, leading to the under-diagnosis of the condition, particularly in underserved populations. This project advances a system with a new camera and a machine learning approach to enable recognition of DR and other retinal disorders by clinicians.
This Small Business Innovation Research (SBIR) Phase I project seeks to explore the feasibility of developing a novel software-enabled non-mydriatic fundus camera that can identifiy DR. The proposed innovation is based on: 1) a portable camera that uses near-infrared (NIR) light, invisible to the human eye, to illuminate the retina and acquire fundus images, enabling the use of the device by non-specialists; 2) a novel framework based on transfer learning, which trains Neural Networks with a limited amount of training data (100 images). In this project, a prototype system will collect NIR retinal images, with the goal of developing an AI classification algorithm capable of processing these images. In parallel, a new image processing algorithm will be developed to improve the resolution of the NIR images, based on contrast normalization methods and noise reduction techniques.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AIFLY VENTURES
SBIR Phase I: Drone Control in Turbulence via Reinforcement Learning
Contact
19745 NORTHAMPTON DR
Saratoga, CA 95070--3333
NSF Award
2037836 – SBIR Phase I
Award amount to date
$255,882
Start / end date
01/01/2022 – 12/31/2022
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 drone control. Current controllers are effective in specific environments but perform poorly in environments and flight conditions such as turbulence, thereby narrowing the scope in which drones can be used. This project will advance a plug-and-play solution in which users can focus on higher-level tasks specific to their use case, like obstacle avoidance and route planning. This new controller has broad applications in both commercial and military settings: it enables stable flight across a wide array of environments, expands the flight envelope in turbulent conditions, and allows for longer missions due to increased control efficiency.
This Small Business Innovation Research (SBIR) Phase I project addresses the problem of drone control in turbulence through the development of a reinforcement learning-based flight controller. The project will enlarge the design envelope for quadcopters as well as provide a system and environment for testing reinforcement learning algorithms that can be applied to other control problems. Contemporary systems rely on Proportional Integrative Derivative (PID) controllers as an essential part of stable flight. These PID controllers rely on holistically tuned, static functions to convert maneuvering commands into voltage changes across drone motors to meet the rotor’s targeted rotation speed. In lieu of statically defined PID equations, this novel controller uses a reinforcement learning algorithm, which is a subset of machine learning where an agent is trained to select actions that maximize a reward across an environment. This technique has led to greater-than-human performance across a variety of different control and game theory tasks, but little is known about how these techniques fare when replacing PID control systems. The primary advantage the development of a reinforcement learning controller would have over simpler PID controllers is the ability for the user to view drone control at a higher level of abstraction, thus mitigating the need to focus on the minutiae of flight control for complex missions.
This award reflects 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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable 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. -
AM BATTERIES, Inc.
SBIR Phase I: Development of Dry Manufacturing for High Energy Density and Low Cost Lithium Ion Batteries
Contact
211 ARLINGTON ST
Acton, MA 01720--2410
NSF Award
2136511 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/01/2022 – 01/31/2023
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase 1 project is to improve the energy density, decrease the cost, and reduce the energy footprint required to produce lithium-ion batteries. The global lithium-ion battery industry is growing at a tremendous rate due to the accelerated adoption of electric vehicles, robotics, and consumer electronics. Currently, a significant portion of innovation in the field of lithium-ion batteries and electrochemical energy storage solutions in general is focused around novel material chemistries and product designs. With the massive growth being witnessed in the industry, efforts to innovate production techniques must be undertaken to improve the entire supply chain. By applying the targeted novel manufacturing method, the ability to fabricate higher energy density lithium-ion batteries at lower cost will improve the competitiveness of manufacturers, increase the competitiveness of advanced battery manufacturing in the global context, and open up new energy storage applications. This technology development seeks to promote a solution that advances the capability and sustainability of battery energy storage solutions, benefitting the lives of U.S. citizens and society globally.
A solvent-free manufacturing technology to produce electrodes for lithium-ion batteries is being developed. This technology provides the capability to fabricate thicker electrodes with finely tuned architecture and performance characteristics. The conventional methods for electrode manufacturing utilize slurry casting which requires energy intensive drying, hazardous solvents, and may leave a considerable environmental footprint. A continuous feed dry spraying system will be designed, manufactured, installed, and operated to optimize the process and product. The technology provides a method to fabricate thick electrodes which will increase the capacity and energy density of the lithium-ion batteries. In this project, ultra-high area capacity electrodes (cathode: ~5mAh/cm2, anode: ~5.5mAh/cm2) will be fabricated with the solvent-free manufacturing process. The high area capacity electrodes will enable high energy density (>300Wh/kg) by reducing the quantity of inactive materials (current collectors, separator, and casing). The knowledge gained through this program may bring a novel dry electrode manufacturing technology to commercial readiness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AMPHIX BIO, INC.
SBIR Phase I: Scalable Manufacturing of Supramolecular Polymers for Regenerative Medicine
Contact
57 EAST DELAWARE PLACE APT 2802
Chicago, IL 60611--1624
NSF Award
2151711 – SBIR Phase I
Award amount to date
$252,906
Start / end date
03/01/2022 – 02/28/2023 (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 create a safe and effective therapeutic for spinal fusion surgeries. Over 500,000 people undergo spinal fusion surgery in the U.S. every year to treat debilitating back and neck pain. Compared to harvesting bone from a donor site on the patient, spinal biologics are popular among surgeons because they offer a synthetic, off-the-shelf implant requiring a single surgical site and offering consistent clinical outcomes. However, safety concerns surrounding these therapeutics have limited its approval for use only to the lumbar region of the spine, and high manufacturing costs of recombinant proteins can be prohibitive for widespread adoption. This project advances a technology that is safer and less expensive than the currently used biologics in spinal surgeries.
This Small Business Innovation Research (SBIR) Phase I project develops large-scale manufacturing methods for peptide amphiphile (PA) molecules, which self-assemble into supramolecular polymers that can reduce the dose of the biological necessary to achieve successful spinal fusion as demonstrated in preclinical large animal models. While highly promising, manufacturing supramolecular polymers at large scale presents challenges because supramolecular self-assembly is highly sensitive to processing steps and conditions. The project goal is to develop a scalable manufacturing method that results in PA assemblies with efficacy equivalent to PA assemblies produced in the research laboratory setting. To achieve this, PA molecules will be synthesized using industry-compatible methods to improve the scalability.
This award reflects 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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase I Project is to improve 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. -
ARCHAIC LLC
STTR Phase I: Camera-Based Multimodal AI for Health Monitoring
Contact
1766 ROCK HILL CHURCH RD
Matthews, NC 28104--3158
NSF Award
2136728 – STTR Phase I
Award amount to date
$255,992
Start / end date
03/15/2022 – 02/28/2023 (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 to mitigate healthcare costs and challenges associated with the nation's growing aging population. The outcome of this project will be a system that enables holistic, accurate, and faster monitoring of elderly people that will 1) improve quality of life and health of senior citizens, 2) address the future nursing shortage, particularly in the geriatric field, and 3) reduce healthcare costs. The proposed technology can impact a wide range of public health applications that require continuous, non-intrusive health monitoring.
This Small Business Technology Transfer (STTR) Phase I project applies real-time computer vision and sensor fusion processing for real-time continuous monitoring and analysis of health-related activities. In addition, this project takes an essential step beyond current solutions by analyzing seniors' group behavior and interactions with objects to determine whether they suffer from loneliness, behavioral disorders, or confusion states. This project utilizes multiple artificial intelligence algorithms to maximize the discriminative power to understand human micro-body motions and thereby create a training framework for personalized behavioral understanding and monitoring. It also proposes an innovative solution to leverage the results of computer vision as attention feedback to thermal sensors to enhance the accuracy and robustness of thermal processing against temperature variations. Furthermore, the project offers an integrative edge-based Internet of Things solution to protect citizens' privacy while providing real-time continuous feedback to responsible personnel. The proposed system offers a novel user experience while protecting personally identifiable information.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ARCTURA, INC.
STTR Phase I: Extremum Seeking Control of Wind Turbines and Wind Farms
Contact
42 LADD STREET SUITE 106
East Greenwich, RI 02818--4361
NSF Award
2126855 – STTR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 12/31/2022
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 introduction of a new wind farm control strategy that is expected to increase the power generated by a typical wind farm by 3-10%. Wind farm owners and operators face continuous pressure to reduce the price per megawatt-hour of the grid energy that they produce. Improving the energy yield of existing wind farms by optimizing array yaw angles (known as “wake steering”) may lower the cost of energy, increase our customer’s profits, and promote greater wind energy penetration in domestic and global grid energy markets.
This STTR Phase I project proposes to develop a new model-free approach to maximizing the annual energy produced by wind farms. On most wind farms, the turbines are operated independently, relying only on their individual wind sensors to determine the wind direction and to make control decisions to orient themselves to generate maximum power. The proposed approach will allow arrays of turbines to work together to minimize losses by steering the wakes of upstream turbines away from the downwind rows, increasing net power production. While this technique has been proposed in the past, the methods employed have relied on control algorithms that use models to determine the key operating parameters. Since every wind farm is different, those parameters must be tuned on-site using expensive and time-consuming calibration campaigns. Moreover, as the turbines age, those parameters can end up far from their optimal values. The new proposed scheme takes a different, model-free approach that may eliminate the need for parameter calibration while ensuring that the array continuously operates at its peak performance even as atmospheric and other environmental conditions change and the physical conditions of the turbines deteriorate.
This award reflects 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)
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)
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. -
AUCTUS BIOLOGICS, INC.
SBIR Phase I: Development of an Optical Biosensor to Facilitate Screening, Validation, and Development of Novel Drugs and their Biological Targets
Contact
2561 US ROUTE 11
La Fayette, NY 13084--3352
NSF Award
2129469 – SBIR Phase I
Award amount to date
$228,697
Start / end date
02/15/2022 – 01/31/2023
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 will improve drug discovery. The proposed project will advance the development of Surface Plasmon Resonance (SPR), a novel optical biosensor technology, that will accelerate the pace and efficiency of drug screening campaigns in academia as well as the pharmaceutical and biotechnology industries. There are currently no biosensor technologies on the market that offer the combination of high sensitivity, robust reusability, antibody-like binding affinity, and low cost. This project will culminate in the development of a technology and reagent-based kits for applications at scale.
The proposed project advances a technology engineered from a temperature, pH, and chemically stable proprietary protein composed of two fragments that bind with antibody-like affinity and specificity. The technology has been demonstrated to be effective in a variety of antibody-like applications, but without the stability shortcomings that plague traditional antibodies. By overcoming key barriers that limit large-scale use of SPR chips, this technology enables chip reuse and streamlines laboratory workflows, thus endowing the system with broad utility in antibody-centered applications. The project has three goals: establish suitability of the technology for the complete characterization of molecular interaction pairs, evaluate the technology’s robustness and versatility, and validate the technology in drug screening campaigns.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AUGRAY LLC
SBIR Phase I: Augmented Reality (AR) Web Commerce for Footware Retailers
Contact
18650 W CORPORATE DR STE 120
Brookfield, WI 53045--6344
NSF Award
2113729 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 enable footwear retailers to allow consumers to virtually try-on products on their eCommerce websites. Research suggests product fit and look are important parameters for over 66% of eCommerce shoppers. This research and development effort provides a convenicence for consumers that is readily implemented by existing eCommerce site. The technology allow customers to measure their foot size using a smartphone camera without a need for an app. The project develops and commercializes a novel Augmented Reality (AR) eCommerce platform, enabling retailers to offer customers unique and immersive online product-try-on shopping experiences instantly, reduces inventory instory, provides seamless conversion of existing e-Commerce websites to AR-enabled commerce platforms contributing to satisfied customers, higher sales, reduced returns, and decreased cost per sale.
This Small Business Innovation Research (SBIR) Phase I project will employ artificial intelligence, machine learning, augmented realiity (AR), and 3D modelling solutions to create eCommerce platforms that convert physical products into 3D models that work on all smart devices seamlessly. The successful product will provide high levels of performance and precision in the superimposition of images. Solution must ensure that the AR model ensures split second inference overlays and tracking streams with lightweight 3D visualizations and > 95% accuracy to fit into the real world. If successful, the proposed AR Commerce platform may be applicable to a variety of applications including retail and medical 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. -
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. -
Akanocure Pharmaceuticals, Inc.
SBIR Phase I: AK-423: A broad-spectrum antiviral and immunomodulatory agent (COVID-19)
Contact
3495 KENT AVENUE
West Lafayette, IN 47906--1074
NSF Award
2032097 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2021 – 12/31/2022
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 stems from the development of an efficient broad-spectrum antiviral agent addressing the current COVID-19 pandemic. The approach can also address future outbreaks of other viruses. The project is targeting the group of COVID-19 patients who will develop severe illness featuring multiple organ dysfunction. Those patients need ICU units and ventilators in amounts that can overwhelm the health care system. This project will develop an antiviral agent to mitigate the social distancing measures and improve quality of life.
This Small Business Innovation Research (SBIR) Phase I project focuses on the development AK-423, a potential efficient antiviral and immunomodulatory agent against COVID-19. The technical objectives focus on testing AK-423 (in-vitro and in-vivo) against COVID-19. Recent reports suggest that the multi-organ damage that occurs during COVID-19 infection is characterized by an exaggerated inflammatory response indicative of cytokine storm, auto-immunity, and a sepsis syndrome caused by complex abnormal immune reactions. An ideal treatment would not only suppress viral replication but would also regulate the abnormal immune response. AK-423 targets a host metabolic process that the virus hijacks. It is also a key process in the differentiation of lymphocytes. Inhibition of such process is proven to dampen the immune response, minimize immune response-induced tissue damage, inhibit production of pro-inflammatory cytokines, and efficiently shut down viral replication. This strategy will deliver an efficient broad-spectrum antiviral agent.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Anomalee Incorporated
SBIR Phase I: Post-training deep neural networks certification against backdoor data poisoning attacks
Contact
692 TANAGER DR
State College, PA 16803--2503
NSF Award
2132294 – SBIR Phase I
Award amount to date
$255,391
Start / end date
04/01/2022 – 12/31/2022
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 secure and certify deep learning models that are becoming ubiquitous in many safety and security-sensitive applications, such as finance, health, military/intelligence, cyber security, critical infrastructure, and personal/consumer use. Strong growth in deep neural network (DNN) deployments is forecast in the near term in several of these domains, some of which are subject to regulatory requirements that artificial intelligence (AI) models be certified to perform as advertised. This project proposes a new method to confidently certify against backdoor attacks.
This Small Business Innovation Research Phase I project will provide the first commercial prototype of a mathematically principled certification service for DNNs against evasive backdoor attacks (BAs). The proposed method is wholly unsupervised, requiring no known examples of poisoned DNNs nor any samples from the (possibly poisoned) training set. This project will advance a broadly applicable and computationally efficient approach through parallel computation leveraging cost-effective cloud-computing services, to address challenges such as very large input feature space dimensions and number of classes, as well as very large DNNs. Another challenge is to make the detector insensitive to the mechanism (e.g., additive, multiplicative) by which the backdoor pattern (BP) is incorporated into a sample across different application domains. In addition to "static" DNNs and image domains, the prototype will be able to: process recurrent DNNs; handle time series, point cloud, and document data domains; and defend AIs used for time-series prediction and regression. APIs will be developed to expand the prototype to defend against related attacks, e.g., backdoor patterns that are perceptible but "scene plausible" or test-time evasion attacks.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BACTANA CORP.
SBIR Phase I: Faecalibacterium prausnitzii supernatant oral formulations to improve insulin sensitivity and treat prediabetes
Contact
400 FARMINGTON AVE.
Farmington, CT 06032--1913
NSF Award
2151168 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 prevent and treat prediabetes and type 2 diabetes. More than 1 in 3 American adults have prediabetes or type 2 diabetes with associated healthcare costs exceeding $327 billion. Current therapies often present adverse effects or are ineffective in some patients. The top five human diabetes drugs alone are expected to cost $23 billion annually by 2024. This project advances a novel diabetic treatment composed of a postbiotic mixture from beneficial gut bacteria. This will improve clinical outcomes for prediabetic patients.
This Small Business Innovation Research (SBIR) Phase I project will evaluate the efficacy and elucidate the mechanism of a potential microbiome-based treatment toward an oral treatment that effectively reduces diabetes-associated markers. The three technical objectives are to: 1) evaluate the technology and demonstrate equivalent or superior performance compared to existing antidiabetic drugs, 2) better understand the mechanism that leads to efficacy in the treatment of prediabetes and type 2 diabetes, and 3) identify the active molecule(s) from the postbiotic mixture. These objectives will be carried out using rodent trials, cell-based assays, and advanced separation techniques.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (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 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. -
BEAMLINK, INC.
SBIR Phase I: Adaptable Ad Hoc Network Architecture for Rapid Infrastructure Development in Disaster Zones
Contact
892 N FAIR OAKS AVE
Pasadena, CA 91103--3046
NSF Award
2136602 – SBIR Phase I
Award amount to date
$250,928
Start / end date
03/15/2022 – 02/28/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is reducing the cost of getting people online and connecting people in emergency situations such as natural disasters. Natural disasters often destroy cellular networks, exactly when people need communication the most. The influx of users on the limited remaining infrastructure often overwhelms existing resources, making it impossible for first responders to coordinate, for families to call their loved ones, and for volunteers to help. In other potential markets, the technology seeks to provide cellular phone access to parts of the world where it is now prohibitively expensive. This project seeks to develop small, portable cellular base stations that can provide access in both emergency and hard to reach and poorly resourced locations.
This Small Business Innovation Research (SBIR) Phase I project researches and implements a small, portable cellular base station. The technological focus for the base station utilizes Global System for Mobile Communications (GSM) / General Packet Radio Service (GPRS) (or 2G and 2.5G) radio for communicating with a high density of cell phones in a computationally cheap manner while utilizing WiFi for local, high bandwidth applications. The technology implements many “micro-cells” in lieu of the current macro cell approach to cellular coverage, blanketing the area with a high number of towers. This decentralized approach provides high reliability even if one or several nodes fail. This project will develop the algorithms necessary for interconnecting large numbers of base stations together and mesh the networking capabilities that provide radio links between each base station. Finally, this project will finalize the mechanical design and make the base station manufacturable at large 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. -
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)
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
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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. -
BICURE LLC
STTR Phase I: In situ, handheld, 3D bioprinting of hydrogel sealant for corneal tissue repair and regeneration
Contact
9205 SPECTRUM
Irvine, CA 92618--3420
NSF Award
2136603 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is the ability to develop a corneal sealant that will achieve significant cost savings for the patient, hospital ecosystem, and taxpayer by circumnavigating the limitations associated with corneal repair using the sutures or cyanoacrylate glue. Nearly 7 million corneal/scleral tears and perforations occur in the US and require surgical intervention. Around one third of these injuries cause blindness and 80% lead to infections and other complications. The high sensitivity of the corneal surface results in extreme discomfort and trauma with even slight abrasions and scratches. A significant portion of patients using current standards of care, i.e. sutures and cyanoacrylate glue, suffer from postoperative complications like eye fluid leakage, infection, and astigmatism requiring extensive care or corrective surgery. The sealant developed here may reduce these issues, resulting in cost savings for patients and insurance companies while improving the patient experience.
The proposed project seeks to optimize and fine-tune the sealant formulation as well as its application onto the corneal surface using a handheld bioprinting pen for the repair of corneal injury as well as the develop an appropriate models for its evaluation. The first objective aims to standardize and optimize sealant extrusion and photocuring onto the corneal surface while conforming to the depth and shape of the corneal injury. The results may optimize parameters to form a sealant film with improved biocompatible, mechanical, and adhesive properties. The second objective aims to establish sealant efficacy in corneal repair via long-term integration with the corneal tissue, using a corneal injury model. The expected results will establish the integrative capacity of the adhesive for filling corneal defects.
This award reflects 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 (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 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. -
BIRDHABITATBOT LLC
SBIR Phase I: A robotic system for removal of invasive plant species
Contact
515 PLEASANT ST
Willimantic, CT 06226--3221
NSF Award
2126637 – SBIR Phase I
Award amount to date
$240,060
Start / end date
08/15/2021 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project is to improve habitat for native plants and wildlife by removing invasive plants with a mobile robot. Worldwide invasion by non-native plant species is a primary concern in forest ecosystem health and biodiversity. Within the highly fragmented landscape of the Connecticut forest, two invasive plants significantly contribute to the degradation of habitat: Japanese barberry and multiflora rose. Current methods to eradicate them are time-consuming, expensive, and ultimately ineffective. This project presents a novel method of detecting and removing Japanese barberry and multiflora rose. Deep learning technology enables additional use with other invasive species, increasing the system's value throughout natural resource management. Additionally, once programmed, the robots will be easily operated, making them usable for a variety of personnel. This SBIR phase I project will advance current robot prototypes being tested for weed detection and removal.
There is currently no mobile robot designed and programmed to remove understory invasive shrub species in a deciduous forest ecosystem. The technical challenges that will be addressed in building a feasible robot prototype include navigating over the unstructured terrain of the forest floor, developing a cutting attachment for the robotic arm, and creating a hybrid soft-rigid platform to withstand forest floor hazards while averting tree seedling damage. The proposed system will operate as follows: (1) an unpiloted aerial system (UAS, i.e., drone) flies over the canopy to capture images of the forest understory; (2) images are then labeled and converted to species location maps; and (3) utilizing these maps, a semi-autonomous mobile robot navigates to the invasive species locations for removal. The robots will be programmed for semi-automated missions monitored by an operator nearby at a safe distance to ensure worker safety.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIRED IMAGING INC
SBIR Phase I: Innovative Breast Cancer Detection Algorithm Using Infrared Images
Contact
44 BRANDYWINE LN
Rochester, NY 14618--5602
NSF Award
2136325 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2022 – 12/31/2022
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve monitoring and prevention of breast cancer with mammograms. Over 48 million screenings are performed each year in the US, and up to 10% women are recalled for further evaluation. Dense tissue found in 40% of women masks tumors in mammograms. Ultrasound is used as a complementary technique but it detects both malignant and non-malignant tumors and an additional biopsy is needed to detect cancer. Over 90% of the recalled women do not have cancer, resulting in added cost and unnecessary anxiety among healthy women. On the other hand, limiting the recalls to under 10% causes some cancers to be missed. This project advances a new infrared imaging (IR) technology unaffected by breast density. It is sensitive to only cancerous tumors because it uses their higher metabolic signature, and it can provide accurate estimates of the tumor size and location within the breast. The proposed IR imaging technology will reduce the overall healthcare cost and improve clinical outcomes.
The proposed IR technology will provide an effective adjunct to mammography and it will identify cancerous tumors in dense breast tissue as well. It uses contactless IR imaging and the spatial and thermal data obtained from multi-view IR images of individual breasts. The IR images are obtained in prone position to avoid gravitational distortions and provide clear optical access over the entire breast, including the region of inframammary folds. The heat transfer from the tumor to the breast’s surface is analyzed and modeled as a straightforward physical system. The temperature profile on the breast surface is iteratively compared with the IR images until a match is obtained indicating whether a cancerous tumor is present. The analysis predicts the malignant tumor size and its location is clearly displayed to a radiologist. The approach is patient-specific. The overall breast cancer detection rate is expected to improve, while reducing the recall rates and unneeded biopsies in healthy women.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BLINXEL LLC
SBIR Phase I: Multi-depth-camera volumetric video recording and streaming
Contact
355 S GRAND AVE STE 2450
Los Angeles, CA 90071--9500
NSF Award
2111631 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 02/28/2023 (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 improve digital content delivery of volumetric content, or representation of 3D subjects. Current volumetric content is commonly limited to very short clips (typically < 10 seconds) due to huge file sizes. This research advances a low-cost, live-streaming, 360-degree volumetric content platform with no duration limits, even on 4G networks. An individual will be able to take low-cost, readily available components and create what would commonly be referred to as a hologram of themselves, for live broadcast and/or recording. The content will be compatible with existing mobile devices, and most commercially available wearable extended reality (XR) devices. both mobile and tethered. Due to the entry-level off-the-shelf hardware that this project will leverage, volumetric content creation costs will be on par with online video production costs, ensuring broad adoption across a wide number of applications, including medical, education, training, safety, entertainment and telecommunications.
This Small Business Innovation Research (SBIR) Phase I project seeks to enable the capture of a human subject using two or more depth-sensors, quickly combine those in a single stream of compressed video, and broadcast them to mobile and wearable devices using existing cloud services. This content can then be viewed on a standard two-dimensional device like a mobile phone, or on a 3D device like an XR wearable. The content will be fully realized, and viewable from any angle at any time. There will be no duration limits, and file sizes will be comparable to standard HD video content.
This award reflects 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
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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. -
BORON NITRIDE POWER LLC
STTR Phase I: Novel Batteries Based on Functionalized Hexagonal Boron Nitride with High Energy, High Power, Long Cycle Life, and Thermal Stability
Contact
155 N HARBOR DR STE 3613
Chicago, IL 60601--7368
NSF Award
2109286 – STTR Phase I
Award amount to date
$256,000
Start / end date
01/15/2022 – 12/31/2022
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of lightweight, thermally safe batteries with high energy densities that can be charged fast, last a long time, are composed of environmentally benign materials, and can store energy at a low cost. Such batteries would enable the large-scale penetration of long-range electric cars and other electric vehicles, including airplanes and drones in transportation. This process reduces environmental pollution and leads to greater energy efficiency.
This STTR Phase I project proposes to use boron nitride based layered ceramic materials as a means of storing electrochemical energy in solid state batteries. This project enhances scientific and technological understanding on the design of advanced functional materials for energy storage at the atomic level. To achieve the targeted high performance energy storage at the macroscopic level, the underlying material structures must be carefully selected on the atomic and molecular levels. Two-dimensional materials, such as graphene or hexagonal boron nitride, may contain functional groups that can be reversibly reduced and oxidized and can be utilized as electroactive species in cathodes of rechargeable batteries. The great advantage of these materials is that they can realize simultaneously high energy and power density for thousands of charging/discharging cycles as demonstrated in graphene oxide batteries with lithium and sodium anodes. Graphene oxide is, however, thermally unstable. The project proposes to substitute graphene oxide with functionalized boron nitride in order to achieve thermal stability while preserving performance. Furthermore, the functionalized boron nitride is also capable to play the role of a solid electrolyte in addition to being an electroactive species. Particular focus will be made on synthesizing -OBF3 functionalized boron nitride. This functional group occurs as a Lewis adduct of surface oxides (such as graphene oxide or boron nitride oxide) with BF3 (an electrolyte component) and is particularly promising as a compact electroactive species and electrolyte.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BOSTON GEOSPATIAL, INC.
SBIR Phase I: Operational Monitoring of Large-Area Critical Infrastructure
Contact
572 RIVERSIDE AVE UNIT 2
Medford, MA 02155--5052
NSF Award
2112228 – SBIR Phase I
Award amount to date
$253,550
Start / end date
01/01/2022 – 12/31/2022
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 lower the geohazard risks for assets within critical infrastructure sectors such as energy, transportation, and utilities. More specifically, the proposed technology will make measuring and detecting ground motion with satellite radar more practical in applications where the observed areas cover very long distances and traverse varying terrain and land types. The innovation seeks to demonstrate that the combined processing of multiple imaging frequencies and polarizations can improve the information collected and that the fusion of global navigation satellite system (GNSS) data can be used to aid insight. The efficacy of space-based satellite radar interferometry in measuring shifts in spatially-sensitive structures such as buried pipelines, foundations, and rail track ballast will be demonstrated over very large areas and linear distances. The technology developed in this project may have a positive impact on the aforementioned sectors by enabling monitoring capabilities that are timelier and more cost-effective than traditional approaches. The geospatial technology may also enable asset operators to be more proactive when it comes to geohazard threats, lowering the frequency of fatal and environmentally-damaging failures.
This Small Business Innovation Research (SBIR) Phase I project seeks to address the key shortcomings of space-based satellite radar interferometry as a means to monitor surface motion threats to critical infrastructure assets. While interferometric approaches for specific types of terrain have been well documented and validated, approaches that produce coherent ground motion results over very large areas with varying terrain and radar scattering mechanisms have not been successfully deployed. Furthermore, combining multiple interferometric observations together to decompose ground motion has received little research attention despite being an important step in translating the relative line-of-sight satellite observations into ground motion components relevant to asset monitoring. This research effort seeks to demonstrate the efficacy of using multiple imaging frequencies and polarizations and combining their interferometric results to create a more continuous view of ground motion over areas with varying degrees of vegetation. This project may also demonstrate that combining both small baseline subset and persistent scatter interferometric approaches can improve the density of resolved scatterers over areas where land type variations create a diverse range of scattering mechanisms. The team also seeks to demonstrate the use and accuracy of GNSS data in the reference setting process as insights are translated into absolute motion components about the geodetic reference.
This award reflects 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
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 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 (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 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. -
BRIO DATA GROUP, LLC
STTR Phase I: Exploring Artificial Intelligence (AI)-Enabled Skills Data For Education-to-Employment Transitions and Career Support
Contact
3120 WOODCREST CREEK DR
Norman, OK 73071--2550
NSF Award
2112276 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 02/28/2023 (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 empower individuals to thrive in a world of innovative disruption through the development of an enduring, data-driven, ready-access digital service that will assist learners to identify opportunity pathways throughout a lifetime of learning and employment. Completion of this project and the addition of the proposed analytical capabilities applied to learner narratives may create a powerful and unique set of tools for individuals, secondary and higher educational institutions, employers, and a range of informal education providers. The research completed in this project and tools produced by it seek to inform a new approach to matching the interests, skills and educational backgrounds of learners to jobs and educational opportunities. This approach engages learners of diverse backgrounds early in their education and assists them in succeeding in many fields that currently suffer from lack of diversity, especially in the STEM disciplines. Better matching of skills and interests to learning trajectories and career options may enhance human development broadly, increase job satisfaction, and lead to a more productive workforce.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop methods for bringing a wide range of learner interests and achievements into a common framework that will be used to match a learner’s current state to specific opportunities and general development pathways. The project also seeks to assess the value of opportunities and chance of success for the student. This research centers on machine analysis of written reflections. Findings digitally mined from written reflections and potentially from other kinds of narrative artifacts are combined with data from grades, test scores, and other skills assessments and certifications to guide learners toward attractive educational and employment opportunities. In addition, findings from interactive visualization tools support human exploratory analyses of machine categorizations in order to improve the delivery of educational 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. -
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. -
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 (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 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. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to improve capacitor technology in power conversion equipment used to electrify our transportation systems. Capacitors are critical components to the systems needed to accelerate the energy transition from petroleum to other fuels. This project will develop new electrical materials and production processes for capacitors. The new electrical materials are formulated to be less hazardous to humans and the environmental while also being compatible with more efficient manufacturing processes. Benefits of the proposed technology include faster charging rates of electric vehicles and reduced sizes of on-board batteries, which lowers the cost and environmental impact of electric vehicle manufacturing. Reduced costs will allow a broader population access to electric vehicles. Through development of these new electrode materials and processes, manufacturing of capacitors in the United States will be available to serve the growing US electric vehicle industry.
This goal of the proposed work is to develop electrode materials and roll-to-roll processes compatible with an integrated, continuous manufacturing process for multilayer capacitor products. By combining additive manufacturing process in a roll-to-roll system, sequential deposition, drying, and curing of alternating layers of dielectrics and electrodes will enable production of multilayer capacitors in a single system at atmospheric pressure. Electrode inks and printing processes used in flexible/hybrid electronics do not meet the specifications to replace vacuum-based evaporation or sputtering of thin electrode layers for capacitor applications. The primary approach will be based on adapting the layer coating and alignment techniques developed for dielectrics to conductive materials. These electrode materials will improve upon state-of-the-art conductive inks with poor interfaces between particles to produce dense layers with uniform thickness and low surface roughness. This project seeks to provide prototyping of multilayer capacitors produced in discrete processing steps for verification of electrical performance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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. -
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
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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. -
CIRCULATECH LLC
SBIR Phase I: Automated Clot Preventing Chest Tube
Contact
2751 SW 130TH TER
Davie, FL 33330--1202
NSF Award
2131777 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2022 – 01/31/2023
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 aims to develop strategies to mitigate occlusion of thoracic catheters (chest tubes). A study by the Cleveland Clinic determined that 36% of chest tubes were completely obstructed at one point, with 86% of these clots existing in the thoracic cavity, undetected by clinicians. The complications that result from occluded chest tubes can include postoperative atrial fibrillation, hemothorax, and cardiac tamponade. The team will design, develop, and commercialize a novel chest tube to solve the high impact clinical need. This novel chest tube seeks to reduce drainage-related complications following cardiothoracic surgery. The novel system proactively manages fluid flow within the inner lumen of a catheter in order to flush and drain the tube, reducing the incidence of blood clogging.
The proposed activity seeks to develop a chest tube that proactively provides fluid flow in order to prevent blood clot formation associated with draining fluid and blood during cardiovascular surgery. The product introduces a novel approach called dilutional coagulopathy for addressing clotting issues, where sterile saline or anticoagulants is proactively used to reduce thrombosis in an enclosed drainage spaces, rather than rely on historical methods of chemical or mechanical barriers for reducing or hindering clot formation. The project aims to develop prototypes using biomaterials and fabrication methods suitable for eventual patient use, and undertake the risks of demonstrating proof of concept and reduced clotting in an animal model of post-surgical drainage complications.
This award reflects 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 – 01/31/2023
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (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. -
COHI GROUP L.L.C.
SBIR Phase I: Deep learning diagnosis and platform for at-home ear evaluations in children
Contact
1455 SKILES LN
Arden Hills, MN 55112--3641
NSF Award
2036021 – SBIR Phase I
Award amount to date
$247,568
Start / end date
02/15/2021 – 12/31/2022
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 improve pediatric health. Pediatric ear infections often manifest at night and the child must wait until the next day for an evaluation and treatment. The intention of this project is to create a deep-learning at-home ear infection diagnostic system.
This Small Business Innovation Research (SBIR) Phase I will advance translation of a pediatric ear-imaging system. The objectives include: generating a training data set with images labeled with correct diagnoses from a pediatric clinical setting; creating a deep learning algorithm with transfer learning from well-established convolutional neural networks for prediction; creating a prototype software interface to label a new image presented to the system; and designing a speculum for at-home image acquisition.
This award reflects 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. -
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. -
CONOX, LLC
STTR Phase I: Sustainable Glass Raw Materials and Processes for the Upcycling of Waste Concrete into SIlicate Glass
Contact
25318 OAK KNOT DR
Spring, TX 77389--4021
NSF Award
2023638 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2020 – 12/31/2022
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 provide waste concrete as a new raw material source for the glass and other industries. It is estimated that 2.2 billion tons of waste concrete is generated globally each year. About 70% of the construction waste generated in the US is concrete, but it is not typically used as a raw material for glass production or other chemical processes. Using concrete as a raw material reduces its contribution to landfills as well as the need for mining virgin raw materials., and contributes environmental benefits. This STTR Phase I project will study processes to prepare furnace-ready concrete for glass production.
This STTR Phase I project will study the feasibility of waste concrete as a raw material constituent (feedstock) for calcium-silicate glass and glass-making. Environmental benefits are possible because concrete contains the same key oxides used in glass making (silicon, calcium, aluminum and iron oxides) as well as sulfur compounds (e.g. gypsum mixed with the cement to regulate setting, and therefore can potentially serve as a candidate raw material in the production of calcium-silicate soda lime and calcium-borosilicate glasses.Research objectives include: 1) characterize variations in chemical composition from industrially relevant sources; 2) determine variation in contaminant concentrations; 3) demonstrate processes and methods to address contaminant variations' 4) characterize the specifications for a furnace-ready waste concrete glass batch; 5) produce pilot batches of calcium-silicate soda lime glass; and 6) characterize variations in produced glasses.
This award reflects 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)
Errata
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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. -
CROSSMHV, L.L.C
STTR Phase I: Rapid-Release Cell Culture Platform for Flow Cytometry
Contact
30683 USF HOLLY DR
Tampa, FL 33620--3068
NSF Award
2126903 – STTR Phase I
Award amount to date
$255,478
Start / end date
01/01/2022 – 12/31/2022
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 enable new health diagnostics, advance personalized medicine, and accelerate research for various diseases, including many types of cancers. Many methods used to diagnose disease are limited by the methods used to process patient samples. Commonly used processes can disrupt or destroy disease markers present in samples, leading to concerns about diagnostic dependability and accuracy. The proposed product platform can address this pain point by retaining disease markers as well as increasing yields which results in higher-fidelity experimental results and ultimately, enhances diagnostic medicine.
The proposed project will advance the development of a transformational biotechnology platform which non-destructively detaches adherent mammalian cells from a cell dish surface. Existing methods can damage these cells and are highly varied in cell yields which greatly limit clinical applications for disease diagnosis and therapeutic discovery. To fulfill its promise as a highly compelling alternative to existing methods, the following technical hurdles will be addressed in this project: 1) determining the optimal composition and design of the material, 2) validating the effects of the platform on cells, 3) using fabrication methods conducive to manufacturing purposes, and 4) benchmarking its performance against existing Flow Cytometry methods for adherent 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. -
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 (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 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. -
CURUVAR LLC
SBIR Phase I: Distributed Secure Enclave For Modern Enterprise Networks And Critical Information Systems
Contact
663 CELEBRATION AVE
Celebration, FL 34747--4979
NSF Award
2051989 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 02/28/2023 (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 protect critical infrastructure and enterprise information systems against malicious digital adversaries at all levels. Critical information systems, such as those which facilitate essential services or maintain highly sensitive/valuable digital assets, represent significant potential targets for highly sophisticated adversaries. Consequently, vulnerabilities in these systems present grave security threats. The proposed project will develop a new method for securing critical information systems that offers both higher protection and accessibility for less sophisticated users.
This SBIR Phase I project proposes to construct and evaluate a prototype implementing core functionality for a Distributed Secure Enclave capable of acting as a decentralized, intrusion-tolerant root of trust for zero-trust security infrastructure. By combining advancements from distributed cryptography and intrusion tolerant distributed systems within a closed/permissioned Distributed Ledger (DL) network, such a platform will have the ability to operate both as a decentralized system of record and cryptographic key escrow service. These capabilities, once proven, could then be extended to provide critical enterprise security services such as secret storage/management, data/document encryption, certificate/key management, identity and access management (IdAM), secure communication services, and many others in a manner that is provably secure—including in the presence of sophisticated adversaries. By constructing and formally evaluating a functional prototype of this technology, this proposed project aims not only to prove the technical efficacy of this particular security solution, but also to demonstrate a novel paradigm for applying DL technologies for practical applications within the enterprise.
This award reflects 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 (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 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. -
DEEPCAST, LLC
SBIR Phase I: Automatic Generation of Physics-Informed AI Models
Contact
1334 BRITTMOORE RD STE 1326
Houston, TX 77043--4033
NSF Award
2037517 – SBIR Phase I
Award amount to date
$255,613
Start / end date
05/15/2021 – 12/31/2022
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to democratize the model building process for multiple industrial applications by: (1) making it easy to build models within hours instead of weeks, (2) cut model building costs by 10x or more, and (3) significantly mitigate risks by providing more accurate and interpretable models that are constrained by underlying physical principles. This technology would unlock a new generation of modeling workflows that are more scalable, have less uncertainty, and improve the structural visibility and interoperability of complex processes that are partially understood. As a result, companies would have tangible ways to reduce modeling costs, streamline optimization and control of operations and ultimately, achieve better decisions at economically viable rates. More broadly, the proposed technology should inspire various innovations and enhancements to products and services that strongly rely on physics modeling. It is expected that tangible results would induce profound effects across multiple sectors, including agriculture, environmental science, civil engineering, manufacturing, aerospace, construction, logistics, and medicine.
This Small Business Innovation Research (SBIR) Phase I project will set the technical and business foundations required to automate and expedite the construction of reduced physics models from data with minimal human intervention. The goal for this project is to implement fast and reliable mechanisms for: (1) mapping spatio-temporal data of the physical world into structural network representations; (2) leverage the data from these network representations to generate a suitable set of equations that explain the underlying dynamics; (3) use advanced optimization techniques to find a list of models that capture the best combination of network and equations matching the observed data; and (4) orchestrate all these pieces into a single artificial intelligence platform that automatically consolidates data and human interactions for model building and visualization. Efforts in Phase I are particularly focused on demonstrating that the resulting models are physically sound and sufficiently robust for describing the dynamics of fluid transport and diffusion based on different amounts of available data and 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. -
DIAMOND AGE TECHNOLOGY LLC
SBIR Phase I: Composing Digital-Twins from Disparate Data Sources
Contact
15714 CRESTBROOK DR
Houston, TX 77059--5218
NSF Award
2106410 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 relates to the creation of a "digital twin," a real-world system projected into spatially-computed environment such as virtual and augmented reality. This technology creates the infrastructure necessary for the application of virtual and augmented reality in industrial workplaces, at scale. By making the full-scale roll out of these technologies possible, the technology seeks to impact human health and safety, operational efficiencies, and environmental risk reduction for process operations facilities, such as oil refineries and chemical plants. The long term impacts of the technology may also enable automation and optimization, improving their efficiency, security, and safety. Such facilities are critical infrastructure and play a significant role in the national economy. The availability of this product may also enhance market opportunities for other businesses in the scanning, spatial computing, and training markets. The impact may be further broadened by adapting the process for digital twin production to new domains unrelated to the industrial market.
This Small Business Innovation Research (SBIR) Phase I project is advancing knowledge and understanding in both machine learning and spatial computing. This project focuses on a method for digitizing a complex, real-world system, in an efficient manner, sufficient to recreate the captured reality as an interactive digital twin. The primary technical hurdle is the combining of different data sources that describe aspects of a particular real-world system into a single complete description. The initial physical systems being modelled are industrial process operations, but the core methods could apply to other types of systems, including natural systems, such as a rainforest. For industrial process operations, the goal is to encode the entire process operations facilities at the component level, with sub-cm accuracy, at 10% of the current time and cost requirements. To achieve this, this project will combine physical scans with engineering documentation and relational probabilities. Once combined, the model will be used as the basis for a digital twin of the real-world system projected into spatial computed environments, such as virtual and augmented reality. These techniques replace a tedious and impractical static scan and human labor workflow with rapid scans, computer vision, and a combination of procedural and trained 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. -
DIFFRACT TECHNOLOGY, INC.
SBIR Phase I: Novel Holographic 3D Optical Metrology Tool for Precision Low-Volume Manufacturing
Contact
6 SUNHILL ST
Portola Valley, CA 94028--8050
NSF Award
2127080 – SBIR Phase I
Award amount to date
$254,901
Start / end date
01/01/2022 – 12/31/2022
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is for the development of a precision three-dimensional (3D) optical metrology tool for in-process quality control. The proposed tool uses a high-resolution, computer-defined 3D light field to perform rapid multipoint non-contact measurements on parts during the fabrication process. The tool uses an adaptive process to enable 3D metrology with sub-10-micron resolution, at a fraction of the price of competing technologies. Low-volume, high-precision manufacturing plays a critical role in the global economy and is currently a limiting factor in the creation of new assembly lines, larger volume manufacturing, research timelines, and tool creation. The tool itself will benefit small businesses in hardware development by improving part quality through feedback during the manufacturing process. Already, surface inspection systems account for a global $3.7 billion market which is projected to grow to $5.3 billion over the next five years. This strategically impactful innovation is aimed at assisting small businesses, students, trainees, and professional specialty machinists in achieving complex, precision tolerances on low-volume parts.
The intellectual merit of this project advances core technology for precise optical projections, based on a novel component that generates a computer-defined high-resolution projected light field to enable both versatility and high-performance metrology. A programmable light field creates the opportunity for direct user feedback by projecting real-time measurement information onto the part under inspection. The objective of this study is to measure and optimize the design of this programmable device by experimentally evaluating the device stability, field of view, spatial resolution, and efficiency for several design permutations. Additional goals include evaluating the device for its manufacturability, repeatability, and commercial viability. Simulations suggest capabilities including a 60-degree angular field of view and sub-10-micron projection spot size at a nominal working distance of 40 centimeters. Further development of this core technology, when combined with commercially available components, will enable the creation of a compact, high-precision, economically viable tool that provides exceptional reliability for metrology 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. -
DIRECT COMBUSTION TECHNOLOGIES, LLC
SBIR Phase I: Integrated Technologies for Addressing Environmental Challenges in the Energy Industries
Contact
6307 BELLE GROVE DR
Baton Rouge, LA 70820--5023
NSF Award
2052367 – SBIR Phase I
Award amount to date
$255,597
Start / end date
05/01/2021 – 12/31/2022
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 capture carbon dioxide from the burning of fossil fuels and sequester it safely from the atmosphere. This project uniquely combines two new technologies to eliminate the carbon dioxide emissions resulting from flaring of huge volumes of natural gas in remote oil fields; the technologies burn it in a novel combustion system and uses the generated heat to treat the oil-field produced water. The cooled flue gases of combustion are then injected via a novel process into oilfields for enhancing oil recovery. This makes the entire process economically feasible and environmentally beneficial.
The proposed combustion system involves a novel concept of “Fire-in-Water” to carry out combustion of a fuel directly within a flowing stream of water, thereby enhancing the heat transfer coefficients by several orders of magnitude compared to conventional indirect heat transfer systems involving metallic heat transfer surfaces (such as shell-and-tube heat exchangers) separating the heated and heating media. This project proposes this combustion system to burn natural gas currently wasted through flares in remote oil fields, resolving a major environmental problem facing the industry. The second innovation utilizes the heat generated by combustion of flare-gas in the novel burner to treat oil-field produced water, another long-standing environmental concern. The third innovation uses the flue gas generated by combustion (of flare-gas) for injection into oil fields to produce trapped oil. The project will demonstrate: (1) Successful adoption (through application of combustion, heat transfer and two-phase flow principles) of the combustor design from steam generator to flue gas generator; (2) The combustor’s ability to burn flare-gas of varying hydrocarbon contents and compositions; (3) The ability to treat oil-field produced water; (4) Field-scale viability; and (5) Mathematical models and computer simulations for implementation and process scale-up.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (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 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. -
DISTRIBUTED SPECTRUM LLC
SBIR Phase I: Ultra-Low-Cost Distributed Spectrum Monitoring
Contact
228 FELLSWAY
Somerville, MA 02145--1004
NSF Award
2112062 – SBIR Phase I
Award amount to date
$231,904
Start / end date
01/01/2022 – 12/31/2022
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 apply low-cost radiofrequency (RF) sensing hardware to detect, monitor, and localize transmitters in industrial and urban environments. This technology can solve key problems in manufacturing and logistics operations such as finding RF transmitters that are interfering with operations or monitoring the health of radio systems. These activities are required in modern industrial environments as increasing numbers of critical systems rely on radio communications to operate. In urban environments, automating the tasks of detecting, monitoring, and localizing transmitters can simplify the management of large-scale radio networks and gather critical data on wireless device usage. Increased instances of intentional jamming and the rollout of new communications standards such as 5G make these tasks critical to the modern city. Traditionally, such monitoring tasks are conducted manually with expensive spectrum monitoring equipment. Automated installations also utilize expensive sensors, making automated spectrum monitoring only feasible in safety-critical areas such as around airports. Lower-cost sensors can be installed permanently at a high density for almost any application, allowing cities and smaller industrial customers to deploy persistent monitoring networks.
This Small Business Innovation Research (SBIR) Phase I project seeks to deploy high-density networks of low-cost sensors, determine the efficacy of existing detection and localization algorithms as applied to the network, and evaluate novel machine-learning (ML) algorithms for similar tasks. This project will also mitigate the technical risk of deploying such a system by characterizing how well commodity software-defined radio (SDR) hardware can perform across a variety of operational environments. No high-density and large-scale test networks of inexpensive radio hardware have been deployed for the purposes of industrial and urban spectrum monitoring, so data gathered throughout this SBIR Phase I project will be useful in evaluating the viability of this approach. By evaluating ML algorithms for signal detection and localization, this project can help determine how effective machine learning models can be at ingesting RF data from low-cost sensors and synthesizing actionable outputs about the radio environment. The result of this project will be an analysis of the detection and localization performance of a variety of algorithms across different environments and sensor node densities.
This award reflects 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 (Estimated)
NSF Program Director
Errata
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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
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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 (Estimated)
Errata
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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)
Errata
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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. -
DYNOCARDIA, INC.
SBIR Phase I: Motion artifact management for accurate and continuous non-invasive blood pressure monitoring
Contact
1 BROADWAY
Cambridge, MA 02142--1100
NSF Award
2151591 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable accurate, continuous, and widely available blood pressure (BP) measurements. The current standard of care is single point-in-time BP monitoring using an arm-cuff device. This method has two basic drawbacks: inaccuracy and the inability to measure BP continuously over 24 hours, limiting clinical insight. The major challenge to continuous reliable BP measurements is motion artifacts due to movement, such as an arm gestures. This project will advance development of a novel device for non-invasive beat-to-beat BP measurement in a cuff-less, wrist-wearable device. Accurate 24-hour BP measurement at home and other settings will significantly improve outcomes for 1.5 billion people globally who suffer from chronic high BP or hypertension, a leading cause of stroke and heart attacks. Other chronic conditions benefiting from accurate 24-hour BP measurement include sleep apnea, heart and renal failure, and dementia.
This Small Business Innovation Research (SBIR) Phase I project utilizes a highly sensitive optomechanical sensor to capture video images of skin displacement over the radial artery to independently measure systolic and diastolic BP continuously. The technology measures BP accurately and continuously in stationary conditions (i.e., seated or lying down). The goal of this project is to identify, characterize and address motion artifacts that occur during routine use in hospital intensive care units and operating rooms.
This award reflects 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. -
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. -
ELATEQ, INC.
SBIR Phase I: Advanced electrochemical degradation of PFAS in water
Contact
31 SALEM PL
Amherst, MA 01002--1888
NSF Award
2150907 – SBIR Phase I
Award amount to date
$236,645
Start / end date
03/15/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impacts of this Small Business Innovation Research Phase I project are to create a method for the degradation of per- and polyfluoroalkyl substances (PFAS) – often called “forever” chemicals - in water. PFAS contamination is a significant global problem, and it is estimated that 97% of US citizens have PFAS in their blood. The resultant human and animal health implications include immunological, reproductive, developmental, hepatic, hormonal, and carcinogenic diseases. Currently, the removal of PFAS in drinking water resources is a major focus of the federal government and among many state governments. However, the cost, intensive maintenance, and complexity of available advanced water treatment technologies have often made their adoption out of reach. While these harmful PFAS are difficult to destroy, the proposed novel process transforms them into harmless byproducts. This project has the potential to treat PFAS-contaminated water with lower energy costs and faster removal rates, which could be broadly useful to affected communities throughout the country. The approach integrates advanced processes without extensive energy requirements and without the need for chemical use and post-processing. This technology is expected to be affordable, scalable, and easy to operate and maintain on-site.
This SBIR Phase I project proposes to design and implement a novel cathodic treatment system for the removal of per- and polyfluoroalkyl substances (PFAS) from groundwater. The unique design proposes to employ both reductive and oxidative cathodes for PFAS removal. The project aims to research, design, and test an electrochemical cell prototype with novel electrode materials that support electrochemically-induced reduction and oxidation processes. Tasks include testing the electrode substrates and catalyst-coating materials and optimizing the operational parameters relative to rapid breaking of C-F bonds and low-energy consumption. The project will develop a robust electrochemical device that operates under environmentally relevant concentrations of PFAS and other co-contaminants, such as natural organic matter and chlorinated volatile organics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMERGENCY MEDICAL INNOVATION, LLC
SBIR Phase I: Development of a nasal compression device with medicated intranasal sponges for the treatment of nosebleeds in any setting
Contact
7825 BROWNS BRIDGE RD
Highland, MD 20777--9557
NSF Award
2136297 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project is to help treat the common nosebleed. Nosebleeds are a common problem that 60% of people experience. The proposed project develops an effective and low-cost innovative technology to address this by combining external pressure with intranasal medication when placed in a nominal manner by any user. The solution would provide a simple method that reduces the need for patients to visit health care services, and reduces the burden of health care providers for treating nosebleeds.
The goal of this project is to design and develop an effective nosebleed treatment device for children and adults that combines external pressure using a prototype nasal clip with intranasal medication sponges. The objectives of this project include completing systematic studies towards (1) design and development of a nasal clip with pre-medicated intranasal sponges capable of consistently applying the proper amount of pressure and eluting the proper amount of medication when placed in a nominal manner, (2) testing of the device using a nosebleed model, (3) identifying manufacturing processes to commercialize and scale the device in a cost effective manner. The outcome will be a functional and lab tested nosebleed treatment clip.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMTRUTH, INC.
SBIR Phase I: A Platform for Health Care Data Integration Using Blockchain and Artificial Intelligence
Contact
1830 DEERMONT RD
Glendale, CA 91207--1028
NSF Award
2125909 – SBIR Phase I
Award amount to date
$254,091
Start / end date
02/15/2022 – 01/31/2023
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to improve health outcomes while managing costs. The proposed technology enables the integration and retrieval of data from many places and formats across a distributed ecosystem secured by blockchain. Healthcare, a $2.9 B market segment, is targeted because the need is great and the US healthcare market is highly fragmented. Making healthcare data faster to interoperate and share while maintaining data integrity, security and privacy is key to potentially improving healthcare outcomes.
This Small Business Innovation Research (SBIR) Phase I project is advancing foundational technology for searching and retrieving heterogeneous data secured in blockchain across a distributed data platform. Multiple data sources with different formats and data models will be transformed into more granular data blocks in blockchain. In addition to normalizing blockchain data into more granular data blocks for sharing and re-use in different applications (i.e., simplifying data integration and interoperability), research will use natural language processing (NLP) to assist in automatically generating metadata tags to facilitate searching across blockchains. To improve the accuracy of data returned in the search, a human expert-curated healthcare dictionary and thesaurus will be created and used in concert with NLP assistance. This combined approach should improve the accuracy of data retrieval by non-IT, healthcare, users across a secure, peer-to-peer data platform where data owners retain full ownership and control of their data. The proposed research will also validate through performance testing new blockchain search capabilies will meet the responsiveness and scale required by healthcare enterprises, a key need for commercialization. In particular, the project will establish benchmarks for speed and latency across a geographically dispersed network.
This award reflects 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 (Estimated)
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. -
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. -
ERLI.AI INC.
SBIR Phase I: Intelligent Fire Detection for Indoor Settings
Contact
44 PEACHTREE PL NW UNIT 1833
Atlanta, GA 30309--5414
NSF Award
2223111 – SBIR Phase I
Award amount to date
$275,000
Start / end date
09/15/2022 – 02/28/2023 (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 validate the company’s novel fire detection principle and the use of soft computing techniques by means of (1) computational experiments, and (2) a wide range of real fire and nuisance experiments on the company’s fire detector prototypes. This will allow the company to resolve any technical hurdles that may arise from the integration of the software and hardware into a minimum viable fire detector expected to significantly outperform current market solutions. The company has utilized real-world datasets of fire and nuisance experiments conducted by NIST to test and benchmark the innovation. Using temperature data, for example, the company’s algorithm detected fires up to 10 times faster than current technology (fixed-threshold). In addition, no missed detection occurred, and no false alarms were triggered in all NIST experiments. While these results are impressive, they are not sufficient to commercialize the innovation given that they are based on 69 experiments only. The activities proposed in phase I are designed to reduce the technical risk and strengthen the confidence in the company’s technology prior to commercialization. This is especially important because of the high regulatory burden and associated liabilities in the fire detection space.
By leveraging ML, erli.ai’s patent-pending technology will process streaming data from heat/smoke sensors to detect the earliest signs of fire and separate fire and nuisance events. We introduce a new alarm triggering principle rooted in the temporal analysis of sensor data instead of the existing fixed-threshold approach. We propose to further develop our computational architecture, which employs deep Long-Short Term Memory (LSTM) neural networks and a variational autoencoder, by developing a theoretical basis for the outstanding performance our algorithm produced. We will develop an anomaly detection evaluation scheme for time streaming clustering using Dynamic Time Warping and Similarity Matrix 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. -
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. -
EVOSEER LLC
STTR Phase I: Carbon-encapsulated sulfur cathodes for next generation batteries
Contact
566 N 9TH ST
Laramie, WY 82072--3315
NSF Award
2112004 – STTR Phase I
Award amount to date
$255,568
Start / end date
03/01/2022 – 02/28/2023 (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 enable next-generation lithium battery technologies that are integral in transitioning toward increased renewable energy deployment. In particular, the project has the potential to overcome obstacles to widespread electric vehicle (EV) adoption including battery capacity limitations, high battery cost, and supply chain issues. EVs currently account for a significant majority of the lithium battery market and this market share will likely increase dramatically as deployment of EVs increases in coming years. The aforementioned issues with lithium battery technologies must be addressed for EVs to reach their envisioned potential. This STTR project seeks to advance a novel process for the production of a critical battery component – the battery cathode.
This STTR Phase I project proposes to advance lithium sulfide (Li-S) battery viability using a novel approach to cathode production. Lithium sulfide batteries can provide more than double the gravimetric energy density of current lithium batteries, but Li-S batteries suffer from a short cycle life due to the poor retention of polysulfide species which are formed at the cathode during cycling. If these polysulfide species are able to diffuse away from the cathode, they participate in several detrimental reactions and interactions with both the electrolyte and anode, and the battery is damaged. This project seeks to retain the sulfur and polysulfides within the cathode using encapsulation within a carbon scaffold. Specific research will include assessments of the maximum sulfur loading that can be achieved in the carbon scaffold, the extent to which the carbon scaffold can be rendered electrically conductive, construction of cathodes from the sulfur-loaded carbon scaffold, and tests of the performance of batteries constructed from these cathodes. In addition, a technoeconomic analysis of the cathode technology will be performed to assess its potential in the context of current lithium battery technology. Expected outcomes include demonstrated technical and economic viability of the cathode 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. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research Phase I project is to advance 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. -
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)
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. -
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 – 12/31/2022
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. -
FLORICA THERAPEUTICS, INC.
SBIR Phase I: Hypothalamus Stem Cell Exosomes for Treatment of COVID-19 (COVID-19)
Contact
899 PINE ST APT 811
Livermore, CA 94551--5426
NSF Award
2032822 – SBIR Phase I
Award amount to date
$275,678
Start / end date
01/15/2021 – 12/31/2022
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 to create a novel type of therapeutic using cutting-edge technology and adult stem cells. This therapeutic may be used in hospitals to treat patients with severe COVID-19 infection; the proposed drugs would be made from the cells of healthy brains and have the capability to correct an aberrant immune response in sick people. This can potentially be used for other neurodegenerative diseases as well as for other drug discovery research.
This Small Business Innovative Research (SBIR) Phase I project addresses the urgent need for development of drugs to modulate the immune response to prevent escalation of COVID-19 to acute respiratory distress syndrome (ARDS). The hypothalamus is crucial to secretion of cortisol and other modulators that dampen the immune response following activation. This project will test whether exosome-based therapeutics produced from hypothalamus stem cells can abate the cytokine storm that causes ARDS in COVID-19 patients. Technical tasks include: 1) engineer pluripotent cells to produce exosomes with enhanced neuronal specificity by transducing cells with the XStamp-BHP1 and XStamp-NCAM lentiviral vectors; 2) grow pluripotent cells at scale using the mTesr3D system; 3) induce cells to differentiate into hypothalamus stem cells; 4) collect exosomes. The technical milestone is to engineer exosomes with at least a 70% enhanced neuronal specificity and to produce highly concentrated hypothalamus stem cell exosome particles. These engineered human hypothalamus stem cell exosomes can be used to dampen the cytokine storm in a mouse model of LPS-induced ARDS. This proposal establishes the feasibility of using hypothalamus stem cells as therapeutic candidates for treatment of ARDS in COVID-19.
This award reflects 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 (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 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)
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 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. -
FUTURE SEMICONDUCTOR BUSINESS, INC.
SBIR Phase I: Manufacturing of gallium nitride (GaN) membranes for efficient thermal management
Contact
228 COLONY DR
Charlottesville, VA 22903--6906
NSF Award
2135112 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2022 – 01/31/2023
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 seeks to provide gallium nitride (GaN) membranes for the production of semiconductors for numerous applications including power electronics, radio frequency devices, and optoelectronics, etc. The prooposed technology seeks to alleviate two major problems in the current GaN-based manufacturing technology: thermal management and expensive wafer material costs - by peeling off the GaN membrane from the parent wafer and integrating it on the heat sink. Integration of thin-film GaN on a heat-sink substrate may solve the intrinsic thermal management issues of GaN-based devices by efficiently dissipating the heat. Commercialization of proposed technology could decrease production costs of GaN-based devices by reusing the expensive parent substrate multiple times while maintain the material quality. Gallium nitride-based technologies have been widely adapted in various fields including healthcare and defense, 5G networks, clean energy applications, electrical vehicles, power inverters and mobile device chargers, etc.
This project proposes to manufacture the high-quality, free-standing GaN membranes integrated on heat sinks by using two unique technologies: remote epitaxy and 2-dimensional layer transfer (2DLT). Remote epitaxy and 2DLT technologies utilize 2D materials inserted between the substrate and epilayer for the growth and lift-off of GaN thin-film. Combination of remote epitaxy and 2DLT processes allow for the production of high-quality GaN membranes with multiple reuses of costly GaN substrates. Feasibility of proposed technology will be confirmed via time-domain thermoreflectance (TDTR) techniques by measuring the GaN and heat sink interface.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FUTURESTHRIVE LTD
SBIR Phase I: A mental health screening tool for youth using AI and game-based technology
Contact
11 STANLEY RD
Darien, CT 06820--3829
NSF Award
2111686 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 improve pediatric mental health outcomes. An estimated twenty percent of children suffer with a diagnosable mental health condition and half of those will show signs and symptoms before the age of 14. Suicide is the second leading cause of death among children aged 10+; affected children that do not receive intervention or appropriate services grow into adults with adverse outcomes. The proposed project develops a modern mental health screener to equip clinicians and educate families by tracking mental health vital signs similar to height, weight, hearing, vision and other signs of health.
This Small Business Innovation Research (SBIR) Phase I project will advance a new mental health screening tool. In a gamified, web-based platform, children aged 4-18 will engage in a dynamic question set designed to identify risk factors known as indicators of mental health concerns. Using a novel combination of artificial intelligence for voice and facial biomarkers, sentiment analysis and machine learning, the screener will provide a first-of-its-kind mental health baseline used by doctors and families to better understand the child’s unique mental health.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Foresight Science & Technology Incorporated
SBIR Phase I: Masking Agents to Promote Ingestion of Organic Pest Ant Bait
Contact
34 HAYDEN ROWE ST STE 156
Hopkinton, MA 01748--1889
NSF Award
2025718 – SBIR Phase I
Award amount to date
$210,876
Start / end date
11/01/2020 – 01/31/2023
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 Phase I project is the development of an environmentally neutral product for control of red imported fire ants (RIFA), aggressive pests that occur in high densities and are specialists of urban, rural, and agricultural habitats, particularly in southern states. The RIFA affects many economic sectors and cause billions of dollars in damage and control costs annually. Their large numbers and potent sting disrupt the quality of life for millions of Americans and 5-10% of these may develop hypersensitivity to their venom, creating significant medical costs. The RIFA reproductive system lead to rapid re-infestation of treated areas; therefore, continuous use of control measures is required, with associated environmental risk. This project will enable commercialization of a new bait that is environmentally neutral and cost competitive. It will be the first new active ingredient for RIFA control in 20 years. Our novel application of masking agents for RIFA control is expected to have a general impact on the discovery of new pest control active ingredients.
This SBIR Phase I project will advance the translation of novel active ingredients for effective RIFA pest mitigation. Prior testing has indicated that additives are needed for this type of pesticide. This project will test additives and optimize formulations for field use of the new ingredients.
This award reflects 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. -
GLOSSIFI INC.
STTR Phase I: Blockchain ontology and services for monitoring and performing analytics on smart contracts
Contact
313 SORTWELL ST
West Columbia, SC 29169--7635
NSF Award
2052118 – STTR Phase I
Award amount to date
$256,000
Start / end date
01/15/2022 – 12/31/2022
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this STTR project addresses a paradox faced by ‘open web’ developers, users, and regulators: the use of centralized platform-creator hosted web portals to interact with an evolving decentralized finance (DeFi) application ecosystem. The proposed work will instrument a new open web paradigm that will improve user accessibility and ability to compose and perform data analysis on smart contracts. The approach will enable improvement of web-service reliability and security while weeding out bad actors. Improving the accessibility and analysis of smart contracts is anticipated to help unlock further value and solutions across a range of applications and new business opportunities that can benefit from dynamic contracting.
This STTR Phase I project proposes to build a blockchain-adjacent metadata model that enhances the utility and security of smart contracts for users and developers. The project will undertake the practical challenge of reverse-engineering smart contracts to outline a metadata model which will enhance discovery and security of services, creating a scaffold for composable apps. The approach will organize blockchain abstractions through code similarity analysis and program de-obfuscation by reverse engineering, instrument compile-time creation and publish metadata models by developers, and demonstrate how this data can be used to build a composable app user experience. The project will deploy privacy-preserving targeted advertising frameworks using deterministic services alongside the data from the metadata model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GP IONICS LLC
SBIR Phase I: Multi-Step Sequential Processing of Gas Ions for Identifying Volatile Organic Compounds in Recirculated Air of Energy Efficient Buildings
Contact
1175 N HORSESHOE UNIT 37
Las Cruces, NM 88003--1223
NSF Award
2035894 – SBIR Phase I
Award amount to date
$255,400
Start / end date
03/15/2021 – 02/28/2023 (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 human health, energy savings, and improved environment. Increased urbanization worldwide and demand for high quality, comfortable ambient air environments is expected to drive an existing market for improved heating, ventilation, and air conditioning (HVAC) systems estimated at $12 billion nationally and $190 billion worldwide by 2026. Respiratory disease and human illness are attributed to unregulated amounts of these constituents in indoor air. This project will inform users about the concentrations and identities of volatile organic compounds (VOCs) in recirculated indoor air from energy-efficient HVAC systems.
This will inform clinical analyses of disease, industrial process monitoring, screening of food purity and authenticity, and commercial aviation security.
This SBIR Phase I project will leverage discoveries in the chemistry of ion fragmentation in strong electric fields in air at ambient pressure and the association of these fragments with molecular identity. Additional merit is derived from algorithms for identification of ion spectra, dependences of fragmentation on electric field strength, and processes to handle ions both in the initial step of ion selection and the final stage of fragment ion analysis. This will be a novel exploration of strong electric field fragmentation of gas ions at ambient pressure. Research objectives include tasks to establish broad understanding of mechanisms of ion fragmentation of volatile organic compounds as gas ions at ambient pressure and establishing autonomous molecular identification using spectral profiles from mobility analysis. The research is organized into three phases including the development of efficient, advanced control of ion fragmentation, the discovery of chemical rules governing ion fragmentation, and the integration of artificial intelligence with chemical instrumentation developed in this project. The key technical result anticipated in this project is a chemical analyzer for autonomous monitoring of the quality of recirculated indoor air in green heating, ventilation, and air conditioning systems in green buildings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRAIN WEEVIL CORPORATION
SBIR Phase I: Improving farmer safety and grain storage efficiencies via a remote-controlled grain management and extraction robot
Contact
1845 CRAIG RD
Aurora, NE 68818--1014
NSF Award
2111555 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 12/31/2022
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 help farmers across the nation improve their grain storage efficiencies in a remote and safe manner. In addition to demonstrating technical feasibility of a mobile robot, this project may help refine key design considerations such as cost, portability, and usability, that will help promote widespread customer adoption during commercialization. Though the robot will be initially designed for commonly stored cereal grains in the U.S., this technology may be applied across numerous agriculture-related commodities around the world. The robotics technology has the potential to enhance farmer safety while simultaneously improving grain management practices that yield more efficient and stable food supply chains.
This Small Business Innovation Research (SBIR) Phase I project explores the use of mobile robots for grain storage assessment. Grain bins provide challenging environments for the operation of robots including: dust and temperature extremes, shifting fluid dynamics, and grain quality challenges. The focus of the research includes classifying and characterizing key grain surface variables that impact robotic effectiveness, identifying the top 3-5 grain management tasks by frequency and importance, and analyzing the impacts of grain characteristics on each task, and designing and conducting controlled environmental studies to quantify performance requirements. The project will also identify and define potential grain engagement paths/patterns for top use case tasks, and analyze potential failure modes for robot operations within grain bins. Once complete, the research may demonstrate the impact on post-harvest workflows, develop autonomous operations, and build a safe robot platform for use in grain bins.
This award reflects 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
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Phase I project is to increase the visibility and availability of data used for control and automation of critical infrastructures. This research proposes the development of a novel technology that takes advantage of flexible, low cost, and low power internet of things (IoT) devices to replicate, transmit, and analyze relevant monitoring and control data. Blackouts in the U.S. cause tens of billions of dollars in outage cost annually. This technology will advance the nation's energy safety, security, and economy by improving the capabilities of critical infrastructure systems to respond to blackouts caused by anomalous events such as natural disasters (e.g., hurricanes, winter storms) and localized faults or cyberattacks. Therefore, the technology developed in this project will decrease restoration time and provide real-time defense against cyberattacks, reducing the loss of electricity to critical users such as hospitals and governmental facilities, and saving billions of dollars.
This Small Business Innovation Research (SBIR) Phase I project will advance the scientific knowledge required to enhance the resilience of critical infrastructures through the integration of IoT networks, monitoring and control technologies, and data analytics. Advances in the use of IoT devices for critical infrastructures integrated with security mechanisms will facilitate the technology transition of the current critical infrastructure. This project will explore and design novel mechanisms for data processing, light-weight encryption, and attack detection. The technology developed in this project will have widespread applications in monitoring and control, not only in the electricity sector, but also in many other critical infrastructures such as water, oil, and gas. A proof of concept will be developed to validate the feasibility of the proposed architecture and algorithms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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
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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. -
General Engineering & Research, L.L.C.
SBIR Phase I: Development of High Efficiency Thermoelectric Materials for Sub 200K Space Applications
Contact
10459 ROSELLE ST STE A
San Diego, CA 92121--1527
NSF Award
2035074 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2021 – 12/31/2022
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovative Research (SBIR) Phase I project will advance the state-of-the-art in low temperature thermoelectric devices for space applications enabling advanced space travel as well as improvements to satellite wireless and worldwide mobile internet availability. With the increased interest in space exploration from industrial efforts, a significantly improved low temperature thermoelectric module could capture a sizable portion of the rapidly growing thermoelectric module market which is estimated to be ~$1 Billion by 2024. Significantly improved low temperature thermoelectrics would also open the door for the use of these devices in other low temperature thermal management systems, where the poor efficiency of cooling technologies operating in the cryogenic regime have been a major challenge.
This Small Business Innovative Research Phase I project aims to improve the efficiency (ZT) of thermoelectric cooling modules using advanced materials and a novel module design concept. Bismuth-antimony (BiSb)-based single crystal materials with applied magnetic fields have long been known as the highest performance materials for sub 100K applications but they have not yet found commercial utility due to a variety of challenges. The research effort aims to address these challenges and develop both p-type and n-type single crystal BiSb based alloys with ZT > 0.4 at 90 K and application of less than 1 Tesla magnetic field, which would be a four-fold improvement in efficiency at sub 100 K compared to current 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. -
HAIRDAYS, INC.
SBIR Phase I: Hair Genome Project - Computational approach to classifying hair profiles and dermatological health disparities in underserved communities
Contact
11 E LOOP RD STE 381
New York, NY 10044--1500
NSF Award
2151351 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 02/28/2023 (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 be an inclusive platform offering individuals access to data-driven, personalized insights on hair health. Hair health plays a large factor in overall mental/physical health; however, an absence of transparent data has disproportionately disadvantaged access to quality products and care information, particularly among minority communities. This disparity has led individuals to use products and/or wear styles that adversely impact hair and scalp health. The proposed technology will bridge these gaps, providing users with hair/scalp health insights and matching them with suitable products and regimens for their hair profile and goals. At the same time, the data and user engagement with the platform can be leveraged to offer brands, healthcare providers, insurance companies, etc. with deeper insights into their customers’ hair care-related goals, pain points, and health conditions. In addition to supporting hair health, this project will mitigate the scalp and hair pathologies (e.g., alopecia, burns, breakage, contact dermatitis) stemming from ill-suited products and care practices.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a data-driven hair intelligence platform that uses big data to democratize hair insights for all. The technology and platform will leverage big data from peer-reviewed publications and science-backed databases as well as the users themselves, to continually refine personalized insights and understand customer needs in the context of their unique hair profile. Using proprietary algorithms, the technology will be able to seamlessly recognize and map different hair types, identify secondary unique factors (porosity, density, texture, etc.), map and analyze different ingredients in products, track and map different treatment regimens and product usage, and develop sentiment analysis, patterns, and predictions. This project will: 1) Develop training dataset and tiered algorithm for hair profile classification with high confidence; 2) Validate and refine the hair profile classification system through a comparative study with dermatology residents; and 3) Establish proof-of-concept demonstrating the connection between accurate hair profile classification and data-driven product/style recommendations to improve hair-esteem.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HARDSHELL LABS, INC.
SBIR Phase I: Remotely Operated Avian Management
Contact
61313 ONAGA TRL
Joshua Tree, CA 92252--3181
NSF Award
2136815 – SBIR Phase I
Award amount to date
$255,014
Start / end date
02/15/2022 – 01/31/2023
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 the facilitation of more widespread and affordable wildlife research, management, and monitoring through the use of internet-connected devices. Internet-mediated human control of laser hazing devices may provide cost-effective damage reduction in agricultural settings. The research is founded on the ability of lasers to repel a wide variety of birds. Human oversight will benefit from remote operation, allowing the research and development activtities to be conducted at a fraction of the cost of an on-site presence. The immediate problem addressed is avian damage. agricultural losses, predation on sensitive species, and aviation hazards. Refining and expanding the proposed model may broaden the range of solvable conservation problems. The proposed system seeks to allow one person to simultaneously operate multiple internet connected devices. The creation of reliable, remote management tools may broaden the scope and improve the efficiency of natural resource management. By allowing remote wildland views and providing opportunities for positive intervention, the technology may increase public engagement with the natural world through formal and informal education, improve the understanding of resource protection issues, and enhance public commitment to solving environmental challenges.
The development of a fully integrated, remotely-operable network of internet-connected, artificial intelligence (AI)-enhanced laser devices for repelling pest birds from valuable agricultural assets is proposed. The primary project goal of the project is to make non-lethal pest bird management more effective, easy, and affordable in agricultural, conservation, and commercial settings that are often remote. Phase 1 research and development will cover the creation and initial field testing of a laser array that is remotely controlled by internet connected operators. Phase 1 performance metrics will focus on reliability and ease of use as there are significant operational challenges in various settings (e.g., lack of wi-fi connectivity in wilderness and remote locations, laser safety, etc.). The project seeks to establish a template for the reliable, remote operation of a wide array of human-controlled devices via internet connections supplemented, where appropriate, with artificial intelligence. This technology may facilitate the wide adoption of more efficient approaches to wildland research, monitoring, and management as the physical presence of the operator will not be required.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HEIGHTS LABS, INC.
SBIR Phase I: Comprehensive Blockchain Transaction Monitoring for Illicit Funds and Actors
Contact
722 CALDWELL AVE
Valley Stream, NY 11581--3619
NSF Award
2136490 – SBIR Phase I
Award amount to date
$255,946
Start / end date
09/15/2022 – 02/28/2023 (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 that it will result in powerful technology for detecting illicit cryptocurrency accounts and funds in close to real time. The commercial and market impact of the technology will be substantial with its ability to trace illicit accounts and funds to a depth and breadth never before possible and to accomplish this in seconds to minutes, as compared to the long to indefinite time it would take conventional network tracing technology. For society at large, the ability to uncover the most complex money laundering and fraud schemes will help cut the flow of funds to the worst actors using cryptocurrency: organized crime, narcotics dealers, child pornographers, human traffickers, terrorists, and rogue nations. With the platform created in this project, governments in conjunction with the private sector will have tools that can effectively address the sophistication of the criminal schemes. This will in turn result in greater growth of the cryptocurrency-based economy as businesses and individuals gain greater confidence that they are dealing with legitimate entities that are not seeking to defraud them.
This SBIR Phase I project will bring to light the most sophisticated illicit schemes involving cryptocurrencies. In doing so, it will secure cryptocurrency systems and advance the fields of network analysis and visualization, which will be needed to understand the schemes. There are three major technical hurdles in the Phase I project. First, the proposed implementation and infrastructure for the network tracing algorithms need to be scaled up to trace the entire Bitcoin and Ethereum blockchains in real-time. Second, to be able to trace addresses to known illicit accounts, a sufficient number of these accounts need to be identified. The proposed project will develop software for cross referencing account addresses with both on-chain and clear and dark web activity to build the lists of known bad actor addresses. Third, for customers to believe the results of the analysis, a network visualization tool to show the chains of custody linking a suspect account to a known illicit account must be created. Because the algorithms can detect the schemes involving thousands of fund transfers between accounts, visualizing the links in a clear manner presents unique challenges. The project will therefore also build the foundation for its novel visualization tool in Phase I.
This award reflects 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 (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 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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
HYPERSOUND MEDICAL, INC.
STTR Phase I: Neuromodulation by Electromagnetic (EM) Energy-Induced Hypersound
Contact
1435 E UNIVERSITY DR STE C-109
Tempe, AZ 85281--8473
NSF Award
2136383 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 02/28/2023 (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 proposes to develop a new way to block pain in the human body. This new technology offers the potential for a novel, less invasive, lower cost, non-addicting solution to pain relief. The project develops a device to be applied near or on the skin, significantly penetrating the tissue to inhibit pain. The primary market is to provide relief from back pain, which affects more than 100 M Americans. Other potential markets include pain suppression from peripheral wounds, neuralgias, migraine, cancer, diabetes-related neuropathies, and degenerative diseases, such as the rheumatoid group.
This Small Business Technology Transfer Phase I Project proposes a new approach to noninvasively modulate selected neural tissues to block pain by known principles of neurological competitive inhibition. The technology employs electromagnetic energy in a novel electrostrictive mode of action within the dielectric nature of cellular media to remotely evoke ultrasound as well as higher frequency hypersound forces in-situ. These induced forces are hypothesized to result in biological effects through the well-known action of cellular stretch activation. This project will further develop instrumentation to produce unique microwave device designs and determine the effects of microwave variables on neuromodulation. The research institution will apply the developed instrumentation on rat and neuronal cell models to define the important operating parameters for ensuring therapeutic safety and 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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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)
Errata
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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 (Estimated)
NSF Program Director
Errata
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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. -
IDEA51, LLC
SBIR Phase I: A Method to Expand Personalized Experiential Learning
Contact
1151 W MILLER ST
Boise, ID 83702--6965
NSF Award
2150912 – SBIR Phase I
Award amount to date
$245,844
Start / end date
06/01/2022 – 01/31/2023
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project is to improve education and experiential learning. The proposed tool will support both synchronous and asynchronous learning while providing students with the opportunity to engage independently and connect their learning to internships, job shadows, service projects, and other real-world learning experiences. This project will enhance teacher capacity to guide and assess student learning, increase transparency and objectivity in assessment, and expand the learning ecosystem of schools by empowering students to engage in and validate authentic, real-world learning experience.
This Small Business Innovation Research (SBIR) Phase I project will develop a novel competency-based evaluation tool and learner recommendation engine designed to: assess a range of currently needed skills and competencies, aggregate assessment data for the purpose of generating a comprehensive learner record in real time, and generate personalized competency pathways and recommendations for learning and growth. The key intellectual merits of this proposal are the formulas used to aggregate assessment data over time and the algorithms used to generate personalized competency pathways and learner recommendations. The technical challenges are the development and testing of the associated algorithms to guide and evaluate learning in both academic and authentic, real-world contexts. Research conducted during this Phase I project enable testing and refining of the data aggregation formulas utilized by the assessment tool, as well as optimization of the learner recommendation algorithms used for the creation of personalized competency pathways.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IF, LLC
STTR Phase I: Automated Continuous Varroa Mite Monitor for Honeybee Hive Health
Contact
5407 FEN OAK DR
Madison, WI 53718--3902
NSF Award
2127468 – STTR Phase I
Award amount to date
$255,262
Start / end date
01/15/2022 – 12/31/2022
NSF Program Director
Errata
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Abstract
This Small Business Technology Transfer Phase I project addresses the health of honeybee hives and the associated $15 billion in annual agricultural services. Honeybee hives are susceptible to the parasitic Varroa destructor mite; unless the hive is treated, the presence of the Varroa mite eventually proves fatal to any bee colony it infests. Monitoring mite levels in beehives requires partial disassembly of the hive and the best counting method sacrifices some bees. Most of the nation’s 120,000+ beekeepers do not adequately test for mites. The expected output of this project is a low-cost, battery-operated “Internet-of-Things” device that can be placed inside hives, passively counting the Varroa mite population, and reporting the results to the beekeeper. The count can be used to indicate when mite treatment is needed and whether the treatment was effective. It prevents costly and unneeded prophylactic treatments that can lead to resistance in mite populations. This project fosters bee colonies that are healthy and productive, while reducing beekeeper workload and reducing unnecessary chemical treatments for beehives.
The intellectual merit of this project is in the novel investigation of the use of near-infrared light wavelengths to determine where acceptable contrast exists between the exoskeletons of honeybees and Varroa mites, and the recognition of parasitic Varroa mites using modern artificial intelligence techniques that can be scaled to down for use in an edge computing environment that has significant limitations in terms of power availability and processing speed. The Phase I effort will integrate an infrared camera with variable wavelength narrowband infrared LED illumination, and photograph unparasitized and mite-infested honeybees. Human researchers will identify mites and use scored images to train an artificial intelligence engine to detect and count the mites.
This award reflects 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 (Estimated)
Errata
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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. -
IMPACT PHOTONICS LLC
SBIR Phase I: A Complementary Metal-Oxide Semiconductor (CMOS) Compatible Single Photon Avalanche Diode
Contact
182 BRATTLE ST
Arlington, MA 02474--2144
NSF Award
2136226 – SBIR Phase I
Award amount to date
$256,000
Start / end date
11/01/2021 – 12/31/2022
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 make 3D cameras for long-range LiDAR (Light Detection and Ranging) more affordable, widespread, and as reliable and simple to use as cameras found in common mobile devices. 3D cameras (LiDAR) are being used for precise positioning and velocity determination of objects in augmented reality applications and are crucial for widespread adoption of autonomous cars and trucks where the 200-300 meter range is required. Eye safety concerns with low-cost silicon sensors force the long-range autonomous vehicle customers to use one pixel at the time or limited field of view imaging using high-cost and complex systems based on materials that require specialty materials and manufacturing. This technology will enable the use of mainstream materials and process technology for the long-range autonomous vehicle segment without compromising eye safety. This capability will reduce cost, lower complexity, and improve reliability of long-range 3D cameras and help propel the autonomous vehicle industry into widespread adoption.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a fully complementary metal-oxide semiconductor compatible single photon avalanche diode (SPADs) based on germanium that operates at eye safe wavelengths. Current germanium-based avalanche photodiodes require cryogenic cooling due to excessive dark noise from tunneling or dislocations. They suffer from poor absorption at the eye safe wavelengths beyond 1450 nm. This project will implement a photon trapping strained heterostructure device architecture which reduces dark counts while enhancing absorption at the operating wavelength. The device structure will be developed with particular emphasis on the semiconductor growth process. The experimental results will be benchmarked to the dark count and absorption requirements for the mass-market, long-range autonomous vehicle application. The technology will offer a highly manufacturable, lower cost alternative to compound semiconductor based SPADs that are often prohibitively expensive to produce in large arrays.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INCEPTION ROBOTICS, LLC
SBIR Phase I: Dense, Socially-Compliant, Autonomous Delivery Robot
Contact
6511 PRINCESS GARDEN PKWY MILES HALL RM 209
Lanham, MD 20706-
NSF Award
2136783 – SBIR Phase I
Award amount to date
$255,428
Start / end date
03/15/2022 – 02/28/2023 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project is to enable autonomous mobile robots (AMRs) to operate in densely crowded spaces in a safe and socially compliant/acceptable manner. A key potential outcome is the development of a collision avoidance method based on Deep Reinforcement Learning (DRL). This method would be capable of handling dense crowds and optimized to run on compact and power-efficient embedded processors. Such abilities would increase the commercial potential and adoption of learning-based navigation methods that have demonstrated excellent collision avoidance and noise handling capabilities. The technology may unlock commercial opportunities by deploying AMRs in the airport, retail, healthcare, and hospitality industries, where the environments are highly dense and dynamic. The airport industry may derive postive impacts from AMRs that can navigate in complex, indoor environments where global positioning systems (GPS) are not allowed by providing contactless deliveries of food, beverages, and other retail products to travelers at the gate.
This Small Business Innovation Research (SBIR) Phase I project investigates a hybrid collision avoidance approach enabling autonomous mobile robots (AMRs) to operate safely in dense crowds, while being socially-compliant in sparse scenarios. Preliminary research has shown that Deep Reinforcement Learning (DRL)-based approaches can compute collision-free robot velocities with inaccurate, uncertain perception data. The proposed DRL-based model will be implemented as an optimized neural network that works on power and cost-efficient embedded processors. The key technical hurdles in this technology are: the DRL model trained in simulation may not perform well in real-world environments (known as sim-to-real gap), the fully-trained DRL model may have some performance degradation compared to the company’s current DRL models due to the lower number of parameters used to run on embedded processors, and the localization modules could compute erroneous locations when the AMR is navigating through a dense crowd due to occlusions. The key objectives of Phase I are to address these challenges.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INITIUM AI INC.
SBIR Phase I (COVID-19): Identifying Medical Supply Shortages on Social Media for Fast and Effective Disaster Response
Contact
245 HUNTERS TRL
Ann Arbor, MI 48103--9525
NSF Award
2030482 – SBIR Phase I
Award amount to date
$255,207
Start / end date
08/01/2020 – 01/31/2023
Errata
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This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project consists of providing immediate help during the COVID-19 crisis by identifying the needs of medical providers and compiling reports for government agencies and medical equipment suppliers and manufacturers. The proposed Natural Language Processing methodology will help (1) hospitals and clinics seeking medical supplies, personal protective equipment, and testing supplies to meet their needs; (2) the government coordinating response; (3) manufacturers and suppliers seeking information regarding needs. Additionally, it can be used to identify other non-medical supply shortages and can be adapted to provide an efficient response for other disasters or outbreaks.
This Small Business Innovation Research (SBIR) Phase I project will leverage recent advances in natural language processing and machine learning to identify at scale needs in medical equipment and supplies, based on insights derived from free text in social media, and convert these needs into a centralized, easily accessible structured data format. The technology will identify expressions of needs on social media; identify users, their specific needs, and locations; and generate geographically sorted actionable formatted lists.
This award reflects 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 (Estimated)
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. -
INTELLIGENT MEDICINE INC
SBIR Phase I: A platform for simulating the combined effect of human behavior and environment on airborne infectious spread (COVID-19)
Contact
430 FRANKLIN ST FL 2
Schenectady, NY 12305--2018
NSF Award
2151672 – SBIR Phase I
Award amount to date
$255,842
Start / end date
03/01/2022 – 02/28/2023 (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 minimize infection by contagious diseases, such as COVID-19. This project advances a cloud-based platform for simulating particle flow in heavily populated, dynamic environments. It will enable facility managers and health/ safety stakeholders to simulate viral particle dispersion in indoor environments for design and mitigation procedures (disinfection, evacuation, etc.). This technology can play a role in mitigating the ongoing effects of the current COVID-19 pandemic and better prepare facilities for the next pandemic.
This Small Business Innovation Research (SBIR) Phase I project supports facility planning and response of infectious disease outbreaks. The project advances a hybrid computational approach to utilizing multi-scale fluid analysis for faster-than-real-time multimodal simulation. The research objectives are to: (1) create a simulation platform that can parallelize equations and perform at near real-time or real-time, which will provide a means to simulate multimodal interactions in real buildings, such as contamination spread in fluid flow, when analyzed with human behavior and mobility; (2) characterize and validate the results of the simulator by measuring particle spread in multiple real building scenarios. It is anticipated that the simulation results of particle trajectory and surface contamination will be at least as accurate as state-of-the-art high-fidelity computational fluid dynamic techniques, but delivered in real time. This project will provide an environment and behavior-specific simulation essential for optimizing airflow and facility controls to reducing airborne infectious transmission.
This award reflects 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
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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. -
INVVAX, INC.
SBIR Phase I: Stable prophylactic antibodies
Contact
4846 TREMEZZO DR
Cypress, CA 90630--3557
NSF Award
2144054 – SBIR Phase I
Award amount to date
$255,927
Start / end date
03/01/2022 – 02/28/2023 (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 solve a variety of infectious diseases for which there is no adequate prevention or therapy, such as HIV, flu, malaria, and the common cold. Vaccination has proven immensely difficult for these diseases, often because there are countless natural strains. Providing antibodies directly represents a possible solution because some of the broadest antibodies can subdue 97% or more of circulating strains. However, antibodies will not last beyond a few months in the body. This project proposes to make a collection of mutations in the constant part of antibodies to stabilize them potentially for decades or even a lifetime. This will improve public health.
This Small Business Innovation Research (SBIR) Phase I project will advance the potential applications of mutagenizing the Fc region of a model antibody toward the eventual development of stable prophylactic antibodies. First, the Fc will be made resistant to all cellular and all major microbial antibody proteases. Mutations conferring resistance of antibodies to some proteases have already been achieved; these will be combined in the model system. Resistance to all remaining proteases will be engineered by targeted mutation, if the cleavage sites are known, and by comprehensive mutation, if the cleavage sites are unknown. High-throughput screening of mutants will be facilitated by full-length Immunoglobulin G phage display. Second, Fc is stabilized in vivo by the neonatal Fc receptor (FcRn). An unbiased screen of all possible single and double mutants in Fc, also by full-length Immunoglobulin G phage display, will isolate mutants that have still further enhanced binding to FcRn.
This award reflects 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
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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
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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. -
Independence Science, LLC
SBIR Phase I: Synergizing Braille and Science: Real-time Accessibility of Tactile Graphics in Laboratory Settings for Blind and Low Vision (BLV) Students
Contact
3000 KENT AVE STE 1303
West Lafayette, IN 47906--1169
NSF Award
2111636 – SBIR Phase I
Award amount to date
$254,767
Start / end date
01/01/2022 – 12/31/2022
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 increase the participation of the underrepresented population of blind and low vision (BLV) persons in the science, technology, engineering, and mathematics (STEM) fields. Through a novel assistive technology that provides BLV individuals with multisensory access to scientific data in real time, this technology will enable access on par with sighted peers. BLV students, unlike their sighted peers, lack independent access to real-time scientific data whether in the laboratory or in the field. This inaccessibility either precludes their full participation in hands-on science inquiry, or leaves them dependent on sighted peers to access real-time data. With this project, BLV students across K-12 and post-secondary institutions, as well as BLV scientists and others interested in STEM, will benefit from a tool that makes it possible for them to work independently in laboratory situations. This innovation will make science laboratory learning and laboratory workplaces more inclusive and equitable for the blind and low vision individuals.
This Small Business Innovation Research (SBIR) Phase I project is focused on developing a 2-dimensional, hand-held, portable, refreshable Braille and tactile graphics scientific data collection tool that can be used to collect quantifiable data in real time using wireless sensors. Blind and Low Vision (BLV) students are as capable as their sighted peers in STEM yet, unlike their sighted peers, lack independent access to real-time scientific data in the laboratory. This effort seeks to address this inequity by leveraging the expertise of blind scientists and pioneers in STEM access technology to iteratively develop a interative versions of novel, blind-accessible innovations which will give BLV students, scientists and others access to quantitative data collected in the laboratory or in the field. This innovation will be optimized for the BLV by documenting usability concerns and making the necessary modifications to hardware and source-code prior to field-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. -
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)
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 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. -
JELIKALITE LLC
SBIR Phase I: EEG-guided intelligent transcranial photobiomodulation to reduce symptoms of autism
Contact
30 WALL ST STE 811
New York, NY 10005--2201
NSF Award
2136474 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/01/2022 – 01/31/2023
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate proof of concept for a wearable device for delivering personalized therapy to mitigate autism in children. One out of 44 children in America is diagnosed with autism. Behavioral therapies with no pharmacological or device treatments show mixed effects. This project advances an effective personalized treatment to augment or replace the state of practice. The device will be used in the privacy of each child’s home without the need for a specialist. The benefit of the proposed system is approximately 33% improvement in autism symptoms, resulting in over $1 million in lifetime savings for each child.
This SBIR Phase I project aims to demonstrate the feasibility of a non invasive wearable medical device that stimulates brain tissue using near infrared radiation in Transcranial Photobiomodulation (tPBM), with integrated EEG feedback on Delta brain waves indicative of therapeutic effect. This project will complete prototyping of a system suitable for use, collect pre-clinical data in children, develop a signal analysis database, and develop algorithms based on the patient’s baseline factors for the desired effect.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
JUGGERNAUT LIFE SCIENCES LLC
STTR Phase I: Smart Semiautonomous Fluid Drainage System for Surgical Procedures
Contact
25 ALDER CT
Iowa City, IA 52246--9409
NSF Award
2136298 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 project will develop a novel automated manner to drain abnormal accumulations of fluid in the abdominal body cavity. The proposed system seeks to progress visualization, sensor and algorithm technologies to semi-automate drainage procedures, standardizing delivery of care and reducing the required clinical resources (personnel and required hospital equipment). Healthcare costs continue to increase in the United States (US). This trend, coupled with current and projected manpower shortages in the healthcare sector, is driving the relevant stakeholders to consider innovative solutions to appropriately manage healthcare costs while still providing high-quality healthcare to patients. While other sectors of the economy have greatly benefited from increased use of automation to improve efficiency and cost containment, for a variety of reasons, the healthcare sector is lagging in implementing these innovations in a systemic way. With this opportunity in mind, this Phase I STTR project aims to prove the feasibility of developing a unique, semi-autonomous robotic platform that will be adaptable to many medical procedures. As envisioned, the technology may lead to key advances, including improved patient outcomes and levels of care while increasing procedure/staff efficiencies, and reducing medical costs.
The objective of this Phase I effort is to demonstrate a proof of concept for an integrated procedural unit for semi-autonomously performing paracenteses. The prototype system to be completed during this stage is comprised of an ultrasound probe, motorized anesthetic syringe, scalpel, and aspiration needle, and can be integrated into standard, commercially available robotic units. The algorithm will be developed using Bayesian indexing based on ultrasound images to execute ascites fluid removal in both virtual and mechanical simulations. Based on the preliminary work done by the multidisciplinary team of medical, robotic, and artificial intelligence (AI)) experts, the company plans to create and test a compact robotic device with the required sensory and driving components. This robotic device will have multiple subunits arranged in a compact and innovative way, capable of accurately imaging and controlling various instruments essential for anesthetizing and then driving the necessary cannulas for fluid aspiration. The project objectives include: (i) design and manufacture of the robotic system, (ii) development of AI-driven segmentation of ultrasound images and optimization of needle placement, and (iii) design and implementation of control algorithms for safe and robust operation of the surgical robot.
This award reflects 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
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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. -
KINETICCORE SOLUTIONS LLC
SBIR Phase I: Safe, Affordable and Green Energy Storage
Contact
2408 MCKENZIE DR
Loveland, CO 80537--6993
NSF Award
2111838 – SBIR Phase I
Award amount to date
$254,820
Start / end date
03/01/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of the Small Business Innovation Research (SBIR) Phase I project is to provide a safe, affordable and environmentally sustainable energy storage solution. This project offers a non-chemical, non-hazardous alternative energy storage to accelerate grid modernization and non-polluting renewable power integration. The project’s core technology is a design that is cost competitive with deployed Lithium ion (Li-ion) chemical batteries, but would be significantly less expensive per charge than Li-ion over its 30+ year service life. This proposed approach allows the long-term advantages of kinetic (flywheel) energy storage (low service life costs, high power throughput, high daily charge cycles, no battery replacements, potential for 24/7 operations) and makes it affordable and safer for deployed stationary grid operations. With solar and wind renewables on par with traditional carbon-based power generation costs, affordable flywheel energy storage is vital to store and dispense intermittent renewable power, enabling the replacement of carbon-based power generation.
This SBIR Phase I project proposes a comprehensive testing effort to verify the technical feasibility of the project’s 3D flywheel composite structure for next-generation energy storage systems. The proposed research and testing objectives are to demonstrate the improved 3D flywheel performance and projected 9x reduction in the traditional flywheel weight for the same energy storage capability. Testing methodology includes dynamic balancing, torque transmission determination, critical failure/fatigue modeling, assessing magnetically coupled commercial external motor/generator power transmission and performance in a TRL-5 operational vacuum environment. The effort will also include energy storage market analysis for commercial market entry based on tested 3D flywheel performance. Anticipated results include the characterization of the 3D flywheel structural technology, demonstrated commercial subsystem operations and readiness to develop a full prototype.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KOVADX INC
STTR Phase I: Using AI to develop a red blood cell health index for the monitoring of sickle cell disease
Contact
470 JAMES ST STE 007
New Haven, CT 06513--3175
NSF Award
2112027 – STTR Phase I
Award amount to date
$255,887
Start / end date
08/01/2021 – 12/31/2022
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to reach underserved communities and address inequities in health care for patients with hemolytic anemias by providing fast, affordable, and accurate diagnosis and monitoring of hemolytic anemias by combining 3D phase imaging with deep learning. Sickle Cell Disease (“SCD”) is a global health problem that significantly impacts the life span, quality of life, and health outcomes of affected individuals. SCD is one of the most common hemolytic diseases in Sub-Saharan Africa and the U.S, affecting up to 3% of the newborn population. However, few resources and research are dedicated to improving the diagnosis and monitoring of SCD. Individuals who lack access to screening and testing are susceptible to an early-life mortality rate of up to 90%. Unfortunately, those who are most likely to suffer from hemolytic diseases like SCD are frequently underserved by advanced health care. This project may significantly reduce the SCD burden by providing monitoring to prevent crises that require hospitalizations and emergency care.
This Small Business Technology Transfer (STTR) Phase I project will advance Artificial Intelligence (AI) innovations for diagnosing red blood cell disease with quantitative phase imaging (QPI). While QPI images can be used to diagnose a handful of hemolytic anemias, no effort has been made to infuse it into health care at scale. This project develops an AI system to identify RBCs in crowded QPI images, as well as other blood cellular components, such as platelets and white blood cells. The project will develop robust machine learning models to learn from these data; in particular, new deep learning models, based on forms of convolutional neural networks and recurrent neural networks, will provide insight based on temporal and spatial 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. -
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 – 03/31/2023 (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 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. -
LANDSDOWNE LABS, LLC
SBIR Phase I: Safer batteries to mitigate injuries from accidental ingestion in children
Contact
1073 N BENSON RD
Fairfield, CT 06824--5171
NSF Award
2110659 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a novel battery design which rapidly deactivates in contact with aqueous environments. Every year, tens of thousands of children suffer as a result of ingesting coin cell batteries. These children may needlessly suffer debilitating and sometimes fatal consequences. Exposure to unforeseen battery ingestions increases with the proliferation of Internet of Things (IOT) and wearable devices that use compact, high energy density, batteries replaceable by the consumer. Such batteries are increasingly required to have higher potential or capacity (or both) and pose an ever-greater risk to unsuspecting children. Worldwide, 10 billion coin cell batteries are sold annually and this is one of the fastest growing, highest margin consumer battery segments. These sales are expected to translate to nearly $2 billion in the lithium battery primary market by 2024. Consumer use of coin cells is growing; By 2030, 125 billion IOT devices are expected to be sold globally many powered by coin cells. The magnitude of the potential child-ingestion problem is significant.
This SBIR phase I project seeks to reduce children's injuries caused by injesting coin cell batteries by using a novel material design to rapidly deactivate coin cell batteries when they come into contact with aqueous environments. The research addresses the fundamental issue of electrochemical burns. The solution will conform to established standards for coin cell batteries in terms of electrical and other performance requirements. Phase I research efforts will include identifying suitable materials for specific component(s) of a coin cell battery, demonstrating that novel material combinations can be manufactured using scalable process, and producing hand-assembled lithium primary coin cell batteries that have an appropriate open circuit potential and electrical discharge characteristics under continuous ohmic load and pulsed discharge conditions. The teams also seeks to demonstrate that fully-assembled cells deactivate rapidly when the cells come into contact with aqueous environments. The tests include the use of highly sensitive source measure unit(s) to apply potential and detect current in aqueous environments. Additionally, material robustness will be tested for electrical, mechanical, and processability parameters. Electrical discharge and battery performance testing procedures will be used in accordance with current 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. -
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
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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
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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. -
LIV LABS INC.
SBIR Phase I: Monitoring and Treatment of Urinary Incontinence in Women
Contact
1415 LAKE AVE
Wilmette, IL 60091--1630
NSF Award
2126867 – SBIR Phase I
Award amount to date
$255,078
Start / end date
01/15/2022 – 12/31/2022
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 care for the 27 million American women with involuntary urine leakage. Such leakage is highly prevalent, affecting one in three adult women and worsening with age. Most women avoid medical treatment, either because they accept their leakage as natural or hold an unfavorable view of treatments like surgery and pelvic floor physical therapy. This research will explore a scalable, high-tech approach to at-home treatments recommended by clinicians. Patients will interact virtually with health coaches and routinely receive personalized, semi-automated help and encouragement. Health coaches will be able to monitor the simultaneous progress of many patients remotely. Benefits include (1) helping more women at lower cost versus current practice and (2) increasing clinician productivity. It could save individual women up to $1,000 annually and eliminate tens of thousands of unnecessary surgeries.
This Small Business Innovation Research (SBIR) Phase I project will develop a healthcare system workflow technology enabled by AI algorithms for tailoring an incontinence home health intervention to a wide variety of patient needs, preferences, and idiosyncratic behaviors. Study use cases will include medical device usage training and exercise regimen adherence. To address these scenarios, researchers will create a clinically-valid, user-specific, dynamic incontinence treatment solution comprising a mobile app for symptomatic women and a health coaching platform that integrates user data and generates tailored interactions. Solution elements will be built to (1) collect and manage high quantities of rich user data, (2) develop and train real-time inference algorithms, and (3) incorporate machine learning approaches to learn from user responses to system outputs (feedback, recommendations, encouragement, etc.). Known principles of health behavior change will be incorporated in adapting interactions for users.
This award reflects 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. -
Lepidext LLC
SBIR Phase I: Oral delivery systems for sterilizing strains of a sexually-transmitted insect virus
Contact
1122 OAK HILL DR
Lexington, KY 40505--3322
NSF Award
2126953 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2022 – 12/31/2022
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 support widespread distribution and adoption of sterilizing biopesticides that are effective and efficient to control Lepidoptera. Lepidopterans, such as the corn earworm, circumvent insecticidal properties of certain crops by developing resistance. Models show that incorporating sterile insects in a corn earworm population can suppress the incidence of resistant individuals in the populations. Enhancing oral infectivity of this sterilizing insect biopesticide will improve product manufacturing, distribution and most importantly, ease of use to support farmer adoption.
The proposed project develops a functional orally-infectious formula of a specific strain of the sexually-transmitted, sterilizing-virus, Helicoverpa zea nudivirus 2 (HzNV2). The resulting technology will be suitable for prototyping and testing oral formulations for sterilizing adult corn earworm moths. Genetic selection and candidate gene approaches are proposed to improve stability of the virus entry complex required for oral infectivity. This project will decorate viral envelopes with genes absent from HzNV-2 and thereby improve virion stability. The pseudotyped virus will be assayed for increased oral infectivity.
This award reflects 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. -
MAREL POWER SOLUTIONS, INC.
SBIR Phase I: Compact Power-Stack and Packaged Power Module
Contact
6155 ALMADEN EXPY STE 400
San Jose, CA 95120--2776
NSF Award
2126828 – SBIR Phase I
Award amount to date
$256,000
Start / end date
11/15/2021 – 12/31/2022
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 modular power sub-systems (power-stacks) that will enable a new generation of power inverters that are compact, re-usable, upgradable, resilient against die-supply shortages, and can be manufactured faster and cheaper. As the world migrates to sources of clean energy and the further electrification of industry, transportation, and homes, there is a significant and growing demand for electric power converters. Widespread adoption of clean energy requires that these converters be simple, scalable, reliable, and cost-effective. Today's designs are inconvenient both for end customers and for converter suppliers, as they typically are: complex, large, heavy, inflexible, expensive, and slow to market. Current inverter are often made by only a few specialized companies and have high technical barriers to entry for inexperienced entrants. Additionally, current inverters are locked to power-die suppliers, making scale-up and re-use challenging. The proposed project will develop and test a novel approach to enable inverters to meet new market demands.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a novel approach to power conversion problems. High speed operation of high-power semiconductor switches typically generates significant heat. The novelty of the proposed innovation over current technologies resides in moving the point of electrical isolation from adjacent to the power-die to adjacent to the coolant, and massively integrating the power path, the control path and thermal path into scalable building blocks. An additional advantage is the ability to develop new manufacturing processes to build and integrate these blocks reliably. The outcomes of this project may be a design and manufacturing approach that results in 50% reduced development time and development cost, 80% lower weight and size, a $100-$200 per unit cost reduction, increased scalability, and improved resilience to die-supply shortages.
This award reflects 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. -
MBF THERAPEUTICS, INC.
STTR Phase I: Protective T Cell Vaccine for SARS CoV-2 (COVID-19)
Contact
640 WOODBROOK DR
Ambler, PA 19002--1828
NSF Award
2131876 – STTR Phase I
Award amount to date
$256,000
Start / end date
01/01/2022 – 12/31/2022
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 (STTR) Phase I project is to develop a fundamentally different next-generation SARS CoV-2 vaccine that addresses current gaps in efficacy, safety, and national and global distribution of vaccines. The rapid global emergence of the highly infectious delta variant underscores the importance of T cell immunity, increasingly recognized as critical to eliciting effective and long-term immunity to SARS CoV-2. An innovative DNA vaccine, delivered as a patient-friendly intranasal spray that does not require refrigeration, will improve public health.
This Small Business Technology Transfer (STTR) Phase I project advances a multivalent SARS CoV-2 T cell vaccine by intranasal/pulmonary administration of calcium phosphate nanoparticle-formulated plasmids. Proteins comprising the SARS CoV-2 ORFeome will be cloned in proprietary plasmids (Aim 1) screened by in vitro challenge with PBMC from recovered donors (Aim 2) and safety/immunogenicity/challenge in vivo in hACE2 mice. The outcome of Phase I will be identification novel ORFs that elicit T cell responses in vivo and that in combination partially protective (50% survival at 14 days post infection) against challenge with SARS CoV-2.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MECHASIM INC.
STTR Phase I: Design and development of novel oral drug formulations by leveraging the food effect
Contact
14 WILLIAM ST APT 2
Medford, MA 02155--6424
NSF Award
2015053 – STTR Phase I
Award amount to date
$224,761
Start / end date
12/15/2020 – 12/31/2022
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 novel food-based oral dosage forms of pharmaceutics potentially superior to traditional tablets as they can be administered at lower doses without compromising therapeutic benefits. Currently tablet form preparations require administration at high doses to achieve desired therapeutic effects, motivating improved oral delivery systems. The proposed dosage forms may have the ability to mitigate food restrictions in drug labels and particularly helping oral drugs with significant gastrointestinal toxicities. Patients could benefit from the flexibility of taking medications irrespective of food to ease complex drug regimens and ultimately improve compliance. The near-term commercial focus will be to advance development toward a general platform with two proposed test drugs.
This Small Business Technology Transfer (STTR) Phase I project seeks to develop more bioavailable dosage forms by exploiting the effect of food in enhancing drug absorption. As more than 40% of marketed drugs and about 90% of drugs in development pipelines suffer from poor solubility and associated low bioavailability, the proposed technology will serve as a platform for drugs showing enhanced absorption when taken with food. This project will effectively enable the use of food ingredients (e.g., lipids, proteins) to develop more bioavailable dosage forms of marketed oral drugs. Activities include use of computational modeling tools to quantitatively estimate the effect of specific dietary food ingredients in increasing the efficiency of drug absorption. Ultimately this process will inform rational, efficient design of novel food-based formulations a priori rather than by a trial-and-error process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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
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 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
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 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. -
MFNS TECH, INC.
STTR Phase I: An Oleophilic Hydrophobic Magnetic (OHM) Sponge for Environmental Remediation
Contact
940 QUEENS LN
Glenview, IL 60025--1971
NSF Award
2151578 – STTR Phase I
Award amount to date
$255,932
Start / end date
04/01/2022 – 12/31/2022
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 is to develop an environmental remediation platform for oil spills and related contaminants in water bodies. Oil spills and associated heavy metals/toxins have significant economic, social, and environmental adverse impacts. The current state-of-the-art approaches are expensive, pose dangers to marine life, and/or generate physical waste. This project introduces a widely deployable sponge technology that attracts oil and resists water. It can selectively remove and recover oil from an oil/water mixture and is re-usable. The materials/methods in the proposed project are cost-effective, scalable, and ecologically friendly.
The intellectual merit of the proposed project is to advance a technology leveraging the interfacial tension at an oil-water interface. This project develops a nanotechnology-based simple and scalable sponge that can selectively sequester oil molecules and metal toxins from an oil-water interface. The proposed system coats commercially available sponges with a nanocomposite material. Activities include optimization of key factors affecting interactions between oil and metal toxins with nanocomposites coated on sponge pores and tailoring both the length-scale and chemical architecture for remediation 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. -
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
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 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 (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 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. -
MODULAR MATTER, INC.
SBIR Phase I: Universally Adjustable Modular Prosthesis Socket
Contact
2915 ISLAY CT
Abingdon, MD 21009--3140
NSF Award
2052296 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2021 – 12/31/2022
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 prosthesis, where discrete, mass-producible modular components can be assembled to fabricate sockets that would otherwise require expensive materials and equipment and hours of custom fitting. The modules can be assembled in virtually limitless configurations and provide a mechanism for conforming to the shape of the individual’s residual limb. This project will also extend a process innovation in the system’s capacity to inexpensively and quickly replace broken components and modify the socket to long-term changes in limb shape, including keeping up with a child's growth or executing complete rebuilds using the same components. The modular design also allows for mass manufacturability of the constituent components rather than specialized one-off manufacturing. The system is suitable for patients of all ages, limb shapes, and for both upper and lower limb sockets, so a broad set of needs can be addressed.
This Small Business Innovation Research (SBIR) Phase I project proposes to create a universally adjustable, semi-flexible modular socket system that adapts to fluctuations in limb volume and shape changes while still providing a secure and comfortable fit. The modular design enables the product to be assembled, configured, and reconfigured to suit the specific limb shape of the patient. In this project, the implications and limitations of mechanically coupling a distributed, modular, semi-flexible socket system to soft tissues will be explored. This includes maximum and minimum pressure and hotspot mapping under physiologically-relevant loading and torque.
This award reflects 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 (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 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 (Estimated)
NSF Program Director
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. -
NANORESEARCH, INC.
SBIR Phase I: Investigate Process-Structure-Property Relationship of Nano-Layered Coatings of Binderless Electrodes by a Nozzle-less Spray Coating Technique
Contact
58 EDGEWOOD AVE NE STE 122
Atlanta, GA 30303--2921
NSF Award
2136777 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 02/28/2023 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a manufacturing process innovation that overcomes volume expansion problems of batteries made by conventional manufacturing processes. These expansion problems limit the broad adoption of high performance, safer, naturally abundant, environmentally friendly, and cheaper raw materials for advanced batteries in applications such as modern electric vehicles and powered aircraft. The proposed project develops a drop-in technology for existing manufacturing infrastructure with the potential to significantly reduce the environmental waste of conventional manufacturing processes.
The SBIR Phase I project will investigate the binderless electrode manufacturing using nano-layered coatings deposited using a nozzle free spray coating technique. The technical challenges include contaminated electrodes with filter residues; non-uniform electrode thickness, density, and porosity; poor repeatability; and lengthy filter removal process, inhibiting scale-up of the vacuum filtration method for making binderless electrodes. This project will validate a new ultrasonic spray coating technique for scaling the production of binderless electrodes. The scope of the research includes: designing surfactant removal and homogeneous dispersion of nanocomposite mixture solution subsystems, synthesizing binderless electrodes with the innovation, and characterizing electrode prototypes. The project's tasks (using an iron oxide anode for demonstration) include selecting precursor materials with appropriate morphologies and sizes for effective bonding between nanocomposites and adhesion on current collector; designing binderless electrode structures; computer modeling and simulation to optimize parameters of binderless electrode structure, electrode nanocomposite constituent morphologies and sizes; advancing surfactant removal, homogeneous dispersion, and thermal=pressure subsystems; developing ultrasonic nozzle-less spray coatings to make prototype electrodes; and characterizing the mechanical and electrochemical properties of the binderless electrode prototypes.
This award reflects 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. -
NEUROSMART INC.
SBIR Phase I: Wearable System for Stress Management via Real Time Stress Tracking and Biofeedback
Contact
221 EASY ST APT 10
Mountain View, CA 94043--3772
NSF Award
2212935 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2022 – 01/31/2023
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 creating a tool for police officers and other service members who are expected to perform their job duties under high stress. This Phase 1 project seeks to develop a technology that creates stress scores and alerts users when they are in “red zones” for decision making based on physiological monitoring via a wearable sensor unit. The initial target market segment for this technology is the ~$1 billion law enforcement market as there is a high need for tools that can help de-escalate situations and potentially improve the use-of-force decisions. The pain points of acute stress impacting decision-making have been validated in military and professional athletic markets as well.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a wearable technology that uses skin conductivity to measure stress and alert users via vibrational feedback. This Phase 1 project proposes to: (1) run a pilot study on police officers to collect skin conductance data during scenario training, (2) build machine learning artificial intelligence (AI) models with a high predictive accuracy of poor decision making using this data, (3) determine ideal sensor location and build a custom wearable strap attachment, (4) develop the mobile application to build a data visualization interface for officers and trainers, and (5) test the effectiveness of delivering vibrational feedback during decision making of officers using the prototype. The successful conclusion of Phase 1 may lead to a hardware-software prototype that measures the police officers' emotional stress using a skin conductance signal, then alerts the user via vibrational feedback when they are in a heightened level of stress.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEURX MEDICAL LIMITED LIABILITY COMPANY
STTR Phase I: Endovascular Thrombectomy System for Ischemic Stroke
Contact
8516 PARKWOOD LN
Philadelphia, PA 19128--1309
NSF Award
2136438 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 02/28/2023 (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 survival and functional outcomes for stroke patients. Stroke remains a leading cause of death among Americans and is the largest source of long-term disability in the U.S. and around the world. Every 30 seconds, an American suffers a major stroke, most commonly caused by a clot obstructing a large cerebral artery supplying a critical area of the brain. This project’s clot-removal technology aims to enable rapid and efficient removal of clot from the cerebral vessels using minimally-invasive image-guided techniques, thereby improving the chances of full recovery and an independently functional outcome. The broader benefit for society is to reduce death or permanent disability from ischemic stroke with its resultant family, community, and economic burden.
This Small Business Technology Transfer Phase I project will lead to the development of a medical device to enable efficient removal of blood clots from the brain arteries of a stroke victim. The platform technology is constructed from microscopic tubes of superelastic metal alloy integrated with a proprietary pattern of laser-cut apertures. The device can be delivered to the stroke clot through a microcatheter to create a shape-formed array of clot-capture elements within a patient’s artery. Tandem capture devices optimize the clot capture system and can be positioned on either edge of a clotted segment within a brain artery. Optimal shape, thickness and materials of the clot capture elements and the delivery system will be characterized, developed, and verified. The proposed work will utilize a previously validated model of stroke thrombectomy to characterize and quantify fundamental clot capture parameters (clot stabilization, retention, and retrieval) among multiple discrete capture node embodiments. Radial force, coefficient of drag during withdrawal inside a cerebral blood vessel and device trackability will be measured for each design using robust three-dimensional human anatomic models of cerebral vessels. The project will enable a design freeze of the optimal device design and validate its performance using a preclinical animal model.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 – 12/31/2022
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. -
NEYROBLASTGX LLC
SBIR Phase I: Genetically Engineered Dendritic Cell to Activate SARS-CoV-2 Spike Protein specific-T Cell (COVID-19)
Contact
26442 BECKMAN CT
Murrieta, CA 92562--7022
NSF Award
2051522 – SBIR Phase I
Award amount to date
$255,997
Start / end date
04/01/2021 – 12/31/2022
NSF Program Director
Errata
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This is a COVID-19 award.Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a specific immunoprotective cell therapy using the SARS-CoV-2 spike protein (Sp) to boost immunity against COVID-19, especially with comorbidities. A durable competitive advantage reflects immune cell engineering with novel coronavirus Sp as a new technological advancement for stem cell-based immunotherapy (SCT) to treat viral diseases, diabetes, autoimmune disorders, or cancer. Use of SCT against SARS-CoV-2 or new virus strains will prevent COVID-19 and post-infection complications, reduce the chance of future pandemics, and strengthen the local and national economy.
This Small Business Innovative Research (SBIR) Phase I project will develop a "DC-COV19" probe system to eradicate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which killed more than 400,000 people in the United States. Our long-term goal is to develop a potent COVID-19 T cell-based immunotherapy (vaccine-like) for high-risk populations to stop or reduce SARS-CoV-2 infections. The SARS-CoV-2 vaccines target neutralizing antibodies but only rely on the endogenous production of T cells. Major Gap: COVID-19 patients showed a significant reduction in the number and function of T cells and required robust vaccine or immunotherapeutic strategies to boost SARS-CoV-2-specific CD4+ and CD8+ T cells. NeyroblastGX LLC (NGL) proposes to develop a probe from dendritic cells (DCs) derived from established genetically engineered human embryonic stem cells (hESC) transfected with SARS-CoV-2 spike protein (Sp). This "DC-COV19" probe will be used to produce high numbers of functional SARS-CoV-2-specific CD4+ and CD8+ T cells ex vivo. Autologous immune T cells will be transferred into COVID-19 patients as a rapid and robust adaptive T cell-based immunotherapy. NGL works with world-class immunologists and clinicians to develop several Sp constructs engineered to transfect DCs to selectively activate SARS-CoV-2-specific CD4+ and CD8+ T cells to fight COVID-19.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NISTRON, L.L.C.
STTR Phase I: Active Transport of Caffeine through a Blood-Brain Barrier Model
Contact
3021 RED FOX RD
Ames, IA 50014--8069
NSF Award
2014346 – STTR Phase I
Award amount to date
$225,000
Start / end date
09/01/2020 – 01/31/2023
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 create a drug-discovery platform that will screen quickly and early in the process for candidate therapeutics that can enter the central nervous system (CNS). The goal is to minimize the lengthy and expensive clinical trials that ultimately fail because of their failure to enter the BBB by providing a high assurance that the drug can pass the blood/brain barrier (BBB). The project will facilitate discovering next-generation interventional treatments for serious brain-related diseases and will greatly benefit patients and families fighting debilitating diseases that are difficult or impossible to treat with current methods. The ability to screen for BBB penetration early is needed. An estimated 2% of small drug molecules and no large molecules are able to pass into CNS to treat neurodegenerative diseases, multiple sclerosis and strokes, accounting for 12% of total global deaths. Each of these diseases represents a major healthcare cost and caregiver burden.
The proposed project focuses on mimicking the BBB. This work will utilize cylindrical hydrogels to provide three distinct regions for the growth of multiple types of cells related to the BBB, thereby providing an environment that is similar to the native system. This will provide a highly relevant model to visualize the active transport of bioactive molecules across the BBB to create effective, next-generation therapeutics for use in the CNS. One goal is to show cell survival throughout ten-day-long trials. Additionally, the genetic response of the cells within the system will be analyzed to better understand their behavior, and the system’s inherent conductivity will show real-time cell-to-cell communication. Once a model is created, the transport of caffeine across the model barrier will be studied and compared with known values of how the molecule acts within the body to begin validating the 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. -
NOSTOPHARMA, LLC
STTR Phase I: Improved drug delivery platforms for localized and sustained drug deposition for traumatic injuries
Contact
7600 CODDLE HARBOR LN
Potomac, MD 20854--3251
NSF Award
2136542 – STTR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 reduce complications due to trauma. Current traumatic injury treatments are systemic and untargeted with unwanted side effects and low efficacy. The proposed project will develop a sustained-release, biodegradable, nanoparticle drug delivery system for treatment of soft tissue trauma complications. The successful commercialization of this technology may advance the state of the art in sustained release technologies and dramatically improve the standard of care for trauma patients by addressing critical needs to enhance medication compliance, as well as the efficacy and safety of medications prescribed following trauma surgery.
This Small Business Technology Transfer (STTR) Phase I project will address the needs to improve traumatic injury treatments through the development of a sustained-release, biodegradablem drug delivery platform that delivers post traumatic medications within the injured tissue thereby obviating the need for unnecessary systemic drug administration. Such a technology has the potential to improve the clinical outcomes of surgical procedures for patients with post traumatic injuries and reduce societal costs associated with additional surgeries and rehabilitation among trauma surgery patients. In addition, it is anticipated that this drug-device combination will reduce surgery times, save money, and prevent complications among affected patients. During Phase I, the team proposes to demonstrate in vitro and in vivo feasibility towards altering the ectopic bone microenvironment with the aid of nanotechnology that will prevent ectopic bone development and progression. The technology uses immunomodulatory nanoparticles loaded with the Hedgehog pathway inhibitor.
This award reflects 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
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 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 (Estimated)
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. -
Nanopath Inc.
SBIR Phase I: Integrated Point-of-Care System for Rapid Pathogen Identification in Urinary Tract Infections
Contact
10 PINEWOOD VLG
West Lebanon, NH 03784--3402
NSF Award
2136683 – SBIR Phase I
Award amount to date
$255,874
Start / end date
01/01/2022 – 12/31/2022
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is improved access to state-of-the-art molecular diagnostic technologies in areas of significant unmet clinical need, such as women’s health. Urinary tract infections (UTIs) are a pressing problem due to the lengthy clinical workflows and large disease incidence. UTIs are one the most common prompts for women to seek health care in the United States and represent a major driver of antibiotic prescriptions. Untreated UTIs can lead to severe complications for the patient, such as systemic bacterial infections. Despite the severity and prevalence of UTIs, diagnostic methodologies remain extremely time-consuming and rely on antiquated culture-based detection, leaving women in pain for up to three days before they are prescribed the appropriate antibiotic therapy. The proposed project will accelerate UTI diagnosis and can be used for other infections as well.
This Small Business Innovation Research (SBIR) Phase I project integrates microfluidic methods for cell enrichment with a novel nanostructured substrate for ultrasensitive detection of target nucleic acid sequences. The reader contains software and optical hardware to detect and analyze the test result at the point-of-care. This technology eliminates the need for bacterial culture and nucleic acid amplification through an ultrasensitive detection modality, providing species-level information and genotypic antibiotic resistance data within minutes. The applications of this proposed platform translate beyond UTIs and have utility in other clinical scenarios that currently employ lengthy culture-based steps and molecular testing workflows, such as respiratory infections, bloodstream infections, and prosthetic joint infections. The project goal is to increase sample throughput through microfluidics optimization and automation and to improve sensitivity through novel sensor geometry design.
This award reflects 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
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 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. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable 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
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 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
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 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. -
OMEGA HYDRODYNAMICS RESEARCH LLC
SBIR Phase I: A Flexion-Based Computational Fluid Dynamics Tool for the Fast Computation of Turbulent Flow over Complex Geometries
Contact
4310 BOULDER POND DR
Ann Arbor, MI 48108--8600
NSF Award
2133757 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/15/2022 – 12/31/2022
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 acceleration of the development of innovative industrial design concepts involving complex turbulent fluid flow using computational fluid dynamics (CFD) software. Although CFD software has broad applications in several industries, the company’s particular interest is in bodies with strong vortical wakes such as bio-inspired renewable energy extraction devices and electric vertical takeoff/landing (eVTOL) vehicles. It is anticipated that the project may lead to the timely and cost-effective design of energy extraction devices without the need to build and test prototypes during the design phase. The project may also enhance the safety and operating envelope of urban air mobility vehicles. The proposed cloud-based CFD software will provide startups and smaller companies (without access to high-performance computing resources) with the ability to perform CFD analysis in reasonable timeframes. The proposed novel reformulation of the Navier-Stokes equations will also have a lasting impact on the education of the next generation of engineers and scientists as they gain a better understanding of the advantages of the new set of equations for turbulent flows.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop a fast high-fidelity computational fluid dynamics (CFD) software for predicting unsteady flow separations over complex geometries at large Reynolds (Re) numbers without any heuristic turbulence modeling. The software will build upon prior work by the proposer who developed a novel flexion-based Large Eddy Simulation (LES) method for high Re turbulent flows. The LES method uses the flexion (vorticity curl) vector as the primary dependent variable in the Navier-Stokes equations to better track sharp vorticity-gradient regions in high Re flows. The method also uses hyperviscous dissipation instead of a parameterized sub-grid model for unresolved small-scale turbulent motions. The flexion-based LES method will be extended to complex geometries by coupling it with a vortex panel method for the body surface. The vortex panel method leads to accurate predictions of the shear stress on wall boundaries from the wall vorticity without the computationally demanding requirement of a fine mesh to resolve the thin boundary layers that occur in high Re flows. The proposed approach represents a new technique of using panel methods, which have a rich history in aerodynamics, to provide boundary conditions for large eddy simulations of the vortical wake.
This award reflects 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
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 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)
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. -
OPEN SOURCE INSTRUMENTS INC.
SBIR Phase I: A Novel Dense Fiber Array for Astronomical Spectroscopy
Contact
130 MOUNT AUBURN ST
Watertown, MA 02472--3932
NSF Award
2111936 – SBIR Phase I
Award amount to date
$240,700
Start / end date
01/15/2022 – 12/31/2022
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 it possible for astrophysicists to dramatically expand their ability to collect the spectra of distant galaxies, and so to advance their understanding of the universe. The most important factor in large-scale spectrographic data collection is the number of spectra taken per viewing hour. The planned Direct Fiber Positioning System (DFPS) is mechanically simpler than the current state-of-the-art positioning systems; it will cost less to produce per installed fiber, and it will provide more fibers per unit area than any existing design. The spectra of galaxies is critical to dark energy and dark matter research programs, and these programs address the greatest open questions in astrophysics today. The relative simplicity of the DFPS mechanical components makes it a better choice for spectrographs of tens of thousands of fibers, but also for much smaller arrays of a few hundred fibers, such as could be installed on smaller telescopes. Thus, the DFPS will win a share of the small market for very large spectrographic instruments, but also to create for itself a large market for smaller spectrographic instruments.
This Small Business Innovation Research (SBIR) Phase I project will be a small Direct Fiber Positioning System (DFPS) consisting of a 4 x 4 array of 16 fibers on a 5-mm grid. Each fiber will provide a 3.6-mm x 3.6-mm range of motion and will be controlled by electronic circuits consuming less than 20 mW. A calibrated camera will view the illuminated fiber tips, monitoring their position with an accuracy of 10 µm, to measure and demonstrate the precision and repeatability of the fiber positioner. The stability of the positioner will be determined over the course an hour in warm and cold environments, and in both horizontal and vertical orientations. The direct method of fiber movement requires accurate control of voltages applied to many fibers in parallel, which is a challenging electrical engineering problem that has been avoided by other, mechanically complex systems. If we can locate fibers with an accuracy of 10 µm in the focal plane of a telescope, we will be able to provide a new and superior type of fiber-positioner, one that will be more compact, less vulnerable to mechanical failure, less susceptible to corrosion, and more resistant to fatigue than any other existing fiber-positioning 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. -
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. -
OPTERA LLP
STTR Phase I: Investigation and Optimization of a Novel, Pheromone-based Tool for Measuring Honey bee Colony Pest and Disease Resistance
Contact
406 HILLCREST DR
Greensboro, NC 27403--1213
NSF Award
2111970 – STTR Phase I
Award amount to date
$255,748
Start / end date
01/15/2022 – 12/31/2022
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 includes the reduction of honey bee colony mortality by up to 75% through early identification and improved breeding of pest- and disease-resistant colonies. Honey bees are dying at unprecedented rates, with annual losses up to 45% in the United States. A primary cause of colony death is the parasitic mite Varroa. The unhealthy brood odor (UBO) assay is a pheromone-based tool that reduces labor costs required to measure Varroa-resistance by 18x, accelerating decision-making by 20%. The assay’s user-friendly design makes honey bee selection and queen evaluation more accessible to beekeepers, who are often restricted by the high technical skill and/or extensive labor required for existing assays. The UBO assay has potential to improve honey bee health and increase profitability of beekeeping operations, and thus may significantly improve global crop pollination and food security.
The proposed project will assess the technical feasibility of using a honey bee pheromone-based assay to predict colony-level disease- and pest-resistance. This novel tool has the potential to improve honey bee health, revolutionize honey bee breeding, and inform important apiary management decisions, as it improves efficiency and efficacy of honey bee selection by enabling rapid and accurate identification of Varroa-resistant honey bee colonies. However, to be highly effective and achieve widespread uptake the technology must be practically and economically accessible, must perform consistently despite environmental variability, and must be established as a reliable indicator of heritable Varroa-resistance traits. The proposed research will employ sophisticated behavioral, biochemical, breeding, and manufacturing techniques to optimize prototype efficacy, safety, and delivery, reduce production costs, assess prototype performance across environmental variables, and provide a proof-of-concept for heritability of Varroa-resistance traits identified by colony response to the prototype assay. Expected results include improvements to the safety and efficiency of the product delivery system, improved understanding of the effects of environmental variability on product performance, and confirmation of the heritability of traits identified by honey bee behavioral response to in-hive tests of the 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. -
OPTICAL WATERS LLC
STTR Phase I: Scaling and Optimizing Manufacturing Methods for Germicidal Optical Fibers (GOF) to prevent disease-causing biofilms in tight channels
Contact
227 HEATHERSTONE RD
Amherst, MA 01002--1692
NSF Award
2136341 – STTR Phase I
Award amount to date
$255,492
Start / end date
01/01/2022 – 12/31/2022
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Technology Transfer Research (STTR) Phase 1 project is to advance the development of germicidal optical fibers (GOF). GOFs side emit ultraviolet-C (UV-C) radiation along their entire length like a glowstick. Their use in tight channels of homes, businesses, and hospitals can eliminate pathogenic bacteria and viruses that cause operational issues, infections and even deaths. The ability to distribute ultraviolet radiation into tight channels outranks the current biofilm prevention approach of using chemical management or surface modification that works for a short duration (days), damage surfaces and produces harmful by-products. This technology holds promise for extension to other industries in biomedical devices, home appliances, air purification and water systems.
This project will advance the manufacturability of GOFs from a non-scalable dip coating process to a draw tower. GOFs consist of two parts: a) a light engine that houses a UV-C LED and b) a UV side emitting optical fiber. UV-C light (265 nm wavelength) is sent from the LED through the glass core and scattered by a nanoparticle coating, resulting in emission of UV-C light into the surrounding environment (air/water). Currently, the specific material needed for the manufacturing of GOFs are not suitable for manufacturing in a draw tower, and the technology is limited to 1 m rigid fibers. Therefore, the specific objectives in this project are to (i) innovate the chemistry of the external nano-enabled polymer able to distribute UV-C radiation for draw tower application, (ii) modify the manufacturing steps in a draw tower to enable large scale manufacturing of < 300 µm diameter for increased flexibility and > 50 m length GOFs and (iii) control nanoparticle positioning in large scale manufacturing to enhance uniform light scattering profile through the length of the fiber.
This award reflects 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)
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 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 (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 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
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve detection of prostate cancer, a highly prevalent fatal cancer in men. Approximately one million prostate biopsies are performed annually in the U.S. Unfortunately the standard diagnostic method is imprecise and inefficient. The proposed project will advance a new method that uses Magnetic Resonance Imaging (MRI) to target biopsies for improved detection.
This Small Business Innovation Research (SBIR) Phase I project will advance diagnosis of prostate cancer by developing a system that combines an endorectal MRI coil and a multichannel array of transrectal biopsy needle guides and allows for endorectal MRI with in-bore biopsy as a single rapid integrated procedure. The project will advance a procedure that optimally combines endorectal MRI and MRI-targeted biopsy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Oncurie, Inc.
STTR Phase I: Self-assembling molecular brachytherapy for treatment of metastatic cancer
Contact
1236 CANTERBURY RD
Raleigh, NC 27608--1926
NSF Award
2136700 – STTR Phase I
Award amount to date
$255,730
Start / end date
02/01/2022 – 01/31/2023
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable radiotherapies for metastatic cancer, estimated to account for 90% of the 600,000 cancer deaths in the US each year. Of the approximately 1.8 million new cancer cases diagnosed each year in the US, nearly half are candidates for improved outcomes using some form of radiation-based therapy. Metastatic cancer, however, is generally not treated with radiotherapies due to the need for prior knowledge of the metastatic sites. The proposed project treats metastatic cancer by using the cancer cells themselves to help deliver the radiation. This technology may generate reliable efficacy of radiotherapy for the treatment of the most lethal forms of cancer.
This Small Business Innovation Research Phase I project seeks to advance radiotherapy that exploits cancer cells themselves as catalysts for therapeutic delivery. After systemic administration or local injection, the monomers are expected to diffuse through tissues and subsequently polymerize, immobilizing radionuclides in the extracellular space of cancer cells. Non-cancerous cells will be minimally impacted, as soluble monomers will remain subject to diffusion and relatively rapid tissue clearance in the absence of cancer cell-derived catalysts. The chemistry at the core of the approach is an enzyme-triggered polymerization of native-like compounds under physiological conditions. The final therapeutic compound features the polymerizable compound and covalently-conjugated radionuclide 131-I, a commonly used radiotherapy isotope.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PANGEA CHAT LLC
SBIR Phase I: Intelligent Language Learning Environment
Contact
2910 LIBBY TER
Richmond, VA 23223--7908
NSF Award
2112088 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/01/2022 – 02/28/2023 (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 will improve the current US deficiency in foreign language skills and bring critical innovations to the $13 billion global online language learning market. Current language learning methods focus on rote memorization and not nearly enough on using the language. Experiential learning opportunities in which students have free-flowing conversations driven by interests are often not introduced until the third or fourth semester of language study. The result is that American students graduate with little ability or motivation to actually use a foreign language and maintain any degree of language fluency. Using novel machine learning technologies and game design, this project will let students learn a language while texting with their friends and help teachers facilitate conversation-based learning in their classrooms. The project will offer opportunities for students in classes located in the US to interact with students in other countries around the globe, turning textbook abstractions into real people, culture, and language. Ultimately, these machine learning solutions enable a platform that the 1.2 billion individuals learning language worldwide can use to supplement textbook instruction with experiential learning for greater long-term fluency.
This Small Business Innovation Research (SBIR) Phase I project will develop a state-of-the-art machine learning solution to address critical challenges in the implementation of
conversation-based language learning. Learning languages through conversation has been shown by previous research to be engaging and effective. However, beginners are often
uncomfortable in the early days because they aren’t confident in expressing themselves. Educators can provide the needed support, but it is difficult for them to give every student
personalized tutelage. This project will jumpstart these initial conversations with the help of in-chat translation, dictionaries, and grammar checking. To cement learning, the project will generate practice activities directly from chats and deliver the activities in the context of those authentic text conversations. This project will analyze the text chats and form hypotheses about student strengths and weaknesses. The system will then test these hypotheses with assessments automatically generated from the same text chats. The Phase I technical objectives are to 1) automatically identify examples of learning objectives in student text 2) align system-generated and human-authored assessment activities and 3) predict student scores on practice activities with increasing accuracy. Over time, the system will understand student needs to maximize learning and engagement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
PARADIGM OF NY, LLC
SBIR Phase I: A Non-thermal Plasma Reactor System for Destruction of Particulate Matter in High-Temperature Diesel Exhaust
Contact
1800 BRIGHTON HENRIETTA TOWN LINE RD
Rochester, NY 14623--2508
NSF Award
2127213 – SBIR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 12/31/2022
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to eliminate more than 95% of particulate emissions (i.e., carbon soot) from diesel exhaust while reducing fuel usage, carbon dioxide production, and vehicle maintenance. Diesel particulate pollutants are directly related to respiratory and heart disease. Curently this is addressed with diesel particulate filters (DPF), devices that trap particulates and do not destroy them. Furthermore DPFs are prone to clogging, resulting in wasted fuel and costly engine maintenance. This project advances a non-thermal plasma (NTP) solution to destroy diesel particulates by converting them into non-hazardous compounds. NTP technology also has potential to be applied more broadly to power plant smoke stacks and other sources of particulate emissions. The proposed solution will develop a NTP device for retrofitting diesel fleets, such as buses, waste haulers and utility trucks, improving engine performance and reducing operating costs.
This SBIR Phase I project researches novel materials and components for use in a non-thermal plasma (NTP) reactor capable of withstanding the harsh conditions within the main exhaust stream of a diesel engine (e.g., 650 C temperatures and high exhaust flow). First generation NTP reactors capable of operating in low-temperature exhaust (e.g., 150 C) have already been developed and sold for use in diesel exhaust gas recirculation (EGR) systems; however, only about 30% to 50% of total diesel exhaust flows through EGR. The objective of this research is to demonstrate feasibility of NTP technology for use in the main exhaust stream to treat 100% of particulate emissions. The research plan will accurately characterize the working environment of the main diesel exhaust system and identify potential designs and parts/materials, creating hybrid or completely new components. Promising candidate components will be assembled into a prototype reactor and evaluated on an accelerated schedule to measure performance representing 6 months of typical operation. The system will be optimized for thermal, chemical, electrical, and mechanical 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.