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Phase I
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123 SEE, INC.
SBIR Phase I: Vision care station for on-demand rapid examination of visual performance.
Contact
9 POLLOCK RD
Wayland, MA 01778--4552
NSF Award
2126964 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 11/30/2022 (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 significantly improve access to vision care for all Americans via a low-cost vision exam kiosk for supermarkets and pharmacies. A key technical component for reaching commercialization and scalability is the development of a contactless and autonomous eye scanner that accurately measures prescription numbers in under 10 seconds. The kiosk enables retailers that Americans already visit on average 20-30 times per year to offer instant vision exams and reports, eye prescriptions reviewed remotely by physicians, and access to high quality but affordable corrective eyewear. With 175 million Americans benefiting from vision correction, this solution could profoundly impact vision care across all communities.
This Small Business Innovation Research (SBIR) Phase I project investigates the feasibility of a novel contactless eye refractor for use in a self-serve and autonomous vision care station for pharmacies and supermarkets. Eye scanning is done via the photo-refractive principle enabling autonomous ocular refraction in mere seconds. A key issue with leading photo-refractor configurations is the resulting drift stemming from gaze misalignment. Instead of refracting single positions in the visual field, the proposed novel configuration refracts the central and peripheral visual field simultaneously, thus guaranteeing the measurement of foveal refractive error. This novel configuration will use commonly available low-cost components and can be manufactured at a fraction of the cost of commercially autorefractors. A software model of the system will be used to efficiently optimize the configuration, after which the design will be built and tested. A physical model eye will be developed and used for testing to confirm the accuracy at a multitude of gaze angles and to confirm result-decoupling of gaze alignment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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)
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 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. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable the 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. -
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 (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, 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 POW LLC
SBIR Phase I: A Hardware-Aware AutoML Platform for Resource-Constrained Devices
Contact
2605 SOMERTON CT
College Station, TX 77845--7466
NSF Award
2136679 – SBIR Phase I
Award amount to date
$255,889
Start / end date
02/15/2022 – 10/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to automate manufacturing inspection, reducing the cost of certain highly engineered projects. This project will develop a system to automatically create machine learning models for resource-constrained industrial hardware. This project enables the fast, affordable, and easy creation of on-device artificial intelligence with significant industrial applications. This will improve robust vision-inspection tools to improve product quality.
This project will develop an efficient solution to create advanced industrial internet of things applications that reduce network stress, minimize latency, and increase security at the edge. While the internet of things has many applications in the manufacturing industry, the vision inspection market can benefit due to its low-latency needs and the high stress it produces in the supporting infrastructure. This project is a flexible and modular hardware-aware machine learning model generation system that reduces manual efforts by automatically generating complex machine learning models for resource-constrained devices. Technical hurdles include the generation of neural networks that consider hardware speed and capacity constraints without human intervention. Technical milestones involve creating an automated model discovery platform tailored for edge devices, new resource-constrained neural architecture search algorithms, and hardware-aware model compression. This research aims to produce a prototype that domain experts with limited computer science training can use to create advanced industrial internet of things 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. -
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 (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 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 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve 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. -
AIRITY TECHNOLOGIES, INC.
SBIR Phase I: Viral inactivation in air and on surfaces across large areas by safe, non-thermal, non-ionizing electromagnetic radiation
Contact
1505 WOODSIDE RD
Redwood City, CA 94061--3432
NSF Award
2036664 – SBIR Phase I
Award amount to date
$254,392
Start / end date
07/01/2021 – 06/30/2022 (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) project is a new and safe non-contact method and device to inactivate viruses in air or on surfaces and objects. The non-chemical method proposed is scalable and can be quickly adjusted to target novel pathogens and therefore prevent or mitigate future epidemics of novel viral pathogens. The solution enabled by the proposed project is a relatively low-cost portable or ceiling-mounted device to be operated in health care settings, offices, schools, public transit, or other locations where the risk of disease transmission is high. The device would provide a continuous antiviral effect in thousands or millions of locations while operating within safe limits for human exposure.
This SBIR Phase I project proposes to validate the concept of a non-contact viral inactivation method that relies on resonant energy transfer from microwaves, and to demonstrate the efficacy in viral assays under operation parameters that are safe for humans and within regulatory guidelines. To accomplish this, a miniaturized and cost-effective high power pulsed microwave source and antenna is required. To this end, a prototype device will be developed that consists of a high-power vacuum electronics device, such as a magnetron or a traveling-wave tube, a custom and novel high voltage power source, and firmware and controls. The power supply will be designed to drive an existing vacuum device, by means of a regulated high-voltage output in the kilowatt range and a floating low-power auxiliary power source. To control pulsed operation, a control algorithm will be implemented in a microcontroller. The prototype will be characterized and used to expose viral samples in common viral growth assays, followed by a quantitative assessment of the antiviral effect. The outcome expected is a functional prototype that achieves significant reduction, e.g., 2 logs, within safe limits that will serve as a blueprint for a novel class of antiviral devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AIRMETTLE, INC.
STTR Phase I: Real-Time Smart Data Lake
Contact
2700 POST OAK BLVD FL 21 STE 152
Houston, TX 77056--5797
NSF Award
2135007 – STTR Phase I
Award amount to date
$256,000
Start / end date
02/15/2022 – 07/31/2022 (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 will be to fundamentally accelerate the pace of data science. New solutions that alleviate or bypass the bottlenecks inherent in existing data analytics technologies are required to unlock the value contained in “big data” and bring greater benefits to research, business, and society at large. The potential benefits include improved quality control for manufactured goods, reduced fraud in financial transactions, and enhanced customization of consumer services. Many common software applications, such as search engines, online shopping, e-commerce, medical applications, and social networks, are backed by data analytical processing services. This project will enable massive data sets to be pre-processed directly by a shared storage service, then allow this capability to be efficiently utilized by client analytic applications. This project will accelerate transformation of analytical data to useful insights while reducing network congestion, simplifying complex analytics systems, and lowering information technology costs.
This Small Business Technology Transfer (STTR) Phase I project examines the challenge of how to dramatically accelerate data-intensive computing problems by enabling large data objects to be processed directly in the storage layer then efficiently utilized by client applications. The technology will be built on a software defined data lake used for big data applications. Key technology will be added to enable JSON, one of the most widely used data interchange formats, to be processed in a distributed manner in-place within this storage solution with the objective of enabling client analytic applications to retrieve not the complete object but only the desired subset of content they require. The storage solution will be augmented to transform the data into a format that can be directly consumed by the clients. This will substantially increase efficiency within the storage itself and between analytics clients and the storage solution – while acceelrating data processing by bypassing bottlenecks. The result will be a smart data lake that can reduce network traffic, improve data freshness, and enable real-time operation – while accelerating big data analytics by an order of magnitude or more.
This award reflects 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. -
AKTTYVA THERAPEUTICS, INC.
SBIR Phase I: AI-assisted identification of small molecules for targeted repair of vascular barrier dysfunctions
Contact
1375 BRIDGE RD
Eastham, MA 02642--3221
NSF Award
2136307 – SBIR Phase I
Award amount to date
$255,487
Start / end date
12/01/2021 – 11/30/2022 (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 identification of treatments for vascular leak disorders. Uncontrolled vascular leak disorders are common pathological processes that lead to tissue damage across multiple organs and over 60 clinical conditions. Currently, there are no drug-based therapies that address vascular leaks. Available solutions are focused on providing supportive care or decreasing inflammation, without addressing the underlying mechanism. This project is proposing a new approach to repair vascular leaks as a therapeutic intervention. By establishing the first drug discovery workflow for the identification of small molecules that repair vascular leakage, this project will enable the development of a pipeline of drugs for multiple conditions. The first condition targeted will be acute respiratory distress syndrome (ARDS), which accounts for 10% of intensive care unit (ICU) admissions and is the leading cause of mortality in ICU. Globally, it affects more than 3 million patients yearly. The proposed solution will decrease the number of deaths and the costs for ICU.
This Small Business Innovation Research (SBIR) Phase I project seeks to validate a new structure-based drug screening platform designed to identify small molecules that activate the molecular pathways responsible for repairing vascular leakage. The proposed platform consists of a unique combination of novel machine learning methods for ligand-binding site prediction, fast docking algorithm capable of screening ultra-large (over a billion molecule) compound libraries with targeted absorption, distribution, metabolism, and excretion-toxicity (ADME-Tox) profile within minutes (5,000 compounds/second). The AI-guided docking approach is combined with in vitro high-throughput assays measuring the mechanisms of vascular leak in a physiologically relevant microenvironment of human tissues to select candidates targeting vascular leak disorders. In this project, the steps of this tiered workflow will be validated and applied to the first target, leading to the identification of a set of new drug candidates.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALERJE, INC.
SBIR Phase I: Food Allergy Management Platform
Contact
440 BURROUGHS ST STE 328
Detroit, MI 48202--3471
NSF Award
2051417 – SBIR Phase I
Award amount to date
$255,331
Start / end date
07/01/2021 – 06/30/2022 (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 the 32 million people in the US suffering from Food Allergy (FA). FA brings psychological, medical and financial consequences for patients and their relatives. The proposed project aims to leverage the latest advances on behavioral science and digital tools to create a platform that supports the implementation of the newly FDA-approved Oral Immunotherapy (OIT) treatments. OIT is a proactive approach that, contrary to other reactive treatments, achieves better patient outcomes. The proposed project will increase scientific understanding about FA through data collection.
This Small Business Innovation Research (SBIR) Phase I project seeks to help FA patients and clinicians in the implementation of OIT treatments. OIT has enormous potential to minimize the severity of an FA reaction before it happens, even eliminating the eventual health risks and inconvenient experiences compared to traditional treatments. Still, the preliminary OIT experiences have shown limitations due to needs for customization for each patient and data flow between patients and doctors. The main objective of this research is to develop and validate a digital platform that leverages behavioral science approaches and Machine Learning (ML) to facilitate adherence to OIT treatments, dosing management, treatment personalization, and patient-clinician communication. The specific work will involve: 1) Developing, training and evaluating a series of proprietary ML algorithms capable of providing new insights and predicting events; 2) Developing and testing other software assets required for the completeness of the platform (mobile app, HIPAA-compliant database and API to integrate with 3rd-party systems); and 3) validating the system in real experiences with FA 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. -
ALIENBYTE SCIENTIFIC SOFTWARE INC
SBIR Phase I: AI-assisted software for fast labeling of medical tomographic images
Contact
12156 PARKLAWN DR STE A
Rockville, MD 20852--1708
NSF Award
2136669 – SBIR Phase I
Award amount to date
$255,807
Start / end date
02/15/2022 – 07/31/2022 (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 extract new valuable information from medical images, accelerate image interpretation by radiologists, and improve patient outcomes. The process of identifying key features in images, known as ``labeling'', is the key to improved diagnosis and management of certain conditions. The innovations proposed here will substantially lower the cost of labeled datasets, enabling access for developers of artificial intelligence (AI) algorithms and improving the use of AI in health care.
This Small Business Innovation Research (SBIR) Phase I project will apply machine learning algorithms to develop a system for assisting in manual labeling of medical tomographic images. The proposed research will result in an adaptive system architecture that evolves to accelerate labeling and increase the volume of labeled data. Moreover, the research will increase labeling accuracy at the edges of anatomical structures. For instance, surgical resections for cancer treatment requires accurate labeling of the edges of abnormal tissue to ensure clean margins and minimal recurrence. Similarly, radiation therapy planning requires accurate labeling of the edges of organs at risk for safety and favorable outcomes. Due to its clinical importance, accurate manual labeling of ambiguities and sophisticated shapes is highly time-consuming. The proposed approach is differentiated from current methods by the inclusion of an additional subsystem for increasing the accuracy of edge labeling.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALSUS MEDICAL, INC.
SBIR Phase I: A Minimally Invasive Transurethral Cryotherapy Catheter System for Benign Prostate Hyperplasia
Contact
101 MISSISSIPPI ST
San Francisco, CA 94107--2523
NSF Award
2049600 – SBIR Phase I
Award amount to date
$255,564
Start / end date
07/15/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to provide a low-cost, safe, and durable treatment option for benign prostate hyperplasia (BPH), affecting 12.9 M Americans annually. First-line pharmacological therapy is the most common treatment for BPH, but these drugs provide modest clinical improvements and induce undesirable, and sometimes permanent, side effects that impact quality of life. This drives an estimated 62-91% of patients to discontinue treatment after 12 months. Patients who fail first-line therapy have the choice to pursue surgery, but due to the high risk of permanent complications, painful recovery, or a poor long-term prognosis associated with current surgical techniques, only 1.1% of all managed patients choose to have surgery each year. As a result, 35% of all managed BPH patients opt to not receive either medication or surgery. This watchful waiting patient population risks irreversible bladder damage if left untreated, where symptoms have been reported to worsen in ~87% of BPH patients over a four-year period. Importantly, it is estimated that sur gical intervention is necessary in 30% of all men afflicted with BPH, leaving millions of Americans without a robust option. The proposed solution treats the prostate with a minimally invasive catheter system.
The proposed project advances translation of a system to provide focal cryoablation to the human prostate. By implementing directional and localized cryotherapy through a series of catheter balloons, the device can remove enlarged prostate tissue while preserving adjacent anatomical structures key for preservation of sexual function and continence. Moreover, treated prostate tissue can be monitored in real time with ultrasound imaging for enhanced safety and treatment guidance. The goal of this Phase I proposal is to optimize a directional cryotherapy system in a benchtop model and verify its use to ablate the prostate lateral lobes. To optimize cryoablative dosing, temperature isotherms will be characterized and spatially mapped in an in vitro prostate tissue model across a range of operating parameters.
This award reflects 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 (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 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. -
AMCYT, INC.
SBIR Phase I: Automated Processes for Rapid Analyzation of Biopsy Samples
Contact
8159 LAUREL WILLOW LN
Sacramento, CA 95828--5392
NSF Award
2110476 – SBIR Phase I
Award amount to date
$255,991
Start / end date
04/01/2022 – 09/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to provide an efficient, automated biopsy diagnostic process which will allow patients to access high quality cancer diagnostics at lower cost and without being subjected to unnecessary and painful repeat procedures from inefficient biopsy processes. The innovation addresses a critical global need to improve the efficiency and analytics of biopsies. An automated, rapid on-site evaluation (ROSE) system will potentially eliminate the 20% fail-rate of fine needle aspiration (FNA) biopsy sampling. The application may also be scaled to provide a solution to facilities that may not be able to afford the rapid onsite evaluation service of FNA.
The proposed project aims to provide an automated, rapid on-site evaluation process by leveraging a system-engaging technology and robotics to increase fine needle aspiration biopsy sampling efficiency and improve patient experience, while reducing costs to ensure accessibility to all facilities. This device will have three processes to produce an image-ready glass slide that a pathologist can access remotely and render an adequacy assessment. The device will perform smearing, staining, and image capture of a fine needle aspiration biopsy sample. Normally, these processes are performed by a pathologist/cytotechnologist, making rapid on-site evaluation service inaccessible to fine needle aspiration providers in most rural or small facilities. With an automated device, the rapid on-site evaluation service may be mroe readily available and accessible at a fraction of cost, saving time and resources for patients and medical 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. -
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 – 12/31/2022 (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 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. -
APPLIED OCEAN SCIENCES, LLC
SBIR Phase I: Developing the First Flow-Through Sensor for Real Time Microplastics Measurements
Contact
11006 CLARA BARTON DR
Fairfax Station, VA 22039--1409
NSF Award
2136729 – SBIR Phase I
Award amount to date
$255,633
Start / end date
12/15/2021 – 11/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the increased ability to gain knowledge about microplastic concentrations in bodies of water rapidly, easily, and relatively cheaply through the first real-time sensor. Microplastics are a worldwide pollution problem that have devastating impacts on ecosystem services, human health, and fishery economics. Interest in microplastics is surging, with many academics, nonprofits, and government agencies all beginning microplastic research and monitoring programs. However, the limiting factor in studying and monitoring microplastics is that all current methods for collecting and analyzing them are extremely time-consuming. There are many current knowledge gaps about microplastic abundance due to bottlenecks in analyzing samples. This technology, in creating the first real-time flow-through sensor to analyze microplastic concentration, would begin to close those gaps. The benefits to the customer of this sensor include reduced labor costs, and reproducible and accurate data. These benefits may inform remediation strategies and policy decisions that could lead to a subsequent reduction of microplastics globally. Reducing microplastics in the environment can have ecological and human health benefits for the American people.
This project aims to build the first flow-through, real-time sensor for microplastics. The technology could reduce the sampling time of microplastic abundances by measuring ultrasonic frequencies. Using very large bandwidth ultrasound energy, the sensor will record different resonant and scattering responses of the suspended plastic particles based on size, shape, and material properties which will vary by plastic composition and weathering state. All of these factors will inform scientists about the concentration and composition of the sample. This technology is differentiated from current measurement methods of microplastic concentration by its novel combination of ultrasound technologies that have already been proven in both the medical and non-destructive inspection communities for in-liquid microparticle classification. This project will allow microplastics measurements to be taken quickly and easily for the first time, allowing for a rapid expansion of microplastics measurements, not only in America’s oceans, lakes, and streams, but also in wastewater and drinking water treatment plants, desalination plants, agriculture irrigation lines, and factory runoff streams.
This award reflects 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. -
AQUAGENX, LLC
SBIR Phase I: A simple, rapid field culture test to quantify Vibrio cholerae in drinking water
Contact
410 N BOYLAN AVE
Raleigh, NC 27603--1212
NSF Award
2136081 – SBIR Phase I
Award amount to date
$246,500
Start / end date
12/15/2021 – 11/30/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop a new water quality test that detects and measures Vibrio cholerae bacteria in drinking water samples. The test is an easy-to-use, field-deployable, and selective without requiring a lab, electricity or complex, expensive testing equipment and methods. The technology generates rapid test results in about 24 hours. Cholera is a waterborne disease that people contract when they drink water contaminated by the fecal bacteria Vibrio cholerae. The disease is an international public health burden prevalent in countries with unsafe drinking water and poor sanitation. The water quality test is a surveillance tool that monitors drinking water supplies and sources for Vibrio cholerae, helps prevent cholera outbreaks before they occur, track sources of cholera outbreaks, and evaluates the necessity and effectiveness of water sanitation. This environmental technology will help impact domestic and international environmental testing, water, sanitation and hygiene, and public health.
This SBIR Phase 1 project will develop novel growth media for the detection of Vibrio cholerae in drinking water. Currently available media do not differentiate between Vibrio cholerae and other Vibrio species. The technical challenge is to develop a field-deployable, direct, quantitative, single-step, culture-based testing method. The project will develop new growth media for two testing methods that generate different types of test results: Most Probable Number quantification and Colony Forming Unit quantification. Technical hurdles include: refining the composition of the media, optimizing the application of the media for both testing methods, validating both methods with challenging test waters, evaluating media stability and shelf life, and evaluating the media against standard, competing technologies. Successful media will meet all requirements for sensitivity, specificity, positive predictive value and negative predictive value. Successful media also will have a one to two-year shelf life. The test will be easy for anyone to use in the field without needing a lab or electricity.
This award reflects 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
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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 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the 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. -
ARITH INC.
SBIR Phase I: Efficient Arithmetic on Quasi-Compressed Data for Performance Improvement
Contact
3913 BIBBITS DR
Palo Alto, CA 94303--4529
NSF Award
2111696 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/01/2022 – 10/31/2022 (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 improve the performance of semiconductor chips. Specifically, it develops a novel method to operate directly on compressed data, saving time, energy, and latency. This improved performance will affect computationally intensive applications such as medical imaging (e.g., CT/MRI), climate simulation, hurricane warnings, and earthquake alerts.
This Small Business Innovation Research (SBIR) Phase I project develops a method to operate on compressed data. Today, computers apply data compression to identify and remove redundancy in the data in order to save storage space. Computers apply arithmetic to compute in integers or real numbers (usually represented internally as floating-point data). However, today's computers first decompress the data, compute, and then compress the computed result, consuming additional time and energy. This project develops an arithmetic and math hardware accelerator capable of processing compressed data directly to dramatically improve computation performance, storage effectiveness, and energy efficiency. This project combines data compression and floating-point engineering to deliver the first-ever Compressed Floating-Point Unit (CFPU) that minimizes semiconductor and energy usage and reduces computation latency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ARIX Technologies Inc
SBIR Phase I: Mobile inspection robot for industrial corrosion detection
Contact
221 TREAKLE DR
Jackson, LA 70748--4341
NSF Award
2111845 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/01/2022 – 06/30/2022 (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 the accuracy, safety, and efficiency of pipe corrosion inspections for petrochemical and other manufacturing facilities. Pipe corrosion is a major issue, estimated to cost 3.4% of the global gross domestic product (GDP), and if left unmanaged, can result in catastrophic safety and economic incidents such as fatalities or fugitive gas emissions (which can total 13 million metric tons/year in oil and gas alone). Current methods to inspect pipe corrosion are expensive, slow, manual, and unable to collect all the necessary data requested by field engineers. The proposed robotic solution addresses these issues by: (1) improving safety and efficiency through improved inspection and localization mechanisms, (2) reducing the need for expensive and dangerous manual auxiliary inspection tasks such as scaffold construction and insulation removal, and (3) reporting significantly higher amounts of analytical data to allow improved decision making by corrosion engineers.
This Small Business Innovation Research (SBIR) Phase I project will enable the development of a new. highly-automated, robotic pipe inspection tool. Current inspection data is both difficult and manually-intensive to obtain. A novel pipe crawling robot has been created that enables automated inspection scans of pipes for a niche use case. Improvements in both onboard sensors and spatial positioning may enable widespread commercial adoption. The proposed research will improve the onboard sensor capabilities of the robot for improved corrosion detection uses and create an artificial intelligence-driven positioning system to improve locomotion, obstacle avoidance, and data integrity. Objective 1 requires both mechanical and electrical research, ranging from physical design challenges (including adhering to strict clearance, size, and weight requirements) to data processing experiments to regulatory research. Objective 2 encompasses research in autonomous movement, obstacle avoidance, and three-dimensional geometry reconstruction. The resulting robot may provide the industry with a safer and cheaper method of inspecting critical piping infrastructure, thus preventing potentially catastrophic safety and financial consequences and environmentally-detrimental leaks.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASANTE BIO LLC
SBIR Phase I: Additive Manufacturing for Soft Tissue Repair by Three-Dimensional Microfiber Fabrication (3DMF)
Contact
5923 POWHATAN AVE
Norfolk, VA 23508--1012
NSF Award
2208745 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2022 – 11/30/2022 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project isto improve the outcomes for implant procedures for soft tissue healing. More than 2 million musculoskeletal repair surgeries are performed in the U.S. each year, representing a $5 B market. Instead of conventional 3D printing that completely melts or fuses synthetic biopolymers into solid and rigid objects, this project will develop a novel 3D microfiber printing process project to rapidly and economically produce clinical-grade printed implants with better performance. This technology will offer a significant reduction in the cost of goods and a faster product development cycle. The novel implants will be available in markets wherein existing products are prohibitively expensive, including ambulatory surgical centers, wherein most of these surgical procedures are performed.
This Small Business Innovation Research (SBIR) Phase I project will progress the design and engineering for a novel 3D microfiber printer that can assemble clinically relevant synthetic biopolymer filaments into fibrous, flexible, high void/porosity implants to promote soft tissue healing. This approach offers improvements in quality, cost, speed, and manufacturability. This project will explore the material strength, cytocompatibility, and biocompatibility using industry-standard testing. Expected technical results include quantitative measures for a controlled fibrous 3D printing method compatible with diverse synthetic biopolymers and across clinical indications. This project will optimize the hardware engineering, polymer, and print configuration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASTEK DIAGNOSTICS LLC
SBIR Phase I: Rapid detection of blood-borne bacteria and determination of antibiotic resistance
Contact
1450 S ROLLING RD
Baltimore, MD 21227--3863
NSF Award
2136428 – SBIR Phase I
Award amount to date
$255,975
Start / end date
12/15/2021 – 08/31/2022 (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 speed up the diagnosis of bacteremia, the root cause of bacterial sepsis, a life-threatening condition wherein the body’s response to an infection injures its tissues and organs. Each hour of delay in administering an effective antibiotic is associated with an estimated 7.6% increase in mortality. This project can impact the treatment and currently expensive care of 1.7 million US patients (49 million worldwide) annually. Poorly suited antibiotics contribute to roughly 270,000 sepsis deaths each year in the United States. This project will advance a rapid (1 hour) identification of antibiotic susceptibility to enable switching from broad-spectrum antibiotic treatment to targeting the specific organism causing sepsis.
This Small Business Innovation Research Phase-I project explores the feasibility of a fluorescence system to detect bacterial metabolic activity and determine antibiotic susceptibility in an hour, with the goal of achieving high sensitivity and specificity while lowering false positive or negative rates common in early results This project will advance the technology in three critical areas: (1) designing a disposable test cartridge that integrates the separation of bacteria from whole blood and introduction of fluorescent dye; (2) limiting background fluorescence to increase result accuracy; and (3) developing software that provides users with easily interpreted results and reliable process control.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will improve 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. -
Access Sensor Technologies
STTR Phase I: Advanced Microfluidic Devices for Point-of-Care COVID-19 Serological Testing
Contact
320 E VINE DR STE 221
Fort Collins, CO 80524--2325
NSF Award
2032222 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/15/2020 – 08/31/2022 (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 Technology Transfer (STTR) Phase I project may reach millions of people and provide a key tool in safeguarding the public health through the COVID-19 pandemic. Sensitive, selective and quantitative detection usually requires complex laboratory-based methods and instrumentation to achieve consistent results; however, this project advances technologies to simplify the process. Antibody testing provides information regarding previous infections; a simple tool to detect presence at low concentrations enables better testing to manage social distancing needs. The proposed technology aims to make blood testing for SARS-Cov-2 simple and quantitative for two types of antibodies. The device will be developed to take patient samples directly with no complicated sample prep. Unique reagents will be created for selective detection of the SARS-CoV-2 antibodies.
This Small Business Technology Transfer (STTR) Phase I project aims to develop the next generation of low-cost point of care immunoassay technology with direct application to infectious disease detection. The technology proposed here combines a new approach to controlling capillary flow driven systems applied to the steps of a traditional ELISA in a disposable device. The device developed in this project will detect SARSCoV-2 specific antibodies in patient samples, and will be able to provide information about the phase of the immune response of a patient. Additionally, adaption of ELISA-like enzymatic amplification into a point-of-care device will provide greater sensitivity and selectivity than traditional lateral flow assays, increasing assay sensitivity and improving detection of early infections. The immunoassays will be evaluated with deidentified patient samples and compared to state of the art laboratory-based detection methods.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Additive Manufacturing Innovations LLC
STTR Phase I: A Next-Generation Computationally Efficient Software for Simulating Additive Manufacturing Processes of Metals
Contact
65 MAIN ST STE 3008
Potsdam, NY 13676--0000
NSF Award
2112175 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
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 I project is to advance simulation software with high computational speed and efficiency for small-scale manufacturing. The proposed technology will perform simulations faster (from days to hours) using a fraction of current resources (from clusters to desktop), while still capturing the underlying physics accurately. Such a powerful tool will serve as a platform that facilitates more innovations in the field of additive manufacturing, bringing paradigm changes in part design and material development. This will bring efficiency improvements of 50-100x to many industrial sectors.
This STTR Phase I project addresses low computational efficiency of existing manufacturing process simulation models due to the finite element analysis (FEA) framework on which the models rely. The proposed innovation consists of three novel concepts: a new FEA framework called additive FEA (AFEA) framework, and two methods called Topologically Conformal Regenerative Discretization (TCRD) and Hybrid Modeling (HM). The proposed project will advance these techniques for computational simulation of AM processes for metals, engineering them for translation at industrial 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. -
Advaita Corporation
SBIR Phase I: A knowledge base and drug repurposing platform for COVID-19
Contact
3250 PLYMOUTH RD STE 303
Ann Arbor, MI 48105--2552
NSF Award
2029572 – STTR Phase I
Award amount to date
$255,993
Start / end date
08/01/2020 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to create a software platform to facilitate the identification of existing drugs that can be re-purposed for other diseases, such as COVID-19. First, identifying FDA-approved drugs that could help COVID-19 patients is expected to save lives. Furthermore, this can prevent the economic consequences of extended or repeated mass quarantine episodes. Finally, the availability of a drug discovery platform for flu-like viruses that includes data from SARS-CoV-2 and other related viruses will add to the national cyberinfrastructure and will allow a better response at the next occurrence of a novel virus.
The proposed project will develop a prototype platform to include: i) state-of-the-art data analysis methods, ii) a comprehensive knowledge base, and iii) an approach complementary to most other avenues currently pursued in the fight against COVID-19. The approach will focus on leveraging transcriptomics and other omics data focusing on the host’s immune response. This system will enable efficient research into issues such as the acute reaction of the immune systems, enabling approaches to mitigate and/or avoid a cytokine storm. This provides important information complementary to development of antiviral medications or vaccines, important for a future pandemic regardless of the virus strain.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AdvanceH2O Corp.
SBIR Phase I: Real-time Predictions During Water Treatment: An Intelligent and Proactive Pathway to Preventing Environmental/Health Hazards and Reducing Operational Costs
Contact
160 RIVERSIDE BLVD #22E
New York, NY 10069--0701
NSF Award
2126156 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I Project is to develop next-generation monitoring & data informatics for wastewater treatment plants (WWTPs). Industry standards to test WWTP performance typically measure the chemistry of the incoming wastewater (influent) and finished output (effluent), without insight into the intervening stages. This lack of data can result in significant environmental and human health hazards for end-users, as well as regulatory fines for WWTPs. This project advances advanced microbial analytics specifically for water treatment to proactively predict and prevent negative impacts at reduced energy, chemical, and financial cost. This project has global application.
This SBIR Phase I Project will combine: 1) Advanced microbial analytics tailor-made for water treatment, including global analysis of DNA, RNA, and profiles from the system microbiomes; and 2) Artificial Intelligence (AI)/Machine Learning (ML). This project identifies real-time WWTP performance predictions based on advanced microbial analytics (key drivers during treatment) to inform process control measures to optimize plant operations. For advanced microbial analytics, the objective is to prove reliable characterizations of microbial ecosystems in WWTP reactors, and to help maintain consistency and stability of the ecosystems over time. This project will propose and optimize a sampling, analysis, and reporting plan for infusion at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
American Nanotechnologies Inc.
SBIR Phase I: Platform for Printable Chemical Sensors
Contact
1517 GREYTOWN WAY APT 406
Knoxville, TN 37932--3437
NSF Award
2111945 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/15/2021 – 11/30/2022 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research Phase I project is to develop a platform for chemical sensors based on thin films of functionalized carbon nanotubes (CNT). Functionalized CNT thin films have demonstrated remarkable performance as chemical sensors in applications as varied as diagnostics, food safety, industrial process monitoring, environmental monitoring, national security, and more. The unique combination of small form-factor and impressive performance give CNT sensors the potential to bring chemical sensing to a myriad of use cases, with a combined market of over $13.2 billion projected by 2027, some which are not addressable with current sensing technologies. High-performance alternatives require bulky and expensive lab-based equipment that cannot be adopted by most users. Those chemical sensing solutions that do have suitable form factors lack the performance of CNTs. Moreover, CNT sensors also offer the benefit of being printable, flexible, and operating at room temperature—all of which contribute to a sensor technology platform with the ability to drastically expand the serviceable chemical sensing market. This work will focus on developing solutions to two key technical challenges.
The intellectual merit of this project will focus on demonstrating the feasibility of using high-purity semiconducting CNTs as the basis material for a thin-film sensor platform. Despite the impressive performance and small footprint of CNT sensors, commercialization of these thin films has been slow to non-existent due to two major challenges: First, due to drift – the tendency of CNT thin-films to degrade over time – sensors fail after 12–24 hours. Given that high-performance CNT sensors require expensive semiconducting CNT materials, such rapid failure is not economically viable. The second major technical pain point is that when transitioned from the lab to real-world applications, thin-film sensors are likely to react with interferents (e.g. humidity, low-molecular-weight compounds, temperature, etc.), resulting in false readings. This proposed work will seek to develop solutions to both technical 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. -
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 (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 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
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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. -
BARLEY & BRITCHES INC.
SBIR Phase I: Sustainable textile manufacturing through protein engineering
Contact
530 7TH AVE # M1
New York, NY 10018--4878
NSF Award
2053091 – SBIR Phase I
Award amount to date
$255,003
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will demonstrate the promise of transforming proteins found in agricultural waste into high-performance, cost-effective and environmentally friendly cotton, silk and polyester-like fibers. Textile production negatively impacts the environment and wastewater. Structural proteins found in agricultural waste are a substitute to natural silk, cotton, and theoretically polyester. The proposed project will advance a new, tough, cost-effective, environmentally friendly, protein-based textile fiber. The proposed textile will be both recyclable and biodegradable. Protein-based fibers will transform the $981 B global textile industry and enable new use of billions of pounds of agricultural waste.
The proposed project will advance a technology to maintain protein primary structure (backbone chemistry) for synthetic textile development. The challenge is to simultaneously restore the protein secondary and tertiary structure responsible for the excellent balance of mechanical and aesthetic properties inherent in natural plant and animal sourced fibers. The proposed process integrates protein molecular biology with novel, ecologically sound fiber formation engineering. Advanced manufacturing will be used to recreate fibers in a closed-loop process recycling chemicals and water without harmful byproducts.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BATTERY STREAK, INC.
STTR Phase I: Nanoparticulate metal oxide electrodes for fast charging lithium ion batteries
Contact
3537 OLD CONEJO RD STE 111
Thousand Oaks, CA 91360--2314
NSF Award
2035681 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this project is to develop and commercialize a fast charging battery which offers better safety with long cycle life compared to today’s lithium (Li)-ion batteries. In traditional batteries, fast charging can cause the battery to become dangerously hot (more than 60°C/140°F) and reduce the life of the battery to one or two charges. The proposed batteries utilize novel electrode materials that can be charged rapidly while generating no/little heat. Safe, fast-charging batteries have strong economic benefits for a variety of applications. Generally speaking, for mobile applications (cars, scooters, etc.), fast-charging batteries allows electrification of these devices by removing the main obstacle to acceptance - long charge times. For automated robots, power tools, and small electric vehicles, using the new generation batteries is expected to reduce the cost of ownership by increasing the battery life by at least a factor of 3.
This STTR Phase I project seeks to develop ultrafast charging batteries using mesoporous electrode materials. The materials are made into a sponge-like electrodes with the pores many times smaller than a human hair. These sponge-like electrodes allow very close contact between the energy storage material and energy transport liquid, the electrolyte, decreasing ion transport distance. The project will further develop the material into commercial fast charge batteries that allow: 1) charging in less than 10 minutes, 2) minimal heating upon fast charging, and 3) three times the cycle life compared to traditional Li-ion batteries. Additional effort will be put on process development to scale the materials production cost effectively. Detailed performance studies at the better cell level will aid in understanding the effect of mesoporosity on fast-charging and heat generation using oxide nanostructured materials. These results will aid in the future development of high rate oxide materials in practical and fast charge Li-ion batteries with improved safety characteristics and minimized heat management requirements.
This award reflects 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)
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 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. -
BETA ANALYTIC, INC.
SBIR Phase I: Development of New Time and Spatially-Resolved, Near-Infrared Photoluminescence Techniques Detecting Trapped Charge in Inorganic Sediments for Geochronology Dating
Contact
4985 SW 74TH CT
Miami, FL 33155--4471
NSF Award
2126530 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 08/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research Phase I project will develop a rapid, Pulsed Near-Infrared Photoluminescence (P-NIR-PL) and Stimulated Luminescence (SL) technique with micron spatial resolution, as a state-of-the art photoluminescence dating method for inorganic sediments, with substantially improved precision, accuracy, and turn-around time for sample processing. Picosecond-NIR-PL is a next-generation analytical platform for inorganic sediments. The team seeks to capture geochronological data from ~1 to 200,000 years prior. The approach addresses challenges with sample processing through the rapid detection of overlapping PL signals that will be deconvoluted and correlated to age. If successful, this project will provide new capabilities to geologists and archaeologists working on new geochronological methods for dating volcanic soils, charred materials, and sand/rock materials from future extraterrestrial sites. A sizable niche market and strong commercialization opportunity exists if optical dating measurements can be performed rapidly and non-destructively, repeatedly with differentiation on the sub single-grain level, and reliably with minimal sample pre-treatment.
The intellectual merit of this project focuses on instrument development to address the immediate demand for an accurate tool for differentiation of quartz and feldspar detection in sediments using an advanced spatial and time-resolved microscopy method with an attached dosing/dating capability for geochronological dating. Separation of PL and SL decays that are previously unexplained will establish a novel geochronological method achieved by expanding the detection into the near-infrared. A picosecond pulsed laser source with picosecond-to-second resolution in kinetic decay will be combined with high spatial resolution to cover a wide range of excitation/emission profiles that uniquely shorten the time required for a single measurement, from 13 hours to 20 minutes. Specifically, the combined time-resolved and spatially-resolved components create a powerful technique to distinguish molecular and crystalline environments as well as to distinguishing emissions from similar spectra and unique elemental microstructures. The proposed activities may advance engineering and science innovation in pulsed optical/NIR dating methods with a focus on high performance, commercial instrument development for rapid sample screening. Establishment of both the state-of-the-art instrumentation and analytical testing service for optical dating will be performed by a new diversified customer segment with implementation of an online geochronological library.
This award reflects 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. -
BIKO BIOLABS, LLC
SBIR Phase I: Plastic Waste Oxidation to Soil Carbon Amendments
Contact
17 JACKSON ST
Cambridge, MA 02140--2424
NSF Award
2126765 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project will be to recycle certain plastics into soil amendments to improve both environmental degradation and agricultural health. Plastic waste is a persistent environmental pollutant partly due to the lack of comprehensive technologies to reduce the in-circulation inventory of these petrochemical products, and comparably low value of plastic-derived and recycled products. The carbon contained within mixed plastic waste represents both a significant pollutant, but also a potentially valuable alternative feedstock for domestic agriculture and regenerating degraded soils. Soil carbon is a key driver in building soil health, agricultural productivity and food security, as well as a significant reservoir for long-term carbon sequestration. This project remediates traditionally non-recyclable, low-value mixed plastic waste and transforms it into a high value compost-like material. The proposed research develops a low-cost, distributed, decentralized process suitable for small, remote, rural, marginalized and underrepresented communities to achieve sustainable, domestic solid waste management as well as build and regenerate soil health for self-sufficient local agriculture.
This SBIR Phase I project will scale and optimize a plastic oxidation process that employs a novel high efficiency intramolecular modification of Fenton oxidation. The aqueous process utilizes a low-cost, green catalyst that does not require high temperatures or organic solvents to cleave and oxidize a wide range of commercial polymers into bioavailable long-chain fatty acids suitable as a soil microbe substrate and soil organic carbon amendment. Compared to the highly variable process of natural biodegradation, this reaction ensures complete remediation before environmental application through controlled chemical oxidation. This research will aim to characterize this novel process towards a scalable technoeconomic model to guide translation at scale. Methods include near-infrared spectroscopy to track the elimination of microplastics and other toxic components common to plastic waste processing. The plastic-derived, environmentally beneficial soil amendments will be further studied in greenhouse and field trials to evaluate key agronomic indicators, such as amendment-microbe interactions, soil health, productivity and others.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOAESTHETICS CORPORATION
STTR Phase I: Novel Acellular Grafts Containing Rifampin and Minocycline for Single-Stage Reconstruction of Stage II-III Pressure Ulcers
Contact
6 DAVIS DRIVE, SUITE 828
Research Triangle Park, NC 27709--0003
NSF Award
2012920 – STTR Phase I
Award amount to date
$251,208
Start / end date
10/15/2020 – 09/30/2022 (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 wound care product to heal bed sores or pressure ulcers (PUs). Over 2.5 million Americans, usually older adults, suffer from PUs annually. PUs can be deep wounds, take many months to heal, cause significant pain; if infected, they can lead to sepsis and death. The annual U.S. cost for treatment of all PUs is estimated to be greater than $11 billion. Current treatment options involve surgical reconstruction with skin or skin substitute grafts, which can fail to heal the pressure ulcer because of infection or because the graft was not strong enough. To address these issues, the proposed project will develop a novel skin substitute that is pro-regenerative, stronger, and releases infection-fighting drugs at the surgical site to allow healing. This could benefit physicians and hospitals treating patients with stage II-III PUs (58% of all PUs); the 3-year market potential is over $150 million. The underlying technology of the proposed solution can be used to make novel grafts for treatment of numerous wound types, improving healing and patient quality of life.
This Small Business Technology Transfer (STTR) Phase I project focuses on demonstrating the feasibility of this drug-loaded, polymer-impregnated acellular biologic graft (ABG) platform technology. Currently, PUs are surgically reconstructed using skin or skin substitute grafts, like ABGs, which often fail due to infection or lack of mechanical strength. By embedding a polymer hydrogel within an ABG, it can be mechanically strengthened. Furthermore, mixing the polymer with drugs (drug+polyABG) enables a drug delivery system that provides sustained, local release of therapeutic agents such as anti-infectives over a 14-day period. This novel approach simultaneously provides an allogeneic scaffold for patient-mediated tissue regeneration and counters onset of common complications during wound healing. This biocompatible polymer impregnation of ABGs for therapeutic applications has not been performed previously. This Phase I project will demonstrate feasibility drug+polyABG by (1) characterizing drug release and bioactivity in vitro and (2) assessing efficacy in an in vivo mouse model of single-stage reconstruction of stage II-III PUs challenged with topical MRSA.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOMIMICS, LLC
SBIR Phase I: Biobased and Biodegradable Superabsorbent Polymers
Contact
170 SHUEY DR
Moraga, CA 94556--2556
NSF Award
2109705 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a new environmentally sustainable material for diapers and incontinence products. In the US, 25 million adults suffer from urinary incontinence, generating up to 1.5 million kilograms of problematic material for landfills. The proposed material will be manufactured using cheap, and renewable raw materials, improving the environmental impact of managing this condition and enabling high quality of life for its users.
This Small Business Innovation Research (SBIR) Phase I project proposes to develop a new superabsorbent polymer (SAP). In the first phase of research, this project will identify design parameters based on polymer architecture, charge density, and gel fraction for a SAP that meets specifications regarding absorbency under load (AUL), centrifuge retention capacity (CRC), and kinetics of absorption. The project will validate the safety and biodegradability in simulated composting conditions. Finally, the project will explore protocols for manufacturing at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOSAPIEN INC.
SBIR Phase I: A novel 3D printed biodegradable mesh delivering active pharmaceutical ingredients in a sustained and localized manner
Contact
325 E 5TH ST FRNT 2
New York, NY 10003--8815
NSF Award
2052049 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/01/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to establish a proof-of-concept for an oncological medical device that will be used as an adjunct treatment for pancreatic cancer (PC). PC is one of the lethal forms of cancer and is the second leading cause of cancer-related death in the US. Chemotherapy is the first-line standard treatment for cancer therapy. The medications used during chemotherapy are administered through an intravenous infusion (IV), pill, or injection. Once these medications enter the bloodstream, they destroy the cancerous cells and the healthy cells. The most common side effects for patients are nausea, vomiting, hair loss, and decreased immunity leading to a low quality of life. Our prototype aims to reduce chemotherapy side effects and the need for in-hospital chemotherapy administration, significantly reducing healthcare costs. The proposed innovative technology offers an alternative to direct surgical resection in the sensitive areas surrounding the pancreas. This treatment will extend the number of patients who can benefit from surgery and increase the overall success of surgeries primarily by preventing local relapse.
This Small Business Innovation Research Phase I project will lay the essential foundation for understanding the medical device product's physical and chemical characteristics. Pancreatic cancer (PC) is a "silent" disease because it is diagnosed at a much later stage when cancer has already metastasized. One of the significant challenges associated with PC treatment is the standard administration techniques (e.g., intravenous injection, oral administration) cannot efficiently deliver a therapeutic concentration of the drug to the tumor site because of the pancreas' anatomy. The innovative technology used in this prototype device will render it as an implantable, biodegradable, drug-eluting product allowing for spatio-temporal control and delivery of various active pharmaceutical ingredients (APIs) directly to the tumor site. Further, reductions in global toxicity and access to traditionally unresectable areas may enable higher concentrations of chemotherapeutic agents than could be tolerated by systemic administration, significantly altering the treatment landscape. This project will address the following four technical challenges related to the formulation and physical characteristics of the prototype, which will determine its release profile and the 3D printing mechanism, and its impact on the device's quality. The research and development routes that are being pursued include (1) assessment of prototype mechanical profile, starting with one API of interest (2) assessment of different polymer compositions and how they impact the flow of the printing material and resolution; (3) testing the use of fluorophores during the formulation of the prototype (4) assessment of different properties of the print material (e.g., pressure, print-head type, temperature, and viscosity) on the quality of the 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. -
BIOSENS8, INC.
STTR Phase I: Novel progesterone biosensor for monitoring fertility health
Contact
6 SUNRISE TER
Needham, MA 02492--1547
NSF Award
2126992 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 Program (STTR) Phase I project is to provide 7.7 M women in the US struggling with infertility a quantitative and affordable way to assess their ovulatory health. This progesterone biosensor is the first outcome of a platform technology that to expand at-home blood diagnostics and analysis for remote health care. This project will produce the first of a novel class of inexpensive, real-time, and point-of-care biosensors that will impact multiple fields and markets, such as human and animal healthcare, agriculture, national defense, and biomanufacturing. The initial application will further expand access to quality health care for underserved populations. The proposed project develops a device to measure progesterone at clinically meaningful low levels from blood samples for patients including women who have never been pregnant, women with ovarian disorders, pre-menopausal and post-menopausal women.
This Small Business Technology Transfer Program (STTR) Phase I project is developing an entirely novel class of biosensors for physiologically important molecules with progesterone being the first example. The technical hurdles to be addressed by the proposed work in this proposal are to first translate optical transduction technology onto low-cost paper strips. Furthermore, determine if this new class of biosensors can measure molecules, such as progesterone, from blood to criteria required for clinical use and commercialization from paper test strips. Lastly, determine the impact of clinical requirements for a low-cost and portable measurement device to read the paper lateral flow strips.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOTECH NATURALE, INC
SBIR Phase I: A simple, targeted and flexible method for transferring value-added genes from wild relatives of crop plants
Contact
640 SW SUNDANCE CT
Pullman, WA 99163--2080
NSF Award
2110676 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 agricultural production. Of the global production differences with projected yields, about 25% results from disease and insects, and the remaining 75% is due to abiotic stresses. Wild relatives of crop plants harbor tremendous number of value-added genes for various agronomic traits including biotic and abiotic stress tolerance, but their transfer using currently available methods is practically impossible as it is time-consuming, technically challenging, and risky as undesirable traits may be transferred with the target trait - rendering it unusable in the field. The proposed project will develop a novel method to transfer useful genes from wild relatives in a precise and targeted manner, without the accompanying undesirable traits. This will improve agricultural yields.
The proposed project will develop a quick, targeted, and precise method of transferring value-added genes from wild relatives into crops, without accompanying unwanted genes (linkage drag). While the crop plants can easily be crossed to their wild relatives, chromosomes of wild relatives do not pair with their crop plant counterparts. This is due to a strict chromosome pairing and recombination control that is present in all crop plants. Lack of chromosome pairing between crop and wild relative chromosomes results in the transfer of whole chromosomes/arms carrying thousands of genes of which only one or two are useful. Tremendous efforts over the last 70 years have resulted in the transfer of 540 genes from wild relatives into wheat. While each transfer effort took more than 10 years, fewer than 10 of these genes are actually present in wheat varieties, mainly because of the associated negative effects of linkage drag as almost all transfers are complete chromosomes, arms or large segments. The proposed project will develop a novel method to transfer value-added genes from wild relatives into crops in less than a year without any linkage drag.
This award reflects 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
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 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 – 07/31/2022 (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 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 (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 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
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 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. -
BLOCKALYTICS, LLC
SBIR Phase I: A Blockchain-Driven, Distributed Memory, Computational Platform for Industrial Analytics
Contact
2998 NESTLE CREEK DR
Marietta, GA 30062--4857
NSF Award
2112099 – SBIR Phase I
Award amount to date
$255,837
Start / end date
04/01/2022 – 09/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide a novel, predictive analytics technology for industrial enterprises that require low-latency analytics insights, i.e., companies that cannot afford the kind of delayed insights that are widely present in almost all Cloud-based analytics solutions. Large manufacturing and energy enterprises are comprised of multiple plants sites spread across different geographical locations. These plants contain critical processes and equipment that are monitored using sensors and Internet of Things (IoT) devices. Predictive analytics, a key component in digital transformation, targets the analysis of large volumes of industrial data to generate insights to improve the efficiency of industrial operations, optimize processes, and reduce the life cycle costs of critical equipment and machinery. The prevailing solutions in today’s market rely on using the Cloud to consolidate data, perform analytics, and extract valuable insights. This process creates significant delays for many industrial processes that require immediate insights into their critical operations. The process is also not suitable for companies that have heightened security and privacy protocols (such as nuclear plants and defense manufacturing). The company seeks to enable companies to conduct predictive analytics on geographically distributed data silos without the need to move data from its location, thus reducing decision latency.
This SBIR Phase I project proposes to develop a technology stack that leverages the blockchain to train advanced analytic algorithms and Machine Learning models across data silos in different locations without relying on the Cloud or any corporate server. Specifically, the project targets the innovative integration of the blockchain Smart Contracts with distributed memory programming frameworks like the Message Passing Interface (MPI). This integration raises several interesting research challenges one of which requires designing basic primitives similar in functionality to a Map-Reduce framework for the blockchain. The second research component revolves around the development of novel algorithmic decomposition schemes for popular Machine Learning algorithms and artificial intelligence (AI) models to facilitate their training in a decentralized manner using the blockchain. If successful, this technology may provide analytic insights faster than the Cloud. It may also significantly reduce the cost and labor associated with implementing and deploying industrial analytics. Data science teams will be provided with the agility and flexibility to modify and redeploy algorithms without having to rebuild and redesign data pipeline infrastructure to a centralized server.
This award reflects 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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of 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 (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 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. -
BOSTON MEATS, INC.
SBIR Phase I: Fiber-Assisted Perfusion for Cultured Meat Production
Contact
444 SOMERVILLE AVENUE
Cambridge, MA 02139--1929
NSF Award
2112169 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the advancement of animal-free meat alternatives. Today, plant-based meats are consumed mostly by vegans and vegetarians willing to accept higher costs or different tastes compared with meat from animals. Recently, plant-based burgers and sausages have become popular, but the situation is very different for whole-cut meats. Steaks or chicken breasts, for example, have unique textures and tastes that are not yet matched by animal-free alternatives. The proposed project will improve the texture of alternative meats and provide a path to improved nutrition, taste, and aroma.
The proposed project addresses a limitation of plant-based meats: they lack the distinct fibrous texture found in natural meats. This project advances ultrafine protein fibers with similar structure to animal muscle fibers. Project aims include ultrafine protein fiber production, development of sterile bioreactor systems to house fiber scaffolds for tissue engineering, and feasibility studies of culturing a variety of agriculturally relevant animal cells in the fiber scaffold bioreactors. The first project aim will overcome the technical hurdle of producing edible protein fibers using scalable food-safe processes. The deliverable for Aim 1 will be edible fibrous protein scaffolds with textures approximating meats. Project Aim 2 will evaluate perfusion systems to securely house scaffolds under sterile conditions conducive to cell culture. The deliverable for Aim 2 will be reusable custom tissue culture chambers. Project Aim 3 will compare a selection of animal cells based on their proliferation rates and viability when cultured in our fibrous tissue engineering scaffolds. The deliverable for Aim 3 will be animal cell-based muscle and/or fat tissues.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BOTANY AI INC.
SBIR Phase I: Development of Unique Flavor Peptide Ingredients to Create Authentic, Sustainable, and Cost-effective Plant-based Food Products
Contact
1400 LAVACA ST STE 700
Austin, TX 78701--1763
NSF Award
2136551 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 10/31/2022 (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 create new meat alternatives. This project advances a process to create animal-free products with the same authentic taste and textures as real meat. The project will develop four different chemicals for producing various meat flavor profiles, and especially in fat systems, and a novel advanced method for the first true authentic beef flavor profile for plant-based food applications. This will lower the risk and industry costs for new and diverse alternative meatless food products.
The proposed project offers a new strategy to address the limitations of existing flavor profiles currently lacking in the plant-based food market by unlocking the power of precision fermentation and peptide encapsulation. Technical challenges include characterizing the unknown “meaty” kokumi peptides properties and identifying the encapsulation parameters necessary for stable capture of both encapsulated umami (BMP) and kokumi peptides. The proposed R&D will (1) generate an advanced encapsulation protocol to capture peptides to produce unique flavor profiles not found in plant-based foods, (2) define the physical and chemical properties of the encapsulated peptides to determine their validity and stability in various food media, and (3) develop first true authentic beef flavor profile for plant-based foods. Research objectives include: (1) formulate and characterize the BMP and kokumi peptides, (2) measure the chemical stability of the encapsulated BMP and four kokumi peptides, (3) measure the encapsulated BMP and kokumi authentic meaty flavor profile in broth and French fry model 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. -
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. -
Bondwell Technologies Inc.
SBIR Phase I: A high-efficiency filter for endotoxin removal
Contact
501 GRAHAM RD
College Station, TX 77845--9662
NSF Award
2035882 – SBIR Phase I
Award amount to date
$235,506
Start / end date
12/01/2020 – 06/30/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a system to improve pharmaceutical manufacturing and sepsis treatment. A toxic substance known as endotoxin is a common contaminant in many types of therapeutics, and it is the primary cause of batch rejection in pharmaceutical manufacturing. The economic impact of pharmaceutical batch failure due to contamination is high due to loss of product and facility closure for cleaning. The endotoxin removal market within drug manufacturing was valued at $315 million in 2018 and is expected to grow due to the increase in biopharmaceutical products. Additionally, endotoxins are dangerous when they enter patients’ bloodstream and can cause various medical complications, including sepsis. The technology has the potential to remove endotoxins from patients’ bloodstream more effectively than current solutions This project will develop a universal high-efficiency endotoxin removal filter that has the potential to not only improve drug manufacturing but also provide a life-saving treatment for sepsis.
This Small Business Innovation Research (SBIR) Phase I project will develop a high-affinity, high-specificity filter for endotoxin removal by using a protein that specifically binds endotoxin and has been shown to remove 99.9% of endotoxin from protein preparations. Traditionally, the use of proteins for product separations cause problems with durability and protein density, stability, and activity. These problems are overcome with unique materials that allow 100% incorporation of active proteins via a stable fusion with substantially increased protein stability. The binding capacity of the materials for endotoxin similar to current solutions (5,000,000 EU/mL) would be considered successful, although the binding capacity is expected to greatly exceed the current standard. Current solutions are compatible with only specific types of therapeutics. A prototype filter will be evaluated for endotoxin separation and protein recovery for three protein therapeutics. An 80% recovery of each therapeutic is expected, with simultaneous removal of 5,000,000 EU/mL of endotoxin. These tests will prove the technical feasibility of the prototype filter by showing the materials have a significantly higher binding capacity for endotoxin than current methods and that they are compatible with multiple types of therapeutics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CACHE DNA LLC
SBIR Phase I: Massively scalable storage of nucleic acids using barcoded polymer packets
Contact
146 SANDY POND RD
Lincoln, MA 01773--2605
NSF Award
2136447 – SBIR Phase I
Award amount to date
$255,819
Start / end date
02/15/2022 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a technology platform for storing biological materials that will improve public health outcomes and enable the storage of the ever-expanding digital data universe. Nucleic acids are the new bits of the 21st century; they encode our health and can be repurposed as alternative storage media for digital data. Harnessing the information encoded in these biological materials requires a scalable way to store and access nucleic acids. For decades, we have relied on energy-intensive low-temperature storage and expensive robotics to maintain the integrity of nucleic acids, which are not scalable. The successful outcome of this proposal is an alternative solution to store massive amounts of nucleic acids, obviating the need for freezers and enabling new products that leverage nucleic acid materials.
The proposed project will lay the foundation for developing a low-cost scalable solution for nucleic acid materials. Current approaches are limited by the requirement of low temperature to circumvent the degradation of nucleic acids, requiring a constant supply of electricity and expensive robotics. Instead, the proposed project focuses on maintaining the integrity of nucleic acids for decades at room temperature and simultaneously enabling search and retrieval functions akin to a computer or internet search engine by leveraging the rapid diffusion of molecules in solution. This ambitious goal will be achieved by using novel synthetic polymers that are made compatible with biological materials to enable rapid encapsulation of nucleic acids while providing long-term protection without the need for low temperature. The resulting synthetic polymers discovered through the project will be tested using purified nucleic acids, including animal, bacterial, or viral genomes, to demonstrate the capabilities and breadth of materials that can be used for the proposed technology.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CAMBRIAN WORKS, INC.
SBIR Phase I: Generalized Approach to Robotic Thermal Management
Contact
12110 SUNSET HILLS RD STE 600
Reston, VA 20190--5916
NSF Award
2111639 – SBIR Phase I
Award amount to date
$255,941
Start / end date
01/01/2022 – 10/31/2022 (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 enabling the use of commercial robotic systems from terrestrial industries in the space domain. This technology will allow the space industry to adopt lower cost, commercial systems for space robotic operation, without the need for expensive customization or unique build approaches. This innovation allows the developing space economy to quickly leverage new capabilities developed terrestrially, rapidly increasing the cadence of on-orbit inspection, assembly, and operational activities. The ability to maintain a persistent and distributed presence and conduct more regular, active operations remotely in space will increase the understanding of the space environment, interactions between space and terrestrial systems (e.g. climate/weather), and will provide new understanding of vacuum and plasma interactions with materials and components in space. These activities will serve to increase the rate of commercialization of space and the build-up of the fundamental infrastructure elements of a space economy, including communications, resource management, transport, and trade or exchange of goods and services. The resulting commercial impact may accentuate and accelerate an ongoing trend in the transition from a government-dominated space domain to a true commercial space economy.
This Small Business Innovation Research (SBIR) Phase I project will study new approaches to managing thermal challenges of operating in a vacuum environment with the technical goal of achieving a wider thermal operating range for the actuators and computing elements of commercial robotic systems. Common failure modes of commercially available robots, specifically issues affecting repeatability of positional accuracy on robotic arm position and controller board component failure, will be analyzed over both hot and cold vacuum operating ranges expected in typical low Earth orbit scenarios. This experimental data, combined with thermal modeling, will be used to identify the highest value component or material property modifications and operational constraints that can be implemented to minimally impact commercial production. Achieving a wider operating range will result in commercial robotic subsystems being able to play a greater role in various orbital regimes and under varying lighting conditions without costly customization and operational impacts (such as allowing operations only in specific sunlight conditions). The results will also provide feedback to commercial robotic system developers that can be used to increase the robustness and efficiency of terrestrial robots in a broader range of terrestrial environments, providing further improvement in space as systems evolve.
This award reflects 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. -
CAPIENDA BIOTECH, LLC
SBIR Phase I: High-throughput drug discovery system
Contact
6076 CORTE DEL CEDRO
Carlsbad, CA 92011--1514
NSF Award
2127159 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 11/30/2022 (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 help chemists find drug candidates that can stick persistently to the correct target and work better in patients. By coming off the target prematurely, a drug stops working and may be cleared rapidly from the body. Current state-of-the-art technologies find weak binders and are plagued by other limitations. The system proposed herein tests large numbers of compounds at high throughput during drug discovery and lead optimization, replacing current systems with low throughput. The identified effective drugs must be selective to the intended target. Furthermore, the proposed system will inform Artificial Intelligence and Molecular Dynamics simulations for optimized algorithms predicting drug performance.
The proposed project will solve an unmet analytical need in drug discovery and lead optimization by providing kinetic results at high throughput to refine drug designs. The proposed novel instrument and assay chemistry system measures how long chemical compounds stay on target. The solution will be benchmarked using FDA-approved drugs that use an allosteric mechanism of action to engage protein kinases AKT1 and AKT2. Inhibitors will be profiled for biochemical binding kinetics, thermodynamic analysis, and kinase selectivity in kinetic assays using novel reagents and commercial instrumentation. Dissociation rates for the allosteric drugs will be compared with literature reports. Analysis at several temperatures will measure the activation energy for the kinase to release the allosteric drug. The results will be a benchmark profile of kinetics and thermodynamics for kinase-inhibitor interactions of successful approved drugs. An advanced instrument will be built and tested in endpoint mode for sample handling, signal linearity, background and dynamic range using control reagents.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CAPORUS TECHNOLOGIES, LLC
STTR Phase I: Electrode Materials and Processes for Atmospheric Pressure, Continuous Manufacturing of Multi-Layer Capacitors
Contact
14001 STONEGATE LN
Orland Park, IL 60467--7604
NSF Award
2151712 – STTR Phase I
Award amount to date
$256,000
Start / end date
04/01/2022 – 03/31/2023 (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. -
CELEFLUX LLC
STTR Phase I: Development of a Novel Minimally Invasive Reconstruction Device for the Treatment of Male Urethral Stricture Disease
Contact
463 SEVERNSIDE DR
Severna Park, MD 21146--2215
NSF Award
2014895 – SBIR Phase I
Award amount to date
$224,998
Start / end date
06/01/2020 – 08/31/2022 (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 supports the development of a medical device that enables minimally invasive graft-based reconstruction of the urethra as a long-lasting treatment for male urethral stricture, a class of conditions causing restrictions in flow. Approximately 1% of men on Medicare are treated for stricture annually, and an estimated 1 in 5 men will get a stricture in their lifetime. A urethral stricture progressively narrows the urethra - leading to urinary urgency, frequent and painful urination, and impaired intimacy. The current state of practice has many challenges: Widely available endoscopic treatment is simple and minimally invasive but rarely curative, with high recurrence rates, and repeated endoscopic intervention worsens the stricture and turns a curable condition into a chronic disease, with devastating consequences to quality of life. Graft-based urethral reconstruction has excellent long-term outcomes but limited availability – as the complex open surgery is performed by a select group of reconstructive urologists. The proposed medical device simplifies minimally invasive graft-based urethral reconstruction to empower general urologists to deliver minimally invasive curative treatment.
The proposed project focuses on demonstrating the anti-migration properties of a temporary indwelling urethral device prototype. The device is designed to deliver a graft to a urethral graft bed, and hold it in place as the graft adheres over a period of 14 days without migrating. Proof-of-concept studies of the mechanically functional prototype will be performed on the bench and in vivo, to be further advanced by integrating proprietary anti-migration features. Key milestones include the prototype's ability to meet: targeted biocompatibility/cytotoxicity benchmarks, anti-migration benchmarks using an in vitro model, and an absence of significant migration in vivo over a 14-day period.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHIBITRONICS INC.
SBIR Phase I: Computer Aided Design Toolkit for Desktop Digital Fabrication of Circuits on Paper
Contact
1652 MOUNTAIN ASH WAY
New Port Richey, FL 34655--4144
NSF Award
2110125 – SBIR Phase I
Award amount to date
$255,928
Start / end date
07/15/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase 1 project is to increase the diversity of people engaging in science, technology, engineering and math (STEM) by broadening the creative and expressive possibilities at the intersection of craft and circuit design. The project hypothesizes that by creating design and digital fabrication tools that leverage familiar paper craft practices and the intrinsic motivational value the arts, circuit design and fabrication can be made accessible to those who are novices to circuit design and fabrication. Research shows that this approach is especially successful for reaching those who otherwise may not participate in STEM, especially underrepresented minorities, girls and women. By developing software to support digital circuit design and fabrication, this project enables users to easily share and build off of digital design templates, expanding the reach of beginner-friendly starter projects and creating a community of learners who can co-create and co-teach. Further, by enabling creators to connect circuit design to consumer-friendly digital fabrication technologies like desktop craft cutters, we will bring the digital manufacturing of electronics out of traditionally technical environments and into entirely new and more mainstream audiences.
The technical innovation is the development of novel electrical design software that greatly reduces the complexity of existing electronics computer aided design tools, making the tool accessible to novice users such as educators, hobbyists and artists. This will be done through the elimination of schematic abstractions along with powerful simulation capabilities uniquely catered for expressive and artistic technological creations. By combining beginner-appropriate electronic footprints with a drawing interface for sketching traces, users will be able to represent their designs exactly as they would appear when built. By incorporating electrical rule checks along with simulation of circuit behavior, the software will allow users to iterate on their designs with confidence before they invest time in fabricating. To address these challenges, the design of the software and accompanying physical toolkit will be designed iteratively and in close partnership with K-12 educators and hobby crafters through a series of user studies to ensure that the intended audience who have never used electronic design software before can manufacture their designs easily while being able to express their diverse interests.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHLOBIS WATER, INC.
STTR Phase I: Desalination Batteries for Energy-Efficient Desalination and Selective Chloride Removal
Contact
320 S BALDWIN ST APT 307
Madison, WI 53703--3741
NSF Award
2136118 – STTR Phase I
Award amount to date
$256,000
Start / end date
12/15/2021 – 11/30/2022 (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 in comprehensively addressing issues related to water treatment, environment protection, and resource recovery through the development of a new desalination technology called a desalination battery. Steady growth in human population and rapid industrial development have led to greater demands for clean water production. At the same time, anthropogenic activities, agricultural practices, and the disposal of wastewater have led to the salinization of natural freshwater resources. The desalination battery combines the functions of desalination and energy generation to reduce the energy and costs associated with desalination, addressing challenges at the intersection of the water-energy nexus. The goal of the proposed research is to accelerate the commercialization of the desalination battery by evaluating the effects of various solution components present in real feedwater types on performance. The project will also establish mitigation plans for problematic solution components. Successful development of the desalination battery will help to safeguard access to freshwater resources and ensure an adequate water supply, which are essential to advance the health and welfare of the American public. Commercialization of the proposed technology will also create jobs for researchers and engineers making a positive economic impact.
The goal of this STTR project is to further develop a new desalination technology, a desalination battery, which is based on the patented use of bismuth (Bi) as a chloride (Cl)-storage electrode in combination with a sodium (Na)-storage electrode. The desalination battery stores and releases energy during the charging and discharging processes. These processes are coupled with the storage and release of Na+ and Cl-. As the energy consumed during charging is recovered during discharging, the net energy required for desalination is drastically reduced. Furthermore, since Na+ and Cl- are removed via ion-specific electrode reactions, it enables membrane-free desalination. While efficient removal of NaCl has been demonstrated, the effects of various other solution components present in real wastewater and seawater are still unknown. The goal of the proposed work is to accurately evaluate the effects of different salinities, pH conditions, and various inorganic and organic species present in real feedwater on the performance of the desalination battery. The project will also develop mitigation plans for any problematic solution components. Accurate technoeconomic calculations will be used to prioritize the most promising feedwater targets and to develop a tailored commercialization plan for specific 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. -
CHOSEN DIAGNOSTICS INC
SBIR Phase I: Absolute protein quantitation in in vitro diagnostics for gut inflammation
Contact
926 LEONTINE STREET
New Orleans, LA 70112--2714
NSF Award
2015077 – SBIR Phase I
Award amount to date
$224,758
Start / end date
05/15/2020 – 10/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the determination of the most accurate method of measuring protein abundance in patient samples. The answers obtained will address a fatal neonatal gut disease, necrotizing enterocolitis, that disproportionately affects African-American preterm infants and lacks disease-modifying treatments. The proposed technology will serve as a clinically-deployable diagnostic for hospitals, reference labs, and drug companies, particularly high-acuity neonatal intensive care units. The proposed project will advance the development of a diagnostic for an underserved population. In addition, the development team will include underrepresented innovators.
The proposed project will optimize the choice of reference standard and detection method for protein abundance. Absolute quantification is a prerequisite for data interpretation and validation between experiments, laboratories, and testing platforms. Current clinical practice exploits only a single type of mutation that gives rise to disease; rarely do they address a target protein with extensive polymorphic variation that is age- and race-dependent. The goal of this proposal is to develop reference clinically robust standards to enable use of a new candidate biomarker in hospital pathology settings. Research objectives include: (1) identification of optimal reference standard composition for two common methods to quantify biomolecules in clinical settings and (2) understanding usage limitations of these reference standards in the background of high sequence variation in the human population.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CIPHERMODE LABS, INC.
SBIR Phase I: Secure and Scalable Collaboration Platform for Effective Detection of Money Laundering and Fraudulent Transactions
Contact
445 S FIGUEROA ST STE 3190
Los Angeles, CA 90071--1602
NSF Award
2126901 – SBIR Phase I
Award amount to date
$256,000
Start / end date
01/15/2022 – 06/30/2022 (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 reduce financial fraud by closing the gap between current secure computation technologies and the technical requirements of modern anti-money laundering. Banks and financial institutions have a strong interest in creating a secure data exchange mechanism. In 2020 alone, the global fraud and anti-money laundering compliance costs exceeded $181 Billion. Audit and transaction monitoring accounted for 19% of this total expenditure. A single-digit percentage improvement in these two categories represents a market opportunity worth hundreds of millions of dollars. A major benefit of the proposed platform is that the complex financial dynamics of organized crime can be targeted and reduced. In addition to anti-money laundering and fraud detection, the secure computation framework generated by this proposal, i.e., a scalable and fast secure data exchange platform, can be applied to areas such as healthcare, the insurance industry, and national security.
This Small Business Innovation Research Phase I project aims to create a systematic solution to overcome the current limitations in fighting fraudulent bank transactions. The main roadblock for effective detection of fraud and money laundering is the lack of a comprehensive view of client data. Currently, each bank has limited information about the client's financial activity and cannot benefit from a holistic view of the client’s profile in other banks. Naive solutions, such as creating a central data exchange entity, have been rendered impractical due to critical data security and privacy concerns. In this project, the team proposes a new methodology to address this challenge by leveraging advanced Secure Multiparty Computation (SMPC). Unlike anonymization approaches that hide a specific part of customers’ data, secure computation protocols guarantee data confidentiality even during a joint computation. In the past, SMPC has been impractical due to enormous computational and communication costs. However, the company has made both theoretical and practical breakthroughs that make SMPC more feasible for effective detection of fraud and money laundering. Further research and development is needed to make the solution truly applicable to real-world anti-money laundering scenarios, and thereby produce a technology that can drastically improve fraud detection.
This award reflects 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 (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 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. -
CISION VISION, INC.
SBIR Phase I: A novel label-free imaging device for real-time detection of lymph nodes during laparoscopic cancer surgeries
Contact
717 ELLSWORTH PL
Palo Alto, CA 94306--0000
NSF Award
2051771 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 11/30/2022 (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 surgeons to see lymph nodes directly during cancer surgeries to (1) improve the quality-of-care for lung cancer, rectal cancer, and some gynecological cancers; and (2) save costs for hospitals by accelerating a time-consuming and potentially inaccurate step in cancer surgeries; (3) improve hospital accreditation performance, since lymph node number is a quality metric and many hospitals fail to meet the requirements stipulated by medical authorities. Decades of clinical evidence have shown evaluating lymph nodes is linked to higher survival rates for cancer patients. This project will develop a device to be seamlessly integrated into the existing surgical protocols and used as an accessory to existing laparoscopic towers and surgical robots. Any cancer hospital will be able to purchase this device, attach it to their existing towers or surgical robots, and improve their quality of care, surgery efficiency, and accreditation performance immediately at an affordable price.
The proposed project addresses a difficult and common problem in surgical oncology – finding lymph nodes in cancer surgeries. Lymph nodes are critically important in the context of cancer because they are the channels for cancers to spread. However, lymph nodes are translucent in color and surrounded by fat, also translucent, making it difficult to find them with current optical systems. This project aims to develop a label-free optical imaging device to visualize lymph nodes with high contrast in real time without any injection. The goals of this project are to (1) build an accessory device attachable to a commercially available laparoscopic tower, (2) obtain optical performance testing results from animal carcasses, and (3) obtain optical performance testing results from cadaver specimens.
This award reflects 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 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to establish an artificial intelligence (AI) system capable of providing data-driven insights for attorneys. The legal community currently lacks data analysis tools to help with civil case preparation, which can lead to suboptimal trial outcomes. The proposed technology can help lower costs through document analysis. The technology is designed to both automate and improve the decision-making process and enable attorneys to expand their case load, as well as enabling cost-effective representation.
This Small Business Innovation Research (SBIR) Phase I project will use federated learning techniques to train the technology’s algorithm across multiple decentralized databases without exchanging data samples, thus keeping information private and confidential. This approach overcomes the lack of access problem in applying AI to legal cases, without compromising data confidentiality. The proposed research will include two major objectives: 1) improve and verify the accuracy of the platform, and 2) create internal checks to ensure that the model does not propagate bias. Computational outputs will be assessed using data and records from randomly selected cases with known outcomes to demonstrate system accuracy; moreover, the model will explicitly account for potential sources of bias.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CLC GLOBAL-USA
STTR Phase I: Lightweight Concrete Interlocking Masonry Blocks
Contact
1647 S LOGAN ST
Denver, CO 80210--2603
NSF Award
2014964 – STTR Phase I
Award amount to date
$224,999
Start / end date
05/01/2020 – 07/31/2022 (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 improve job-site safety of dry-stacking installation of masonry walls without binding mortar through the use of novel Aerated Interlocking Masonry Units (AIMU). The AIMU multi-component wall system combines the advantages of wood and those of concrete and is potentially applicable for mid-rise multi-family housing, a key component of affordable housing stock in the US and worldwide. These AIMUs can be laid quickly, safely, and accurately, reducing time and labor for cost-effective construction in the US and globally. The proposed construction platform will improve durability and offer lower lifetime costs than standard wood-based wall construction.
This Small Business Technology Transfer (STTR) Phase I project will further develop a construction technology using masonry blocks via dry-stacking without binding mortar. Aerated Interlocking Masonry Units (AIMU) are made of cellular lightweight concrete (CLC) and an activated adhesion. The proposed work will conduct testing to confirm the AIMU's ability to fill incursions and block irregularities, evaluate interfacial shear resistance between the interlocking features, and evaluate the interfacial adhesion activated through pressure or moisture. These fundamental properties are critical to resolving the primary barriers for translation of dry-stack masonry construction technology. The project will also demonstrate rapid outdoor dry-stacking AIMU installation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CLIMATEAI INC
SBIR Phase I: An Artificial Intelligence-Based Global Seasonal Forecasting System
Contact
2318 WILLIAMS ST
Palo Alto, CA 94306--1420
NSF Award
2026025 – SBIR Phase I
Award amount to date
$241,820
Start / end date
09/01/2020 – 07/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to provide timely and highly localized climate forecasts, plus information such as extreme heat and frost risk, to insurance, energy, and agricultural stakeholders. Climate forecasting at sub-seasonal to seasonal (S2S) timescales is challenging, yet essential for proactive risk management of extreme natural hazards. This project will leverage artificial intelligence and cloud computing to implement a data-intensive approach for revolutionizing global climate forecasting. The project will provide efficient and accurate seasonal forecasts at relatively low computational cost in a user-friendly web environment.
This Small Business Innovation Research (SBIR) Phase I project aims to utilize advanced artificial intelligence techniques in order to develop a localized, timely, and reliable climate forecasting system that is industry-focused and crop-specific. In this project, state-of-the-art artificial intelligence techniques will be deployed to advance operational climate forecasting skill at a global scale. While conventional forecasts are trained exclusively on observational data, this project will train models on historical simulations and reanalysis, then evaluate them with observations. In this approach, the training dataset is substantially larger, consequently improving accuracy. This processing at scale is enabled with cloud resources.
This award reflects 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 – 09/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I Project will improve 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. -
COLOWRAP, LLC
SBIR Phase I: Novel, Non-Manual Solution for Mitigating Endoscope Looping in Riskier Colonoscopies
Contact
3333 DURHAM CHAPEL HILL BLVD STE A200
Durham, NC 27707--6238
NSF Award
2129569 – SBIR Phase I
Award amount to date
$255,801
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a functional prototype for a novel abdominal compression device that prevents endoscope looping during colonoscopy, a common complication that causes pain, procedure failure, and increased risk of bowel perforation. Looping is typically countered with manual application of external pressure to the abdomen by nurses, which is inconsistently effective and can lead to staff injury. This project proposes a novel compression device that provides a safe and effective alternative to manual abdominal pressure to improve colonoscopy outcomes.
This Small Business Innovation Research (SBIR) Phase I project will address the technical challenges associated with engineering a colonoscopy compression device addressing the deficiencies of existing devices in patients with low body mass index (BMI) and low abdominal tissue volume. This project will accomplish this by first characterizing the differences in pressure applied by existing colonoscopy compression devices in high versus low BMI patients using pressure mapping. The results of this study will be utilized to design an adjustable and re-usable insert system that can be used during colonoscopy to apply different amounts of focused pressure. A prototype device will be produced and tested for localized pressure within a pressure range optimize to prevent looping in a low-BMI patient.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMON SOLUTIONS LLC
SBIR Phase I: High-Resolution Image Segmentation for Natural Resource Management
Contact
1191 BRUCKNER CIR
Mountain View, CA 94040--4562
NSF Award
2112419 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2021 – 06/30/2022 (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 produce currently unavailable high-resolution vegetation maps and analyses that enable stakeholders (i.e., government agencies, academic researchers, land managers, non-governmental organizations, and private companies) to rapidly assess the health of ecosystems that are threatened by human development and environmental change. Producing this information will result in better management of natural lands and their associated services and goods, globally valued at $125 trillion, such as buffering current and future infrastructure from natural disasters (i.e., managing wetlands that dampen storm surge) and improving human health and well being outcomes (i.e., disease prevention and livelihood security, respectively). Compared to traditional ground surveying methods, this project will revolutionize the ecosystem health evaluation and management process by reducing work hours by approximately 50-90% and project costs by approximately 40%-70%.
This SBIR Phase I project will demonstrate the feasibility to expand the accessibility and scalability of machine learning image segmentation to the fields of natural resource management, environmental conservation, and ecological research. The technical innovation of this project is a replicable machine learning model for vegetation analysis and ecosystem assessment that will expedite the ability to process and classify aerial imagery into individual species layers that can be used to assess vegetation composition and dynamic changes in species populations most influenced by human activity and climate change on a global scale. While there are examples of employing machine learning image segmentation in these fields, they are specific to regions or species and are incapable of scaling across diverse ecosystems and image resolution levels. The goal of the project is to create a machine learning model that can quickly and accurately delineate vegetation types from aerial imagery across diverse sets of data. This goal will be achieved following a development strategy of model exploration, data collection/annotation, model refinement, testing and evaluation, and model deployment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMPLETIONAI LLC
SBIR Phase I: Extrusion quality inspection with machine learning
Contact
20 HIGH ST
Marblehead, MA 01945--3408
NSF Award
2025977 – SBIR Phase I
Award amount to date
$275,993
Start / end date
10/01/2020 – 06/30/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to improve product quality in products generated in continuous extrusion environments. For instance, 2-55% of raw material can be wasted in plastics extrusion. In aggregate at least $500M raw material is lost each year in the US alone, creating additional environmental concerns because this waste plastic is typically not reusable nor recyclable. Manual inspection is problematic for this process at scale. This project will apply intelligent systems to automatically detect and act upon imperfections, improving efficiency and financial performance. The system will initially be applied to plastics extrusion, and later to a wide range of industries including metals, food and pharmaceutical production.
This Small Business Innovation Research (SBIR) Phase I project will allow development of novel machine learning and artificial intelligence technologies to automatically detect output of substandard quality in continuous manufacturing environments. The research will generate real-world plastics production data from a range of sensor inputs to train AI models to classify outputs. New approaches in AI/ML will be applied to develop robust, adaptable models to infer error states in product output. Research will also cover the development of technologies to detect failed product output in changing factory conditions, such as fouling of camera lenses or unexpected movement of the hardware.
This award reflects 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 (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 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. -
CONTEXTUALIZE, LLC
SBIR Phase I: Agent-Based Identification of Constitutive Relationships from Large Manufacturing Datasets
Contact
483 E 2ND AVE
Castle Rock, CO 80108--9212
NSF Award
2111638 – SBIR Phase I
Award amount to date
$255,964
Start / end date
08/01/2021 – 07/31/2022 (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 utilization of data resources. While data is an integral part of contemporary business—used to inform strategic, technical, and financial decisions—data collection remains federated in many fields, including manufacturing, because logistical, practical, and strategic hurdles prevent centralization. Consequently, these data resources quickly become isolated. No longer FAIR (Findable, Accessible, Interoperable, Reusable), the value of data so expensive to collect is lost. The proposed technology addresses two major concerns facing effective utilization of federated data. First, it develops a unified interface to analyze and explore federated data, without sacrificing control over data access. Second, it integrates machine learning with an understanding of the physical system.
The proposed technology is a mathematically rigorous translation between neural networks and the constitutive relationships describing the underlying physics. The two approaches will leverage measurements of a process environment, including time, temperature, and pressure, as well as mechanical strength or chemical reactivity. Neural networks, which are general and easy to train, estimate system behavior through statistical correlations, which is ideal for repetitive, complex systems, such as manufacturing processes; but they require increasingly large and diverse datasets to expand the conditions under which they are reliable. In contrast, constitutive relationships, which often take years to develop, can be used to predict how a system will behave under new conditions. This system will integrate both approaches.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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
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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. -
CROSS CULTURED FOODS PBC
SBIR Phase I: Mining microbial diversity to culture new categories of cheese and other sustainable foods
Contact
3421 HOLLIS ST UNIT D
Oakland, CA 94608--4157
NSF Award
2112405 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 08/31/2022 (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 build a more sustainable food system by crafting cultured foods leveraging microbial diversity. Growing awareness of the environmental and health toll of animal products has persuaded many to seek plant-based foods, but the search is often curtailed by unappetizing and expensive products. For example, cheese is one of the best-loved foods in western cuisine, but by weight it has a carbon footprint larger than chicken or pork and contains lactose, which two-thirds of people cannot digest. To date, plant-based cheeses have failed to achieve anything similar to the rich depth of flavor associated with dairy cheeses. The proposed project will build a platform to rapidly develop novel cultured foods from sustainable ingredients.
The proposed project will systematically mine microbial biodiversity for new strains usable in creating cultured foods. A key technical hurdle to inventing new cultured foods has been a lack of tools to profile complex microbial communities and chemical mixtures. Using high-throughput methods from microbial ecology and analytical chemistry, this work seeks to rapidly evaluate microbes for their potential to create compelling flavors. This is an iterative process involving the identification, isolation, optimization and combination of microbial strains that are compatible with to process of making high-quality, plant-based cheeses. The primary goals are to craft a new category of hard, aged cheeses that captures the complexity and addictiveness of dairy cheese, while requiring far fewer natural resources.
This award reflects 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 (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 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. -
CROSSTALK LLC
STTR Phase I: Rebooting Artificial Intelligence Inference with a New Configurable Computing Fabric
Contact
2245 SW WALDEN DR
Harrisonville, MO 64701--2444
NSF Award
2036249 – STTR Phase I
Award amount to date
$256,000
Start / end date
02/15/2021 – 07/31/2022 (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 data harnessing and real-time intelligent decision making. The proposed technology is a new reconfigurable computing platform capable of performing a variety of Artificial Intelligence (AI) tasks in a distributed and parallel manner to deliver the best performance at a lower cost. The end products are AI accelerator chips that can be integrated in Accelerator Cards or as co-processors to be applied in both server and edge computing solutions to accelerate AI tasks. The general market need is particularly acute for data center and cloud computing industries where major pain points are performance bottlenecks and high costs due to custom chips or reliance on graphic processing units. The core value propositions of the proposed technology are faster compute, programmability at run-time, and easier integration with existing software to enable execution of popular machine learning frameworks.
This Small Business Innovation Research Phase (SBIR) Phase I project centers around a novel computing approach where computing and memory elements are parallel and distributed, and interconnection between computing elements is flexible. The project develops an integrated circuit chip that can be reconfigured at run-time to behave as a custom application-specific integrated circuit for each running Artificial Intelligence (AI) application to deliver the optimal performance. It will overcome the memory bottleneck that traditional computing technologies face where data needs to be continuously loaded to and from memory. The proposed technology also addresses the adaptivity challenge for evolving AI models and datasets. The proposed activities include a chip fabrication using a 28nm commercial semiconductor foundry process, extensive benchmarking of the new technology for scalability, adaptability to data size and shape, and research on a software interface to execute codes developed by existing machine learning frameworks in the new chip. The prototype chip is expected to demonstrate distributed and parallel computing capabilities along with dynamic reconfigurability. The benchmarking work is anticipated to reveal at least an order of magnitude improvement over more conventional graphics processing unit based approaches.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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. -
CURRENT SURGICAL INC.
SBIR Phase I: Smart needle for precise tumor ablation
Contact
417 SHEPHERD ST NW
Washington, DC 20011--5943
NSF Award
2055559 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/15/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project is to enable doctors to treat previously untreatable cancerous tumors through the development of a smart surgical needle. There are many clinical situations in which a patient cannot receive curative surgery because of the proximity of the tumor to critical anatomy; for example, the central bile duct in liver cancer. In these cases, patients are forced to decide between a number of non-curative treatments that have poor outcomes and significant side effects. Innovation in early-stage tumor treatments will expand treatment options to under-served communities and patient populations. Liver cancer, for example, disproportionately affects Native Americans, Hispanics, and African-American populations in the US, with as many as 30% to 66% patients never receiving any treatment. One reason is that surgical treatments require significant operating room infrastructure (for example, three-dimensional medical imaging) to provide high-quality outcomes; unfortunately these facilities are concentrated in research hospitals and access is not widespread. The technology developed here will address these tumors, and will apply to the more than 600,000 patients in the US yearly that suffer from cancers of the liver, kidney, lung, and breast.
This Small Business Innovation Research Phase I project will demonstrate feasibility of small-size sensors to transform ablation technology into a first-line treatment for all cancerous tumors. By placing imaging sensors onto the tip of a needle, the device can overcome performance limits encountered when using traditional image guidance. This increased performance, in combination with real-time image analysis, can sense temperature variation in a variety of tissues. The ability to sense temperature variation will be combined with needle tip-based energy delivery to provide an all-in-one closed loop ablation device, with the capability to treat previously untreatable tumors. This project will demonstrate the application of deep-learning techniques, combined with physics based simulations, to enable precision ablation monitoring. Subsequently the ablation monitoring will be combined with ablation control to test the feasibility of precise closed-loop ablation in ex vivo tissue with sufficient accuracy for future clinical implementation. This foundational work will then guide the development of the desired needle probe embodiment.
This award reflects 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 – 07/31/2022 (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. -
Cellulose Sciences International
STTR Phase I: Use of Hydroxycinnamic Acids and Their Oligomers as Substitutes for Synthetic Growth Promoting Supplements in Livestock Feeds
Contact
510 CHARMANY DR STE 259
Madison, WI 53719--1266
NSF Award
2015010 – STTR Phase I
Award amount to date
$225,000
Start / end date
08/01/2020 – 10/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to enhance the health of livestock without addition of synthetic antibiotic and antioxidant compounds. The proposed technologies are corn kernel fiber byproducts of ethanol production from corn. The need for such compounds has grown as livestock is now more often raised in concentrated animal feeding operations that confine animals and result in abnormal oxidative stress. The program is based on extracting these naturally occurring compounds from agricultural residues. These extracts can be used in place of antibiotics and synthetic supplements currently in livestock feeds. The process proposed will enable production at a cost competitive with synthetic supplements.
This STTR project proposes to assess the biological activity of hydroxy cinnamic acids and their oligomers (HCAs) as beneficial supplements in livestock feed. They are ester-linked to a hemicellulose known to occur in seed crop brans. The linkage is hydrolyzed during pretreatment of corn bran fiber to prepare it for conversion to ethanol and the HCAs dissolve in the pretreatment solution. As free acids they recover their character, which includes antimicrobial, anti-inflammatory and antioxidant properties. The project will provide kilogram quantities of HCAs for use in feeding trials with young swine, wherein they will be compared with naturally sourced feed supplements currently in use in Europe, as well as un-supplemented feed. Components of the extract will be identified and comprehensive biochemical analyses performed, including study of the gastrointestinal physiology and intestinal permeability. Studies will also be performed of gut microbiomes and how the processes involved are influenced by substitution of HCAs as the primary feed supplement. Successful completion of these studies will provide a basis for more comprehensive studies of the use of HCAs as supplements in the diet of other livestock.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Construkts, Inc.
SBIR Phase I: Hands-on Learning Platform for Middle School Mathematics
Contact
1114 CLOVERDALE CT
Winnabow, NC 28479--5677
NSF Award
2110698 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the integration of hands-on and computer-based learning to teach the relationship of mathematics to physical constructions. The learning experience is designed for desktop and tablet computers as well as augmented reality headsets. This project is founded on the idea that creativity can open the door to understanding the relationship between one’s imagination and skills that are taught in the classroom. Mastering the abstract concepts of middle-school math is critical. The proposed system maps creative ideas to abstract mathematical concepts, supporting the ability to transfer knowledge of mathematical concepts to real-world situation, and adaptable to the entire K-16 education space.
This Small Business Innovation Research Phase 1 project will support the research and development of a learning platform consisting of Internet-of-Things hardware devices, a construction knowledge engine and learning module applications. The project uses both declarative and procedural learning by merging the physical, virtual, and computational worlds for creative problem-solving, and spatial thinking and fine motor dexterity skills development using a building, sense-making, and synthesis learning framework. This system consists of connectable blocks that render a virtual model to be analyzed for mathematical and structural features. The project will design a prototype through the tasks of development of the pilot middle school mathematics curriculum, creation of technical designs for manufacturing, and validation for deployment at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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. -
DEEPBITS TECHNOLOGY LLC
SBIR Phase I: Enabling Robust Binary Code AI via Novel Disassembly
Contact
20871 WESTBURY RD
Riverside, CA 92508--2974
NSF Award
2112109 – SBIR Phase I
Award amount to date
$255,742
Start / end date
08/01/2021 – 07/31/2022 (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 novel binary code AI applications for cybersecurity, by providing a fast and accurate method to reverse-engineer executable code. Current solutions are slow and inaccurate, and the volume of code analyzed by cybersecurity applications is huge. Cybersecurity companies either deploy tremendous computing resources to handle huge volumes of code or only extract superficial features from code for AI models, making those solutions extremely vulnerable to adversarial attacks. The proposed solution will not only save computing resources but will allow for improved solutions by extracting complex features from executable code and applying more advanced AI models.
This Small Business Innovation Research (SBIR) Phase I project provides an innovative disassembly solution for binary code. The lack of a fast and accurate disassembler has become an obstacle to the applications of novel AI approaches in the cybersecurity industry. The proposed solution combines state-of-the-art binary analysis techniques and newly emerging deep learning techniques to build a fast and accurate disassembler. The proposed solution utilizes GPU technology to accelerate the disassembly process. The final disassembly is expected to be over 100 times faster than state-of-the-art disassemblers, while achieving the same or better accuracy.
This award reflects 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. -
DIANT PHARMA INC.
SBIR Phase I: Continuous Manufacturing for Nucleic Acid Lipid Nanoparticles to Improve the Supply Chain of Therapeutics and Vaccines (COVID-19)
Contact
1392 STORRS RD UNIT 4213
Storrs, CT 06269--4213
NSF Award
2151477 – SBIR Phase I
Award amount to date
$256,000
Start / end date
02/15/2022 – 11/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the need for advanced manufacturing technology that can produce future therapeutics and vaccines. Future clinical treatments will rely on continuous manufacturing to meet demand, both with respect to volume and drug product personalization. This project will incorporate continuous manufacturing principles and process analytical sensors and technology. These processes will enable faster responses to global health crises, such as the COVID-19 pandemic.
This Small Business Innovation Research (SBIR) Phase I project will develop a compact, end-to-end, advanced manufacturing system for nucleic acid lipid nanoparticles. This new system will follow current Good Manufacturing Practice (cGMP) and will support end-to-end manufacturing by connecting to a nucleic acid assembly system and a fill-finish system to produce injectable-ready materials. One major goal of this research is to advance the understanding of nanoparticle drug delivery to enable manufacturing injectable ready materials on demand and on-site.
This award reflects 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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project is 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. -
DISCRETE LATTICE INDUSTRIES, LLC
SBIR Phase I: Automated Assembly of Discrete Cellular Structures
Contact
31732 4TH AVE
Laguna Beach, CA 92651--6969
NSF Award
2036680 – SBIR Phase I
Award amount to date
$254,430
Start / end date
02/01/2021 – 06/30/2022 (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 architected, cellular materials at large scales. Size constraints of 3D printing can be overcome by discrete assembly of modular, mass-produced parts. This approach benefits from incremental assembly, which eliminates scale limitations and enables best-practice manufacturing for reliable, low-cost part production, and interchangeability through a consistent assembly process across part types. Further, the system can be automated. Precision and repeatability are embedded in the parts themselves. This project will match state-of-the-art performance metrics while reducing reliance on fixed tooling, offering customization for user-defined products.
This Small Business Innovation Research (SBIR) Phase I project will address issues of large-scale, digital manufacturing by introducing a new type of material based on modular, cellular units. In contrast to continuous, layer-based, additive deposition processes, this approach relies on discrete assembly. Here, global geometries are defined by local constraints, errors can be incrementally detected and corrected, heterogeneous parts can be joined, and parts can be repaired, reused, and recycled. The goals of this project are to define a material system (constituent material, unit cell geometry, and fastening solution) that can achieve high stiffness-to-weight ratios at low cost. Such properties do not currently exist in a single monolithic material; rather, they are achieved through expensive processes to shape traditional materials into complex geometries. These methods are labor-intensive and have significant capital expenditure for tooling. This project will demonstrate the ability of discrete lattice materials to match state-of-the-art while offering cost reductions through automation, reduction in factory overhead, and performance benefits unachievable with traditional methods. Analytical and numerical models will be used to project performance and cost at larger scales (greater than one hundred meters).
This award reflects 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 – 06/30/2022 (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 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 – 07/31/2022 (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 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. -
DRAKEFORD SCOTT & ASSOCIATES
SBIR Phase I: An integrated digital approach to mental health and skill development for workforce re-entry (COVID-19)
Contact
4600 E WASHINGTON ST STE 300
Durham, NC 27713--3317
NSF Award
2031542 – SBIR Phase I
Award amount to date
$255,998
Start / end date
08/01/2021 – 07/31/2022 (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 to provide integrated digital tools to support mature learners in rejoining the workforce. The proposed system leverages best practice in engaging learners virtually through several different tools, enabling them to interact both with facilitators and their peer groups; moreover, content can be delivered in a self-paced fashion. Furthermore, the system incorporates new understanding of mental health challenges in operating virtually to support re-entry to the workforce. This is particularly critical in the realignment of the workplace following the COVID-19 pandemic.
This Small Business Innovation Research (SBIR) Phase I project synthesizes a number of technologies such as self-paced digital courses, peer-to-peer virtual environments, and live coaching to provide both functional instruction and social/emotional support for return to the workforce. The proposed project will test the feasibility of both the digital tools as well as pedagogical approaches to assess feasibility of an integrated 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. -
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 – 09/30/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to expand access to artificial intelligence (AI) talent and spur innovation to solve hard problems while protecting privacy. Machine learning and AI are bringing transformational change to governments, private companies, and social sector organizations. Yet in the coming years, innovation will be hamstrung by limited access to AI talent. Open innovation, such as machine learning (ML) competitions, provides governments and firms the ability to tap into a global talent pool to solve some of their most pressing and vexing challenges. Yet there is currently an immense barrier to running these competitions: the data must be made available to participants, which can preclude running a competition if the associated data are too sensitive to release due to concerns about privacy, security, or confidentiality. With data talent in increasingly high demand, government agencies, companies, and others have demonstrated a willingness to invest in this fashion. The proposed project develops a method to maintain data privacy at scale.
This Small Business Innovation Research (SBIR) Phase I project will develop an end-to-end competition system that provides privacy guarantees for data used to build crowdsourced algorithmic solutions. Open ML challenges typically work by providing participants with training data to learn underlying patterns, then evaluating resulting predictions on unlabeled test data. For many important problems, making training data available in this way violates concerns about privacy or enables abuse. The critical gap is preserving the privacy of training data while enabling participants to build models that can learn from it. This project will bring together recent advances in three of the most promising approaches in privacy-preserving data analysis: homomorphic encryption, federated learning, and differential privacy. Each technique will be developed and tested in a dedicated challenge structure with two core properties: 1) to preserve the privacy of sensitive data; and 2) to ensure competitors are able to get feedback on submitted models during the competition to inform algorithm improvements. Each competition system will result in a set of performance measures, including benchmarked algorithm performance and data privacy guarantees, to assess system feasibility.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DYNAMAC MICROWAVE, INC.
SBIR Phase I: Environmentally Sustainable Manufacturing Technology for Fabrication of Radio Frequency (RF) Filter Products
Contact
1229 W CAPITOL DR
Addison, IL 60101--3116
NSF Award
2151757 – SBIR Phase I
Award amount to date
$254,214
Start / end date
04/15/2022 – 03/31/2023 (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 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. -
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
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 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. -
ECATE LLC
SBIR Phase I: In-pixel, real-time neural digitizer to restore connectivity in spinal cord injuries
Contact
530 S HEWITT ST UNIT 544
Los Angeles, CA 90013--0000
NSF Award
2126398 – SBIR Phase I
Award amount to date
$253,885
Start / end date
08/15/2021 – 07/31/2022 (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 quality of life for people who suffer from debilitating forms of paralysis by restoring their lost functionality. There are 5.4 million people in the United States who suffer from paralysis. Not only do these patients suffer from the physical pain that comes with their condition but also, they are afflicted by financial and psychological burdens. The prostheses that are being used today are either passive and affordable or active and unaffordable for the majority of these patients. Active prostheses represent the forefront of brain-computer interfaces development. Current protheses suffer from drawbacks such as constant patient training, the necessity for bulky skin electrodes, variability in electrode positioning, and limited efficacy when worn and operated by the patients themselves. This device first targets incomplete paralysis by functioning as a neural relay station that bridges the disconnect between the healthy neural section above and below the site of injury.
This Small Business Innovation Research (SBIR) Phase I project seeks to overcome the limitations of current brain-computer interfaces to not only restore functionality in people with paralysis, but to recreate a real-time, seamless experience for them. Most available neural probes rely on highly invasive, sharp shanks to penetrate neural tissue. These probes cause considerable inflammation, ultimately leading to device failure. Current devices detect signals extracellularly which leads to a low signal-to-noise ratio making signal extraction very challenging. This project will improve brain-computer interfaces by introducing nanoarchitecture to the sensing electrode in order to achieve intracellular sensing. This sensing dramatically increases the signal-to-noise ratio making signal extraction considerably simpler. This device is based on an active pixel complementary metal oxide semiconductor architecture which will turn neural signals into a string of ones and zeros making signal extraction considerably simpler. This process will minimize the patient-interface training time. This project will fabricate three-dimensional, nano-architected sensing electrodes with high-aspect ratio and high-density nanoneedles, mimicking the natural neural cell environment. The nanoneedles spontaneously penetrate neurons, achieve superior intracellular recording, and reduce chronic inflammation to promote device longevity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECHOWEAR LLC
SBIR Phase I: The integration of smart wearables in the telehealth management workflow
Contact
204 COIT AVE
West Warwick, RI 02893--2218
NSF Award
2136605 – SBIR Phase I
Award amount to date
$255,719
Start / end date
12/01/2021 – 11/30/2022 (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 design a care-centered digital health platform for remote symptom monitoring of Parkinson’s Disease patients. Parkinson’s is a progressive neurological disorder affecting various movement and mobility, sleep quality, emotional and behavioral health, and other factors, with symptoms manifesting individually. Approximately 10 million people around the world currently live with Parkinson’s Disease. The total economic burden of Parkinson’s is roughly $51.9 Billion in the U.S. alone. Patient-provider communication is a significant challenge. This project proposes a digital health platform offering a patient-friendly mechanism for reporting symptoms and experiences in daily-life settings to the care team.
This Small Business Innovation Research (SBIR) Phase I project will design and pilot an interoperable digital health framework with an overarching objective to address the challenges of remote symptom monitoring. Neurologists have insufficient confidence in the patient-generated self-reports (paper-based logs) as they can be prone to biases and over-/under-reporting. This research will explore integrating commonly used smart wearables (such as smartwatches and smart finger rings) into a digital health platform to offer symptom monitoring services. A key technical challenge is to make the integration of wearables interoperable within the standards of electronic health records (EHR). Another focus is to identify appropriate data reporting and presentation for clinical oversight and decision-making. The project will pilot the digital health platform on patients with Parkinson’s and clinicians to measure feasibility and performance and to evaluate its potential to 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. -
ECOSYSTEMONE LLC
SBIR Phase I: Instructor-friendly intelligent VR platform for secondary and post-secondary distance learning and STEAM education
Contact
3270 CABRILLO AVE APT 431
Santa Clara, CA 95051--2233
NSF Award
2052404 – SBIR Phase I
Award amount to date
$255,550
Start / end date
08/15/2021 – 09/30/2022 (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 use virtual reality (VR) to create immersive, highly engaging environments for collaborative remote learning. As more students take at least some of their classes online, there is a need to develop virtual learning environments that support diverse learners with different strengths, interests, and learning preferences. The project will support diverse learning environments by leveraging the rich data available from VR to detect and classify learner engagement in an immersive, collaborative learning experience. As a major scientific contribution, the new system will provide feedback on levels of learner engagement and ultimately make recommendations for personalized learning activities.
This Small Business Innovation Research (SBIR) Phase I project seeks to create a novel real-time recommendation system for maintaining learner engagement in a collaborative, immersive, VR learning environment. The research will collect behavioral data that can identify different engagement types during collaborative learning to support learners with different strengths, various interests, and learning preferences. Subsequently, the metadata will allow for the development of algorithms for automating real-time, system-generated recommendations for personalizing curriculum options. The knowledge gained will aid diversity and increase engagement in remote VR learning as well as other collaborative, digital 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. -
EDUMD, LLC
SBIR Phase I: Artificial Intelligence for Competency-Based Medical Training
Contact
1812 ASHLAND AVE STE 110
Baltimore, MD 21205--1506
NSF Award
2112208 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (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 train physicians efficiently, assure high-quality patient care, and provide the United States with a robustly competent physician workforce. Current assessment practices require attending physicians and surgeons to review tens-to-hundreds of data points, removing them from clinical activities. Integrating a machine learning model in an existing resident assessment system to predict performance can address trainees’ learning needs and identify excelling, competent, and struggling residents months earlier. This is vital to patient care: earlier identification of trainee performance can benefit patient care faster than the current human-based, semiannual process. Improved tracking and documentation of competence may be of interest to multiple stakeholders including patients, hospitals, third-party payers such as insurance companies or the Centers for Medicare and Medicaid Services, and the residency accreditation entity, the Accreditation Council for Graduate Medical Education. Improved, automated assessment models using existing trainee data help training programs facing increasing documentation burden, as well as hospitals and third-party payers interested in reducing adverse health events for the patients they serve.
This Small Business Innovation Research (SBIR) Phase I project will integrate an artificial intelligence model to support resident physician training programs in customizing training based on individual learners’ needs. Starting with plastic and reconstructive surgery and one of the four training programs in the United States engaged in time-variable training is an efficient way to create, test, and assess the model’s efficacy. The created machine learning model will be assessed for its predictive ability at different points during resident physicians’ training and compared with attending physicians’ assessments of trainees’ skills. Such models make time-variable training feasible enabling adaptive, needs-based scheduling of various educational rotations. This has the added advantages of keeping residents fully engaged in their training and returning faculty physicians to clinical care faster, improving job satisfaction and reducing risk of burnout. Ultimately, time-variable training and use of their associated machine learning models will reduce the direct and indirect costs of graduate medical education; accelerate the entry of new, fully competent physicians into the workforce; and retain valuable physician educators in the workforce.
This award reflects 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 – 06/30/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to 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
Please report errors in award information by writing to awardsearch@nsf.gov.
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
Please report errors in award information by writing to awardsearch@nsf.gov.
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. -
EMERGING FUTURES LLC
SBIR Phase I: PolyBrickâ„¢: Polymer-regolith composite landing pads build from in-situ lunar materials
Contact
934 SW TANGENT ST
Portland, OR 97201--2259
NSF Award
2048453 – SBIR Phase I
Award amount to date
$255,916
Start / end date
11/01/2021 – 10/31/2022 (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 enhance exploration and commercial development of the Moon and, eventually, solar system, by lowering the risk of damage to surface and orbital infrastructure from ejected lunar dust during rocket landings and launches. This activity is in the area of material processing/manufacturing in space, and focuses on the space infrastructure (civil works) market sector, similar to roads and airports on Earth. Creating a viable, cost-effective solution to mitigate lunar dust will lower the cost of accessing the lunar surface and accelerate the development of lunar surface infrastructure that is necessary for all aspects of sustainable commercial space development, including mining, manufacturing, construction, habitation, power generation, communications, and in particular, transportation. Facilitating lunar exploration will expand scientific knowledge of the solar system. It will also enhance commercial development that will expand economic opportunities by opening new areas of the economy in space, with inevitable spin-off benefits for life on Earth. In the long term, the capacity to create new areas for habitation on the Moon and throughout the solar system will have profound impacts on human society.
This Small Business Innovation Research (SBIR) Phase I project proposes building lunar landing pads to address the problem of surface dust ejected during rocket landings and launches, which can otherwise damage both nearby and distant infrastructure, including those structures located the other side of the Moon and in orbit. To minimize transport costs from Earth, surface infrastructure must be constructed from local materials as much as possible. Instead of using high-energy processes to harden regolith, this approach will bind it with a high-performance polymer created from lunar volatiles co-located with water-ice in polar regions. This solution reduces mass, cost, and technical risk by leveraging anticipated water-ice mining operations and utilizing discarded volatiles from their operations to produce high-quality polymers. The approach may be sustainable, producing enough material annually to replace worn-out sections of landing pads. Phase I will focus on converting raw volatiles into polymer precursors, fabricating/testing candidate composite materials, and elaborating the concept of operations, through a combination of research, modeling, and laboratory experiments. Information gathered during Phase I will narrow the range of candidate polymers for further consideration, identifying chemical synthesis pathways for more extensive development, and highlighting areas of improvement to maximize commercial success.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMPO HEALTH, INC.
SBIR Phase I: Feasibility of Automated Computer Vision Analysis of Diabetic Foot Complication Images from an At-Home Non-Intrusive Imaging Mat
Contact
415 GRAND AVE STE 201
South San Francisco, CA 94080--3635
NSF Award
2127957 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (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 reduce the prevalence of severe diabetic foot ulcers. These ulcers affect one-fourth of patients with diabetes over their lifetimes, significantly impacting mobility and life expectancy. When treatment for an ulcer is too late, the only option is often amputation; in fact, diabetic foot ulcers account for the majority of non-traumatic lower extremity amputations. Reducing the incidence of severe ulcers will improve the health and welfare of the American public as well as mitigate the economic burden of diabetes on the American healthcare system. By some estimates, treatment for diabetic foot ulcers accounts for one-third of all direct diabetic healthcare spending. Therefore, preventing these ulcers would save the US healthcare system tens of billions of dollars per year. The proposed solution will monitor foot ulcers consistently to prevent further damage.
This Small Business Innovation Research (SBIR) Phase I project will develop a computer vision system for detecting and monitoring diabetic foot ulcers with an imaging device. The current standard of care is for patients to inspect their own feet visually every day, but these inspections happen inconsistently and unreliably. If successful, this system will automatically identify patients’ feet consistently across several days and lighting conditions. It will classify late-stage wounds, allowing physicians to monitor progression or healing of ulcers. Further, it will estimate the risk of future ulcers, enabling early-stage 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. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to 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. -
ENABLE THERAPEUTICS LLC
SBIR Phase I: Antibody-Enzyme Fusion for the Treatment of Myotubular Myopathy
Contact
68 DONNA RD
Framingham, MA 01701--7910
NSF Award
2051854 – SBIR Phase I
Award amount to date
$251,034
Start / end date
05/01/2021 – 10/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/ commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a novel antibody-enzyme fusion (AEF) for the treatment of a devastating rare disease called Myotubular Myopathy (MTM) that affects about 1 in 50,000 male births in the US. The proposed AEF addresses the underlying cause of the disease by increasing activity of a protein that has been shown to do so in mice. The market for approved MTM therapeutics is likely to exceed $1 billion over the next few years once a safe and effective drug is approved. No current treatments exist for MTM, but two experimental drugs are currently being studied in clinical trials. The proposed AEF may play an important treatment role by overcoming immune reactions to other drugs and may be essential for chronic treatment later in life after other gene therapy effects have diminished.
This Small Business Innovation Research (SBIR) Phase I project aims to produce and deliver an important protein, BIN1, the exogenous delivery of which has been shown to rescue the molecular pathogenesis of the disease-causing MTM1 mutation in a mouse model. The key technical objectives of this project will demonstrate that Fab-BIN1 can be robustly produced using typical mammalian cell culture, penetrates disease-relevant cells, and restores abundance and phosphorylation levels of proteins known to be affected by disease-associated MTM1 mutations. The latter two goals will be accomplished by orthogonal methods immunofluorescence and Western blot, with a cell-penetrating antibody as an active negative control, and disease-recapitulating MTM1 knockout myoblasts as the in vitro test system. The anticipated outcome of this project will justify advancement of Fab-BIN1 to later-stage preclinical study.
This award reflects 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. -
ENGENIOUSAG, LLC
SBIR Phase I: Low-cost in-planta nitrate sensor
Contact
1111 WOI RD
Ames, IA 50011--1085
NSF Award
1914251 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop technology to address a significant pain point for farmers associated with reducing nitrogen fertilizer input costs. The technology is based on in-planta sensor technology that will allow farmers to more carefully and precisely tailor nitrogen applications to each part of each field. By monitoring nitrate accumulation within plants, farmers will receive real time readouts of which fields and which portions of fields are nutrient constrained and could produce more yield following the application of additional nitrogen fertilizer. These readouts also will identify those fields that already have sufficient nitrogen, meaning that further applications would simply reduce farmer profit and environmental sustainability. Widescale adoption and use of these sensors will not only improve farmer profitability, but also improve water quality and ecosystem health via reductions in agricultural losses of reactive nitrogen.
This SBIR Phase I project proposes to develop an in-planta sensor for monitoring nitrate concentrations in plants at low cost and in near real time. Existing stalk nitrogen measurement must be conducted in a laboratory setting, requiring farmers to collect samples, mail them to a testing lab, and wait from one to two weeks to receive test results. The cost of the laboratory testing is high enough that only a fraction of farmers conducts nitrogen testing. The in-planta nitrate sensor technology will allow farmers to appropriately sample their fields and provide rapid feedback, allowing farmers (or their crop advisors) to incorporate the data into real-time decisions. This project seeks to develop an in-planta sensor through the fusion of silicon-based microelectromechanical systems (MEMS) technology and novel nanomaterials. The project will overcome major technical challenges through improving materials, fabrications, packaging, and validation, including optimizing MEMS fabrication processes to minimize sensors at low cost, improving packaging robustness for sensors, and validating sensor prototypes in a greenhouse. The in-planta sensor will directly detect stalk nitrate concentrations with minimal invasion, while being robust to interference from other ions present in the plant stem or stalk.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EPIRUS, INC.
SBIR Phase I: Antiviral Electromagnetic Pulses (COVID-19)
Contact
12831 WEBER WAY
Hawthorne, CA 90250--5536
NSF Award
2035140 – SBIR Phase I
Award amount to date
$243,000
Start / end date
12/01/2021 – 11/30/2022 (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 an energetically-based device to eliminate pathogens safely. The ongoing COVID-19 pandemic has shown the importance of sanitizing and protecting against viral pathogens known and unknown. The proposed approach of using energy for disruption of viral particles has high potential for sanitization. This electromagnetic approach can penetrate walls, thereby offering a method to sanitize hard-to-access building systems, such as HVAC air ducts and air flow systems.
This SBIR Phase I project proposes that an electromagnetic pulse (EMP) device can be used as an antiviral and antibacterial mechanism. This project proposes to develop the world's first software-defined electromagnetic pulse into a wireless, “safe for humans” anti-bacterial and anti-viral device. This project will explore the use of varying electromagnetic fields to compromise the viral capsid and inactivate the virus. The project will identify the frequencies effective for pathogen inactivation and then will develop a device to deliver those frequencies.
This award reflects 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 – 06/30/2022 (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. -
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. -
EXCIPLEX, INC.
SBIR Phase I: Advanced Mycotoxin Detection with Novel Photochemical Diagnostics
Contact
203 TWIGG DR
Ann Arbor, MI 48104--2274
NSF Award
2127018 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 11/30/2022 (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 improved sustainable food production. Mycotoxins are common contaminants found in cereal grains that can track through feed production and ultimately poison livestock animals. These poisoning events manifest as waste and inefficiency within human food supply chains. Animals consuming contaminated feed grow more slowly, produce less milk/eggs, are more susceptible to disease, etc. This equates to lost profits for the famers, lost meals for the consumer, and concerns over long-term food security. This SBIR Phase I project addresses this challenge through detection of these toxins. This technique offers a potentially transformative new tool in the field of point-of-source diagnostics, while simultaneously addressing the needs of the industry. This toxin detection system will be faster, simpler, and more versatile.
The proposed project advances a new generation of mycotoxin detection technologies. This technique employs novel compounds designed to associate with a specific mycotoxin of interest to enable reliable quantitative detection. These detector compounds operate by changing the spectroscopic properties of the toxin, such that it can be detected even in complex biological mixtures like animal feed. The project investigates the extraction buffer composition and the detector compound design. The buffer and detector compound combinations will be optimized by characterizing the spectroscopic signatures under different excitation conditions. This research program will target the two key classes of mycotoxins most relevant to industry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EYSZ, INC.
SBIR Phase I: Identifying Interictal Features of Epilepsy With Oculometric Data from a Naturalistic Setting
Contact
107 SANDRINGHAM RD
Piedmont, CA 94611--3614
NSF Award
2136572 – SBIR Phase I
Award amount to date
$256,000
Start / end date
12/15/2021 – 08/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to improve the treatment and cognitive function of epilepsy patients by using eye-tracking measurements to detect seizures, neurocognitive symptoms associated with epilepsy, and side effects of anti-epilepsy drugs. Epilepsy results in an estimated $28 B in direct costs annually in the U.S. and affects the quality of life of patients and their caregivers. The proposed eye tracking technology paired with seizure detection and cognition monitoring modules will have a positive economic and societal impact. For example, some patients with epilepsy may be able to return to work sooner, and the burden on caregivers to monitor seizures and side effects may be reduced. Earlier identification of co-morbidities can enable simple interventions, such as additional support in classrooms, to improve long-term outcomes. In addition, the technology will help clinicians diagnose and refer drug-resistant patients to specialized epilepsy centers, much sooner than the current average time of 18 years. Finally, the solution will improve side effect monitoring in clinical trials for new antiepileptic drugs and help optimize dose recommendations. These advances in turn will accelerate the development of new anti-epileptic therapies.
This Small Business Innovation Research (SBIR) Phase I project aims to improve the lives of epilepsy patients by using passive observation of eye movements in a naturalistic setting to objectively and reliably identify seizures and monitor neurocognitive symptoms and drug side effects. The proposed solution will use a wearable device to collect eye movement data over time, and this data will be analyzed to quantify changes associated with impairments in cognitive functions like attention and reading speed. This data then will be used to develop a personalized therapy response profile to assist clinicians in managing epilepsy. The goal of this NSF Phase I project is to determine whether non-seizure, spontaneous eye movement data can provide insight into clinical features, including the improvement or worsening of seizures and possible antiepileptic drug side effects. This project will advance a comparison of passive eye tracking data to gold standard neuropsychiatric assessments over time and as medication adjustments are made.
This award reflects 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. -
Emagine Solutions Technology
SBIR Phase I: Improved Maternal Health with Predictive Patient Monitoring
Contact
9040 S RITA RD STE 1270
Tucson, AZ 85718--2929
NSF Award
2111902 – SBIR Phase I
Award amount to date
$275,845
Start / end date
08/01/2021 – 07/31/2022 (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 clinical outcomes associated with preeclampsia, a potentially life-threatening condition of pregnancy occurring in the second trimester through the postpartum period. It annually affects 1 in 20 births, or 150,000 women in the U.S.A., with disadvantaged women experiencing a 2-3x increase in mortality. In the US preeclampia triples the cost of care for pregnant women, costing an estimated $2+ B per year; globally it costs 70,000 lives annually. Currently there is no way of predicting the onset of this condition. This project proposes software to predict onset to improve clinical outcomes.
This Small Business Innovation Research (SBIR) Phase I project will research and develop a predictive model with 80%+ accuracy using machine learning to detect preeclampsia in the earliest stages by gathering patient-provided clinical data to inform a novel algorithm. It can be used from earliest detection through the postpartum recovery period and can provide models and alerts to both clinicians and 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. -
Eonix LLC
SBIR Phase I: High-Performance, Low-Cost Anode-Free Lithium-Ion Batteries for Electric Vehicles and Consumer Electronics
Contact
300 STATE ST APT 346
Knoxville, TN 37922--4424
NSF Award
2052168 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2021 – 06/30/2022 (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 create a new type of lithium-ion battery for electric vehicle (EV) battery packs. Passenger vehicles representing 27% of global oil consumption. The proposed material will enable a new affordable, long-range EV reducing battery costs by reducing the battery size by 65% and the cell cost by up to 40%.
This SBIR Phase I project proposes to understand the influence of formation conditions and electrolyte composition on the generation of anode-free solid electrolyte interphase (SEI) using electrochemical and thin film characterization techniques. In the absence of a robust SEI, anode-free batteries experience rapid capacity loss that stems from either “mossy” lithium growth or precipitous electrolyte decomposition. These degradation routes result in cells that typically function for less than 50 cycles at room temperature. The impact of formation temperature and current density on anode-free SEI formation during galvanostatic charge/discharge will be analyzed using Scanning Electron Microscopy (SEM) and X-ray Photoelectron Spectroscopy (XPS) as well as conventional electrochemical techniques. These techniques will also measure the impact of varying electrolyte salt/solvent compositions on anode-free SEI formation. The dependence of temperature on cycle life with the optimized SEI conditions will be evaluated through galvanostatic charge/discharge. The key objective of the project is to clarify the formation conditions and electrolyte composition that results in the generation of a smooth SEI layer featuring ideal lithium mosaic columns capable of reversibly cycling with minimal capacity fade at room temperature.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FELIX BIOTECHNOLOGY, INC.
SBIR Phase I: Leveraging machine learning to enable generalized phage therapy for pulmonary infections
Contact
329 OYSTER POINT BLVD FL 3
San Francisco, CA 94111--1233
NSF Award
2126731 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 08/31/2022 (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 new therapy for bacterial infections, especially those resistant to current antibiotics, which have generated antibiotic-resistant “super-bug” bacterial infections that cannot be treated easily. Bacteriophages (‘phages’) are viruses that only infect specific bacteria and cannot infect humans. Phages kill harmful bacteria, but they currently do not work well as general solutions that can be prescribed broadly because each phage only kills a subset of bacteria; therefore a unique phage may be required for different people with the same infection. This project develops new technology to understand how phages target bacteria. It uses machine learning to determine the parts of each phage responsible for killing specific bacteria, in order to make phages for broad use in treating infections. This innovation is a key competitive advantage, and helps both national health and defense by creating new treatments for antibiotic-resistant infections, which cost >$64 billion annually and may become the next major pandemic.
This Small Business Innovation Research (SBIR) Phase I project will develop machine learning algorithms that identify genetic determinants of host range in phages in order to engineer phage to have expanded host range. The widespread evolution of multidrug-resistant infections is a major threat to global health, and traditional antibiotics have significant adverse effects on patients and their microbiomes. Phages can solve this global health challenge, but the inability to expand and tune phage host-range to create a generalizable therapeutic remains a key barrier to commercial success. This project will leverage machine learning and proprietary high throughput phage characterization methods to generate maps of phage-host interactions to identify genes that determine phage host range, and use novel engineering techniques to validate these genetic determinants of host range. The expected outputs are twofold: 1) a machine learning model for predicting variants, genes, or genomic regions that determine phage host range and 2) an engineered phage with expanded host range. This work will further scientific understanding of phage biology and phage-host interactions, while also providing a platform to develop phages with tunable host range for therapeutic, agricultural, and environmental 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. -
FINKE, CODY
SBIR Phase I: Reducing Emissions and Cost in the Production of Conventional Cementitious Materials
Contact
557 59TH ST
Oakland, CA 94609--1527
NSF Award
2112162 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 reduce cost and environmental impact associated with Portland cement, the most common general-purpose cement. A new process for making Portland cement has not been introduced in nearly 100 years, and its production accounts for for 5.5% of global greenhouse gas emissions, with 60% from the rock and the remainder from the fuel used in the process. This project proposes a different process that can reduce emissions.
Currently cement is made via the thermal decomposition of limestone to produce lime and CO2. This project advances a technology based on selective extraction of calcium from non-carbonate rocks for conversion into cement. The process also produces amorphous silica as a byproduct. Because calcium is not associated with carbonate, the emissions associated with manufacturing process are reduced. This research will be focused on thermal decomposition of the calcium-bearing compound in the process stream to make calcium silicates as a basis for the cement.
This award reflects 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 – 08/31/2022 (Estimated)
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 (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 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. -
FLOW RAIDER, LLC
SBIR Phase I: Micro-textured surfaces for high-performance drone propellers
Contact
101 S CHERRY-GROVE AVE
Annapolis, MD 21401--3629
NSF Award
2036312 – SBIR Phase I
Award amount to date
$255,864
Start / end date
01/01/2021 – 08/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project seeks to improve the performance of drones - unmanned aerial vehicles - that are quickly being adopted for numerous commercial and civil applications. It is estimated that by 2021 the number of new drones will reach 29 million worldwide. Two of the main challenges in drone operation are the limited flight time and the noise generated by the drone propellers. Both of these represent obstacles for a more efficient and universal use of drones, and both are linked to propeller aerodynamic performance, more specifically, flow separation on propellers. This project aims to use micro-textured surfaces to create favorable aerodynamic conditions to mitigate noise, vibrations, and efficiency losses. Passive mitigation of aerodynamic inefficiencies will prolong component lifespan, reduce radiated noise, and increase energy efficiency.
This Small Business Innovation Research (SBIR) Phase I project seeks to evaluate the effect of micro-textured surfaces that were previously shown to be effective in increasing lift, reducing drag, and mitigating noise from airfoils on drone propeller blades. The improvements may increase payload capacity, extend the flight time, and reduce the noise of drones. The main goal of the proposed effort is to design propellers with a micro-textured surface that improves the efficiency up to 10% over leading industry propellers and mitigate generated noise. Thrust, torque and noise will be quantified for a combination of micro-textures and propeller designs. Additionally, field experiments will be carried out to understand the impact of the micro-texture on flight performance, noise, and maneuverability of a drone. Project will pursue an overall understanding of micro-texture/flow relationship to effectively design micro-textured surfaces for industrial 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. -
FRUGI BIOTECHNOLOGY INC.
SBIR Phase I: Modular, Paper-based, Secured Diagnostics for Managing Viral Outbreaks (COVID-19)
Contact
2233 MCKINLEY CT
Ames, IA 50010--4508
NSF Award
2112144 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 Small Business Innovation Research (SBIR) Phase I Project is a cost-effective way to manage and track viral outbreaks in animal, human, and plant populations, including tracking for situations like the COVID-19 pandemic. It overcomes the challenges of current viral screening methods, namely PPE required for collecting samples, handling of samples to centralized analytic sites, cost of tests, and reliance on limited reagents. The platform proposed in this project could be used on-site at an animal production facility or at home. The scanner can be placed at many municipal and commercial locations (e.g., drug stores) or the envelope can be conveniently mailed for assessment. The dual read modality gives timely feedback to the client, as well as the capability for anonymous aggregation of readout data - essential for real-time tracking of viral outbreak and informing resource allocation to mitigate spread. This diagnostic platform would generate impact, allowing: 1) animal producers to mitigate virus spread and reduce loss and 2) businesses, schools, and other organizations to make real-time data-driven decisions on closures and health policies.
The proposed project focuses on assessing technical feasibility of three critical elements of a diagnostic platform: (1) the ability to couple isothermal RNA amplification directly to cell-free extract using custom formulations, to simplify usability (eliminate current off-card amplification with commercial kits) and reduce cost; (2) Production of a scalable and efficient cell-free extract well-suited for amplification of reporter proteins by RNA circuits to increase the rate of protein production and reduced RNA degradation. The performance of this extract will inform the time to result as well as the cost of card, necessary metrics for translation; and (3) production of new toehold riboregulators (2 to 3) selective to virus targets relevant to the animal industry (e.g., swine flu, porcine respiratory). These will also inform the limits of detection. This project will evaluate the feasibility of such as 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. -
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 (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 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. -
Fathhome, Inc.
SBIR Phase I: An Ozone-Based Field Sterilizer for Rapid sterilization and Reuse of N95 Respirators and other PPE in Response to COVID-19
Contact
1960 MANDELA PKWY BAY 3 SPC 23A
Oakland, CA 94607--1647
NSF Award
2036370 – SBIR Phase I
Award amount to date
$255,999
Start / end date
02/15/2021 – 07/31/2022 (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 impacts of this Small Business Innovation Research (SBIR) Phase I project is to develop a new rapidly dry-sanitizing technology for disposable single-use personal protective equipment (PPE) and other articles in a manner that preserves material integrity and function to enable multiuse during pandemic and post-pandemic times. It will promote energy and water conservation, and reduce plastic waste significantly. This ozone-based sanitization technology will benefit all frontline workers regularly exposed to infectious diseases such as COVID-19. The need for rapid sterilization technology is likely to grow to mitigate social distancing configurations. Schools, daycare centers, health and fitness facilities, factories, and airports will need to implement sterilization protocols. With this technology, clothes, face shields and masks, phones, smart devices, and all manner of personal articles can be easily sanitized in less than ten minutes. The market for small industrial-scale waterless appliances with the capacity to offer on-demand sterilization may also expand rapidly. While ozone is used in a wide range of sterilization technologies, there is currently no consumer-friendly dry washing machine. Thus, this project may also support development of an eco-friendly and effective laundry solution. Together, the sanitization and safety tasks will advance this technology as a viable waterless sanitization device, with the distinct advantage of lower cost, compact size, operational ease, and accessibility.
The proposed project advances translation of a low-cost, rapidly deployable gas-based field sanitizer that does not require water, solvents, or detergents. To combat infectious viruses and odor-causing bacteria, this technology must meet aggressive benchmarks set by federal regulatory agencies for ozone emissions while achieving the highest bioburden reduction levels short of an autoclave. This project will optimize the ozone dose (ppm and time of exposure) required for viral inactivation and testing mask fit and filtration efficiency after repeated exposure to high ozone concentrations. The device will also incorporate new containment and neutralization technologies to meet environmental safety requirements. The device performance will be characterized by monitoring the exhaust for residual ozone during and after 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. -
G-SPACE, INC
SBIR Phase I: The role of gravity in advanced materials manufacturing for the era of digital transformation
Contact
1266 PARKINGTON AVE
Sunnyvale, CA 94087--1559
NSF Award
2015155 – SBIR Phase I
Award amount to date
$245,000
Start / end date
08/01/2020 – 07/31/2022 (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, design, and optimization of new materials in the absence of gravity. The current approach to in-space manufacturing is primarily trial-and-error. The proposed technology will advance a systematic approach to in-space manufacturing, enabling the development of new materials with better properties and cost-competitive associated infrastructure.
This Small Business Innovation Research (SBIR) Phase I project will advance the translation of material development in zero-G environments. Chemical formulations of known materials may be unstable under the effect of body forces, but the mechanisms through which these forces impact the phase diagram remain unknown. This project will integrate experimental, computational, and machine learning techniques to identify material formulations amenable to zero-G manufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GASKIYA DIAGNOSTICS LLC
SBIR Phase I: Development of a field diagnostic for the rapid detection of White Spot Syndrome Virus (WSSV) in shrimp aquaculture
Contact
1100 WICOMICO ST STE 323
Baltimore, MD 21202--4113
NSF Award
2015009 – SBIR Phase I
Award amount to date
$224,980
Start / end date
08/01/2020 – 07/31/2022 (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 increase aquaculture productivity by reducing disease impact. Disease costs billions in losses each year to the aquaculture industry and threatens the global food supply. The disease caused by White Spot Syndrome Virus (WSSV) can devastate a shrimp farm and costs over $1 billion in losses each year. Farmers are often unaware of a disease issue until animals show advanced signs of disease or there are mortalities. Laboratory diagnosis is expensive and results take days-to-weeks, which is often far too long for results to be actionable. Early warning of white spot disease can enable farmers to take immediate action to reduce losses, reducing costs and increasing industrial robustness. This project advances a new diagnostic to quickly, easily, and reliably detect WSSV in cultivated shrimp in a new easy-to-use, on-site test.
This SBIR Phase I project will advance translation of a novel diagnostic for WSSV in a technology incorporating engineered proteins with specific targets into a paper-based biosensor. Prior studies demonstrated proof-of-concept with a paper-based immunoassay with polymerization-based amplification for detection of protein-based biomarkers for HRP2–the primary protein biomarker of malaria–with sensitivity as low as 70pM. This project will bioengineer thermostable rcSso7d DNA-binding proteins to bind the WSSV target and incorporate them into the paper testing format. Assay sensitivity, reagent composition, and dynamic range will be explored as part of an effort to understand the biological and functionally meaningful limits of the developed assay. Tasks include a WSSV challenge study to evaluate the sampling parameters and detection limits of the prototype in laboratory cultured shrimp. The resulting prototype will rapidly and selectively bind the WSSV target and yield stable, easily interpretable, colorimetric results.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GEOMAT, LLC
SBIR Phase I: Nanoremediation of oily waste waters from spills and discharges
Contact
1225 LAUREL ST STE 219
Irmo, SC 29063--0000
NSF Award
2036258 – SBIR Phase I
Award amount to date
$275,937
Start / end date
02/01/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impacts of this Small Business Innovation Research (SBIR) Phase I project address oil pollution in Alaskan waters by reducing costs associated with oil cleanup projects. In Alaska, the challenges of remoteness and cold raise oil cleanup costs by 100 times compared with other areas. The technology is a magnetic nanoparticle, 80,000 times smaller than the width of a human hair, that can completely remove oil from water. To become competitive with current oil cleanup methods, it will undergo improvements for large scale production. The project also includes design, building, and testing a new prototype device for the technology. The technology will make spill cleanup faster and reduce environmental harm. In Alaska alone, oil spills cost $150 million to clean up annually.
This Phase I project is a cost-effective, environmentally-benign nanoparticle technology that can quantitatively remove oil from contaminated water. Alaska has been targeted as a testbed due to limitations posed by cold and geographical remoteness that raise oil cleanup costs 100-fold compared to less remote regions. The goal of the project is to develop an oil removal device that can be deployed to remote regions with low cost and effort, reducing the length and cost of a spill response. The first aim of the project will optimize the nanoparticle synthesis to minimize costs and maximize active yield at commercial scales. A laboratory-scale, prototype oil removal device will be designed, built, and validated to enable pilots with larger volumes of contaminated water. The initial application will be to dewater oil recovered from the environment within the holds of barges; this can exceed 80% water. Dewatering reduces waste volumes and transportation costs, reducing environmental exposure and subsequent environmental health impacts from oil pollution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GLOBAL COOLING TECHNOLOGY GROUP, LLC
STTR Phase I: Innovative Two-Phase Cooling with Micro Closed Loop Pulsating Heat Pipes for High Power Density Electronics
Contact
13856 S 36TH WAY
Phoenix, AZ 85044--8211
NSF Award
2124797 – STTR Phase I
Award amount to date
$256,000
Start / end date
11/15/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of improved thermal cooling solutions for mobile devices. Cooling solutions today are often unable to meet the demands of 5G/6G telecommunications with thermal heating rates up to 10 times that of 4G technologies. Even current high performance 5G mobile phones have greatly increasing thermal loads, which, in turn, increase the external touch temperature of the smart phone and often trigger the phone to slow down its speed. The proposed technology may result in improved cooling for increased performance without limitations of performance throttling. Enhancing thermal cooling capabilities of cutting edge mobile devices may help enable widespread adoption of 5G/6G telecommunications, virtual and augmented reality, artificial intelligence, self-driving cars, and big data applications.
This Small Business Technology Transfer (STTR) Phase I project develops a new passive micro-two-phase cooling based on pulsating heat pipes, which consist of a loop of microchannels in a flat plate in which oscillations of the coolant in the serpentine are generated by vapor bubbles to pump liquid and vapor to transport higher heat loads. The design harnesses complex self-induced pulsations to better perform the work of transferring larger quantities of heat by enhancing the pulsating heat pipe's fluid motion with localized obstructions to create distributed bubble nucleation points. The same obstructions will be used to improve the micro-thermal heat transfer processes. The project introduces microfluidics to pulsating heat pipes. The research objectives of the proposed project are to demonstrate substantial improvements in thermal performance compared to competing cooling technology (vapor chambers) at the same thin form factors.
This award reflects 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 (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 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. -
GODWIT KEY COMPANY
SBIR Phase I: Key 360 Species Survival Database (K3SS)
Contact
5015 CAPE MAY AVE UNIT 309
San Diego, CA 92107--2575
NSF Award
2125285 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 08/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase 1 project is to create a more collaborative and efficient way for scientists to combat species loss. The project proposes to create the a centralized database for a complete view of all of the issues affecting species survival which can be tracked in real-time. This project will allow scientists to expedite their research while offering the public more transparency about environmental data. The company aims to provide a high level of transparency about what factors are directly and indirectly affecting species survival and provide actionable steps that businesses, organizations, governments, and individuals can take to make a difference that they can see in real-time, and model well into the future. They seek to democratize conservation and bring new skills, people, and funding streams to the science and practice of conservation.
This SBIR Phase 1 project consists of the development of a comprehensive database, which exists in the cloud, that encapsulates all of the factors that affect biodiversity. The project will result in a robust data system that can host and pull environmental data from all over the world, track the populations of the world’s species, and measure conservation support and influence from the general public. The project will also allow users to query data in the cloud and use artificial intelligence (AI) capabilities to further their research. The project will track both scientific data and data about support efforts from conservation organizations and the general public. The tracking of these factors will inform decision-making bodies on what methods are most effective in preserving biodiversity. The core technical risk to be addressed through Phase I research and development is standardizing diverse qualitative and quantitative data so that they can be used together.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GOTENNA, INC.
SBIR Phase I: Scalable Mesh Routing to Augment Low-Power Wide Area Internet of Things (IoT) Networks
Contact
81 WILLOUGHBY ST FL 4
Brooklyn, NY 11201--5232
NSF Award
2136427 – SBIR Phase I
Award amount to date
$229,723
Start / end date
03/15/2022 – 11/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project seeks to enhance the understanding of wireless mesh networks and deep reinforcement learning algorithms in order to significantly expand the coverage and robustness, accelerating Internet of Things (IoT) adoption across the globe. These improvements to sensor systems seek to benefit a range of applications including public safety, smart agriculture, supply chain logistics, smart cities, wildlife monitoring, healthcare and other markets. The coverage and cost benefits are especially impactful for the U.S population in rural or economically-disadvantaged areas that lack cost effective connectivity and are unable to take advantage of the IoT benefits. Further, the project will enhance industry-academia partnership, enable the technology transition of innovations, and expand the participation of women in science, technology, enducation and mathematics (STEM).
This Small Business Innovation Research (SBIR) Phase I project seeks to enable scalable, longer-lasting, and higher-throughput Low Power Wide Area (LPWA) Internet of Things (IoT) networks by using LPWA IoT Mesh Augmentation (LIMA) devices to augment the connectivity between end-nodes and gateways in a cost-effective and easy-to-deploy manner. The mesh network of LIMA devices will adaptively multi-hop relay messages to maximize effective capacity and range. The teams seeks to augment the connectivity of LoRaWAN (a standard for Long Range Wide Area Networks) with a goal of increasing coverage range several-fold, reducing the battery drain of end-nodes, and enabling higher uplink bitrates. The core challenge for such LIMA is the development of a scalable multi-hop mesh routing protocol that, unlike existing protocols, accommodates the ultra-low bit rates that characterize LPWANs, and is generalizable across the diverse applications of LPWAN technology. The LIMA solution builds upon two synergistic innovations: (a) embedded-control routing, that uses a very small amount of bits in the data packet header in lieu of control packets, and thereby achieves scalability and energy-efficiency in ultra-low-capacity, energy-constrained networks and (b) relational deep reinforcement learning based routing that combines Reinforcement Learning and Deep Neural Networks (DeepRL) with the use of relational features to learn routing policies that adapt to a variety of link dynamics and traffic conditions. The LIMA solution does not require changes to end-nodes. The anticipated technical deliverables include mesh networking software, a simulation model, a 4-node prototype using a LoRa integrated circuit, and experimental analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project seeks to 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. -
GREENSIGHT AGRONOMICS, INC.
SBIR Phase I: WeatherHive: High Resolution Environmental Sensing Using Nanodrones
Contact
12 CHANNEL ST STE 605
Boston, MA 02210--2333
NSF Award
2036232 – SBIR Phase I
Award amount to date
$255,996
Start / end date
02/01/2021 – 08/31/2022 (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 an improved system to sense and map atmospheric conditions using nano-drones that are the size of small birds; these systems have benefited from recent innovations in miniature power electronics and flight control sensors. The proposed project leverages the safety, cost and portability advantages of these small form factor aircraft in a system of coordinated drones flying in formation to measure wind, temperature, humidity and gas concentrations. Each flight of the swarm can cover hundreds of square miles, creating a high resolution 3D map of atmospheric properties. This enables the study of wind currents and gas movement for applications including detection of urban gas leaks, smog movement, and forest fire detection. Satellite measurements can be validated and improved through aerial measurements. This research will benefit public health.
This SBIR Phase I project will advance new software to analyze and optimize nano-drones. This project will expand the understanding of miniaturized (under 100 g) drone performance and enable the development of advanced nano-drones to carry out valuable sensing missions. This project will: (1) validate an optimization framework with laboratory test data; (2) develop a novel, portable drone docking station allowing for easy launching, landing and charging of hundreds or thousands of drones by a single operator, eventually enabling fully automated use for continuous monitoring applications; and (3) develop visualization and analysis tools to facilitate data analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (Estimated)
NSF Program Director
Errata
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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
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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 (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 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. -
HC Simulation, LLC
SBIR Phase I: Creation of a virtual population of older, black patients with hypertension and comorbidities for improved treatment development
Contact
1577 BARNES RD
Canton, MS 39046--4880
NSF Award
2110147 – SBIR Phase I
Award amount to date
$236,969
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a tool that will streamline the clinical trial process, reducing time and money spent without sacrificing safety or an understanding of a treatment’s efficacy. Medical treatments do not work equally well on all patients. Finding a responsive population on which to perform a study directly impacts the likelihood of a new therapy’s success while minimizing risk to patients who would see little or no benefit. The tool will allow clinical trials to be run virtually as computer programs in software that simulates human physiology. This technology will be valuable at all stages of treatment development: suggesting new therapies, testing for adverse effect, planning clinical trials, interpreting trial results, and predicting results when a new therapy is introduced outside of the clinical trial. This project is focused initially on the development of a critical under-represented population: older black men with hypertension and associated diseases, including heart disease and diabetes. Simulations of specific populations will allow researchers and clinicians to anticipate issues, enabling more effective treatment plans.
This Small Business Innovation Research (SBIR) Phase I project will develop a virtual population of 50-70 year old hypertensive African-American men with and without common cardiovascular comorbidities including congestive heart failure and type II diabetes. The virtual patients will be instantiations of a differential-algebraic model of human physiology, reflecting interactions between factors such as hormone concentrations, electrolytes, and more. The virtual population will be generated from clinical data collected from other studies and the approach can be used for other specific populations who may be historically under-represented in trials. This model can be used to estimate responses to clinical interventions (device and pharmaceutical therapies) to inform treatment development and further trials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HEALTHTRENDS.AI LLC
SBIR Phase I: Coronavirus API (COVID-19)
Contact
7 LAWRIDGE DR
Rye Brook, NY 10573--1020
NSF Award
2042690 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/01/2021 – 06/30/2022 (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 to accelerate development of a digital infrastructure trust layer for public health data around monitoring and responding to COVID-19 public health objectives. This project will provide both trust and accessibility through the application of blockchain technology to public health data to transform it into verified, legally weighted, and tamper resistant data upon which decision makers in the public and private sector can benefit. This innovative combination of new technological solutions will allow for better products, data analytics, predictive modelling systems, and ESG (environmental, social and governance) responsiveness based on organized and trusted systems. Since public health statistics are used by private enterprise as well as the public sector and the general public, the addition of a trust layer to public health data more widely is important as fidelity in statistics is critical to effective individual and organizational action.
This project’s goal is to develop tools and practices to make authoritative, reliable data available, enabled by cryptographic techniques and accessible to a broader set of individuals and organizations. The scope of the project looks to develop aggregation, access, and reporting systems which can support new decentralized economics, such as smart contract marketplaces, while remaining interoperable and accessible to users of legacy technology. The solution requires creation of a single, trustworthy platform that combines research, development and commercial application of emerging blockchain approaches with a suite of supporting technologies and systems including: distributed data infrastructure, flexible delivery methods, intuitive interfaces, and analytics tools. This research hopes to allow for the creation of novel resources to support the trustworthiness and consequently, the fundamental usefulness of all public health data records. The expected outcomes include: improved data integrity using blockchain-backed systems, tools enabling accelerated innovation in data driven decision making, and a prototype marketplace for COVID-19 resources managed by blockchain.
This award reflects 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 – 06/30/2022 (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. -
HIGGINS ENVIRONMENTAL ASSOCIATES, INC.
SBIR Phase I: Research and Development for the A-Pod HAB Trap and Removal Process
Contact
19 ELIZABETH ST
Amesbury, MA 01913--5410
NSF Award
2025679 – SBIR Phase I
Award amount to date
$254,504
Start / end date
08/01/2020 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (Phase I) project is to reduce human and environmental health risks posed by Harmful Algae Bloom (HABs) impacts to water resources. Communities across the nation allocate substantial financial resources to address HABs in their water bodies as HABs can be extremely toxic. However, this ecological problem can be treated as an eco-mining opportunity because HABs are tiny eco-miners that scour, collect, and concentrate excess nutrients in water bodies. The proposed technology is an eco-sensitive mining technology designed to harvest, trap, and permanently remove these HABs, their toxins, and the often ore-grade concentration of nutrients they contain. This project will advance a technology to permanently and sustainably removing the HABs, their toxins and the excess nutrients they contain. As a fully scalable and rapidly deployable, cost-effective technology, it will rapidly resolve HAB impairments and related health risks.
The intellectual merit of the proposed project is to target HABs, trap them through mechanical filtration, separate them through flotation, and monitor and test the effluent water for toxins. The proposed research is focused on development of remote and automatic operation capabilities to further minimize potential contact with HABs. The process can be deployed in less than one day to surround and control small or very large areas of HABs, does not require a land-based treatment area, and does not need electricity or high capacity pumping systems to work. It can trap and remove HABs actively or passively.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HIKARI LABS, INC.
SBIR Phase I: Illuminating dark web electronic commerce
Contact
4620 HENRY ST
Pittsburgh, PA 15213--3715
NSF Award
1938323 – SBIR Phase I
Award amount to date
$225,000
Start / end date
12/01/2019 – 11/30/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to combat online trade in counterfeit and illicit goods. The project will integrate the results of a decade of academic research on anonymous online ("dark net") marketplaces and modeling of counterfeit pharmaceutical online sales with novel monitoring solutions for traditional e-commerce marketplaces. It will allow for the development and validation through pilot customer tests of an integrated platform for automated continuous data collection and analysis of the major players in the counterfeit and illicit goods online business. Through automation, the proposed technology should considerably reduce costs to brand protection managers (and law enforcement), allowing them to use their limited resources more effectively. This work should also help address some pressing economic and public health issues linked to the proliferation of counterfeits, such as counterfeit drugs.
This Small Business Innovation Research (SBIR) Phase I project will demonstrate automation of many manual online counterfeiting monitoring activities. The project will also show that intuitive visual interfaces can help customers (law enforcement agencies, brand protection managers) have immediate access to higher-level objects more useful for investigative purposes. These higher-level objects include metrics on the amount of sales conducted by a specific entity, deduplication between vendors, or inventory clustering. To do so, the project will further develop automated classification and analysis using techniques that were prototyped in the research lab, scale these techniques up to a production environment to further minimize human intervention, and combine these techniques with novel algorithms developed for slightly different application cases (traditional e-commerce marketplaces).
This award reflects 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
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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. -
HYQ RESEARCH SOLUTIONS, LLC
SBIR Phase I: Incorporating High Dielectric Constant Materials into clinical imaging: A Novel Approach for Accelerating 1.5T MRI
Contact
2151 HARVEY MITCHELL PKWY S STE 208
College Station, TX 77840--5241
NSF Award
2015016 – SBIR Phase I
Award amount to date
$249,966
Start / end date
05/15/2020 – 06/30/2022 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project will target clinical Magnetic Resonance Imaging (MRI) scanners where there is limited MRI access to a larger patient population. Enhanced spatial resolution and reduced scan time are in urgent demand for investigating a comprehensive range of biological systems from single cells to humans. Long scan times reduce the efficiency of radiology department processes and increase the overall cost to clinics and patients. In the research community, high-resolution MRI is a powerful tool for understanding metabolic activity. This project will pioneer an entirely different solution to the fundamental problem of long scan times by introducing special materials into the clinical MRI scanners most commonly used to address the challenge of signal strength versus patient safety, which ultimately limits the throughput for research studies and clinical tests. The proposed materials developed under this SBIR program will have an immediate impact on animal and human health studies where neuroscientists are using MRI techniques to monitor brain activity and cognition.
The proposed SBIR Phase 1 project will advance the development of a new approach to MRI, an indispensable clinical imaging modality for radiology and one of the most powerful research instruments for life science. However, it has an inherently low signal-to-noise ratio, limiting both imaging resolution and scan speed. Development efforts will focus on incorporation of high permittivity dielectric materials into MRI scanners to increase the signal-to-noise ratio by over 40%, thereby cutting the scan time by half. The dielectric materials would be placed near the patient to increase the MRI signal through stronger electromagnetic coupling. Materials with dielectric constant values between 4,000 and 6,000 will be synthesized and incorporated into clinical 1.5 Tesla MRI scanners. Oxide materials with the optimized dielectric properties will be synthesized and characterized before fabricating the final device. The project will pursue an integrated systems approach including electromagnetic simulation, ceramic processing and testing. The magnetic field strengths will be optimized by simulating a range of dielectric materials in the MRI scanner and ultimately tested in clinical scanners with a phantom.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IAMBIC INC.
SBIR Phase I: Virtual Assessment of Foot and Gait for Smartphone-Enabled Personalized Treatment
Contact
829 9TH AVE APT 2B
New York, NY 10019--4426
NSF Award
2112198 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 08/31/2022 (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 modeling and treatment for various disorders. The initial application is to personalize footwear. This project uses a smartphone camera to determine the size and orientation of feet and gait. It combines computer vision, image processing, machine learning, material science, and anatomy and physiology to develop a virtual solution to fit shoes. This enables a new low-cost method for evaluating physiological conditions with potentially straightforward consumer solutions.
This project supports a novel data-analytics solution that provides accurate footwear recommendations based on static foot shape and dynamic foot function, using only a smartphone to capture images. This project will develop the algorithms using machine learning and statistical modeling for a user to evaluate the potential utility of a comfortable shoe. This project will evaluate the prediction accuracy of a prototype 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. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase I project supports law enforcement in solving crimes committed with firearms. In 2020, gun crime in the U.S. reached an all-time high with over 300,000 crimes committed and 40,000 people killed by a firearm, resulting in a $280 billion impact on the economy. There are approximately 800,000 law enforcement officers and 18,000 agencies in the U.S., and many of them have little to no access to forensics technology due to its cost and complexity. The total addressable market for this technology is estimated at $360 million per year in the U.S. This project advances hardware and software for next-generation portable ballistic devices, matching a spent shell casing to the weapon that fired it.
The intellectual merit of this project is to advance the collection and analysis of forensic ballistics data. This project will develop: (1) a ruggedized scanner to allow detailed, microscopic, three-dimensional imagery to be captured in the field; (2) an optical system that addresses the inherent difficulties and scattering challenges of scanning metals; (3) a user interface to upload images and receive leads, while preserving chain of custody and security; and (4) a cloud-based analytical system capable of comparing digitized/pixelated imagery to provide a “match” back to investigators.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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 (Estimated)
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)
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 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. -
IMMERGO LLC
SBIR Phase I: An immersive virtual reality platform for remote physical therapy and monitoring
Contact
229 VAN NESS AVE
Santa Cruz, CA 95060--3535
NSF Award
2111847 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to investigate the research and development of an intelligent, immersive, virtual reality (VR) platform for remote physical therapy and patient monitoring. This innovation enhances biomechanical analysis to facilitate telerehabilitation through off-the-shelf consumer VR head-mounted displays in patient homes and clinics, effectively providing a means for in-patient success metrics and full-body exercise guidance using a centralized, remote virtual platform. Such technology may have the ability to enable greater affordability, accessibility, and accuracy of physical therapy for patients and therapists alike. Patient throughput could potentially be doubled through remote visits in virtual environments and automated physical health documentation. In addition, the platform will be designed to support therapists working in marginalized communities of "medical deserts," where patients are uninsured and care is significantly limited by hospital capacity, physical distance, doctors per population, and cost. This software-as-a-service immersive physical therapy platform may reach a projected annual revenue of $2.08M USD. With remote tools and predictive physical therapy analytics, more individuals will receive access to treatment regardless of their socio-economic and demographic background.
This Small Business Innovation Research (SBIR) Phase I project will provide an immersive virtual reality environment where therapists can meet their patient in a 3D virtual clinic and use the platform's tools to aid in patient evaluation. This technology addresses the shortcomings of widely used current telehealth platforms (most often videoconferencing) where therapists find it difficult to perform common evaluations such as movement abilities and balance coordination tests. The goal of this project is to build an updated machine learning algorithm with integration on the virtual platform to enable therapists to remotely evaluate their patients with high accuracy biomechanical metrics. The goal is to achieve remote rehabilitation of patients that is comparable to that of in-person patient rehabilitation. In addition, pilot research will be performed with healthcare organizations to assess this technology in providing patient success metrics and exercise interaction through commercial head-mounted display virtual reality systems. This technology has the potential to positively change a consumer's physical therapy experience by significantly reducing traditional clinical and insurance costs, enabling remote access for populations of low-socioeconomic backgrounds, alleviating discomfort for patients, and increasing remote recovery insights.
This award reflects 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)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project is to 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. -
INFINIFLUIDICS, INC.
SBIR Phase I: On-demand Continuous and Sterile Manufacturing of Injectable Drug Delivery Systems at Industrial Scale on a Portable Microfluidic Chip
Contact
3401 GRAYS FERRY AVE BLDG 176
Philadelphia, PA 19146--2701
NSF Award
2111954 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2021 – 06/30/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the promotion of injectable drug delivery systems (iDDS) that will lead to the acceleration of medicine from lab to clinics, reductions in production costs, and the ability for generic manufacturers to produce complex sterile injectable drugs seamlessly. The U.S. faces constant drug shortages, placing patients in danger of treatment delays. Such shortages are often due to issues in manufacturing, requiring new strategies to meet the future needs of patients and pharmaceutical industries. The solution is to develop manufacturing technologies that can generate iDDS on demand to fulfill dynamic market needs. Technologies that can develop particle-based drug delivery formulations will advance the capabilities to treat diseases such as cancer, cardiovascular disease, and other ailments. Such drug platforms have less competition and a higher market potential compared to traditional dosing methods, and with the global market for iDDS estimated to be over $300 billion, this market segment has high potential for such drug manufacturing efforts.
This Small Business Innovation Research (SBIR) Phase I project will generate a portable, scalable, reproducible, plug and play ready platform for on-demand generation of iDDS. The key objectives of this research are: 1) Develop robust design and process parameters of an individual microfluidic unit to integrate on chip with VLSDI technology, 2) Validate the compatibility of FDA approved solvents for human use with VLSDI technology to generate injectable drug delivery systems (iDDS), 3) To develop standardized processes to robustly operate the VLSDI chip with 100% reproducibility, re-usability and robustness with precise control over product attributes. By combining microfluidics with semiconductor technology on a chip platform, the proposed innovation would allow for >10,000 microfluidic units per chip, which can be used to increase production of multiple lifesaving drugs. If successful, this technology would increase economic efficiency and productivity at individual and organizational levels in pharmaceutical manufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INFRASTRUCTURE ANALYTICS COMPANY
SBIR Phase I: Infrastructure-to-Everything (I2X) Communication Technology for Autonomous and Connected Vehicle Support
Contact
3675 MARKET ST STE 200
Philadelphia, PA 19104--2897
NSF Award
2052170 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2021 – 06/30/2022 (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 enhance the robustness and security of infrastructure-to-everything (I2X) communications through the use of a hybrid wireless technology that can be embedded inside civil infrastructure. The technology could augment the sensing modality of existing autonomous and semi-autonomous vehicles by improving the overall system efficiency, security, and robustness under uncertain driving conditions. The technology could be used to mitigate adversarial manipulation and tampering of infrastructural landmarks like traffic signs and could also be used as a fallback mechanism when geo-navigation signals are unavailable. The technology will also provide a flexible integration platform for state and federal stakeholders to enforce new guidelines and checkpointing standards. The technology will be flexible enough to implement new communication protocols that can lower the barrier for other mobility-based businesses to enter the autonomous driving market. In addition to mobility applications, infrastructure owners and state/federal departments of transportation (DoTs) could use this technology for large-scale interrogation of structural health monitoring sensors.
This Small Business Innovation Research (SBIR) Phase I project will develop an embedded hybrid radio-frequency identification (RFID)-based system for infrastructure-to-everything (I2X) communications. A major challenge to implementing embedded I2X devices is the limited availability of power. It is not feasible to replace batteries when the devices are deployed in asphalt or concrete structures or underneath a bridge-deck. This problem is solved by the proposed technology using a hybrid system that combines the long lifetime of passive RFID tags with low-latency of their active counterparts. This project will: (1) characterize the radio-frequency energy required to enable I2X communications;(2) evaluate the energy available for embedded wireless devices that adhere to Federal Communications Commission regulations; (3) build commercial-ready devices that can survive the embedding and the compaction process; (4) develop basic software to support meaningful information exchange with the embedded I2X prototypes; and (5) verify prototypes in small scale field deployment studies. The end goal of the project will be to develop the I2X prototype using commodity electronics while still achieving an at-scale price point that is cheaper than the cost of the construction material used in road surfaces and in other civil infrastructure.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INFUSENSE LLC
SBIR Phase I: Point-of-Care Electrochemical Platform for the Rapid Detection of Drug Toxicity
Contact
6415 RIVER TIDE DR
Nashville, TN 37205--2403
NSF Award
2124746 – SBIR Phase I
Award amount to date
$253,590
Start / end date
08/15/2021 – 07/31/2022 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that poisoning by prescription drugs affects over one million people annually and is the leading cause of injury-related death in the United States. Other than opioids, prescribed benzodiazepines, antipsychotics, and antidepressants are the most common causes of accidental poisoning and attempted suicide. Drug testing plays a central role in the detection and management of poisoned patients, and the ability to rapidly identify the cause and institute prompt targeted treatment has the potential to reduce morbidity and save lives. Currently, screening of blood and other biological fluids for toxic drug levels requires specimen processing, taking hours or days to obtain results from commercial laboratories. Immediate, accurate, low-cost testing for urgent care in the ambulance or emergency room will improve outcomes for the rapid diagnosis and care of patients after accidental poisoning and attempted suicide. The biosensor device and drug testing methods described in this project can be performed for low cost at the first point of contact and are scalable for rapid commercial and clinical adoption into a global drug screening market valued at $1.1 billion.
This Small Business Innovation Research (SBIR) Phase I project will test a new solid-state biosensor device reporting real-time and accurate quantification of toxic drug levels in the blood using inexpensive, disposable test strips similar to a diabetes glucometer or from saliva like a sublingual electronic thermometer. Current drug toxicity assays use specialized laboratory methods that require blood sample processing and can take hours to days to obtain results. Biosensors are an interface between biology and electronics that convert specific chemical information into measurable electronic signals (e.g. a glucometer). The three specific outcomes of this project will be; 1) a handheld medical device providing accurate and real-time measurement of blood levels of all classes of antipsychotic, neuroleptic, and anticonvulsant drugs in clinical use, and other common drugs of abuse, from a drop of blood or saliva, 2) validation of the accuracy of the biosensor for target drugs relative to current laboratory analysis methods (e.g., mass spectroscopy), and 3) demonstration that the biosensor can distinguish between classes of medications, drugs of abuse, and potential clinical interferents in blood using specific analytical methods and modifiable biosensor coatings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INHERENT TARGETING, LLC
STTR Phase I: Near Infrared Nerve-Specific Fluorophores for Fluorescence-Guided Surgery
Contact
2416 SW 5TH AVE STE 200
Portland, OR 97201--4910
NSF Award
2036434 – STTR Phase I
Award amount to date
$244,277
Start / end date
08/01/2021 – 07/31/2022 (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 technology that will reduce intraoperative nerve damage using fluorescence imaging to enable surgeons to see the unseen. Intraoperative nerve injury is a major complication of surgery, affecting all specialties and often causing irreparable damage. Nerve damage occurs in ~17% of all surgeries and intraoperative nerve injuries affect 50 million patients annually worldwide, incurring undue pain, loss of function, and high costs to the healthcare system. Currently, no clinically approved technology exists to enhance intraoperative nerve recognition - surgeons rely solely on anatomical knowledge and visualization. The proposed project will finalize development of first-in-kind nerve targeted substance allowing surgeons to “cut by color” – identifying and sparing nerves more effectively to reduce these complications and the associated costs, estimated at $12.5 billion annually.
The proposed project is focused on the development of near-infrared nerve-specific fluorophores for fluorescence-guided surgery (FGS) that are clinically viable for translation to human studies. Recent work has allowed modification of the base structures of the fluorophores to significantly improve brightness, solubility, and toxicity while maintaining high nerve specificity. The immediate milestones of the work proposed herein include (1) characterization of a library of benzo[c]phenoxazine small molecule derivatives with chemically tuned water solubility and quantified nerve specificity, (2) elucidation of the biological target and mechanistic understanding of nerve-specificity for the fluorophores, (3) preliminary single-dose toxicology analysis in rodents, (4) quantified pharmacokinetics, pharmacodynamics, and biodistribution to determine the optimal imaging dose and time window, and (5) identification of a lead compound for clinical translation. Successful completion of the proposed work will enable selection of a lead candidate with a proven safety profile and bright, long-lasting (~1 hour) nerve-specific fluorescence for identification of buried nerve structures at up to 1 cm depths.
This award reflects 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 – 07/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research (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. -
INNOVISION, LLC
SBIR Phase I: Patient Digital Twin and Performance Capture System for Scoliosis Physiotherapy
Contact
6250 WOODEN SHOE LN
Dayton, OH 45459--1558
NSF Award
2136086 – SBIR Phase I
Award amount to date
$255,735
Start / end date
01/15/2022 – 09/30/2022 (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 focuses on scoliosis physiotherepy. Physiotherapy Scoliosis Specific Exercises (PSSEs) have been proved effective in treating scoliosis patients; However, PSSE effectiveness can be significantly reduced due to inappropriate planning, unclear requirements, and poor compliance. This project seeks to develop a hardware-software integrated system which employs a synthetic, immersive environment for physiotherapists and patients to conduct PSSEs effectively. The technology may save costs for patients, expand services for clinics, and improve the outcomes of scoliosis physiotherapy. The commercialization of the technology will be conducted via business to business and business to customer mechanisms.
This Small Business Innovation Research (SBIR) Phase I project focuses on the development a hardware-software integrated system which employs a patient digital twin (PDT) and a performance capture system to create a synthetic, immersive environment for physiotherapists and patients to utilize telehealth communication between physiotherapists and scoliosis patients. The technology seeks to improve the accuracy and completeness of diagnosis and assessment, optimize physiotherapy design and planning, facilitate effective patient communication and education, and help patients to perform physiotherapeutic exercises according to instructions and compliance requirements. By using PDT, the diagnosis of scoliosis and assessment of spine deformity can be performed in 3D space thus improving the completeness of assessment and the design of PSSEs. By building a light-weight performance capture system, body shape, pose, and motion can be captured in 3D space in real time. The teams seeks to represent the prescribed PSSEs in 3D games by animating the PDT with motion captured during clinic practice. In this way, the actual poses and motions of a patient during home exercise can be monitored, evaluated, and used to instruct with adjusted 3D games as reference. The goal of Phase I is to demonstrate the technical and commercial feasibility of the proposed innovation, which will be accomplished through a technical feasibility study, initial prototyping, and a commercial feasibility demonstration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INNSIGHTFUL INC.
SBIR Phase I: Biometric Wearable Device for Real-Time Mental Health Intervention of Anxiety
Contact
1195 VANDERBILT CT W
Sunnyvale, CA 94087--2452
NSF Award
2112055 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 utilize artificial intelligence for mental health interventions, with an initial application of college students. Over 60% of U.S. college students suffer stress and anxiety that can manifest in physical symptoms such as palpitations, chest pressure, stomach aches, muscular tension, diarrhea/constipation, and fatigue. The significant negative impact of stress and anxiety affects learning, development, and social engagement, and ultimately can contribute to destructive behaviors such as drug and alcohol use. This project proposes an intelligent, personalized digital health technology that integrates biometrics for automated, early detection of increasingly stressed states as a cost-effective way to inform interventions and improve college retention. This application can be expanded to other populations for improved mental health outcomes.
This Small Business Innovation Research (SBIR) Phase I project improves mental health through integration of wearable biometric sensors, artificial intelligence (AI), and a user interface to guide both automated and interactive psychotherapy interventions. A wearable wrist band device will passively capture biosignals to detect signals of anxiety to inform an automated analysis. The app can then provide varying levels of alerts and intervention as appropriate for the magnitude of the event. This can be used for mental health monitoring broadly.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INOON, LLC
STTR Phase I: Multiple Eye Disease Detection Using a Smartphone
Contact
10402 IOLA AVE
Lubbock, TX 79401--5920
NSF Award
2015102 – STTR Phase I
Award amount to date
$225,000
Start / end date
08/15/2020 – 06/30/2022 (Estimated)
Errata
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Abstract
The broader impact/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to proactively manage eye health. Approximately 285 million people and 39 million people suffer respectively from visual impairment and blindness. Monitoring of eye disease in early stages is critical to slowing its progression, but currently this assessment requires specialized equipment in ophthalmology practices or optometry offices. Smartphone-based disease detection is customizable, portable, easy-to-access, and multi-functional.
This Small Business Technology Transfer (STTR) Phase I project aims to design and develop an eye disease diagnostic tool using a smartphone. This project will develop and validate novel data acquisition, image processing and machine learning techniques for keratoconus, glaucoma, and cataract detection, including new algorithms for detection of motion and noise artifacts to reduce image corruption.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSECTAPEL, LLC
SBIR Phase I: Long-Lasting Insect Repellent Systems Based on Fatty Acids and Their Derivatives
Contact
10152 GREENVILLE HWY
Wellford, SC 29385--9528
NSF Award
2051917 – SBIR Phase I
Award amount to date
$207,799
Start / end date
12/01/2021 – 11/30/2022 (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 enhance public health by the introduction of safer insect-repelling textiles. The Phase I SBIR effort will lead to the development of textiles embedded with a new long-lasting insect repellent system derived from coconut fatty acids. This project will advance a safer insect repellent to reduce vector-borne diseases and to eliminate the health issues resulting from currently available synthetic products. The insect repellent market is currently valued at $5.64 billion, and the proposed work will address issues generated by synthetic repellents.
This SBIR Phase I project proposes to test new coconut fatty acid-based compounds that enable the prolonged release of insect repellent fatty acids via textile impregnation. With growing health concerns over the use of DEET and increasing occurrences of permethrin-resistant strains of mosquitos, active compounds based on coconut fatty acids are a viable option for safe and effective replacement. The proposed research is to develop and to test the release system that will gradually supply insect-repelling fatty acid via the degradation of labile chemical bonds which hold the compound. These developmental products are envisioned to provide prolonged insect repellency compared to the supposed gold standard synthetic repellents such as DEET and permethrin. The SBIR Phase I research will include proof of concept trials, development of analytical methods for accurate analysis of the active ingredient (chromatographic or spectroscopic), release studies, application trials (using standard methods established in the textile industry), and field performance testing on live insects (via surveys designed for agricultural research). A technical challenge for this project will be ensuring efficient impregnation of fabrics/textiles with the proposed insect repellent system and obtaining a suitable release timeframe after all steps of the fabric treatment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSILICA, LLC
SBIR Phase I: Advanced Cancer Analytics Platform for Highly Accurate and Scalable Survival Models to Personalize Oncology Strategies
Contact
7106 RIVER RD
Baltimore, MD 21209--1069
NSF Award
2012214 – SBIR Phase I
Award amount to date
$224,454
Start / end date
08/15/2020 – 06/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will develop personalized clinical decision-making in cancer care. An estimated 17 million cases of cancer are diagnosed globally each year. Over $90 billion per year is spent in total on cancer-related health care in the U.S., and cancer patients pay over $4 billion out of pocket for health care. Therapeutic strategy selection and clinical trial research targeted to oncology become exponentially complex when unique types of cancer are considered, as well as how they may uniquely impact gender, race, ethnicity, and age of affected populations. The proposed technology will develop advanced bioinformatics models and visualization tools to guide decision-making by oncologists. It will develop and use advanced survival models targeting cancer types, other biological and chemical factors, and patient demographics.
This Small Business Innovation Research (SBIR) Phase I project will focus on three objectives. 1) We will develop and validate transfer learning models that leverage large data sets from high-incidence cancer types to improve results of cancer types with sparse data. 2) We will leverage these data in a disease-agnostic platform using a recurrent neural network to account for temporal variation to predict survivability. 3) We will develop visualization tools for clinicians to understand causal relationships. This system will use several innovations: a) Transfer Learning to Scale Available Data: Since cancer survival modeling is limited in many cancer types due to lack of data, we will demonstrate the feasibility of transfer learning in this context. b) Single Recurrent Neural Network: We will implement a recurrent neural network to improve performance and allow a single network to be trained across all cancer types and patient population characteristics. c) Control Feature Mediation Analysis: We will develop accurate survival models with an understanding of the sensitivity to inputs. d) Clinician-Driven Interpretation and Visualization Tools: The framework needs interpretation and visualization features to reduce data into reports easily digestible for clinical decision-making.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSOMA BIO INC
SBIR Phase I: An Injectable Protein Matrix to Enhance the Stability of Autologous Fat Grafts
Contact
701 W MAIN ST
Durham, NC 27701--5013
NSF Award
2052243 – SBIR Phase I
Award amount to date
$252,992
Start / end date
07/15/2021 – 06/30/2022 (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 related to the use of a patient’s own fat tissue for repair after injury or surgery. Removing tissue to eliminate damage through disease or trauma is universally followed by repairing tissue to restore form and function. While a broad range of materials are available, the use of a patient’s own fat for these procedures has long been considered an obvious option. Fat can be safely harvested, is rich in stem cells and growth factors and has other desirable properties, depending on the location from which it is harvested. The use of this material for surgical procedures has been inhibited by a loss of specific physical properties during the harvesting procedure. Providing a matrix to reconstruct these properties is likely to render fat grafting a more commonplace procedure. By optimizing structure and formulation of this matrix material, tissue engineering can be disrupted with an off-the-shelf option enabling harvested fat from a patient to address the hundreds of thousands of reconstructive procedures undertaken each year.
The proposed project is based on the use of elastin-based recombinant proteins to address the current limitations of tissue repair scaffolds. The proposed technology uses highly disordered proteins to produce defined 3D structures to replicate mechanical and biological activities of the body. Using iterative design and molecular engineering, the team has generated a new class of biomaterials that are uniquely suited to meet the key criteria for a fat grafting support matrix, including injectability, in vivo phase transition to a firm solid, and biocompatibility to allow cellular viability and vascularization. This project focuses on optimization of the matrix for reconstruction procedures, including facial, breast, amputation sites and foot pad tissues. A range of materials with unique biomechanical properties are likely required to address each of the target use cases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTACT THERAPEUTICS
SBIR Phase I: A thermogel-based drug delivery platform for the upper gastrointestinal bleeding treatment
Contact
740 BROADWAY ST
Hayward, CA 94545--3716
NSF Award
2014730 – SBIR Phase I
Award amount to date
$244,999
Start / end date
08/15/2020 – 10/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an innovative method to treat upper gastrointestinal bleeding (UGIB). UGIB results in more than 550,000 hospitalizations per year in the US alone with a mortality rate of up to 20%. The gastrointestinal (GI) bleeding market is projected to be nearly USD 1 billion by 2026, with the overall hemostatic agents market reaching over USD 5 billion. Current solutions require endoscopy performed by a specialist or hospital admission. The proposed approach is a drinkable formulation to stop bleeding after ingestion, eliminating the need for endoscopic intervention or hospitalization. The technology developed in this project could then be applied to other bleeding scenarios, including field/combat medicine or rapid treatment of hemorrhage during surgical complications. The gel can also be used as a drug delivery vehicle for a variety of disorders of the upper GI tract.
This Small Business Innovation Research (SBIR) Phase I project will demonstrate a new approach to achieve hemostasis in patients with upper gastrointestinal bleeding (UGIB), based on a novel thermosensitive gel (thermogel) formulation. The drinkable formulation is liquid at ambient temperature and becomes a mucoadhesive gel when warmed to body temperature, thereby treating hemorrhage in the upper GI tract without the need for endoscopic intervention. Its action is based on two synergistic effects: (1) The in situ gelation of the mucoadhesive thermogel provides a mechanical barrier against blood flow, and (2) the slow release of drugs from the thermogel at the hemorrhage site enables more rapid healing. Initial efforts will be dedicated to formulation development wherein compatibility of the thermogel with different drug candidates will be evaluated, and optimization of the gelation temperature will be performed. The best formulations will then be tested in vitro for stability, drug release kinetics, and mucoadhesion. Finally, the effectiveness of the proposed approach will be assessed in preclinical models of bleeding, demonstrating its superior ability to reach hemostasis. This is expected to apply to disorders including gastroesophageal reflux disease, eosinophilic esophagitis, and oral mucositis.
This award reflects 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. -
INTERSPHERE, INC.
SBIR Phase I: Sub-Decadal Weather and Climate Forecast System to Mitigate Risk for Energy and Natural Resource Applications
Contact
320 E VINE DR STE 318
Fort Collins, CO 80524--2332
NSF Award
2112245 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase I project is to reduce weather and climate risk for organizations within the environmental and natural resource sectors through multi-year forecasts. The proposed forecast system uses a combination of Earth science and computer science to create a highly interpretable forecast system that is optimizable for the needs of specific industries. These multi-year ("sub-decadal") forecasts help renewable energy resource assessment, hydropower applications, and the mining industries. Better forecasting can lead to cheaper energy, more reliable long-term water supply management, and the improved environmental sustainability of mining operations.
This SBIR Phase I project will advance development of a sub-decadal weather and climate forecast system integrating geoscience and machine learning. Project activities include: assessing the technical feasibility; evaluating the computational scalability; determining the relevant industry-specific inputs and outputs; and validating the output and interpretability. The algorithm must scale across multiple spatial and temporal timescales.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTHEPENDANT, INC.
SBIR Phase I: Early Detection and Prediction of Mobility and Cognitive Decline
Contact
20 MASON ST
Lexington, MA 02421--6328
NSF Award
2013985 – SBIR Phase I
Award amount to date
$244,988
Start / end date
07/01/2020 – 06/30/2022 (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 early detection of cognitive decline and fall risk, particularly in the elderly. The proposed project will develop an artificial intelligence system to assess cognitive issues and estimate how likely a subject is to fall, enabling a new level of security for a vulnerable population.
This Small Business Innovation Research (SBIR) Phase I project advances early detection of mobility problems and cognitive decline. This will be accomplished through the development of machine learning algorithms assessing gait dynamics (with dual-task information) in habitual settings. Research objectives include: (1) Developing a machine learning algorithm for fall prediction, (2) Developing preliminary mobility and fall prediction scoring system, (3) Estimating the cognitive state, and (4) Developing an accurate automatic fall detection 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. -
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. -
INZIO, INC.
SBIR Phase I: Autonomous 3D Printer/Former for On-Site, Affordable Construction
Contact
4771 BAYOU BLVD STE 276
Pensacola, FL 32503--1930
NSF Award
2126746 – SBIR Phase I
Award amount to date
$255,437
Start / end date
09/01/2021 – 08/31/2022 (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 make possible small-scale, high-quality automated construction. This proposal investigates a method to automate the concrete forming process from design to construction, including site assessment, design, and material construction. This platform can provide fast on-site construction, reduce renovation timelines, and provide habitat affordability.
This project advances translation of an automated concrete forming process, including concrete material formulations, robotic path planning/ machine vision for construction sites, and end-effector electromechanical designs. Other processes to be engineered include 3D mapping of existing site conditions, associated design processes, robotic path planning and material scheduling, and project execution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IRIS LIGHT TECHNOLOGIES, INC.
STTR Phase I: PIC: Electro-luminescence and doping of black phosphorus for printed lasers on silicon photonic chips
Contact
2218 W CORTEZ ST
Chicago, IL 60622--3522
NSF Award
2136800 – STTR Phase I
Award amount to date
$256,000
Start / end date
12/01/2021 – 11/30/2022 (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 demonstrate the viability of a new manufacturing process for on-chip lasers for silicon photonics using printed nanomaterial inks. The difficulty of a scalable method for fabricating on-chip, multi-color lasers is a major challenge for the silicon photonics market. Specifically, today's standard manufacturing of photonic chips does not include on-chip lasers. Without integration of laser engines to drive the circuits, the market potential of light chips is constrained by design and price. The technology developed here can allow foundries to mass produce chips with lasers and open multiple new markets for silicon photonics including wearable photonic sensors, optical data transfer, autonomous vehicle light detection and ranging, quantum information, fiber-optic gyroscopes, and healthcare applications such as immunoassay tests and medical imaging.
This Small Business Technology Transfer Phase I project develops on-chip embedded lasers to enable fully functional silicon photonic chip manufacturing. Currently, the laser solutions being employed in silicon photonics include bonded lasers and heterogeneous integration. The system integrators that assemble silicon photonics modules rely on often cumbersome methods of gluing individual lasers to silicon chips, keeping costs high and throughput well below desired levels. The photonic inks developed here will overcome this challenge by enabling an in-foundry laser solution via wafer-scale additive manufacturing. The photonic ink emits broad-spectrum light covering the visible to the near-infrared range and can be tailored to emit at specific wavelength bands relevant to different markets by altering the number of atomic layers. The goals of this Phase I project are to demonstrate electroluminescence from a p-n junction made from doped, few-layer nanomaterials.
This award reflects 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 (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 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. -
Infecho Scientific LLC
STTR Phase I: Implementation of an ultrasound technology for continuous in-situ monitoring of lubricant viscosity
Contact
1340 ASHLAND RD APT A
Columbia, MO 65201--8213
NSF Award
2013639 – STTR Phase I
Award amount to date
$224,770
Start / end date
07/01/2020 – 07/31/2022 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is to advance development of an innovation in lubricant viscosity sensing to enable continuous oil condition monitoring. There are 285 million vehicles, aircrafts and vessels in the US, and more than one-half of the lubricant changes based on mileage and time are estimated to be premature and unnecessary. For the moving vehicles in the US alone, this technology could save over $1.3 billion in oil cost and prevent the requirement to dispose over 70 million gallons of used oil every year, with additional savings from reduced labor and vehicle downtime. The proposed technology will benefit consumers and industrial users with prolonged vehicle/machine life and reduced maintenance cost. Furthermore, it will reduce oil waste and the substantial cost of oil recycling, enabling greater sustainability.
This SBIR project will advance a proposed ultrasound technology for in-situ oil viscosity monitoring inside engines using ultrasound wave behavior. The proposed project operates without delicate or motion-based sensing mechanisms, enabling use in a harsh environment with strong vibrations and noise. This unique method gives highly reliable measurement, making this technology advantageous for applications in-situ. This project will design sensing probes suitable for installation and use in engines; calibrate them under simulated conditions; and test them for continuous measurement of oil viscosity in a running engine in-situ. Data will be collected to refine new algorithms in anticipation of an advanced 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. -
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 (Estimated)
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
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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. -
KINETICA LABS, INC.
STTR Phase I: Smartphone-based Biomechanical Analysis for Job Risk Assessment
Contact
1600 HURON PKWY FL 2
Ann Arbor, MI 48109--5001
NSF Award
2051916 – STTR Phase I
Award amount to date
$0
Start / end date
08/01/2021 – 07/31/2022 (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 prevent work-related musculoskeletal disorders (WMSDs), a leading cause of pain, suffering, and disability in the US workforce. The proposed technology estimates forces exerted on the human body and 3D motions solely by processing videos captured with a smartphone, and without needing to attach sensors to the workers or objects. This technological advancement will provide safety professionals with a rapid, easy and affordable ergonomic risk assessment tool without hindering activity at job sites, improving outcomes for potential patients. Among many industries that suffer from WMSDs, immediate targets are manufacturing and distribution that have high injury rates.
This Small Business Technology Transfer (STTR) Phase I project aims to overcome the current hurdles posed by invasive, time-consuming, and cumbersome force measurement for ergonomic risk assessment at job sites. The proposed technology estimates forces exerted on key body parts (e.g., neck, shoulder, back, and knees) and their motions through videos captured with a smartphone and without interfering with workers’ ongoing work, thereby making ergonomic risk assessment non-invasive, rapid and easy. However, for application at real job sites where frequent occlusions (objects or structures obscuring the worker’s body) and complicated work environments pose a significant challenge to estimating forces and motions from videos, the algorithms used in the technology have to be improved and tested with a diverse range of motion and force data. This project aims to address these technical challenges through a new data augmentation approach, refinement and optimization of force estimation models, and extensive lab and real job site data collection and 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. -
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. -
KISMET TECHNOLOGIES LLC
STTR Phase I: Rapid Acting Disinfectant Spray for Slowing the Spread of COVID-19
Contact
2331 BANCHORY RD
Winter Park, FL 32792--4703
NSF Award
2032056 – STTR Phase I
Award amount to date
$255,536
Start / end date
08/01/2020 – 06/30/2022 (Estimated)
NSF Program Director
Errata
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This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is development of a disinfectant spray to curb the transmission of SARS-CoV-2 via contact with contaminated surfaces. COVID-19 transmission occurs primarily via respiratory droplets produced by an infected person and by contact with a surface where a droplet containing the virus exists. Mitigating infection by contact with surfaces is a measure that will slow the spread of novel viruses ahead of development of a vaccine or other protective measures. In conjunction with other measures, a novel disinfectant will support public health during the COVID-19 pandemic. Current disinfectants require times ranging from 30 seconds to 10 minutes for disinfection to begin after application and do not continue to disinfect. The proposed technology creates a temporary, continually disinfecting film that remains on the application surface.
This STTR Phase I project will demonstrate both the rapid performance of a novel spray and its ability to form a temporary and continually disinfecting film post=application. This technology employs a select medium containing fast-response doped nanoceria where the oxidizing response/mechanism is engineered to perform several disinfectant reactions in parallel. A safe, rapid, multi-disinfectant approach using engineered nanoceria has not previously been demonstrated for use. The project will also demonstrate the post-application disinfection properties. The goals of this project will be achieved with the following: 1) development of an anti-viral, multi-mechanism disinfectant formulation, 2) demonstration of efficacy and safety, 3) study of product stability, and 4) demonstration of temporary film formation, stability, and activity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KODA HEALTH, INC.
STTR Phase I: Digital Advance Care Planning Platform
Contact
2450 HOLCOMBE BLVD STE X
Houston, TX 77021--2039
NSF Award
2051460 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 08/31/2022 (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 may significantly improve the quality of end-of-life care through Advanced Care Planning (ACP). It is not always possible to align patients' end-of-life wishes with the care they receive. The proposed project develops a digital platform for ACP. This system will use a machine-learning guided dialogue to deliver personalized audiovisual content adapted to individual and cultural preferences. This system may improve palliative end-of-life care for many.
This Small Business Technology Transfer (STTR) Phase I project addresses the technical challenge of providing a personalized platform that performs digital motivational interviewing and adapts audiovisual content and input queries to patients’ personae. A major hurdle of applying machine learning to ACP is the variability in personal and cultural factors, as well as validation of the integrity of the responses. The project centers on the collection and analysis of psychometric data from two patient surveys combined with other health information. The project objectives are: (a) Execute a benchmark training patient survey for the machine-learning algorithm for a study on the influence of gender, ethnicity, and health status on ACP; (b) Develop a reliable persona detection tool using machine learning algorithms guided by the data, avoiding the introduction of unconscious bias; (c) Demonstrate that the platform improves completion rates and patient satisfaction compared to ACP administered by human health workers and static online platforms without machine learning; and (d) Demonstrate the alignment of the digital process with patient wishes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KODIKAZ THERAPEUTIC SOLUTIONS, INC.
SBIR Phase I: Horizontal genomic transfer technology: Bioengineering DNA sequences for the creation of a non-viral targeted cancer cell specific gene therapy platform
Contact
180 VARICK ST FL 6
New York, NY 10014--7424
NSF Award
2103565 – SBIR Phase I
Award amount to date
$255,831
Start / end date
08/15/2021 – 07/31/2022 (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 clinical outcomes for cancer treatment. Horizontal genomic transfer (HGT) has the potential to deliver a variety of lethal payloads to tumors with high specificity. The proposed platform will enable better cancer therapies with lower side effects. To accelerate translation, this project proposes the development of a high-throughput platform to enable the evaluation of the specificity, lethality, and efficiency of therapies based on HGT across many different cell types, multiple dosing and many other variables. These defining features of the proposed HGT platform will permit the rapid and cost-effective development of novel gene therapies to improve patient care.
This Small Business Innovation Research Phase I project aims to create a framework for the rapid high-throughput screening of cell-specific HGT-based therapeutics. HGT was previously thought to only be present in species like bacteria and fungi, but has recently been discovered in human cancer cells. Preliminary data has demonstrated the HGT’s abilities to deliver different expression vectors in animal models and in culture, but the efficiency of delivery and expression is currently unknown. This project will interrogate identified HGT and their sequences in the lab to better understand how to further optimize them to maximize delivery and expression of genomic payloads. The first aim proposes the development of the high-throughput screening platform for assessing integration and expression efficiency of HGT, and the second aim proposes the correlation of flow cytometry data with HGT integration into the tumor cell genome. Successful completion of the project will inform HGT platform development to evaluate numerous cellular parameters simultaneously and ultimately accelerate product development for cancer therapies and potentially in other indications.
This award reflects 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 – 07/31/2022 (Estimated)
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. -
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)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project advances the state-of-the art of an emerging class of vision-based, autonomous navigation technologies to open new possibilities for low-cost/high-performance personal assistive robots. The robotics solution enables mobility-impaired individuals to have more agency over their environment and enjoy a higher quality-of-life. This helps address the severe shortage of caregivers for the elderly and post-acute care patients by empowering individuals to maintain their independence, extending the impact of caregivers, and reducing the cost of care in both home and facility settings. Additionally, by providing affordable and reliable isolation support in COVID-19 care settings, the proposed solution can help decrease the financial burden and increase the public health outcomes associated with COVID-19 disease management. The core robotics solution has an immediate addressable market of 11 million high-needs users in the U.S. alone, with projected revenues of roughly $1.65 Billion five years after product launch. Further commercialization opportunities come from licensing parts of the developed navigation technology for other robotics applications and developing an ecosystem of complementary products around the core robotics solution.
This Small Business Innovation Research Phase I project seeks to enable a new generation of assistive service robots that are comparable to commercial robots in performance, but significantly more affordable for individual use and personal care applications. The innovation adopts emerging visual positioning technologies from Augmented Reality to enable robust navigation for mobile robots using low-cost, consumer-grade electronics, while addressing a key limitation of visual positioning systems namely, that external lighting conditions and other changes in an environment can dramatically impact their performance. The innovation addresses these challenges via a combination of hardware and software that learns and stabilizes the highest value visual elements of the environment to maintain persistency across lighting conditions and long periods of time — a development critical to making assistive robots cost-effective for adoption at a large scale. Research objectives include: fully developing and integrating the visual persistency system, to achieve accurate and replicable robot navigation performance across a representative range of lighting conditions and visual characteristics of the target operating environments and benchmarking the resulting solution against state-of-the art technologies, to demonstrate its superior performance (i.e., it can successfully localize in at least 90% of cases where other solutions fail).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LADON ROBOTICS LLC
SBIR Phase I: Autonomous Wind and Solar Powered Cargo Vessels
Contact
8006 213TH ST SW
Edmonds, WA 98026--7452
NSF Award
2130478 – SBIR Phase I
Award amount to date
$256,000
Start / end date
03/15/2022 – 08/31/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop autonomous, ocean-going cargo vessels powered by a combination of wind and solar power. These vessels will enable the provision of cheaper and more frequent sea freight service to isolated communities, such as those in coastal Alaska. The technology seeks to the lower operating costs by removing liquid or solid fuels or onboard crew, enabling the vessels to be more readily right-sized to particular routes and markets. The project may also have positive impacts on the environment by eliminating fossil fuel emissions and reducing marine noise impacts on wildlife, such as marine mammals.
This Small Business Innovation Research (SBIR) Phase I project will integrate existing robotic and energy capture technologies with newly developed wind/solar combined energy optimization software and autonomous contingency management. A vessel using both the wind and sun for propulsion has a difficult energy optimization problem, both on a minute-to-minute basis but also on the scale of an entire voyage; This project will build a model for solving this intermitancy problem given specific vessel performance characteristics and weather predictions. Likewise, this project will build a framework for addressing the autonomous contingency management problem for uncrewed marine surface vehicles given a particular set of vehicle and system characteristics. The focus will be on ship-to-shore communications contingencies because those are the most serious for the contemplated target system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
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
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a 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. -
LITERASEED, LLC
STTR Phase I: Advancing Health Equity using Interactive Condition Assessment and Monitoring
Contact
27227 N 31ST DR
Phoenix, AZ 85083--5836
NSF Award
2041991 – STTR Phase I
Award amount to date
$256,000
Start / end date
07/15/2021 – 06/30/2022 (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 build a condition assessment and monitoring platform that leverages artificial intelligence (AI) for intelligent decision support to expedite diagnosis and facilitate personalized therapy solutions. Currently, patient history data is obtained verbally, and poor health communication between clinician and patient potentially causes 78% of misdiagnoses, resulting in 80,000 avoidable hospital deaths and $750 billion in costs to the US economy each year. Language barriers exacerbate this situation significantly, increasing the risk of severe and frequent adverse outcomes by 49%. Patients with cultural, language, and low health literacy are twice as affected. The proposed work has three major technical objectives: (1) develop an interactive visually-supported healthcare data capture user interface (UI) to overcome communication and language barriers, (2) develop an AI-based risk assessment engine to communicate symptoms to the provider for triage decisions, and (3) leverage predictive analytics to recommend appropriate treatment options and develop a visualization-based condition monitoring and management tool. The proposed data collection and AI-powered provider decision support platform will empower patients and providers by enhancing communication, improving health outcomes, and reducing healthcare costs.
This Small Business Technology Transfer (STTR) Phase I project is designed for accessibility across all levels of literacy and is language-agnostic. The platform’s digitally-native, cloud-based approach allows it to be scalable for widespread impact and faster impact. The frontend app captures important patient information and symptoms before the patient exam and summarizes the patient self-report in an easily readable format for the clinician. The clinician will potentially be more prepared, facilitating the delivery of personalized care and improved outcomes by avoiding misdiagnosis, errors, and complications earlier in a patient’s journey. The AI-based model pulls structured data, such as demographic information and symptoms from the patient self-report, and the dataset undergoes supervised learning using historical, real-world outcomes data. Multiple AI models will be evaluated, including classification and neural network models, and those with sufficiently accurate performance will be considered as inputs for ensemble learning, the final prediction output for this project. Example outputs include patient evaluators such as consistencies within the patient’s self-report, an estimated risk assessment score, and an approximate diagnosis accuracy score.
This award reflects 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 (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 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. -
LUMENASTRA
SBIR Phase I: A Wearable Non-Invasive Deep Tissue Thermometer
Contact
12416 N 63RD ST
Longmont, CO 80503--9134
NSF Award
2126774 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2021 – 07/31/2022 (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 measure biological temperatures for many important problems in health care, by advancing a novel temperature sensor. In the near term, a wearable, non-invasive sensor can prevent heat stroke and exhaustion for at-risk cohorts, such as the US military, which suffers from 2800 annual cases of heat stroke in active-duty personnel. Furthermore, heat stroke early warning could diminish injuries and deaths among U.S. high school and college athletes and 7.4 million first responders who typically operate under stressful conditions. Beyond heat stress, this thermometer can monitor elevated brain temperature during the critical hours following stroke or traumatic brain injury (affecting 4.8 million patients per year), which can cause additional brain damage and permanent disabilities. The proposed sensor can directly measure tumor temperature during heating therapy, potentially improving clinical outcomes for some of the 1.8 million patients per year by 20-40% while reducing dosage of debilitating chemicals and radiation.
This Small Business Innovation Research (SBIR) Phase I project will demonstrate a novel, non-invasive temperature sensor capable of accurately measuring deep tissue temperature several centimeters below the skin, wherever placed. The proposed sensor detects small microwave signals in a noisy environment by incorporating 20+ signal processing and noise reduction methods with technologies similar to those used in radio astronomy. Non-invasive brain temperature measurement is particularly important as the brain generates and manages its own critical operating temperature, and elusive as it can only be inferred from surrogate measurements without directly cutting into the skull. Direct brain temperature monitoring with a wearable device may provide early warning of many health 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. -
LUMO IMAGING LLC
STTR Phase I: Dermatologist-level detection of suspicious pigmented skin lesions from high-resolution full-body images
Contact
10801 PLEASANT HILL DR
Potomac, MD 20854--1512
NSF Award
2127051 – STTR Phase I
Award amount to date
$255,999
Start / end date
08/01/2021 – 07/31/2022 (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 Program (STTR) Phase I project is to improve outcomes in dermatology and enable improved clinical care in the absence of specialists. The proposed technology enables cost-effective screening for cancer, psoriasis, atopic dermatitis, and other inflammatory skin conditions. In the United States, psoriasis affects about 8 million people while about 31.6 million people in the United States have some form of eczema, including atopic dermatitis. The proposed system generates a highly magnified image of the skin for analysis by a clinician or an artificial-intelligence based automated system.
This Small Business Technology Transfer Program (STTR) Phase I project integrates several subsystems: 1) a scanner and software to capture and reconstruct super high-resolution (dermatoscope level) model of the entire skin surface of patients in a matter of minutes; 2) a multispectral illumination system to provide more information than currently available from a typical white-light systems, potentially leading to superior sensitivity and specify in lesion detection and classification; and 3) a system to find and classify lesions automatically from high-resolution images. This system advances the automated classification of images beyond those filtered previously by a clinician. Moreover, the system's UV illuminations system potentially can be used in a photodynamic treatment regimen.
This award reflects 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 (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 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. -
MANHATTAN BIOSOLUTIONS, LLC
SBIR Phase I: Genetically Engineered BCG as a Microbe-Based Platform for Vaccination Against COVID-19
Contact
2180 CENTER AVE APT 1F
Fort Lee, NJ 07024--5839
NSF Award
2029504 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2022 (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 to develop a safe and affordable COVID-19 vaccination technology, with broader utility in managing other contagious diseases. The new platform is based on modified bacteria, with a long history as a safe pediatric immunization for tuberculosis. The proposed technology is expected to show heat-stability, safety, cost-effectiveness, and ease of mass production. It can be used for children and at-risk groups including first responders, the elderly, and those with underlying conditions. This can be delivered in emerging and disadvantaged environments as well.
The proposed project enables a novel microbial vaccine platform based on recombinant BCG bacteria (rBCG) engineered to target SARS-CoV-2 and protect against COVID-19. The goal of this project is to develop BCG that expresses SARS-CoV-2 protein fragments, which could lead to the induction of appropriate immune responses against SARS-CoV-2 specific antigens. For this project, new rBCG candidates with the highest secretion and durable expression levels of viral polypeptides will be selected and prioritized, based on their biological properties. The rBCG vaccines will be evaluated for safety and immunogenicity in animal models. Promising candidates that show no adverse events and induce robust T-cell and antibody responses will be selected for future preclinical 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. -
MAP OS LLC
SBIR Phase I: Semantic Annotation of Hypertext and its Application in Event Mapping
Contact
9 SKAGIT KY
Bellevue, WA 98006--1021
NSF Award
2050294 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/15/2021 – 08/31/2022 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to help applications of augmented reality, location-based search, and real-time live mapping of the world, and to build a digital twin of the earth. Event information is dynamic and hyperlocal. Thus it is important to ground the location and time of events to real GPS coordinates and universal time. This creates technical challenges of entity disambiguation and resolution, and real-time processing event information to reflect last-minute changes. The proposed natural language grounding work also helps create a mirrorworld with information interlinked between the virtual internet and physical spaces and events.
This Small Business Innovation Research (SBIR) Phase I project will be the first to investigate neural language model pre-training over semi-structured hypertext on a web scale (55TB of compressed data monthly). This will greatly accelerate understanding of noisy web text, while the majority of research to date has been conducted on clean plain text only. This project will also attack the challenge of machine reading with document-level annotations in a semi-supervised fashion, while the predominance of study has been carried out with more precise word-level annotation in a fully supervised way. The technical goal of this project is to create a scalable infrastructure that allows quick iterations of mining web scale data, and an ensemble of algorithms that are adapted to learning structured information over hypertext. It is an unsolved challenge for most small businesses that in the past only the internet giants have attempted. The resulting machine learning algorithms will be capable of interpreting semi-structured web data, in contrast to typical structured annotation to understand hypertext.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAP-COLLECTIVE, INC.
SBIR Phase I: Development of a Distributed Ledger System to Track Environmental Sustainability
Contact
3030 K ST NW 102
Washington, DC 20007--5156
NSF Award
2126844 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (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 track potential environmental impact in a tamper-proof fashion. This database can be used for outreach, benchmarking, and other applications. The forecasts developed can be used to inform strategic resource allocation decisions and other discussions regarding environmental sustainability.
This project integrates traditional carbon analysis methods, such as Life Cycle Assessment, with distributed ledgers and the internet of things to create a global carbon emission tracking system. This system will incorporate data from a sensor network measuring air quality, water quality, atmospheric carbon levels, and other variables. This project will conduct design and development of a dynamic system of carbon tracking using blockchain to verify records over time, creating a centralized, tamper-proof record for global carbon emissions. The project will also develop improved models and forecasts on various regional, industrial, and temporal scales.
This award reflects 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 – 07/31/2022 (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 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. -
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 (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 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 – 11/30/2022 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of 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. -
MENTE, INC.
STTR Phase I: Applying real-time data streams to predict operating room resource allocation with neural networks
Contact
12 CHANNEL ST STE 502
Boston, MA 02210--2326
NSF Award
2015012 – STTR Phase I
Award amount to date
$244,954
Start / end date
07/01/2020 – 06/30/2022 (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 reduce the cost of surgical operations. Instrument tracking enables hospitals to optimize the supply chain, with a potential annual benefit to the US healthcare system of $8.5 B. Predictive scheduling can save $500k per operating room (OR) by closing gap times between procedures. Similarly, instrument prediction assistance can save an OR an estimated $14 per minute. The project will gather procedure and tool data from the operating room and apply artificial intelligence to optimize OR processes. This project has the potential to improve the overall function of the surgical team by anticipating surgical instrument needs.
This Small Business Technology Transfer (STTR) Phase I project advances the fields of medicine and artificial intelligence by leveraging intraoperative data gathered by surgical instrument tracking. This unique data stream offers one of the first quantitative windows into a surgical operation. The objective of this project is to create computational tools to improve operating room scheduling and instrument supply, and test them with real clinical data. Transformer networks, commonly used in natural language processing tasks, will be adapted for this application and leveraged as an autoregressive tool to predict parameters of interest. The system will generate data regarding variations among surgeons, procedures, and 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. -
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 (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 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. -
MINERALOGIC LLC
SBIR Phase I: Predictive Tools for Characterizing Carbon Sequestration in Mined Materials
Contact
3371 W TISCHER RD
Duluth, MN 55803--9786
NSF Award
2035430 – SBIR Phase I
Award amount to date
$254,741
Start / end date
02/01/2021 – 07/31/2022 (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 provides tools to identify and realize opportunities to use mine waste rock in carbon sequestration projects. This project encompasses research and development activities necessary to translate observations on the geochemistry of rock weathering into a comprehensive toolset for mining companies to characterize the potential for geologic materials excavated during mining to sequester atmospheric carbon dioxide as solid, geologically stable carbonate mineral phases. The service will employ a novel predictive modelling tool and a method for determining the site-specific data to parameterize the model.
The proposed project will characterize the carbon sequestration potential of mined materials through a novel framework for conceptualizing silicate mineral weathering. Currently no established tools characterize this potential with sufficient accuracy to optimize the design of rock storage systems for carbon sequestration. The proposed innovation will include a novel implementation of mathematics of the “shrinking core model” into a reactive transport framework to simulate diffusion-controlled silicate mineral weathering and subsequent carbonate mineral precipitation. The innovation also includes a novel application of mine waste characterization test work to identify site-specific reaction kinetics of multi-mineral assemblages for model parameterization. Research and development activities include mineral characterization of weathered mine waste and waste analogues, mathematical model development, and re-interpretation of published and proprietary kinetic data. Geochemical data on the weathering of mined materials at the lab and field-test scale will be provided by industry. The model will be used to predict the rate of sequestration occurring at the field tests. The predictive skill of the model will be tested via comparison to observed carbon sequestration rates.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MINERVA LITHIUM LLC
SBIR Phase I: Point-Of-Use Nano-Mosaic Filter Technology for Lithium
Contact
2901 E GATE CITY BLVD STE 2400
Greensboro, NC 27401--4904
NSF Award
2045379 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/15/2021 – 07/31/2022 (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 in the development of an efficient, rapid, and cost-effective point-of use technology to recover lithium from brine resources. Current brine operations are capital intensive and incur significant lead time (2 years) with low recovery (30%) for producing high-grade lithium. The proposed technology targets two-fold reduction in operation cost, high lithium recovery (90%), and reducing extraction time from 2 years to less than 24 hours. Contributing to the world-wide Total Addressable Market (TAM) of ~$992 billion, this technology will impact the global lithium market, growing at an estimated compound annual growth rate (CAGR) of 1.9% for energy storage, electronic bikes, electrification of tools, and other battery-intense applications.
This small Business Innovation Research (SBIR) Phase 1 project proposes to develop a point-of-use nanomembrane filter for lithium extraction from non-traditional water resources. The proposed filter utilizes a robust, porous, and surface charged tailored sorbent of a novel coordination polymer framework prepared from an abundant natural polyphenol. The sorbents possess molecular sieving ability, tailorable pore size up to the pore dimension <2 nm, and functional coordination sites for high binding affinity for lithium ions. The novelty of the innovation over current technologies (e.g., solar evaporation and ion-exchange techniques) is nano-based filter technology with selective affinity for lithium, enabling rapid and efficient extraction and recovery of lithium. The research objective is to demonstrate the proof-of-concept for recovery within 24 hours as either lithium chloride or lithium carbonate with targeted recovery efficiency and conversion >90% in a subsequent step. The project includes: (1) Fabricating the membrane from the molecular sieves, (2) evaluating the lithium sieving performance, recovery, and conversion, and (3) fabricating a prototype filter unit. These developments will directly address current limitations in extraction time and efficiency, cost, recovery efficiency of lithium, and environmental impact of solar evaporation, ion-exchange and solvent extraction, and osmosis membrane 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. -
MIZAR IMAGING LLC
STTR Phase I: A novel dual paraboloid mirror device for enhanced light collection in confocal and fluorescence microscopy
Contact
2 GOOSENECK RD
Chapel Hill, NC 27514--4600
NSF Award
2014972 – STTR Phase I
Award amount to date
$225,000
Start / end date
09/01/2020 – 08/31/2022 (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 improve research in the life sciences. This research often uses confocal and fluorescence imaging technologies to capture high-resolution, high-contrast images of biological samples. However, these methods traditionally require high levels of illuminating light, resulting in damage to tissues, disruption of normal processes like cell division, and competing with the light being measured in the experiment. The proposed solution will improve the collection of light in these microscopes. This will allow researchers to minimize damage to samples, thus removing current experimental constraints and enabling the development of new and far-ranging applications on an already powerful research platform. The proposed technology will be useful for disease and pharmaceutical research.
The proposed project will involve the development of a simple, add-on, mirrored sample chamber unit capable of enhancing confocal microscopy capabilities by substantially increasing microscope fluorescence collection efficiency limits. This will require overcoming design challenges because the use of mirrors to collect and refocus emitted light has rarely been attempted in confocal microscopy. The proposed R&D work includes: 1) sample chamber and mirror design and prototyping, 2) design of mounting hardware and integration with an existing confocal system, and 3) exploration of compatible modalities, including Total Internal Reflection Fluorescence microscopy and Stochastic Optical Reconstruction Microscopy. Completion of the proposed objectives will lead to the development of a device that increases the light collection efficiency beyond the current 40% limit, is compatible with any detection objective, and does not require a separate optical path to the detector.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.