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Phase I
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109 THERAPEUTICS, INC.
SBIR Phase I: Novel injectable long-acting local anesthetic for postoperative pain management
Contact
825 N 300 W STE 300
Salt Lake City, UT 84103–1459
NSF Award
2026176 – SBIR Phase I
Award amount to date
$255,838
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project develops novel pain therapeutics that can reduce or eliminate the use of opioids after surgery. Opioid-based medications are a mainstay of postoperative pain management, with approximately 80% of surgical patients receiving prescriptions, but may result in opioid-misuse disorders with 10% of patients progressing to long-term use. In addition to being potentially deadly, this use can be associated with adverse events, such as addiction, respiratory depression, cognitive impairment, nausea, constipation; consequences include increased cost of care, hospital length of stay, and readmission rates. The goal of the proposed work is to develop a prototype long-acting local anesthetic that is easy-to-use, can provide sustained local anesthesia for 72 hours, and presents limited safety risks. This SBIR Phase I project will perform formulation optimization of a novel long-acting local anesthetic for postoperative pain management. Currently, options for long-acting local anesthesia suffer drawbacks such as limited duration, high costs, inadequate efficacy, cumbersome equipment, and risk of infection; these limit their utility as safe and effective postoperative pain management. This project will optimize formulation parameters for the desired drug release profile. Additionally, the stability of the resulting formulations will be validated to ensure adequate shelf-life stability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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2WITECH SOLUTIONS LLC
SBIR Phase I: Fast field detection of trace fluorocarbon compounds in water
Contact
110 CANAL ST 2ND FL
Lowell, MA 01852–4574
NSF Award
2025338 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this SBIR Phase I project is in the development of a low-cost, high sensitivity sensor to measure contaminants in groundwater. These measurements are currently performed using technologies that are relatively expensive ($250-300 per water sample) and have a long turn-around time (10-15 business days). The proposed on-site optical detection technology targets a 10-fold reduction in test price ($20-30 per water sample), and fast detection time (<10 minutes). The proposed sensor will possess the following advanced attributes: high sensitivity, high specificity, fast detection, ease of operation, low power consumption, zero chemical release, low operational cost, remote measurements, and long-term stability without the need for recalibration. Moreover, direct use of the sample water will potentially eliminate uncertainties associated with measurement techniques. This Small Business Innovation Research Phase I project is directed toward development of a powerful on-site detection and monitoring system for trace levels of perfluoroalkyl substances (PFAS) in groundwater. The proposed technology uses fluorescence quenching induced phase shift. A fluorescent material with PFAS molecule binding sites will be fabricated and its PFAS-induced fluorescence quenching will be experimentally evaluated. Using phase fluorometry, the phase shift of quenched emissions against excitation pulses will be recorded and correlated to the concentration of PFAS in water. The key technical risks lie in improving sensitivity by three orders of magnitude for a complex aqueous sample. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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3D HEALTH SOLUTIONS, INC.
SBIR Phase I: Improving in vitro prediction of oral drug permeability and metabolism using a novel 3D canine organoid model
Contact
822 ASH AVE
Ames, IA 50014–7827
NSF Award
1912948 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I Project is to provide the pharmaceutical industry with improved pre-clinical screening assay for oral drug absorption. Current in vitro methods for characterizing gastrointestinal absorption are based on unreliable assays, with 90% of all drugs developed ultimately failing to enter the market. Practically, these limitations delay the development of critically needed therapeutic drugs and dramatically increase drug prices and health care costs. There is, therefore, a critical need to develop more predictive in vitro testing assays that will allow for early selection of the most promising drug candidates to reduce the number of live animal studies and their associated costs, while accelerating transition from pre-clinical research to early drug development. The technology is based on the discovery, fundamental characterization and bioarchiving of adult canine intestinal stem cell lines, called 3-dimensional (3D) canine intestinal organoids. These miniguts emulate the physiology of the functional intestine much more closely than currently available methods and have the potential to provide superior drug screening over currently used assays. This SBIR Phase I is a proposal to establish that in vitro predictability of oral drug absorption can be improved using canine intestinal organoids vs. standard 2D in vitro assays, such as Caco2 and MDCK cell lines. In Aim 1, the goal is to determine intestinal absorption and permeability of therapeutic drugs as a function of disease and intestinal segment as compared with conventional in vitro models. This will be achieved by quantifying passive and active permeability of drugs, as well as drug transporter expression and function in 3D canine organoids vs. conventional cell systems. In Aim 2, the goal is to determine intestinal metabolism of therapeutic drugs as a function of disease and intestinal segment in canine organoids compared to standard in vitro models. Ultimately, quantitative data generated through these experiments will be imported into a commercial software to simulate the disposition kinetics of a predefined set of candidate drugs. Performances of the model predictions will be evaluated by comparing simulated vs. observed drug kinetic plasma data from the literature for validation purposes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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3D MICROFLUIDICS LLC
SBIR Phase I: Fast and scalable printing of high-resolution microfluidic devices using HLP technology.
Contact
36 GRAMPIAN RD APT 4
Liverpool, NY 13090–4045
NSF Award
2013942 – SBIR Phase I
Award amount to date
$224,606
Start / end date
05/15/2020 – 12/31/2020
Abstract
The broadder impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of microfluidic devices for life sciences research. Currently, devices with high-resolution microchannels are typically manufactured using sophisticated cleanroom microfabrication facilities, requiring technical expertise, high costs, and long turnaround times; these factors inhibit their use. This project will enable rapid manufacturing of customized microfluidics devices with substantially lower costs and turnaround times. This technology will impact research in applications including fundamental cell biology, drug screening, cellular therapy, toxicity testing, and tissue engineering. This SBIR Phase I project will advance the translation of hybrid laser printing (HLP), combining the quick and large-scale printing capability of Continuous Liquid Interface Production (CLIP) with precision processing of additive multiphoton polymerization (MPP) and subtractive multiphoton ablation (MPA) into a single versatile machine. Technical challenges in material discovery and scalability will be addressed in this work: 1) Discover new materials not only compatible with HLP process but also showing the necessary durability, transparency, biocompatibility, and impermeability to fluids; and characterize key HLP parameters, such as ablation z-range used in MPA mode and dead-zone thickness used in CLIP mode; and 2) Scale the maximum printable size of HLP process using a novel multiscale CLIP strategy combined with a step-stitch projection printing method. The project will develop a prototype for life sciences 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.
Errata
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Addenda
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3I Diagnostics, Inc.
SBIR Phase I: Development and assessment of a diagnostic platform for rapid identification of COVID-19 patients without using custom reagents
Contact
20271 Goldenrod Lane
Germantown, MD 20876–4064
NSF Award
2029745 – SBIR Phase I
Award amount to date
$256,000
Start / end date
07/01/2020 – 12/31/2020
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to deploy a diagnostic to rapidly and inexpensively detect COVID-19 infections. Beyond the short-term goal of identifying COVID-19 patients, the technology will lend strong support for real-time infection tracking nationally. The same hardware components of the diagnostic can be used to identify a wide variety of pathogens without custom reagents. The system will work with a cloud-based database and monitoring system to rapidly identify hotspots of increased pathogen activity, enabling faster response to new pathogens since no hardware-related development, manufacturing, and distribution are needed. Once a new pathogen’s fingerprint is obtained, it can be easily distributed to deployed instruments to enable immediately tracking of the new pathogen. This Small Business Innovation Research (SBIR) Phase I project aims to develop a rapid diagnostic capable of detecting SARS-nCoV2 directly from sample matrices without the use of custom reagents (like DNA) or a cold supply chain. The approach isolates intact virus directly from the specimen with the help of a disposable cartridge and a syringe pump. The isolated virus is then identified using Fourier-Transform Infrared Spectrometry (FTIR). The proposed work leverages the differential response to mechanical stress between the virus and the components of a sample matrix. This differential response is used to selectively lyse only the sample matrix components, not the virus. The debris is subsequently separated from the virus by size-based separation methods such as filtration, enabling rapid isolation of a broad range of pathogens directly from the sample. FTIR is used to identify the isolated virus since pathogens exhibit unique spectral fingerprints in the infrared region. The proposed Phase I effort will develop the protocol for isolating and identifying intact virus and will demonstrate the performance with nasopharyngeal swab samples. The results will be compared against results from RT-PCR methods to assess comparability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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3I NANOTECH, INC.
SBIR Phase I: A Chip-Based Nanosensor for Troponin T Detection in Human Blood
Contact
2901 E GATE CITY BLVD STE 2400
Greensboro, NC 27401–4904
NSF Award
1913695 – SBIR Phase I
Award amount to date
$224,491
Start / end date
07/15/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this SBIR Phase I project to develop a portable chip-based diagnostic device to detect the biomarker troponin T in human blood for cardiac disease diagnosis. This nano-biosensor has the potential to improve patient outcomes and reduce healthcare costs. Many patients who experience chest pain, an early symptom of a heart attack (myocardial infarction, MI), are first seen by EMS (emergency medical services) and are transported to a hospital in an ambulance. EMS are equipped with electrocardiogram (EKG) devices, but approximately 40% of all heart attacks cannot be diagnosed with an EKG alone. This leads to longer wait times for a definitive diagnosis, causes difficulty for patient transport decisions, delays treatment for those experiencing a true MI, and causes unnecessary hospital admissions for patients who are later found not to have had a heart attack. Blood-based biomarker assays, which are currently not performed in a prehospital setting, are needed to reach a conclusive diagnosis for all heart attack types. A portable device to monitor troponin T in a prehospital setting would result in faster treatment via improved diagnosis, better routing of patients to appropriate medical centers, and a decrease in unnecessary hospital stays. The cardiac biomarker market, including troponin, is expected to grow to $9.9 billion by 2022. The innovation of the proposed technology lies in the metal nanostructures on the diagnostic chip. These nanostructures allow proteins to be delivered to the sensing area and detected in a high sensitivity manner, while excluding larger debris, such as blood cells. The proposed work will leverage optical techniques for real-time label-free detection of protein biomarkers at the nanostructured chip. The current method for manufacturing the detection chips is slow and uneconomical. This Phase I work will address the high-risk, high-reward technical challenges by creating a low-cost, high-throughput fabrication method to mass manufacture nanostructured chips with reproducible optical properties. Additionally, this Phase I work seeks to validate blood sample delivery to the sensing area and troponin T detection in blood using an integrated microfluidic device. The selectivity and specificity requirements will be addressed by attachment of custom DNA molecules to the sensing area. These pieces of DNA are designed to bind in a highly specific manner to troponin T only. The outcomes of this Phase I project will establish the scientific and technical foundations necessary to move into a Phase II project by developing a low cost and easy to use point-of-care device suitable for rapid prehospital diagnosis of heart 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.
Errata
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42BIO, LLC
SBIR Phase I: Immunity Transfer by Magnetic Separation (COVID-19)
Contact
10203 SW 49TH LN
Gainesville, FL 32608–7159
NSF Award
2029723 – SBIR Phase I
Award amount to date
$255,993
Start / end date
08/01/2020 – 03/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the COVID-19 global pandemic. Recently, transfusions of plasma from recovered COVID-19 patients has shown some efficacy in treatment. This is due to antibodies in the donor plasma that recognize the SARS-CoV-2 virus, boosting the recipient’s immune system to better fight COVID-19. By mixing donor plasma with magnetic particles coated with molecules that can capture these therapeutic antibodies, we will magnetically extract, purify and concentrate these antibodies for use in COVID-19 treatment. This technology can potentially be extended to other diseases as well. This Small Business Innovation Research Phase I project proposes to develop chemical conjugation strategies and novel magnet arrays capable of isolating large amounts of therapeutic antibody from each unit of plasma. This strategy introduces the potential to harvest large amounts of therapeutic SARS-CoV-2 antibodies from a single recovered COVID-19 patient, enabling treatment of multiple patients from the plasma of one convalescent patient. The antibody-depleted plasma can be returned to the donor, enabling multiple plasma donations without the requirement of permanently removing plasma from the donor. In addition, access to purified antibodies should enable scaling of the therapeutic dose, potentially conferring longer immunity or inducing a more robust immune response in the 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.
Errata
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A-Alpha Bio, Inc.
SBIR Phase I: Developing a Rapid Antibody Generation Platform for Emerging COVID-19 Variants
Contact
4000 Mason Road
Seattle, WA 98195–0001
NSF Award
2033772 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2021
This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve and accelerate the development of antibody therapies to fight the COVID-19 pandemic. Antibody therapies are in development to target SARS-CoV-2, the virus responsible for COVID-19, but emerging virus mutations may result in resistance and require the development of new therapies. Antibody therapies typically enter the clinic after a year of development or longer, and the medical and economic consequences of this delay are severely felt throughout the world. To reduce the time to produce an antibody against an emerging SARS-CoV-2 mutant, this project develops a computational platform trained using massive experimental datasets to rapidly predict the therapeutic potency. This platform will enable drugs against SARS-CoV-2 mutants to more rapidly reach the clinic, saving thousands of lives. Moreover, the proposed platform can be utilized to predict therapeutic efficacy against future coronavirus strains unassociated with the COVID-19 pandemic, providing an invaluable tool to fight future pandemics. The proposed project will demonstrate the feasibility of using quantitative and library-on-library protein interaction datasets to train machine learning models for predicting antibody binding to novel SARS-CoV-2 variants. Existing approaches to build computational predictions for antibody drug development have been limited to few target variants, since datasets with binding measurements against hundreds or thousands of targets are not available. This project involves optimizing and validating a cell-based platform for generating a sufficient quantity and quality of antibody-antigen binding data for training computational models. The platform uses genetically engineered yeast cells and next generation sequencing to link protein interaction strength with cellular mating frequency. To demonstrate feasibility, large multi-chain antibody libraries will be genomically integrated in yeast and enriched for binding to SARS-CoV-2 and related coronaviruses. Next, a large network of antibody-antigen interactions will be measured and validated for quantitative accuracy by comparing to biophysical measurements. Finally, the resulting data will be used to train machine learning models and evaluate their predictive power using cross-validation. Training of computational models with sufficient predictive power will demonstrate the feasibility of using quantitative and library-on-library binding data coupled with machine learning to develop a platform for rapid antibody development to a novel SARS-CoV-2 mutant. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ACATECHOL, INC.
SBIR Phase I: Virucidal surface coatings for prevention of COVID-19 transmission
Contact
2265 E FOOTHILL BLVD
Pasadena, CA 91107–3658
NSF Award
2034178 – SBIR Phase I
Award amount to date
$255,864
Start / end date
08/01/2020 – 07/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from reducing overall COVID-19 mortality, and reducing the incidence of morbid secondary infections in intubated patients such as ventilator-acquired pneumonia (VAP). The market for antifouling/antimicrobial indwelling endotracheal tubes (ETTs) was estimated at $1.85 billion in 2017 with 6.6% annual growth, and further increases are likely due to the outbreaks of COVID-19 and other respiratory diseases. More than 50% of COVID-19 deaths are attributable to acute respiratory distress syndrome (ARDS) from secondary healthcare-acquired infections, such as VAP. Unfortunately, ETTs used for ventilation do not prevent bacterial settlement upon their surfaces (biofouling). To date there is only one FDA-approved antimicrobial ETT that does not target fouling as the root cause of VAP, leaving this critical issue unaddressed. The proposed technology advances the development of ETTs with novel coatings and can potentially be used in other indwelling biomedical medical devices, including urinary-, central venous-, and hemodialysis catheters (estimated market size: $77.7 billion by 2026). A ~10% reduction infection rate with this technology could prevent 1.7 million healthcare-acquired infections, annually saving 99,000 lives and $28-45 billion associated-cost in the US. This technology will also support research in antimicrobial interactions with surfaces. This SBIR Phase I project proposes to establish the feasibility of gemini-surfactant inspired coatings on ETTs to reduce COVID-19 mortality. Current approaches to prevent biofouling in ETTs involve incorporation of biocidal Ag+ ions or deposition of hydrophilic polymers resembling traditional surfactants to the surface. However, such biocide-release coatings liberate Ag+ ions that are cyto- and genotoxic and are subject to gradual depletion of the active agent. Meanwhile, the polymers are limited by both intrinsically hydrophobic regions in their backbones and the low surface activities of conventional “parent” surfactants. This project will advance the development of a new class of antifouling coatings combining structural elements of powerful gemini surfactants displaying surface activities orders of magnitude higher than their conventional counterparts, with the molecularly precise and durable surface modification technique of silanization. By mimicking the structures of gemini surfactants, incorporating multiple ionic “head” groups into the coating via silanization, hydrophilicity and antifouling/antimicrobial properties will be greatly increased relative to conventional antifouling 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.
Errata
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Addenda
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ACRIGEN BIOSCIENCES, INC.
SBIR Phase I: Development of a safe gene editing system via CRISPR-Cas and Cas inhibitor co-delivery
Contact
202 STANFORD AVE
Kensington, CA 94708–1104
NSF Award
2015148 – SBIR Phase I
Award amount to date
$225,000
Start / end date
08/15/2020 – 01/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enable safe and effective human gene editing, providing therapies targeting myriad human genetic diseases. CRISPR (clustered, regularly interspaced, short palindromic repeats) and CRISPR-associated (Cas) genes compose adaptive microbial `immune systems' found in diverse bacterial species, serving as a defense mechanism against viral infection. The simplicity, programmability, and versatility of CRISPR-Cas systems have enabled genetic modification of many organisms and offer immense therapeutic potential for treating human diseases. However, CRISPR-based gene editing can also cause off-target edits, resulting in the introduction of mutations, insertions, deletions, or DNA restructuring at unintended off-target editing. This effect can cause significant problems. The proposed technology will develop tools to safely translate CRISPR-based gene editing to in vivo human therapeutics. This Small Business Innovation Research (SBIR) Phase I project is to advance a technology based on virus-encoded CRISPR-Cas inhibitor off-switches, enabling control of off-target gene editing. These anti-CRISPR proteins are a novel class of robust protein inhibitors that can be genetically encoded for co-delivery with the CRISPR editing machinery. This proposal will focus on understanding CRISPR editing kinetics to pinpoint the ideal ‘editing window’ providing the highest therapeutic benefit while minimizing off-target risk. Second, the project will design a system for simultaneous delivery of the CRISPR editing machinery along with the anti-CRISPR inhibitor to leverage this new ‘editing window’. Genetic regulatory elements will be used to tune the expression of the various components of the system and provide the framework for a therapeutic delivery system. This work will enable safe and effective gene editing in a therapeutically relevant context, providing a toolkit for translation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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ADVENTUS MATERIAL STRATEGIES, LLC
SBIR Phase I: Polyacrylated Glycerol (PAG) Polymers in Asphalt Maintenance Applications
Contact
133 BELLINGER ST
Daniel Island, SC 29492–7568
NSF Award
1912741 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this project is to introduce a novel and renewably resource-derived polymer, Polyacrylated Glycerol (PAG), to the asphalt road maintenance industry. The project will demonstrate the performance and efficiency of PAG to improve the performance and life expectancy of common asphalt maintenance applications. If successful, this project will create a pathway to new demand for glycerol, a significant byproduct of the bio-diesel industry. Furthermore, it will create the potential to replace up to 50,000 tons per year of petroleum-derived polymers with a green product having significant renewable content. This Small Business Innovation Research (SBIR) Phase 1 project will explore the potential for PAG elastomers to perform as adhesion promoters, sealants, primers, and asphalt additives in asphalt roadway maintenance applications. A series of laboratory produced PAG polymers with variations in molecular weight, average acrylic functionality, and residual acrylic acid comonomer content will be explored using a series of laboratory-based tests designed to characterize performance of asphalt primers, seal coats, tack coats, micro surfacing, and chip seals modified with the PAG polymers. In addition, this Phase 1 project will explore the potential to scale-up the manufacturing of the PAG polymer from a laboratory scale to pilot 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.
Errata
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AEROMUTABLE CORPORATION
SBIR Phase I: Sensor and Control System Development and Integration for Semi-Truck Fuel Savings Device
Contact
1452 E 53RD ST
Chicago, IL 60615–4512
NSF Award
1940360 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/15/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to reduce fuel consumption and improve safety in the trucking industry while increasing profitability. Over 70% of US freight tonnage is moved by the trucking industry, but at highway speeds, aerodynamic drag uses over 65% of the total vehicle energy. This project will develop a network of sensors and an artificial intelligence (AI-)control system. This will be integrate with an experimental device that modifies the aerodynamic behavior of semi-trucks using air injection, enabling continuously optimized aerodynamic performance. This project will create a sensor system able to describe the micro-climate of a semi truck in real time, and an AI-control system to determine the trailer’s best aerodynamic profile based on current operating conditions. This system would create an energy savings for all US fleets of up to 3B+ gallons of unburned diesel for an annual total addressable market of $20B. This SBIR Phase I project proposes development of an aerodynamic add-on prototype for trucks to save fuel by dynamically changing the trailer’s aerodynamic profile. To capture the operating conditions around the trailer in real time, this project will develop a sensor system to accurately measure the environment surrounding the vehicle. This project will explore relationships among environmental measurements, optimize the number and location of sensors, conduct the relevant systems engineering studies, and build a 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.
Errata
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Addenda
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AI METRICS, LLC
STTR Phase I: AI-assisted Assessment, Tracking, and Reporting of COVID-19 Severity on Chest CT
Contact
432 RENAISSANCE DR
Hoover, AL 35226–4231
NSF Award
2032534 – STTR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
This is a COVID-19 award.Abstract
The broader impact /commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to leverage artificial intelligence (AI) to reduce errors and improve accuracy, standardization, agreement, and reporting in evaluation of COVID-19 lung disease severity on chest computed tomography (CT) images. Chest CT procedures play a critical role in COVID-19 patients but current methods for evaluating chest CT images lack accurate, quantitative, or consistent information, leading to text-based reports that are difficult to interpret. The proposed AI-assisted COVID-19 chest CT workflow will efficiently capture the fraction of lung involvement and improve communication with clinicians by providing a standardized graphical report, key images of important findings, and structured text. The quantitative data will standardize reporting on an individual patient basis and provide data for population-level analyses, thereby offering the potential to significantly advance scientific knowledge of COVID-19 lung disease on a national level. This STTR Phase I project proposes to develop an AI-assisted COVID-19 chest CT workflow to rapidly and objectively quantify the percentage of lung involvement, classify lung involvement using the COVID-19 Reporting and Data System (CO-RADS), track common and uncommon COVID-19 lung findings, and automatically generate summary reports with a graph, key images, and structured text. The standard-of-care for assessing and reporting COVID-19 lung disease severity on chest CT images involves dictated text-based reports that are subjective, highly variable, inefficient to generate and interpret, prone to errors, incomplete, and qualitative with data provided in an unstandardized format. The proposed AI-assisted COVID-19 chest CT workflow will reduce interpretation errors and omissions and improve accuracy, standardization, inter-observer agreement, efficiency, and reporting in evaluation of COVID-19 disease severity and response to treatment. This project will validate the working prototype with a team of expert clinicians. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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AINCOBIO LLC
SBIR Phase I: A Microbial Enrichment Device to Reduce the Cost of Sequencing Metagenomes
Contact
2300 OLD SPANISH TRL APT 1003
Houston, TX 77054–2137
NSF Award
1913372 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be the acceleration of discoveries in microbiome science by wider adoption of whole metagenomic and metatranscriptomic sequencing. These DNA and RNA sequencing techniques are the gold standard for data generation in microbiome-based drugs and diagnostics, but are prohibitively expensive for large-scale research efforts. The high cost is due to two factors: First, customers are required to sequence large quantities of DNA and RNA to adequately analyze the microbiome; and second, research projects are plagued by long turnaround times due to lower sample throughput. The proposed product will enrich microbial cells and will remove contaminants before the sequencing analysis begins. If successful, the commercial impact of this product for end-users will be substantial cost savings and the ability to expand their customer base, enabling scientific progress to accelerate in microbiome research. Accomplishing the technical aims set forth in this Phase I proposal will significantly reduce technical risk in the company's commercialization efforts by demonstrating proof-of-feasibility for a single-use device and bench-top instrument capable of enriching microbes prior to metagenomic sequencing. This SBIR Phase I project proposes to develop a microbial enrichment tool to significantly reduce the cost and difficulty of analyzing microbiomes using DNA and RNA sequencing. At present, sequencing laboratory directors only are able to analyze microbiomes at tremendous expense because samples are highly contaminated with DNA and RNA derived from host cells. The proposed solution is a disposable cartridge and a control instrument that will enable lab personnel to rapidly enrich microbes directly from samples without the use of bioengineered tags or labels that introduce bias, and enable the generation of sequencing libraries composed primarily of bacterial DNA and RNA. The technical challenges in this proposal are to convert the current laboratory method for enriching bacteria demonstrated previously into a bench-top instrument that uses a simple and disposable device compatible with current sequencing workflows that requires minimal operator steps. The system's performance in Phase I will be evaluated using spike-in samples with bacterial isolates and mock communities to simulate realistic microbiomes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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AKROBOTIX LLC
SBIR Phase I: A Universal Flight Management Unit for Unmanned Aircraft Systems
Contact
235 HARRISON STREET STE 402
Syracuse, NY 13202–3119
NSF Award
1938518 – SBIR Phase I
Award amount to date
$224,996
Start / end date
12/15/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to enable safe and reliable autonomous unmanned flight operations. Unmanned aircraft systems (UAS) are used in a growing number of applications requiring increased vehicle autonomy, such as indoor operations, civilian infrastructure inspection, precision agriculture and aquaculture, remote sensing, wildlife tracking and conservation, and package/medicine delivery. As the diversity and number of applications of autonomous UAS keep growing, platform-independent solutions to onboard autonomy become increasingly important. Potential market segments for the proposed technology are focused on the most challenging use cases such as last-mile delivery, urban infrastructure inspection, and passenger air vehicles (air ambulance, air taxi, air shuttle). Therefore, technological advances in platform-independent onboard autonomy, particularly for small unmanned aircraft systems (sUAS), can have a large positive societal impact by enabling safety and reliability of UAS. This Small Business Innovation Research (SBIR) Phase I project investigates a universal flight management unit (FMU) for nonlinearly stable and robust autonomy of UAS, in a platform-independent manner. At present, there is a dearth of nonlinearly stable and robust flight stacks that are platform/model-independent and real-time implementable on existing hardware, particularly for sUAS. Two critical challenges to be overcome for reliable platform-independent autonomy of UAS are: (A) dynamic stability in the presence of constraints on onboard processors, sensors and actuators; and (B) robustness to dynamic external uncertainties (e.g., wind, weather) and internal causes (e.g., changing payloads, onboard faults). The scientific objectives of this Phase 1 research are: (1) onboard trajectory planning, control and navigation for autonomous operations of UAS to provide dynamic stability and robustness to disturbances and sensor noise; (2) embedded software-hardware integration of guidance, navigation and control algorithms with commercially available hardware to build a FMU for onboard autonomy; and (3) experimental verification and validation of this FMU on different quadrotor unmanned aerial vehicle platforms, including a flying-wing platform. The underlying framework behind this platform-independent FMU will be nonlinearly stable and robust model-free control and estimation techniques that ensure safe and reliable autonomous operations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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AL VENTURES, LLC
SBIR Phase I: INNOVATIVE RADIATION AWARENESS FOR LAW ENFORCEMENT AND FIRST RESPONDERS
Contact
4904 AVENUE H
Austin, TX 78751–2531
NSF Award
1913420 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 02/28/2021
Abstract
The broader impact/commercial potential of this project includes protection of municipal-level first responders and local communities from radiological hazards through affordable continuous wide-area radiation monitoring (RM). Radiological threats range from the ultimate high-consequence-rare-event posed by radiological dispersal devices and stolen or unaccounted for special nuclear material to more common and routine radiological events triggered by radiological sources from construction, power, medicine, and industry. Regardless of the threat, current radiological equipment and training is inadequate, and first responders are ill-equipped to deal with radiological incidents that occur in urban environments. Due to technology and training costs, comprehensive radiation surveillance systems can be adopted by only the largest and wealthiest cities, leaving most municipalities and local first responders unprotected. The project will develop an RM system that is easily deployed, alerts to spectral anomalies as well as radiation levels, requires no specialized training for front-line operators, and is vastly more cost effective than existing systems. This RM system can be deployed in a variety of complex environments regardless of size or density. The end result is accurate, real-time mapping of large geographical areas that can be used to detect, analyze, and interpret radiation levels in a variety of environments. This Small Business Innovation Research (SBIR) Phase I project provides innovative approaches in building a spatial-temporal-spectral database of gamma radiation to monitor change detection over large urban areas. The concept is to improve general radiation awareness as well as source detection capability by having continuous monitoring. Rather than attempting to identify specific isotopes in spectral observations ? which is difficult at long distances and requires highly sensitive detectors ? it is possible to detect temporal anomalies in spectral shape by keeping a database of past observations. This provides for profound increases in detection distance or likewise, in faint source detection. For successful commercialization of the RM system, innovative research is needed in two main areas: 1) universal multi-sensor integration through boot-strapped autocalibration and integrated continuous health monitoring, which this proposal will address via field deployment of multiple sensors to characterize with novel sensor-to-sensor fusion methodologies; and 2) municipal infrastructure optimization that will permit surveys to be conducted in a distributed fashion without dedicated survey vehicles, which this proposal will address by collecting data and building operational research optimization models for key aspects of the mobile sensor deployment concept, answering critical questions on the economic viability of the approach. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ALIGN SCIENCES LTD
SBIR Phase I: Enhanced Light Generation in Printed Displays
Contact
609 TERRY ST APT B
Longmont, CO 80501–4989
NSF Award
1913948 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will stem from the advancement of material processing techniques for carbon-containing (organic) materials. Carbon is ubiquitous on Earth and conveys to materials made from it a variety of strategic and technical advantages. Advances in chemistry and materials science are increasing the utility of organic materials in the semiconductor industry. This is enabling organic materials to replace rare metals which can be ecologically damaging to mine or must be sourced from politically sensitive parts of the world. The $100 Billion display industry is leading this revolution with the commercialization of the organic light emitting diode (OLED). Critical weaknesses make the manufacturing of OLEDs extremely expensive, especially for large displays. The result is an industry-wide effort to move away from conventional semiconductor manufacturing techniques and to printing. Printed OLED displays are substantially less expensive but are 50% less power efficient. As a result, they are not suitable for devices reliant on battery power. This limits their commercial potential to less than 25% of the total display market. The proposed project will leverage recent discoveries in the properties of organic materials to develop a new processing technique for printed OLEDs. Incumbent OLED manufacturing technology orients the light emitting component of the device in a way which maximizes power efficiency. This is not currently possible in printed displays. We will develop new methods of depositing thin films of OLED materials to create oriented emitters. Based on the results of experiments, we will gain knowledge of the fundamental mechanism which enables molecular orientation in solution deposited thin films. We will use this mechanism to demonstrate that our processing technique is compatible with the display printing supply chain and facilitate future integration of our technology into OLED printers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ALLOY ENTERPRISES INC.
SBIR Phase I: Advanced bonding and cutting techniques for manufacturing solid aluminum parts
Contact
26 DARTMOUTH ST # 2
Somerville, MA 02145–3834
NSF Award
2026052 – SBIR Phase I
Award amount to date
$255,999
Start / end date
07/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in creation of a new aluminum parts manufacturing process. Aluminum is used extensively in many industries and can used in environmentally friendly applications. The proposed technology combines next-generation laminated object manufacturing (LOM) with a novel metallic bonding process and software advancements to create solid aluminum parts ten times faster than current additive technologies. This process can produce parts faster and at a lower cost compared to existing solutions. This SBIR Phase I project addresses aluminum oxidation for manufacturing applications in which the oxide layer between foils must be disrupted. The team will explore multiple bonding techniques to minimize manufacturing defects while maintaining consistency of thermomechanical properties. The project's three principal goals are: 1) establish mechanical testing and optical inspection methods, 2) develop and optimize cutting and bonding processes, and 3) create a sample part to demonstrate technical 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.
Errata
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ALTECT, INC.
STTR Phase I: Thermal Runaway and Pressure Suppression (TRAPS) for Lithium-Ion Batteries
Contact
1509 PRINCETON AVE
Austin, TX 78757–1321
NSF Award
1913998 – STTR Phase I
Award amount to date
$225,000
Start / end date
08/15/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) or STTR Phase I project is to develop and commercialize a technology to mitigate safety concerns associated with lithium-ion (Li-ion) battery technologies in electric vehicle, transportation, and energy storage applications. Li-ion battery technology is one of the most transformative innovations in the past decade and continues to provide a platform for future technology development. The potential market size for Li-ion battery technology is substantial. Fueled by growth in energy storage and electric vehicle industries the Li-ion battery market is expected to grow to over US$100 billion by 2025. Adoption of Li-ion battery technology in the energy storage market being impeding by safety concerns, namely fire and explosion hazards. The technology to be developed in this Phase I project has the potential to be a low-cost, passive solution to mitigate these hazards, and alleviate these concerns. The technology has potential to have high market penetration in energy storage and transportation industries, and will enable adoption of transformative technologies that pushes us toward a greener and more sustainable energy future. This Small Business Technology Transfer (STTR) Phase I project will explore and develop technology for passive mitigation of Li-ion battery fire and explosion hazards. For large multi-cell battery systems in energy storage, vehicle applications and among others, these hazards can damage nearby infrastructure and cause injury or death. Li-ion batteries can undergo a self-heating failure called thermal runaway that releases flammable gases. Thermal runaway poses significant challenges for available fire and explosion suppression systems because the gas release can continue unabated despite suppression of the incipient fire. Current mitigation approaches treat the consequences of the fire and do not address the root cause of the hazard, namely the production of flammable gases. The approach here is to develop technology to mitigate the root cause of the hazard and reduce the flammability of the battery gases. There is a clear need to increase the scientific understanding of passive mitigation mechanisms of hazardous and flammable gases in the thermal runaway environment. The overall objective of this project is to further the scientific understanding of these passive mitigation techniques and demonstrating proof-of-concept performance for Li-ion battery 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.
Errata
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ALVA HEALTH, INC.
SBIR Phase I: Defining the Multimodal Signature of Stroke
Contact
3 Washington Ct
Towaco, NJ 07082–0000
NSF Award
1914078 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project falls within the scope of the grand challenges in health informatics. There are excellent protocols for the management and treatment of acute stroke, however, these protocols are only effective once patients have been admitted into the healthcare system. Health care providers, however, have limited interaction with their patients, and these interactions occur in the highly constrained environment of the clinical setting. Physicians have limited control over patient behavior and limited ability to recognize stroke symptoms outside the clinical setting. For patients with high stroke risk, there is currently no system available to monitor stroke symptoms and initiate a response in real-time. Thus, there is a need to monitor patients remotely, where the current systems for stroke response fail to provide coverage. The proposed solution will expand the provision of stroke symptom monitoring to the daily lives of patients. Tracking patients as they go through their daily lives will considerably enrich our knowledge of stroke and will allow extension to monitoring for other neurological and neuropsychiatric disorders and diseases. This Small Business Innovation Research (SBIR) Phase I project addresses the real-time detection of stroke. Ischemic stroke affects 700,000 Americans, costs approximately $33 billion annually, and is the fifth leading cause of death and a leading cause of disability in the US. IV tissue plasminogen activator (tPA) has been an FDA approved therapy since 1995, yet only 5-10% of eligible patients receive this therapy. Arrival time in the emergency room after initial stroke symptoms is directly associated with better outcomes after tPA and endovascular therapy, with a time window of 4.5 hours and 24 hours for these treatments, respectively. Despite massive public health campaigns, identifying symptoms of stroke and activating emergency response systems remains a major challenge. The goal of this project is to develop and test a wearable and computational solution to effectively alert ischemic stroke victims and initiate emergency response in a timely manner. The solution will consist of a wearable device with multiple modalities, which are fed to a smartphone and a cloud-based analysis system for real-time analysis and detection. Once deployed, the device is expected to dramatically improve stroke emergency response and increase the number of patients receiving IV tPA and other reperfusion therapies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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AMBIDEXTROUS LABORATORIES, INC.
SBIR Phase I: Advanced Artificial Intelligence for Robotic E-Commerce Pick-and-Pack Automation
Contact
4070 Halleck St
Emeryville, CA 94608–3532
NSF Award
2014689 – SBIR Phase I
Award amount to date
$223,071
Start / end date
06/01/2020 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of a reliable, flexible, and scalable logistics network for distributing essential items and supplies. Recent projections suggest that by 2022, total US e-commerce sales will exceed $900 B. The market for piece-handling automation across US e-commerce is estimated at $9.6B.The process for getting items from producer to consumer involves many touchpoints where operators pick and pack individual items. These processes are currently manual and highly repetitive, incurring a high rate of injuries. Errors in these processes are costly to e-commerce providers and may result in critical supplies getting lost or significantly delayed. However, automating pick-and-pack has been challenging due to significant diversity in warehouse processes and requires new Artificial Intelligence (AI) robotic control systems that can manipulate a large number of unique items in warehouses. Innovations in AI operating systems for robotic deployments can positively impact all aspects of the national supply chain and ensure a rapid and robust distribution network of essential items and consumer goods within the United States. This Small Business Innovation Research (SBIR) Phase I project advance the translation of simulation-to-reality transfer learning for robotic picking. By generating millions of simulated robotic grasps and sensor readings, deep neural networks can be trained to reliably pick and place a wide variety of objects for a particular application. This project will develop and evaluate new algorithms for robotic piece picking to develop flexible robotic control software for material handling across a variety of physical instantiations. The research objectives are to decrease computation time for grasping policies, plan grasps across multiple tools simultaneously, and integrate grasp policies with order handling processes encountered in e-commerce distribution centers. The research objectives will be systematically tested on a standardized robotic picking system on a set of test objects to evaluate 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.
Errata
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AMBOTS, INC.
SBIR Phase I: Swarm 3D Printing and Assembly for Autonomous Manufacturing
Contact
5112 VALHALLA ST
Springdale, AR 72764–5003
NSF Award
1914249 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a swarm 3D printing and assembly (SPA) platform via the cooperation of multiple 3D printers and assembly robots. The SPA platform provides a new approach for faster and affordable large-size printing with multiple materials. It addresses several major barriers (e.g., limited printing capability and scalability, relatively high cost) for the adoption of 3D printing for business or personal use and provides commercial opportunities in different industries, such as architecture and construction. The ultimate vision of the project is to develop a model of a generic digital factory with autonomous mobile robots. This factory model can be replicated in communities around the world to create a network of smart factories as a digital manufacturing infrastructure such that on-demand, customized manufacturing becomes affordable. Similar to how the infrastructure of the electricity grid and the Internet transformed society, this envisioned digital manufacturing infrastructure will make it easier and more economical for product designers and entrepreneurs to bring new products to market without being discouraged by the complexity and cost of production and supply chain management. This Small Business Innovation Research (SBIR) Phase I project aims to expand current 3D printing capabilities with a swarm 3D printing and assembly platform (SPA). SPA synergistically integrates 3D printing techniques with swarm robotics, thus effectively addressing the issues pertaining to print time, print cost and print quality - the three objectives that current 3D printing technologies cannot simultaneously achieve. The primary intellectual merit of this project lies in a new approach to realizing cooperative 3D printing and manufacturing between multiple independent 3D printers and robots, which provides a modular and reconfigurable digital manufacturing platform. In this project, we propose a new hardware platform based on a novel mobile 3D printer with a Selective Compliance Assembly Robot Arm (SCARA) and a new software to coordinate multiple mobile 3D printers and assembly robots. This enables multi-color and multi-material printing, as well as integration of pre-manufactured components into print jobs. The anticipated technical outcome is an integrated SPA system that is capable of printing large-scale objects while assuring print quality comparable to current small-scale commercial 3D printers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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ANCHOR PRODUCT DESIGN LLC
SBIR Phase I: Rapid Design and Prototyping System for Lab-On-Chip Devices
Contact
74 MAPLE ST STE H
Stoneham, MA 02180–3130
NSF Award
2014688 – SBIR Phase I
Award amount to date
$225,000
Start / end date
06/01/2020 – 11/30/2020
Abstract
The broader impact/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to reduce cost and increase accuracy of solutions for the healthcare industry, including point-of-care diagnostics, therapeutics, and drug development, by enabling new lab-on-chip technologies. These technologies rely on microfluidic devices, small plastic parts that automatically and efficiently conduct scientific experiments with tiny volumes of liquid samples. Point-of-care devices can have a particularly profound impact on underserved communities by allowing access to testing otherwise unavailable due to cost and resource issues. The proposed system will decrease the time and expense required to develop technologies addressing these challenges. This SBIR Phase I project addresses the speed of lab-on-chip development through three main technical innovations: 1) A library of microfluidic features for design of microfluidic parts; 2) A rapid tooling system rapidly producing microfluidic molds; and 3) The macro-to-micro interface where lab-on-chip devices connect to the outside world. The proposed project will create an automated system to quickly and reliably connectorize microfluidic devices, increasing reliability and ease of use. The performance goal is a complete lab-on-chip prototyping system providing fully functional devices in less than a week. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ANKYRBIO LLC
SBIR Phase I: A Universal Drug Delivery System for Wet Epithelia
Contact
2403 SIDNEY ST STE 255
Pittsburgh, PA 15203–2194
NSF Award
1938499 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader/commercial impact of this SBIR phase I project aims to enable the use of biologics, a newer class of drugs transforming medicine due to its marked effectiveness and specificity, to treat diseases at wet surfaces of the body. Many diseases occur at wet surfaces in the body including the oral cavity, joints, lungs, and gastrointestinal tract. Local application of biologics is currently not used in these areas because the drugs are rapidly washed away before they have any benefit. Biologics are sometimes administered by infusion to treat these diseases, but this has risks of serious, even life-threatening side effects. If biologics could instead be delivered locally, side-effects would be much less of a concern and diseases at wet surfaces could be treated more aggressively and effectively than currently possible. Successful completion of the project will establish proof-of-concept for the technology and create a new platform to treat these diseases to the benefit of patients in ways that were previously impossible. The company will work with pharmaceutical partner companies to utilize their combined resources to commercialize these products and improve health outcomes. The central idea is to anchor biologics to wet surfaces so that they act for longer periods (hours or days). Traditional approaches to prolonged drug delivery use some form of problematic carrier; most cannot be used with biologics. The project will validate the technology as a treatment for common dry eye disease, using a mouse model. Antibodies are by far the largest class of biologics, and a procedure has been developed to attach anchors to antibodies while maintaining their activity. The research aims are to validate that: 1) Attaching an anchor prolongs the time an antibody resides on the cornea. The residency time on the corneal surface will be measured using fluorescently labeled antibodies with and without an anchor. 2) An anchored anti-inflammatory antibody is an effective drug to treat dry eye. The effects on the severity of dry eye disease by treating mice with antibodies with and without an anchor will be determined. These aims will test the hypothesis that attaching an anchor to a biologic increases its residency time and its therapeutic efficiency providing proof-of-concept. No other publicly known method of solving the drug washout problem in this manner to treat dry eye disease exists. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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ANTITHESIS LLC
SBIR Phase I: Cost-effective manufacturing to enable adoption of a novel nutrient-dense chickpea dough platform in mass-market processed foods
Contact
152 E STATE ST APT A
Ithaca, NY 14850–5572
NSF Award
1940271 – SBIR Phase I
Award amount to date
$225,000
Start / end date
10/15/2019 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an alternative for high-calorie, nutrient-poor, palatable foods. This proposal will create a nutritionally dense ingredient portfolio, based on a novel chickpea dough, with broad application in processed foods. The set of ingredients will consist of crunchy, high-protein, higher-fiber, and low-calorie ingredients with broad applicability in the processed food space; this could potentially impact population health, including prevalence of type II diabetes, obesity, and their co-morbidities. Such a change in ingredient sets will also result in a large commercial impact of this research. Economic benefits include the development of new products, brands, production and processing equipment to optimize the use of these novel, chickpea based, nutrient dense ingredients. This Small Business Innovation Research (SBIR) Phase I project focuses on the evaluation of a novel chickpea dough to create a nutritionally dense ingredient portfolio with broad application in processed foods. Generally, foods produced with nutritionally dense ingredients have strong flavors and poor acceptance, but alternatives require processing that is slow, inefficient, and costly. To solve this challenge, we are evaluating a novel microwave technology. The goals of the proposed innovation include: identification of formulations and processing parameters for several ingredient applications, demonstration of consumer sensory acceptance, and validation of scale-up viability through cost analysis. Technical goals include: Prediction modeling of heating patterns and identification of shapes, sizes, and ranges of processing parameters; drying trials to identify a versatile dough formulation for multiple applications; shelf stability tests; consumer acceptance tests to prove market viability; and nutritional analysis to fully characterize the final products. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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APERTUREDATA INC.
SBIR Phase I: Solving Visual Data Problems for Large Scale Machine Learning Applications
Contact
805 Rose Blossom Drive
Cupertino, CA 95014–0000
NSF Award
2015166 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/01/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to offer a unifying backend that will enable seamless and scalable visual data access for Machine Learning (ML) deployments. This is achieved by removing the need for a fragmented system design from numerous independent products in an otherwise unified pipeline. Improvements in ML have made it possible for businesses to extract insights from information-rich visual data such as images and video. Handling big-visual-data for ML and query purposes requires storage and access methods designed for visual ML. With the current off-the-shelf alternatives, ML engineers and data scientists are forced to merge unprepared data solutions to address visual data management. Businesses pay the technical debt in the form of a) extra data platform resources, b) talent mismatch when ML engineers and data scientists are forced to engineer infrastructure, and c) delayed product launches. This project creates a unified system with one solution across the various stages of ML starting from data collection, curation, to training, inference, and business queries. This Small Business Innovation Research (SBIR) Phase I project will lead to a novel data management platform designed for large-scale visual data, with an interface specialized for Machine Learning (ML) and Expert Insights queries. The project aims to build infrastructure to support thousands of concurrent clients, trillions of metadata entities, and petabytes of visual data, as will be common in the domains with increasing use of visual data. The platform is scalable without affecting performance, particularly for the emerging area of visual data management for ML deployments. The work will include visual data storage when receiving data from a large number of IoT-like devices and a ML-aware application programming interface for low-latency, high-throughput access of big-visual-data. The scalable metadata database is designed to exploit new memory technology and novel caching and tiering methods using content-based knowledge of image/video data via novel formats. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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AQUEDUCT FLUIDICS, LLC
SBIR Phase I: A Modular and Reconfigurable Liquid-handling Toolkit for Laboratory Research
Contact
2209 NAUDAIN ST
Philadelphia, PA 19146–1109
NSF Award
2011316 – SBIR Phase I
Award amount to date
$249,996
Start / end date
05/15/2020 – 01/31/2021
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project will develop a benchtop liquid-handling toolkit to increase research productivity in physical- and life-science laboratories. Movable research equipment expenditures in university science and engineering projects were $2.1 billion in 2016 alone and are anticipated to grow.The proposed toolkit will increase the output and effectiveness of researchers across many disciplines in science where significant time and personnel resources are devoted to highly repetitive protocols. With the proposed technology, a researcher without experience in robotics and programming may select devices from the toolkit, create a custom configuration, and then execute specialized protocols through an icon-based user interface. Digitized protocols can be re-run or shared to verify results and disseminate process parameters, thereby facilitating collaboration and enhancing repeatability among labs. The intellectual merit of this project is the development of a modular and reconfigurable liquid-handling toolkit. The toolkit consists of discrete devices including valves and pumps, a central hub synchronizing device actions and storing recorded data, and an intuitive user interface. The research objectives include: 1) the development and validation of the devices integral to the toolkit; (2) the testing and integration of the devices, hub, and user interface; and (3) conducting usability tests across multiple scientific disciplines. To meet these objectives, mechanical design of the devices must be completed, the devices must be assembled, a system-wide communication protocol must be developed and validated, and a user interface and web application must be developed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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ARACARI BIOSCIENCES, INC.
SBIR Phase I: Vasoreactive Perfused in Vitro Vascular Network
Contact
226 JASMINE AVE
Corona Del Mar, CA 92625–3034
NSF Award
1843331 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 01/31/2021
Abstract
This SBIR Phase I project proposes to commercially develop an in vitro (cell culture) platform to enhance the efficiency of drug discovery. Every drug delivered to a human engages the network of blood vessels for delivery to the target tissue or as part of the removal. An essential feature of the blood vessel network is an extensive network of small vessels surrounded by smooth muscle which can contract and dilate to control blood flow, and thus drug delivery. There are no in vitro human platforms that can mimic this biological function, despite the fact that cardiovascular toxicity is the leading cause of failure in clinical trials. As such, a pre-clinical tool to assess vascular toxicity would significantly impact the drug development process. Developing a successful drug averages 10-12 years and nearly $2.6 billion. Despite the fact that ~60% of the total development costs are spent on human clinical trials, fewer than 1 in 10 entering clinical trials will succeed. There is a significant opportunity to improve the accuracy of preclinical drug screening which, in turn, will generate dramatic cost savings and shorten time-to-market. The company's proposed vasoactive human vascular network represents a leap forward in technology to simulate the human response to new and existing drugs. Furthermore, the platform technology has broad future applications including the incorporation of tissue specific function (e.g, human tumor cells) and patient specificity which will further advance drug development and precision medicine. There are currently no in vitro platforms that can mimic vasoconstriction or vasorelaxation, processes which require vasoresponsive smooth muscle cells. Competing technologies line prefabricated tubes or membranes with endothelial cells to mimic the vasculature which will never be able to simulate vasoactivity. Since the company's platform is comprised of living dynamic microvessels, the company is uniquely positioned to create a platform with this functionality. The primary objective is to develop a 3D perfused human vascular network with smooth muscle providing the capacity to characterize vasoactive substances. The company will achieve the primary objective by completing two specific aims: 1) Incorporate human smooth muscle cells into a 3D in vitro vascular network; and 2) Quantify the dose-response of the 3D perfused vessel network to a panel of vasoactive drugs. Achieving vasoactive functionality in an in vitro vascular network will be the first demonstration of this critical biological phenomenon, and will meet an important commercial need in the pharmaceutical 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.
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AREANNA, INC.
SBIR Phase I: Highly power efficient and scalable hardware accelerator for AI applications
Contact
1224 ROSE ST
Berkeley, CA 94702–1139
NSF Award
1938256 – SBIR Phase I
Award amount to date
$224,996
Start / end date
10/15/2019 – 11/30/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is providing faster, cheaper and lower power alternatives to central processing units (CPUs) and graphic processing units (GPUs), making machine learning more accessible to students, engineers and scientists. In general, this will lead to faster product development and shorter time-to-market in the artificial intelligence market. Highly power-efficient machine learning accelerators make training and complex inferences possible on so-called "Edge" devices and can revolutionize the way machine learning tasks are performed for end users. By enabling fast and power-efficient Edge computing, this innovation benefits society by reducing data traffic while preserving privacy and data security since data never leave the device. The Total Addressable Market for hardware accelerators for machine learning applications was estimated to be around $1B in 2017 but will likely grow at a 50% Compound Annual Growth Rate (CAGR) until 2025 to $66 B. High power-efficiency and scalability of this innovation gives it an immense competitive advantage to penetrate different segments within this market. The proposed project aims to develop a fast, scalable and area- and power-efficient matrix multiplier for machine learning applications. Matrix multiplication is at the heart of all machine learning algorithms and is the most computationally expensive task in these applications. Most hardware accelerator solutions store inputs, weights and partial sums in memory and retrieve them sequentially in order to perform matrix multiplication. The data movements between memory and computational units dominate the overall power consumption and latency of the system. By performing computations in memory, a significant power and area savings can be achieved. This SBIR project seeks to develop a technology to perform mixed-signal matrix multiplication in memory to significantly improve the speed and power- and area-efficiency of machine learning accelerators. Phase I will involve the design and verification of a matrix multiplier that can perform machine learning tasks more efficiently. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ARMADA MARINE ROBOTICS, INC.
STTR Phase I: Asymmetric Propulsion for Enhancing Marine Maneuverability
Contact
77 MCCALLUM DR
Falmouth, MA 02540–2249
NSF Award
2026230 – STTR Phase I
Award amount to date
$255,821
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will enhance technological understanding of Asymmetric Propulsion, which will in turn enhance scientific understanding of the oceans. Asymmetric Propulsion uses a single-bladed propeller to both move and steer an Autonomous Underwater Vehicle (AUV). In addition to eliminating the need for control fins, reducing cost and complexity, and increasing efficiency, it can also allow AUVs to hold station over objects of interest. This capability has numerous scientific, military, and commercial applications because it allows the same robot to perform large-area surveys and then hold station over specific objects and perform close-up inspections. Such missions currently require multiple specialized robots and supervision from a support ship. Providing these dual capabilities in a single AUV will enable surveys without a ship, reduce costs and energy, and increase the rate and resolution of ocean studies. The focus of this Phase I project is improving control of Asymmetric Propulsion for holding station relative to an object of interest. This Small Business Technology Transfer (STTR) Phase I project will develop and test control algorithms that preserve roll stability when Asymmetric Propulsion is used to turn and maneuver torpedo-shaped AUVs. Using a single motor with an asymmetric propeller to both move and steer an AUV is mechanically simpler but computationally more complex. Holding station relative to an object by actuating a single degree of freedom is a nontrivial under-constrained control and navigation problem. This problem has numerous applications in marine, terrestrial, and aerial robotics. A simplifying approach is to implement a library of scripted behaviors that can be selectively executed based on position input from visual sensors. These behaviors will independently be constructed to reduce the sudden torques that induce roll in torpedo-shaped AUVs. This approach will lead to a successful demonstration of stable maneuverability using a surface test platform that is free to move in roll. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ARTIMUS ROBOTICS INC
SBIR Phase I: A study of the electromechanical failure modes in HASEL actuators
Contact
3380 34TH ST APT C
Boulder, CO 80301–1950
NSF Award
2014648 – SBIR Phase I
Award amount to date
$249,998
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of mechanical devices used in robotics systems. Despite advancements in AI and computer vision, robots and machines are still limited by the actuators used: Motors are heavy, expensive, and not adaptable for variable tasks, while pneumatics are plagued by trade-offs between speed and portability, low efficiency, and controllability. This Phase I project focuses on the development of Hydraulically Amplified Self-Healing ELectrostatic (HASEL) actuators - a new class of self-sensing, high-speed, soft electrohydraulic actuators with benefits in high performance, low cost, and versatility. Phase I will address the failure mechanisms of HASEL actuators in order to improve reliability and robustness for applications including industrial automation, consumer robotics, and defense. This Small Business Innovation Research (SBIR) Phase I project aims to investigate and enhance the electromechanical performance of HASEL actuators to evaluate their long-term commercial viability. The three key objectives of this project are: 1) Studying the dielectric characteristics of the HASEL actuators using material science approaches to enhance the breakdown strength of actuators, (2) Investigating the influence of inhomogeneous electric field concentration on HASEL actuators using electromechanical testing to further mitigate the influence of such effects, and, 3) Translating the results from objectives 1 and 2 to develop and characterize HASEL actuators using industrially-relevant metrics such as force output, lifetime, and specific energy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ASPERO MEDICAL, INC.
SBIR Phase I: Advanced Balloon Endoscopy Overtube
Contact
4690 OSAGE DR
Boulder, CO 80303–3903
NSF Award
2013877 – SBIR Phase I
Award amount to date
$224,031
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to address an unmet need in incomplete colonoscopy procedures, as they can result in missed colorectal cancer and ultimately increase healthcare expenditures related to follow-up procedures, with an estimated $1 B in the colonoscopy market. The proposed device will transition over 15% of colonoscopies today that are incomplete to fully screened procedures at a fraction of the cost of a colonoscopy. This proposed approach offers an entirely new manner for completing incomplete procedures to minimize costs, while improving patient outcomes and overall clinical experience. The proposed SBIR Phase I project will demonstrate feasibility of an integrated balloon overtube that can be used intraoperatively as a mid-procedure, time-efficient addition on the endoscope. Current balloon overtubes are used only in challenging conditions, due to their troublesome slippage and inefficient application, but their use during colonoscopy can significantly improve cecal intubation rates and overall outcomes. The proposed advanced balloon overtube directly addresses the need to maximize complete colonoscopies. This project will advance the development of an intraoperative tool for endoscopists. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ASTROLABE ANALYTICS, INC.
SBIR Phase I: Predictive Analytics for Battery Formation
Contact
4625 UNION BAY PLACE NE
Seattle, WA 98105–4026
NSF Award
2015127 – SBIR Phase I
Award amount to date
$250,000
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the acceleration and improvement of battery manufacturing and production. Forecasting battery safety and lifetime is largely an unsolved problem in the battery industry. For manufacturers, this uncertainty increases cell cost through control measures during production as well as the precautions taken to avoid warranty events. This project proposes "data science-as-a-service" for battery formation to address both issues. By streamlining the battery formation, test, and grading process, manufacturers benefit from reduced work-in-progress (WIP) inventory waiting for final inspection, reducing facility space requirement to store WIP cell, and reducing scrap rates and increasing manufacturing yields. The impact of these improvements will potentially enable wider spread adoption of electric vehicle applications, a major driver for battery demand. This Small Business Innovation Research (SBIR) Phase I project focuses on developing information technology infrastructure and algorithms for the prediction of battery performance during cell production. By combining state-of-the-art machine learning techniques with data management and manufacturing execution systems, battery cell manufacturers will greatly reduce the cost to operate and manage cell formation and test - an environment which has been largely underserved for innovation. The proposed project objectives will be achieved through two developing battery classification and prediction machine learning algorithms to improve early detection of battery failures. Novel implementation of the proof-of-concept algorithms in battery production environments will improve the key performance indicators of these battery manufacturers. Regression and clustering models will be used as often as possible, and the bulk of the technical work will be dedicated to the feature engineering required to elucidate changes in the change and discharge voltage profile during the first few cycles. New features will be developed by a) modelling physical processes (e.g. growth of the solid-electrolyte interphase layer) expected for a given cluster group or b) employing dynamical systems techniques like time-delay embeddings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ATOLLA TECH LLC
SBIR Phase I: Smart Sensor for Precision Agriculture
Contact
184 MAPLE AVE
Rockville Centre, NY 11570–4373
NSF Award
1842973 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to improve the current spraying practices in agriculture. Inefficient crop spraying causes drift which can lead to crop damage or unwanted pesticide use in neighboring non-target crop areas. It may contaminate nearby bodies of water or be an issue for human health. Our company would solve this through the implementation of a closed loop sensor system which would remotely determine the efficiency of sprayer machines and the spray pattern of the material continuously and in real time. Farmers will benefit through reduced costs of wasted materials resulting from over-spraying, while feeling safe against pest and fungus infestation resulting from under-spraying. The initial intended customers are large orchards, vineyards and tree farms. Those farmers generally use airblast sprayers which are highly inefficient and waste about 45% of the material. Those chemicals either hit the ground and contaminate it or pollute the air. An owner of a large farm that implements our proposed device will save a significant amount on chemical costs and also avoids the consequences due to drift of chemicals onto neighboring farms, public roads, or non-agricultural areas. This SBIR Phase I project proposes to introduce a new technology to the agricultural sector. This technology has been previously built for complex and sophisticated applications in mostly academia and government sectors. We look to provide a new functionality while reducing the size and cost of the technology. It would be used as a new and improved method of calibration, replacing a tedious and often ignored current process. Furthermore, the sensor would be integrated as a closed loop system for autonomous sprayer adjustments. A complete software solution would accompany the hardware in order to make it approachable to the non-scientific community. This project will prove the potential of our technology as a competitive player in the rapidly growing ag-tech field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ATOM BIOWORKS INC
SBIR Phase I: COVID-19 Rapid Sensing Using Structural DNA Biosensor
Contact
1201 RIGGINS MILL RD
Cary, NC 27519–8117
NSF Award
2027816 – SBIR Phase I
Award amount to date
$248,368
Start / end date
06/01/2020 – 05/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of a new rapid COVID-19 virus diagnostic system that recognizes specific virus surface characteristics and generates accurate results within minutes. The current viral diagnostics standard involves complex instruments and technical expertise to run, taking hours to produce and interpret a result. The proposed technology is a sensor that selectively interacts with the COVID-19 virus to produce visible results without expensive instruments or time-consuming procedures. The fundamental technology can also be adapted to rapidly and cheaply develop new diagnostic tests. The lower cost of the test and faster sample-to-result time will greatly improve disease measurement and control, supporting public health needs. This project proposes to develop a highly functional, sensitive and specific diagnostic for the diagnosis of coronavirus based on a Pattern-Recognition Enhanced Sensing and Therapeutics (PEST) concept. The proposed diagnostic solution uses algorithmically designed structural DNA to form a trap that will detect the “signature pattern” of the pathogen and selectively bind to it to generate a signal, without the need of DNA/RNA preprocessing or amplification associated with the current state of practice. The proposed work is to build a pre-clinical prototype of PEST-enabled lateral flow-based COVID-19 rapid diagnostics; the technical performance goal is a sample-to-result time of 5 minutes. The proposed work will also perform pre-clinical validation to validate its specificity and detection limit, as well as implement mechanisms to improve the assay specificity to avoid cross-reaction to other virus types in the Coronavirus family. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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AUTOMAT SOLUTIONS, INC.
SBIR Phase I: AI Robotics-driven Material Discovery Platform
Contact
46305 Landing Pkwy
Fremont, CA 94538–6407
NSF Award
1938253 – SBIR Phase I
Award amount to date
$224,355
Start / end date
03/15/2020 – 02/28/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to accelerate the development of new high-performance battery materials with an Artificial Intelligence (AI) robotics-driven material development platform. The platform uses machine learning and robotic high-throughput automation to accelerate effective experiment planning and minimize errors. It will potentially have a substantial positive impact on the commercialization of superior battery materials (projected to be a $14 B market by 2025), to support growth of electric vehicles and other sustainable transportation. This Small Business Innovation Research (SBIR) Phase I project aims to build a material development platform featuring a closed-loop machine learning and robotic high-throughput automation, and to develop a high-performance polymer electrolyte product for lithium batteries. The platform can potentially change how material innovation is performed and enable accelerated discovery of electrolytes and other battery materials. The platform’s workflow iterates the following: (1) initial electrolyte knowledge base collection; (2) machine-learning model training using the knowledge base; (3) new electrolyte prescription by the model; (4) parallelized experimental validation via high-throughput equipment; and (5) knowledge base updates. Phase I will help to (1) build key electrochemical and mechanical modules on the robotic system for electrolyte development, (2) improve machine learning models in terms of feasibility, flexibility, and the capability of optimizing multiple objective functions, and (3) develop the polymer electrolyte formulation in order to improve its three primary properties, including ionic conductivity, voltage stability, and mechanical modulus. It is anticipated that the platform will achieve high productivity and effectiveness, significantly improve electrolyte properties, and identify an electrolyte that meets commercialization system 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.
Errata
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AV-CONNECT, INC.
SBIR Phase I: Automated Learning of Vehicle Energy Performance Models
Contact
1054 FONTANA DR
Alameda, CA 94502–6820
NSF Award
2019458 – SBIR Phase I
Award amount to date
$255,352
Start / end date
08/01/2020 – 01/31/2021
Abstract
This Small Business Innovation Research (SBIR) Phase I project will research an internet-of-things (IoT) platform to automatically learn vehicle energy performance models (VEPMs). VEPMs are used to predict driving range and battery state of health in electric vehicles (EVs) on a per-vehicle, per-driver, per-route basis, and 8-10 times more accurately than today. It is estimated that over $150 billion will be invested in the electric vehicle ecosystem over the next decade. A significant obstacle hindering rapid EV adoption is range anxiety representing user concerns over the achievable distance and where/ when to charge the EV. Range anxiety can be alleviated by providing EV drivers with contextual intelligence on their realistic driving range and recommended charging strategy, based on travel plans, driving behavior and vehicle model. Increasing EV adoption by consumers reduces transportation system fossil fuel consumption and emissions. As part of this effort, a cloud application programming interface (API) will deliver predictions based on the learned VEPMs; this will also enable energy-aware applications such as eco-routing, eco-cruising, eco-powertrain control, and planning of charging stops, among others, both at the individual vehicle and at the fleet level. Energy-aware applications can increase the overall energy efficiency of electrified fleets. The intellectual merit of this project is to advance an IoT architecture to automatically learn VEPMs from real-time vehicle sensor telemetry and other data, such as maps and route topography. The plan is divided into three integrated goals: (1) the building of an IoT framework leveraging physics principles to capture the vehicle motion and powertrain efficiencies, as well as data-driven approaches to capture human factors, and uncertainty in maps and measurements, (2) efforts to address scalability and generalization of the learning in geographical areas with limited data and reduced expert supervision, and (3) the experimental validation of the platform on real-world driving data collected in a set of representative conditions. Statistical learning theory will be merged with predictive control theory using a mix of physics-based and data-driven models in the learning process. Scalability and accuracy will be attained by updating models in real-time using data and sharing models among vehicles of the same manufacturer. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Access Sensor Technologies
STTR Phase I: Advanced Microfluidic Devices for Point-of-Care COVID-19 Serological Testing
Contact
2401 Research Blvd.
Fort Collins, CO 80526–1826
NSF Award
2032222 – STTR Phase I
Award amount to date
$256,000
Start / end date
09/15/2020 – 08/31/2021
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.
Errata
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Active Layer Parametrics, Inc.
SBIR Phase I: Differential resistance method to profile 3D semiconductor structures
Contact
5500 Butler Ln
Scotts Valley, CA 95066–3571
NSF Award
1938643 – SBIR Phase I
Award amount to date
$224,999
Start / end date
10/15/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to reduce cost and accelerate development of high-performance electronic devices. The electronics industry is a major growth engine with enormous impact that includes health (e.g., medical devices), education (e.g. computers, internet), and cleaner energy and environment (e.g., LEDs, photovoltaics). Innovation in semiconductor device design and fabrication continue to foster faster processing speeds and larger storage capacities. However, continuing on this path requires improved metrology techniques and tools providing in-depth information about materials employed in device structures, so that the ever increasing development cost of advanced devices can be controlled. The proposed work will demonstrate a new electrical characterization method with the potential to reduce this cost and accelerate development of semiconductors for important applications such as artificial intelligence, computing, communications, transportation and energy. The proposed project targets development of a novel electrical characterization technique and tool to make measurements on three-dimensional (3D) semiconductor structures. Many advanced electronic devices employ semiconductor layers in the shape of 3D structures, such as fins, and there is an urgent need to develop metrology approaches to fully characterize such structures. The proposed innovation will generate resistivity depth profiles through 3D structures in a conformal manner. The goal is to achieve a depth resolution of at least 1 nm and develop a good understanding of dopant activation in such structures. A piece of hardware will be developed to apply the technique to samples comprising a sea of 3D features to demonstrate the concept and feasibility of the proposed 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.
Errata
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ActiveMEMS LLC
SBIR Phase I: Advanced Micro Vibration Energy Harvesters for Energy-Autonomous Internet of Things
Contact
300 Briarcrest Dr
Ann Arbor, MI 48104–6775
NSF Award
1913991 – SBIR Phase I
Award amount to date
$224,941
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this project is to address the power problem, which significantly limits the deployment and functionality of next generation wireless sensors and internet-of-things (IoT) nodes and inhibits their impact on energy and efficiency savings in the most needed areas of smart manufacturing, smart transportation, and building automation. Most high-impact IoT applications typically require miniaturization and placement of wireless sensor nodes in hard-to-service locations in vast numbers, where the battery replacement or electrical wiring is not practical or too costly. This research and development effort will explore the fundamental and technological limits of vibration energy harvesters, and development of novel micro vibration energy harvesters with high power density, multi-axis operation capability, and wider frequency bandwidth. These low-cost micro vibration energy harvesters aim to enable energy-autonomous wireless sensor nodes that will open up new markets and high-impact applications for self-powered IoT nodes, achieve energy savings and increased efficiency in multiple industries due to enabled continuous data gathering, reduce the ecological footprint of millions of wasted toxic batteries, and significantly decrease the maintenance cost of industrial IoT networks. This Small Business Innovation Research (SBIR) Phase I project aims to develop a millimeter-scale vibration energy harvester that can provide high power density, multi-axis operation capability and sufficiently wide operation bandwidth, as a maintenance-free and low-cost renewable power source for next-generation industrial IoT nodes. Existing vibration energy harvesters have limited practical applications in real life, as they suffer from large size, high-cost, low power density, high operation frequency, and extremely narrow frequency bandwidths. Moreover, commercial harvesters can only operate at a single vibrational axis and cannot harvest efficiently from complex three-dimensional vibration profiles found in real-life applications. This SBIR Phase I project will focus on novel device architectures to achieve a high-power density in a highly compact device volume and to harvest energy efficiently from low-amplitude vibrations along any spatial directions. In addition, new device architectures will be investigated to obtain further improved performance and additional functionalities. Analytical simulations and finite element analysis will be performed to optimize device performance. Prototypes will be fabricated via a proprietary advanced micro manufacturing method to obtain high-quality piezoelectric thin films on silicon wafers. Fabricated harvester prototypes will be tested at conditions simulating target 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.
Errata
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Advaita Corporation
SBIR Phase I: A knowledge base and drug repurposing platform for COVID-19
Contact
3250 Plymouth Rd. #303
Ann Arbor, MI 48105–2552
NSF Award
2029572 – STTR Phase I
Award amount to date
$255,993
Start / end date
08/01/2020 – 07/31/2021
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.
Errata
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Advanced Paving Technolgies Inc.
STTR Phase I: Asphalt Rehabilitation Utilizing a 3D Shaped Asphalt Overlay
Contact
117 Seafoam Ave.
Monterey, CA 93940–0000
NSF Award
1938570 – STTR Phase I
Award amount to date
$224,466
Start / end date
12/01/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project are to use lidar and advanced computer modeling with a 3D asphalt paving machine for asphalt rehabilitation by enabling milling only over areas where the material has broken down, then applying a 3D asphalt overlay tailored to compensate for surface deformations. This will reduce the overall footprint of the project by reducing the milling, hauling and remixing of asphalt by at least 50%, as well as reducing traffic congestion. This will produce a better, longer lasting road at a fraction of the time and cost while delivering it in a way that is much friendlier to the environment and society. Benefits of this approach are to create higher quality roads that are safer, enable improved gas mileage, and reduce vehicle maintenance costs; and faster completion of paving projects at reduced cost. This Small Business Technology Transfer (STTR) Phase I project will study an innovative method of asphalt rehabilitation utilizing a 3D asphalt overlay. Current asphalt paving machines are limited to delivering a flat layer of asphalt inadequate to address surface deformations and requiring the entire road surface to be milled flat. The goal of this research project is to transform an uneven road surface into a smooth, flat driving surface with an International Roughness Index (IRI) <=60, but without having to grind down the entire surface to a flat plane. Research will include scanning multiple test sections of roadway and using the point-cloud data to model and design the 3D shape of a compensating asphalt overlay for each test section. The asphalt overlay is then delivered by a paving machine modified to deliver asphalt in 3D. Additional scans will be performed both before and after final compaction of the test sections to assess the accuracy of predictive algorithms and provide feedback into subsequent tests. The anticipated result will show that a 3D asphalt overlay can be modeled and accurately delivered to produce a smooth flat driving surface without having to mill down the entire surface flat. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Aerogel Technologies, LLC
STTR Phase I: Continuous Manufacturing of Mechanically-Robust, Superinsulating Aerogel Monoliths and Thin Films via a New Ambient-Pressure Freeze Drying Technology
Contact
1001 W Brentwood Ln
Milwaukee, WI 53217–4118
NSF Award
2014881 – STTR Phase I
Award amount to date
$224,557
Start / end date
06/15/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to enable affordable manufacturing process for aerogel, an ultralight structural material that can reduce the fuel consumption and emissions of cars, planes, and rockets. Aerogels are a class of ultralight materials exhibiting unparalleled thermal insulation, soundproofing, and energy-absorbing properties. New structurally-durable aerogels can serve as ultralight alternatives to plastics with potential applications in vehicle lightweighting, energy-efficient buildings, and ultralight armor. The proposed work facilitates transitioning these materials to applications and reducing operating costs, reliance on typical fuels, and emissions in the transportation and construction sectors. It will also benefit artificial tissue scaffolds, apparel, bulletproof vests, and energy storage. This STTR Phase I project will advance the translation of aerogels. Manufacturing monolithic aerogels is currently challenging and expensive because of high-pressure batch processing. The proposed work will develop a first-of-its-kind, potentially continuous, accelerated atmospheric-pressure freeze drying technology to enable cost-efficient manufacturing of monolithic polymer-based aerogels of unlimited dimensions. This will require a multidisciplinary approach integrating freeze drying, fluid physics, and nanoporous media in which jet impingement arrays will be used to achieve drying rates approaching a vacuum-based process without requiring a vacuum or pressure chamber. The research will focus on mass transfer phenomena related to removal of solvent from sol-gel-derived nanoporous gel media without damaging the gel's delicate skeletal framework. The research plan includes fluid flow modeling and experiments to demonstrate process feasibility for large-scale translation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Aerosol Devices Inc.
SBIR Phase I: Development of a Low-cost, Scalable Sampler for Airborne COVID-19 Virus Detection
Contact
430 N. College Ave, Ste 430
Fort Collins, CO 80524–2675
NSF Award
2027696 – SBIR Phase I
Award amount to date
$281,000
Start / end date
06/01/2020 – 05/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of an accurate, robust tool for sampling airborne viruses, bacteria, fungi and other bioaerosols. Major deficiencies with existing sampling technologies limit their broad utility in fighting the COVID-19 pandemic, and the proposed technology could substantially inform pandemic mitigation efforts. Customers for the proposed instrumentation include public health professionals, epidemiologists, medical researchers studying infectious and allergenic airborne diseases, homeland security and the military, industrial hygienists, aerobiologists studying the microbiome of the built and natural environment, and indoor air quality investigators. This technology will have applications beyond the current COVID-19 pandemic. This SBIR Phase I project proposes to develop an urgently needed diagnostic tool for investigating whether SARS-CoV-2 , the virus that causes COVID-19, is present and transmitted as an aerosol, including as submicron particles. Existing air samplers are grossly inefficient in capturing particles smaller than 1 micrometer, and the sampling itself can damage the cellular walls and destroy genomic material. The technology proposed has a unique condensation growth tube (CGT) that collects and concentrates virtually all airborne particles from 5nm-10µm and instantly preserves the DNA/RNA, making it vastly more effective at sampling aerosolized viruses for genomic recovery. However, conventional CGT samplers are too large, expensive, and difficult to operate for widespread COVID-19 monitoring. This SBIR project will accelerate development of a simple, low-cost, scalable virus sampler for broad deployment by minimally-trained technicians. The project will fabricate several prototypes and demonstrate their efficacy both in the laboratory and in sampling airborne SARS-CoV-2 particles in key indoor locations such as medical facilities, nursing homes and/or public transportation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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Altrix Medical, LLC
SBIR Phase I: Smartphone-based Automated External Defibrillator
Contact
15504 Vine Cottage Drive
Centreville, VA 20120–3750
NSF Award
1842149 – SBIR Phase I
Award amount to date
$224,502
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to save lives through the proliferation of miniaturized automated external defibrillators that attach to smartphones. Sudden cardiac arrest (SCA) will kill more than 325,000 Americans this year outside of the hospital. An SCA can cause death if it is not treated in minutes. If an AED is available, it can save a person's life; some estimates suggest a 27% increase in the number of people who could be saved if AEDs are available and used when needed. A miniaturized AED embedded in a smartphone case could save lives by making AEDs more available and ensuring those who carry them are reachable by emergency medical services. The strategy is to equip law enforcement, firefighters, EMS personnel, and potential citizen first responders with this device and use smartphone technology to ensure they are reachable when in proximity to someone experiencing an SCA. It provides an opportunity for a new paradigm in first response: AED carriers that can be located during the first critical moments of an SCA. Through this research, hundreds of thousands of lives can be saved each year. This Small Business Innovation Research (SBIR) Phase I project will prove out the concept of a regulatory-compliant miniaturized AED that integrates with a smartphone. The work includes researching and designing components and electronics that will enable creation of this critical medical device and accomplish three overarching goals: (1) design and develop the miniaturized components, interconnects, firmware and software necessary to implement the hand-held AED Smartphone case in Phase Two by evaluating high voltage power supply and switching electronics and completing a power converter and switching design capable of generating the required energy from an on-board lithium-ion battery and supporting a bi-phasic waveform; (2) develop the smartphone software and firmware necessary to implement the device itself, guide a user through the emergency protocol, and send GPS information to EMS to allow them to locate proximal first responders; (3) integrate the hardware and software into a prototype that demonstrates a path to a form factor function unit in Phase 2. Research and designs of interconnects and encapsulation methods developed as part of this effort will offer insight into the miniaturization of myriad electronics both within and outside the medical domains. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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AmberWave, Inc.
SBIR Phase I: Ultra-Thin Silicon Solar Cells for Lightweight Flexible High-Efficiency Photovoltaic Modules
Contact
45A Northwestern Dr.
Salem, NH 03079–4809
NSF Award
1914062 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to support the societal need for higher adoption of clean renewable energy. The new kind of high-efficiency, lightweight and thin photovoltaic modules that will be enabled by this project will be ideal for integration at the factory with roofing materials for Commercial and Industrial (C&I) buildings. This will address half of the U.S. C&I rooftop market (low-slope metal roofs) that is poorly served by existing photovoltaic modules due to weight limits, wind-loading effects and other factors. In addition, it will drop total C&I rooftop photovoltaic system cost by up to 40% through reduction of installation materials and labor, as well as simplification of system design, permitting, etc. This disruptive innovation can turn C&I photovoltaic systems--today the smallest of the 3 major U.S. photovoltaic market segments--into a key driver for US solar growth. This photovoltaic module product is ideally suited for US manufacturing. The SBIR Phase I proposed project will allow the first ever exploration of Silicon heterojunction solar cells with absorber thickness substantially below 40 microns. Higher thickness silicon heterojunction solar cells have already achieved world record efficiency of over 26.5%. For the ultra-thin silicon design targeted by this project, theory predicts an open circuit voltage (Voc) of at least 780mV, well in excess of current records for any silicon solar cell. High Voc will reduce photovoltaic system resistive losses as well as minimizing system performance degradation from high operating temperatures. With respect to solar wafer technology, this would be a new kerfless approach to realizing silicon heterojunction solar cells, leading to a new type of robust flexible thin photovoltaic module, with much higher efficiency, superior reliability, and lower cost compared to current flexible thin film photovoltaic options. In this Phase I project we will target Voc of at least 720mV. We will also investigate optimizing the rear reflector design for silicon heterojunction solar cells, to maximize light absorption in the thin silicon absorber layer. Finally, we will identify a detailed path forward to 24% efficiency for this solar cell design. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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AmpX Technologies, Inc.
SBIR Phase I: Integrated Onboard Charger and Auxiliary Power Module for Electric Vehicles
Contact
387 Technology Advmnt Bldg
College Park, MD 20742–3371
NSF Award
1842929 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 01/31/2021
Abstract
The broader impact/commercial potential of this project is to develop the first low-cost and integrated onboard charger and auxiliary power module for electric vehicles, facilitating deployment of next-generation electrified transportation systems. It is noteworthy that there are more than 250 million registered passenger vehicles in the U.S. Over 40% of greenhouse gases and 70% of emissions come from the transportation sector, and transportation is 99% dependent on one source of fuel: petroleum. Mainstream adoption of electric vehicles is essential if the U.S. is to gain energy security and substantially reduce carbon emissions. The electric car industry has passed its tipping point; however, electric vehicles are still in the very early stages of development. Like early computers, the pieces that make up an electric car are large, heavy, costly and unable to efficiently communicate amongst themselves. The proposed technology not only reduces the volume, cost, and weight of onboard chargers for electric vehicles, but also enhances their efficiencies, and enables bidirectional operation to support future Smart Grid functionalities. This project will lead to creating jobs once the technology matures toward commercialization. This Small Business Innovation Research (SBIR) Phase I project will lead to design and development of an innovative integrated and bidirectional onboard charger for electric vehicles. Currently, all the upcoming and commercially available electric vehicles are equipped with an individual onboard charger to charge traction batteries and an additional auxiliary power module to power auxiliary loads. These converters are heavy, bulky, costly and need to communicate over a variety of controller area networks. The intellectual merit of this project is in the innovative topology, design, control, development, packaging, and validation of the first charger which integrates an onboard charger and an auxiliary power module. This SBIR Phase I project involves the design of the converter, investigation and design of the controller, design and implementation of the electromagnetic interference filter stage, creating the schematics and layout, thermal management, reliability analyses, enclosure design, and final alpha prototype assembly and verification. This important work will (1) lead to theoretical advancements in the design, control, and integration of power electronic converters, (2) involve interdisciplinary research in power electronics, control, packaging, and thermal management, and (3) lead to commercialization of the first integrated onboard charger and auxiliary power module for electric vehicles. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Articulate Biosciences, LLC
SBIR Phase I: Bioinert Viscoelastic Gels as Diseased Soft Tissue Lubricants
Contact
189 Tappan St
Brookline, MA 02445–5819
NSF Award
1819435 – SBIR Phase I
Award amount to date
$224,945
Start / end date
06/15/2018 – 05/31/2021
Abstract
This SBIR Phase I project aims to demonstrate the technical feasibility of a first-of-its-kind injectable gel for treating osteoarthritis. Osteoarthritis, a disease of the body's joints, affects greater than 27 million Americans, and the proposed activity will de-risk the proprietary gel technology to warrant continued development of a medical device for treating osteoarthritis. The product is a bioinspired polymer gel solution, to be administered by injection into the joint, which will lubricate, cushion, and protect the joint's cartilage from wear, and thereby slow the progression of osteoarthritis. Upon successful completion of this project, the company aims to complete the preclinical and clinical studies required to gain regulatory approval for the product emanating from the proposed activity. From this project, a deeper fundamental understanding of body-biomaterial interactions will be gained, benefiting engineers, clinicians, and ultimately patients. The anticipated commercial success of this product will result in job creation both before and after completion of product development. As joint pain is one of the leading causes of missed work, disability, and general depreciation of quality of life, successful completion of the proposed high-technical-risk project will lay the foundation for development of an impactful medical device which will treat the highly prevalent disease osteoarthritis. The innovation of this project's technology lies in the patented synthetic techniques and composition of a tissue-protective gel solution that remains in the joint capsule at therapeutic concentrations for significantly longer than current injectable gels remain. All injectable viscoelastics approved in the United States for treating osteoarthritis are comprised of hyaluronic acid, a biopolymer which degrades rapidly upon injection; in contrast, the product in this project uses a synthetic, bioinspired polymer which resists degradation and maintains effective viscoelastic properties for four months, whereas current products' viscoelasticity is degraded after one week. The project's first objective will, through a radiolabeled biodistribution study, ascertain the gel's distribution throughout the body following injection into rodent knees, to demonstrate 100% clearance out of the animal and no accumulation within any tissues or organs. The project's second objective will develop the material processing techniques and syringe filling protocol for formulating the gel into its final product form and ensuring product performance and safety specifications are met. Completion of these objectives will allow product to be made under FDA-compliant Design Control for a pivotal large animal study to be conducted following this project, along with completion of formal biocompatibility testing for submission to FDA to seek approval for a First-in-Human clinical trial. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Attogene Corp
SBIR Phase I: Development of a portable, sensitive, user-friendly electrochemical biosensor for detecting Pesticide residues
Contact
3913 Todd Lane Suite 310
Austin, TX 78744–1057
NSF Award
1940054 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2020 – 08/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a portable, faster, cheaper, more sensitive, more consistent user-friendly electrochemical biosensor for detection of organophosphate and carbamate pesticide (OPaC) residues. While OPaC chemicals have greatly improved crop yields, they have also (1) caused accumulation of pesticide residues in the food chain, (2) promoted the generation of pesticide-resistant insects, and (3) contaminated the air, water and soil. OPaC residues, therefore, are a significant public health concern. The proposed sensor will: increase the sensitivity and specificity for monitoring OPaCs (2) reduce costs associated with pesticide monitoring, and (3) improve portability of monitoring devices. Finally, the proposed biosensor technology could be adaptable for analyzing biofluids, making it transformative in monitoring environmental exposures. This Small Business Innovation Research Phase I project proposes to develop a more sensitive, field-deployable electrochemical biosensor for the detection of organophosphate and carbamate pesticide (OPaC) residues. The system’s principle is that OPaCs bind/inhibit the activity of a highly sensitive designer acetylcholinesterase (AChE) enzyme, diminishing a readily detectable electrochemical current. At the system’s core is a novel AChE enzyme more sensitive to OPaC residues than those currently in use. The approach will further optimize the performance of this novel enzyme by rationally designing variants that decrease aggregation and increase/improve thermal stability, core packing, surface polarity, and backbone rigidity. Finally, the approach will enhance OPaC detection sensitivity even further by increasing the surface area of the electrochemical sensory apparatus. Briefly, the procedure is to submerge the sensor into a buffer to acquire and assign baseline data, add test samples to allow any OPaCs to bind to the optimized AChE enzyme on the sensor, add the AChE substrate acetylthiocholine to the sample, and measure electrochemical inhibition. Taken together, this novel biosensor will result in a major shift in the way OPaC analysis is performed and pave the way for reliable, sensitive, and low-cost field 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.
Errata
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Axon Dx LLC
SBIR Phase I: Development of AI Software to Capture and Identify Circulating Rare Cells in Lung Patients
Contact
379 REAS FORD RD STE 1
Earlysville, VA 22936–2407
NSF Award
2015008 – SBIR Phase I
Award amount to date
$224,426
Start / end date
06/01/2020 – 05/31/2021
Abstract
This broader impacts/commercial potential of this SBIR Phase I NSF project is to develop Artificial Intelligence (AI) software to identify circulating lung cancer related cells efficiently and accurately. It is estimated that there will be over 200,000 new cases of lung cancer in the US in 2020, driving the cost above $166 billion. The current standard of care requires close monitoring of these patients, with chest Computed Tomography (CT) scans taken every 6 weeks. Patients also undergo pelvis CT scans concurrently if their cancer is determined to be at later stages. The proposed technology will provide the clinician additional data for early detection of lung cancer with a simple blood draw in a clinical laboratory setting for immediate feedback to the patient and clinician, thus avoiding more invasive procedures and radiation exposures. The proposed project will advance liquid biopsy techniques in R&D clinical settings. This project’s novel imaging system’s ability to identify the fluorescent tumor-derived cells will provide a more sensitive and reliable methodology to detect early-stage disease and differentiate indolent from aggressive lung cancer, with further potential to be integrated into lung cancer screening programs. Utilizing advanced Artificial Intelligence (AI) algorithms and world-class optical immunofluorescent detection methods, this project’s fluorescent microscope will be an AI-driven image processing system. This project provides an unprecedented solution for detecting low levels of rare cells in a clinical setting through the combination of high resolution multichannel optical imaging, proprietary fluorescent taggants and assays, and state-of-the-art AI segmentation and classification 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.
Errata
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BEACON STREET INNOVATIONS, LLC
SBIR Phase I: Technology for displaying computerized refreshable graphics for the vision impaired
Contact
2690 BRYDEN RD
Columbus, OH 43209–2246
NSF Award
1912959 – SBIR Phase I
Award amount to date
$224,430
Start / end date
07/01/2019 – 10/31/2020
Abstract
The broader impact of this Small Business Innovations Research (SBIR) Phase I project will be to improve access to digital content by the vision impaired community. This access will improve the quality of life for the vision impaired as well as improve the probability of employment. Multiple studies have shown a connection between Braille literacy and employment rates. Creating a tactile display not only improves access to digital media through braille usage, but also allows several new paths to interact with digital content, including through maps, vertical math and graphical images currently not accessible with existing devices. Our research into a new cell creates a basic building block for new graphical tactile displays. The proposed project targets the problem of creating a low cost and refreshable tactile display cell for the use by the vision impaired. The objective is to design, fabricate and test a series of tactile display cells and then perform a merit evaluation for both usability by the vision impaired and for scaling into low cost production. This research will draw on technology under development for computer display Braille cells, and then modify these designs for use in tactile displays. Samples will be produced based on multiple designs and evaluated for technical and economic merit. The end goal will be to demonstrate tactile display cells which are practical for use by vision impaired, allowing access to graphical information via digital media for the first time. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BEACON TECH INC.
SBIR Phase I: Harnessing Natural Language Processing for Scalable Text-based Behavioral Health Care
Contact
8 MARKET PLACE, STE 300
Baltimore, MD 21202–4113
NSF Award
1913999 – SBIR Phase I
Award amount to date
$224,835
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to address a systematic behavioral health and substance use provider shortage, cost-effectively improve patient retention in treatment, and proactively treat chronic behavioral health patients. Left untreated, these conditions cost over $1 trillion annually and result in countless early deaths. Peer support is an effective tool to engage patients unwilling or unable to access clinical care, particularly in marginalized populations. However, scaling peer support is challenging, with current online support forums rife with trolling and abuse. Our Natural Language Processing (NLP) tools can extrapolate the emotional sentiment of text messages, automatically flagging clinically relevant or critical content. This allows clinicians to easily moderate groups by focusing their time on the patients most in need, while peers generate the touchpoints necessary for day-to-day engagement. This Small Business Innovation Research (SBIR) Phase I project will greatly enhance the ability of clinicians to track the mental health of patients within a support group. Currently, a challenge in managing peer groups is identifying the health of a group as a whole - some groups can be far more constructive than others. Given the volume of messages generated in an online support group, together with expected caseloads for care manager and peer support specialists, who may be managing dozens of groups, this is an impossible task without the aid of technology. To achieve this goal we focus on three main areas: 1) improving the performance of our existing NLP algorithms by developing novel techniques to identify and track multiple conversations that might be co-occurring in the group, 2) developing a method of tracking the overall health and stability of a group by analyzing interactions among peers and 3) design new interfaces that effectively display all of the insights generated by the algorithms. These NLP tools will power a platform to give patients more access to support. Providers will have access to a novel high-fidelity data source to better triage outreach and personalize care. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BEHAIVIOR LLC
SBIR Phase I: Project PAIR: Optimized Managed Care Through Personalized AI for Individuals in Recovery
Contact
4620 HENRY ST
Pittsburgh, PA 15213–3715
NSF Award
2025931 – SBIR Phase I
Award amount to date
$255,007
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a remote monitoring system that can alert caregivers to relapses in opioid use. Over 23 million Americans are addicted to drugs and alcohol, and these addictions billions per year. Most tools to help people stay in recovery have low or mixed success rates. Reducing relapse saves lives and families and it reduces rearrests, reincarcerations, and rehospitalizations. In this proposal machine learning and pattern recognition, both forms of artificial intelligence (AI) will be aid identification of and response to potential relapse. Benefits include conserving emergency response resources, but more importantly, improving long-term intervention success. This Small Business Innovation Research (SBIR) Phase I project will establish the feasibility of identifying and predicting a future state of craving / obsession or relapse using physiological and smartphone data, a use-case where physiologically underpinned alerts alter current care coordination workflows, and a use-case where relapse after discharge from inpatient facilities for rehabilitation can be significantly averted. Technical objectives include: 1) devise a novel data-driven framework for accurately and objectively estimating probability for relapsing into opioid use using individualized classification models; 2) Deploy and assess efficacy of model risk stratification system and monitoring dashboard at addiction treatment centers through feedback from managed care providers; 3) Assess and compare efficacy of craving vs. prediction models for just-in-time interventions vs. standard practices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BENANOVA Inc
SBIR Phase I: COVID-19-impermeable high-performance porous coatings for respiratory personal protective equipment
Contact
840 Main Campus Dr. #3550
Raleigh, NC 27606–5221
NSF Award
2034453 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 07/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project encompasses development new coatings for face masks and filtration pieces for N95-grade respirators. The outer layer will repel the viral particles while the inner layer will adsorb moisture, making the mask comfortable for wear and assisting with social distancing compliance during the COVID-19 pandemic. The coatings are efficient in their function, provide reliable protection, and are durable. This technology is also highly promising for applications in other types of personal protective equipment such as gowns, drapes, medical aprons, as well as coatings on disposable medical devices. Apart from the medical sector, this platform has potential advantages for other goods, pharmaceutical formulations, and personal care products. This SBIR Phase I project proposes to develop innovative formulations for deposition of high-performance superhydrophobic and superhydrophilic coatings on textile surfaces for personal protective equipment. The technical innovation is fabrication of novel dendritic polymer particles with extraordinary high surface area and unusually strong adhesivity. The soft dendritic colloids are formed when a polymer solution is injected into turbulently sheared anti-solvent medium. Random stretching of the polymer solution droplets by the turbulent anti-solvent flow causes the polymer to precipitate in the form of soft dendritic structures. The critical technical hurdle is scaling manufacturing of large volumes of soft dendritic particles with fractal morphology. Technical objectives are: 1) develop an efficient liquid-based process for soft dendritic colloids fabrication on a bench scale; and 2) characterize textiles coated with the new formulations using a series of morphological, filtration efficiency, and breathability 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.
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BEYOND THE DOME INC
SBIR Phase I: Energy Efficient Supercritical Water Oxidation
Contact
1192 CLINTON STREET
Redwood City, CA 94061–2237
NSF Award
1843662 – SBIR Phase I
Award amount to date
$223,882
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to help wastewater treatment plants become compliant with emerging environmental regulations, while saving energy and without adding cost. It has potential to reduce the amount of biosolids that need to be shipped off-site and landfilled by up to 85% as well as completely destroy odors and pathogens. As a result, the project may also enhance social justice throughout the country. Currently, low-income and disadvantaged communities inherit waste from other communities, sometimes very far away from where the waste originated. They inherit the stench, the vectors (rats, flies, birds) and toxins. For example, 7% of the biosolids produced by New York City end up in Alabama, via trains and trucks. People living near the landfills and along transportation routes no longer use their porch because of the stench. By improving the economics of a technology that destroys organics much better than state-of-the-art technologies, wastewater treatment plants will become cleaner, less malodorous and use less energy. Other markets could open as well including clean power and chemical manufacturing. Finally, the project may lead to increased hiring of employees over the next three years. This SBIR Phase I project proposes to create an affordable and reliable process to cleanly and completely destroy organic waste, extract more resources and energy from sludge and biosolids at wastewater treatment plants while considerably reducing the amount of biosolids that need to be shipped off-site for disposal. This objective will be achieved by improving a process that uses water contained within the waste to create a hyper oxidative environment. Similar processes use costly and hazardous pure oxygen, are extremely energy intensive, and are plagued with high maintenance cost. By making innovations in energy recovery, the use of air as an oxidant instead of oxygen is possible without the large cost associated with having to heat and compress an entire air stream- oxygen plus inert nitrogen. Once optimal technical conditions for energy recovery are identified, the project will enter the design and fabrication phases. The resulting new energy recovery module will be added to an existing system. The prototype will be tested for continuous operation. New insights into energy recovery will be gained, which will benefit the scientific community as a whole. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BEZOAR LABORATORIES, LLC
SBIR Phase I: Novel Probiotic-Based Feed Additive Formulation for Enteric Methane Mitigation
Contact
1113 URSULINE AVE
Bryan, TX 77803–4952
NSF Award
1914140 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be to develop an affordable, easy-to-use, novel feed additive formulation for dairy cows that will result in reduced enteric methane production while providing financial benefits for producers. Methane is the second largest contributor to greenhouse gases and the raising of ruminant animals is a significant source. Methane is not only burdensome to the environment, it is also wasteful to the dairy industry because its formation in animal digestive systems creates a 10% loss in potential energy for meat, milk, leather, or animal labor. As such, there is growing desire from consumers, advocates, and the dairy industry to produce a more environmentally friendly product. Preliminary results of incorporating this novel feed additive formulation point towards an additional $20 of income per head from the increase in feed efficiency, along with a 50% decrease in enteric methane formation. This SBIR Phase I project proposes to develop a novel probiotic that, when paired with nitrate, will reduce enteric methane emissions in dairy cows. The research plan will include four successive 28-day periods, with 21 days for diet adaptation and seven days for data and sample collection, to assess the effects of a nitrate and P. fortis formulation. The experiment will consist of a replicated 4 x 4 Latin square design. Eight ruminally-cannulated, mid-lactation multiparous Holstein cows will be assigned to one of two Latin squares and fed each of four diets over the four periods. After completion of this study, a more precise cost-benefit analysis will be performed with the resulting data, which will include milk yields, nitrogen balance, metabolic data, and methane outputs. In addition, the plan is to examine the rumen microbiome via sequencing to better understand the mode of action. In conjunction with the product manufacturing cost, this data will be used to determine the feasibility of this product. Cost savings are expected from producing a more environmentally friendly dairy, a reduction in foodborne pathogens, a decrease in morbidity/mortality, and an increase in feed efficiency. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BEZWADA BIOMEDICAL LLC
SBIR Phase I: Development of a bioabsorbable tissue adhesive
Contact
15 ILENE COURT
Hillsborough, NJ 08844–9807
NSF Award
1937713 – SBIR Phase I
Award amount to date
$224,973
Start / end date
01/01/2020 – 06/30/2021
Abstract
The broader impact/commercial potential of this SBIR Phase I project will advance the development of a bioabsorbable tissue sealant for use in the closure of internal surgical site wounds. Wound care is associated with significant healthcare and economic costs. Surgical wounds account for the majority of acute wounds, as there are over 100 million surgical incisions a year globally, where approximately 80% require a closure product. Improper or ineffective closure of surgical wounds can result in a number of complications, including infection, scarring, improper healing, and blood loss. Currently available products for use in closing internal surgical wounds are often limited in their effectiveness due to low versatility, safety concerns, and slow curing times. An ideal tissue adhesive would provide sufficient strength and be bioabsorbable, thus providing for effective wound closure for internal and external applications. Bezwada Biomedical seeks to meet this unmet need through the development of a polyurethane-based adhesive for internal surgical wounds that is biodegradable, easy to use, and biocompatible. Successful commercialization of this technology will provide clinicians and surgeons with an effective and versatile wound closure product for surgical applications, thus decreasing the likelihood of complications that significantly impact patient outcomes and increase the costs of care. This Small Business Innovation Research (SBIR) Phase I project will develop a polyurethane-based tissue adhesive incorporating hydrolyzable linkage bridging using safe and biocompatible compounds through an innovative chemistry approach. The hydrolyzable feature differentiates the technology from existing absorbable polyurethanes and is the result of highly reactive aromatic isocyanates with a hydrolyzable link connecting the aromatic rings, allowing for safe and tunable degradation. The overall goal of the proposed program is to identify a single lead polyurethane formulation with two Technical Objectives: 1) synthesis of monomers and development of formulations; 2) assessment for physical, mechanical, functional, biocompatibility, and ease-of-use properties to identify the optimal formulation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BIOCOGNIV INC.
SBIR Phase I: Development of a Novel Diagnostic Test for Pulmonary Embolism Based on Artificial Intelligence and Spectral Analysis of Blood
Contact
4 OAK HILL DR
South Burlington, VT 05403–7344
NSF Award
2014934 – SBIR Phase I
Award amount to date
$209,881
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from the development of a fast, non-invasive, and highly accurate test to diagnose pulmonary embolism in the emergency department. In the United States, pulmonary embolism (PE) affects up to 1 million patients per year and is responsible for nearly 100,000 yearly deaths. Its diagnosis is challenging due to the presentation of nonspecific symptoms and the lack of high-accuracy screening methods. While the current standard of care is to rule out PE with an established blood test (D-Dimer), approximately 90% of those results are false positives, causing the test to be used with restraint in the clinic, and leading to both the underdiagnosis of the disease and the overuse of strongly radiative imaging methods like CT pulmonary angiograms. A new, highly specific test for PE could increase patient safety, standardize clinical care processes, reduce costs and save lives. This Small Business Innovation Research (SBIR) Phase I project will develop and validate a new diagnostic tool for PE based on the combination of fast blood spectroscopy and modern machine learning (ML) algorithms. A key aim of the research is demonstrating that ML combined with blood spectroscopy can substantially outperform the D-Dimer biomarker test, which has notoriously low specificity (~40%). An important Phase I milestone will be to show that the specificity of the resulting PE test either (a) already surpasses that of the D-Dimer test when trained on the relatively small dataset used in this Phase I proposal, or (b) substantially increases with the size of the training dataset, so that the test can outperform D-Dimer simply by procuring a larger pool of blood samples. The technical challenges addressed in this phase include evaluating different spectroscopic methods and modalities, minimizing the coefficient of variation for spectra acquisition, as well as designing and optimizing ML models for one-dimensional spectral 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.
Errata
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BIOME HEALTH, INC.
SBIR Phase I: CapScan: Non-Invasive Sampling and Analysis of the Human GI Tract to Advance Inflammatory Bowel Disease Research
Contact
26160 RANCHO MANUELLA LN
Los Altos Hills, CA 94022–2034
NSF Award
1936687 – SBIR Phase I
Award amount to date
$224,079
Start / end date
02/01/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a tool to non-invasively measure inflammatory markers, microbes and metabolic profiles inside the human gastrointestinal (GI) tract for a variety of medical conditions. Initially, the device can be used for the diagnosis and management of inflammatory bowel disease (IBD). This device and the data it collects will be used to improve the treatment of obesity and related metabolic disorders, such as type II diabetes, that cumulatively cost the US economy over $200 billion per year. Given the centrality of gut physiology to human health, there will likely be additional uses of the technology in monitoring human health, eventually making it as routine and informative as a blood test is today in the practice of medicine. This Small Business Innovation Research Phase I project will deliver a pill-sized device to the distal small intestine region of the human GI tract and trigger the collection of the luminal contents in that region. The device will need to accommodate tremendous variation in the physiology of the human gut. The sampling device will encounter a biochemical environment ranging from pH 1 to pH 8. The time required for normal peristalsis to deliver the sampling device to the desired region of the GI tract will vary from 3 to 10 hours. Furthermore, cost and safety constraints strongly favor the use of a passive device with no actively powered sensors or actuators. A multidisciplinary approach using mechanical and material science innovations can meet these challenges and make the proposed device a platform sampling technology for IBD, and GI disorders in general. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BIOMIMICRY DESIGN ALLIANCE, LLC
SBIR Phase I: Genius of Place Database
Contact
1229 KRAMERIA ST
Denver, CO 80220–2714
NSF Award
2015132 – SBIR Phase I
Award amount to date
$224,297
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to bring biomimetic ideas to traditional architecture. This project consists of a development of a robust and innovative database to catalyze incorporating scientific concepts into designs for the built environment. This project will inspire the design of naturally resilient structures. This SBIR Phase I project proposes to develop an innovative sustainability tool that abstracts the knowledge of biology from scientific literature and makes it available to architects and designers such that the built environment sector can support biomimetic ideas implementable in terms of material availability and structural codes. The project will be organized by building challenge category, biome, and function. It will filter champion organisms that have already solved the specified function, and provide translated principles and images to explain the solution. The project will interpret, capture, store, and systematically distribute their translation of natural systems models for diverse application in the built environment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BIOSENIX LLC
SBIR Phase I: SenixBand - Remote Independent-Living Monitor and Frailty Status Tracker for Older Adults
Contact
6549 W IVY MOUNTAIN WAY
Tucson, AZ 85757–1502
NSF Award
1914287 – SBIR Phase I
Award amount to date
$224,595
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will revolutionize the way older adults who live independently at home are monitored. According to the American Association of Retired Persons (AARP), nearly 90% of older adults (age 65 and above) prefer to stay independently at their homes, coining the term "ageing in place". The proposed monitoring system monitors older adults in real time for changes in physical activity, falls, and loss of balance. These parameters can indicate changes in frailness in older adults which if addressed early can extend their period of independent living. The system will monitor blood pressure, heart rate, heart rate variability, and common cardiac conditions that often accompany loss of balance or falls, which can trigger early and more informed intervention that will allow issues to be addressed before a more serious injury occurs due to a fall. Current industry solutions rely on reactively initiating assistance after a fall is detected, which are usually too late to reverse the age-related deterioration and are ineffective at extending independent living. Ability of living independently longer for older adults will translate into significant savings in cost of care and will also improve their wellbeing. The proposed project will develop an end-to-end monitoring systems for older adults living independently at home consisting of: 1) Development of a small wearable device for measurement of Heart Rate, Pulse Oximetry, Blood Pressure, and ECG; 2) Development of activity monitoring system and classification of activities that can be used in tracking frailty of a monitored older adult. Changes in frailty can be observed remotely, allowing for early intervention and potentially the ability to reverse physical or mental degradation. In addition, the system can assist in the decision when the older adults need a full-time caregiver to remain at home, which is difficult and usually preceded by some serious accident or medical emergency, such as a fall resulting in hospitalization or a serious illness. Such delayed decision can have serious life-threatening consequences. The advancements will be made in activity monitoring, non-invasive continuous blood pressure monitoring to track changes in blood pressure, and integration of anomaly detection into ECG waveform analysis to provide additional information when loss of balance or fall occurs. Such real time monitoring will tax the battery of the wearable device and will be addressed by exploring anomaly-based energy management to prolong battery life. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BIOZ, INC.
SBIR Phase I: Development of a Semantic Search Engine Using Natural Language Processing to Generate Validated Technique-Based Recommendations for Life Science Research Methodology
Contact
316 STATE ST STE 200
Los Altos, CA 94022–2815
NSF Award
2014969 – SBIR Phase I
Award amount to date
$225,000
Start / end date
04/15/2020 – 03/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of an artificial intelligence (AI)-supported search engine that facilitates reproducibility and efficiency in life science research. Development of the proposed technology will allow researchers to quickly access unbiased recommendations on techniques and products to advance scientific discovery. By streamlining the literature search process and optimizing research at the experimental design stage, researchers are able to avoid lengthy trial-and-error in the laboratory and accelerate productive experiments. By providing researchers with literature-supported and relevant experimental recommendations within minutes, the proposed search engine can spare researchers time and resources spent on experimental methods poorly suited to their research goals, while also enabling researchers to explore promising methods potentially outside their standard operations. This Small Business Innovation Research Phase I project seeks to address the persistent problems of experimental inefficiency and irreproducibility that slow life sciences research. Phase I efforts will advance the development and evaluation of a proof-of-concept search engine for recommendation of techniques associated with antibodies, a filter mechanism capable of refining search results, and automatically generated graphical analytics presenting key data on technique usage. Leveraging machine learning and Natural Language Processing (NLP) to scan the entire body of peer-reviewed literature and extract data relevant to technique-based search terms, search outputs will accordingly rank antibodies and protocol conditions. To filter results, constraints, such as access to equipment or target genes, will be imposed through development of NLP algorithms capable of identifying relevant contextual information indicating conformance to imposed criteria. Accuracy and relevance of the developed platform's search results will be compared to a popular research-based search engine and is expected to demonstrate highly refined search outputs and recommendations, supporting improved experimental design. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BLEEXY, LLC
SBIR Phase I: Dynamic Product Experience Protocol and Marketplace
Contact
11561 STUART MILL ROAD
Oakton, VA 22124–1117
NSF Award
1941282 – SBIR Phase I
Award amount to date
$250,000
Start / end date
01/15/2020 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to create a platform where content creators can upload digital content and retailers can easily integrate and get curated product content. Moreover, such a platform should give the opportunity to brick-and-mortar stores to create on the fly e-stores (buy-online, pick-up in store). Such a platform will bring a new supply side capability to e-commerce that will serve to enhance competition. The proposed innovation provides data robustness and relevance to the retail industry. This SBIR Phase I project proposes to create a decentralized e-commerce infrastructure allowing retailers to access and deliver trusted, rich product data content across all digital channels. This project will advance a decentralized Dynamic Product Experience Protocol and Marketplace (DPXM) to create a comprehensive digital product data catalog, to be validated through a Proof-of-Quality (PoQ) consensus algorithm. This project’s goal is the optimization of the PoQ algorithm to generate random graphs and temporal random networks to accommodate for a continuously expanding network, to prevent copyright and IP infringements, the clustering of hostile agents to impose specific content that benefits them and to ensure the fairness of agent selection and payment. The algorithm will adjust the parameters needed to compute the trustworthiness scores of the participating agents. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BLOSSOM SURGICAL LLC
SBIR Phase I: New laparoscopic power morcellator with containment system for minimally invasive surgeries.
Contact
3333 SE CRYSTAL SPRINGS BLVD
Portland, OR 97202–8425
NSF Award
2014749 – SBIR Phase I
Award amount to date
$224,892
Start / end date
05/15/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this SBIR Phase I project is to advance the development of a novel system for abdominal minimally invasive surgery (MIS). The proposed procedure will be a safer, cleaner, and more efficient method of removing tissue specimens, such as a uterine fibroid, uterus, kidney or spleen, through a small incision. Existing MIS methods and instruments are not yet optimized for the removal of the separated tissue from the cavity without enlarging an incision or limiting the surgeon's visualization and maneuverability. The proposed method will use novel, safer and more efficient instruments developed for the removal of large tissue specimens via MIS. The proposed project will explore translation of an integrated power morcellator and containment system for cutting and removing large tissue specimens from inside a cavity without subsequent contamination. The proposed project is to conduct tests with standard MIS equipment, including a 5mm 30 degree angled laparoscope, laparoscopic camera, light source and monitor, and a CO2 rapid insufflator. The specimens to be cut will be beef tongue and potato, which is representative of a fibroid uterus. The proposed project will inform a surgical protocol to 1) improve safety and efficiency, and 2) prevent cavity contamination by the removed tissue. The simulator and trocar sleeves will be evaluated for traces of tissue contamination using the highly-precise ATP test. The project will explore the parameter space associated with the procedure, including the maximum time the power morcellator is in the on position, blade temperatures, and cavity pressure; as well as post-procedure examinations of the blades and shaft for cracks and fatigue fractures; and of the containers for abrasions, punctures and 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.
Errata
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BLUE CRANIUM, LLC
SBIR Phase I: Cognitive Communications Payload Module for CubeSat Applications
Contact
20525 CENTER RIDGE RD STE 614
Rocky River, OH 44116–3424
NSF Award
2025828 – SBIR Phase I
Award amount to date
$255,937
Start / end date
08/01/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance communications and on-board processing capabilities for small satellites or CubeSats, which is important with growing civil and commercial demand for satellite communications services. The proposed payload module provides a number of cognitive communications functions focused on intelligent networking capabilities for CubeSat platforms and swarms. These functions enable robust, reliable global connectivity by allowing for customer CubeSats to efficiently and autonomously communicate within swarms and with other networks for applications including Earth observation, sensing, situational awareness, new space, and communications. This Small Business Innovation Research (SBIR) Phase I project will develop and demonstrate a flexible, comprehensive cognitive communications payload module to enhance communications functions in networking for CubeSat platforms and swarms. This project will demonstrate the technical feasibility of the proposed innovation, apply advanced and emerging on-board processing and communications technologies, and develop and integrate hardware and software to develop a prototype payload module for CubeSat applications. The prototype will perform several cognitive functions allowing for intelligent networking for CubeSat platforms and swarms: intelligent routing, network self-healing, ad-hoc networking with other available networks, and data store and forward capabilities for sparse networks and network build-up phase. Autonomous operation will improve data transmission, data packaging and routing, latency mitigation, and user-initiated services for commercial, government, and academic CubeSat operators. This effort will focus on three key areas: 1) developing the cognitive engine architecture and software, 2) acquiring and integrating a software-defined radio and single-board computer, and 3) developing an appropriate API. The objective of this project is to prototype the cognitive communications payload module in preparation for testing, demonstration, flight qualification, and commercialization. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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BLUSPHINX INC
SBIR Phase I: Synthesizing Business Software Customizations
Contact
3215 DOE RUN
Austin, TX 78748–1814
NSF Award
2026005 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from enabling small companies to enjoy affordable, customized ERP (Enterprise Resource Planning) systems. An ERP system is a platform integrating a centralized database with functionalities to support the core business processes. A customized solution can generate substantial efficiency gains, economic savings, and competitive advantage, but this has typically required specialized expertise unavailable to small firms. This project will generate a solution to help small businesses remain competitive. This Small Business Innovation Research (SBIR) Phase I project will build on recent advances in program synthesis to automate software customizations in an ERP. The specific rules and requirements of a company are expressed as a set of easy-to-write declarative rules. The ERP synthesizer will automatically ensure that a combination of tasks is guaranteed to obey all specified rules. This project will build a tool to automate most ERP customizations while minimizing many classes of software errors by construction. This project will also explore the trade-offs of using this 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.
Errata
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BOX ROBOTICS, INC.
SBIR Phase I: Enabling Safe, High-Speed Autonomous Mobile Robots in Warehouse Environments
Contact
2025 WASHINGTON AVE
Philadelphia, PA 19146–2632
NSF Award
2026137 – SBIR Phase I
Award amount to date
$255,730
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of an autonomous mobile robot (AMR) software stack designed to safely optimize material movement throughput in warehouses. Currently, AMRs in warehouses operate at less than half the speed of their human-driven counterparts due to the robot’s limited perception capabilities. A consequence of this decision is a dramatic reduction in the vehicle’s potential throughput, translating to a smaller facility fleet size with associated cost and material savings. Improved AMR operation will address warehouse labor shortages and improve safety. According to the Occupational Safety and Health Administration (OSHA), there are roughly 85-90 forklift fatalities each year, and over 7,000 injuries requiring days away from work. By automating forklift trucks with the proposed software stack, these safety incidents will be significantly reduced. This project will develop software associated with safer AMRs based on systems used in autonomous cars. This Small Business Innovation Research (SBIR) Phase I project is developing a software stack for autonomous mobile robots (AMRs) in warehouses to improve AMR agility and spatial awareness to human-like levels. The proposed innovation takes inspiration from advances in self-driving cars through the use of high-definition (HD) mapping and three-dimensional (3D) perception. These HD maps will leverage the latest advances in 3D LiDAR systems and deep learning approaches for object detection, enabling operation at higher speeds. This project will enable safe increases in AMR speeds from 2.0 to 3.0 m/s. To ensure vehicle safety is not compromised, systems will be tested to and meet the American National Standards Institute/Industrial Truck Standards Development Foundation (ANSI/ITSDF) B56.5 safety standard for object detection 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.
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BRILLIANTMD, LLC
STTR Phase I: CLEAR: Reducing Claims Denials in Healthcare Through Blockchain and Machine Learning
Contact
2607 EUCLID AVE
Austin, TX 78704–5418
NSF Award
1914203 – STTR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to create transparency around the business logic used by stakeholders in the healthcare system to make transactional decisions as well as create alignment around the current status of healthcare transactions that are part of the work in process. To most people who interact with the healthcare system, it functions more or less as a "black box" with decisions that sometimes defy logic and common sense. Our goal is to use Blockchain and Machine Learning technology to convert this "black box" into a "glass box." The commercial impact of this project could be an up to 25% reduction in claims processing costs for healthcare providers by the elimination of redundant work, re-work and errors. This STTR Phase 1 project proposes two innovations: 1) claims transaction and reason codes managed through a Blockchain so that Providers and Payers can confidently know the accurate status of a claim, and 2) sophisticated statistical and deep learning algorithms for predicting the likelihood of a claim denial with natural language processing of associated notes and appeals. Our product is a mathematically driven software service that utilizes and innovates with multiple technologies: Blockchain distributed ledgers, smart contracts and tokens, and prediction, recommendation, forecasting, non-linear optimization and natural language processing engines within a privacy-preserving data management 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.
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Bansen Labs LLC
SBIR Phase I: Open hardware and software platform to enable configuration and control of IoT devices for people with disabilities
Contact
1234 Forest Green Drive
Coraopolis, PA 15108–2771
NSF Award
1939533 – SBIR Phase I
Award amount to date
$249,702
Start / end date
12/01/2019 – 11/30/2020
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to improve the access of people with disabilities to the growing ecosystem of Internet of Things (IoT) technologies, thus improving their ability to be independent, connect with others, seek and retain education and employment, and contribute to society both economically and socially. In particular, nearly 20 million US citizens live with disabilities affecting upper limb movement, thus impacting their ability to configure and control devices around the home. This project aims to develop an open platform that allows these consumers customized control of their home devices, using assistive input controls such as adaptive joysticks, sip-and-puff inputs, chin switches, or eye gaze, as well as off-the-shelf consumer input devices such as trackpads or mice. The proposed project would advance the consumer Internet of Things (IoT) landscape by enabling end user programmability for IoT applications, giving end users (non-programmers) the ability to modify, control, and automate their devices and services. Our system will draw on a newly patented device control architecture with novel customizability and intuitive access to non-programmers. The use cases supported by the platform would previously have required engineers to spend days or weeks of dedicated time building custom solutions for users; instead, the platform will make these use cases available to non-technical users on a wide scale without requiring custom engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BassInSight, Inc.
SBIR Phase I: Tool to estimate object visibility to fish in complex aquatic environments.
Contact
2112 Burlison Dr.
Urbana, IL 61801–6606
NSF Award
1913419 – SBIR Phase I
Award amount to date
$224,977
Start / end date
08/01/2019 – 11/30/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop tools that will create vast amounts of water quality data for the nation's inland, fresh waters. The data allow for direct environmental monitoring and for validation of other remote sensing GIS techniques to measure inland water quality. Algorithms will also be developed to use the data to allow anglers to customize their selection of lures based on the time and location where they are fishing. The difficulty for the angler is anticipating which lures are most visible to the fish, because fish see differently than humans. This project develops software tools and water quality sensors that allow anglers to customize their fishing strategies for any type of water. The product will ultimately recommend lures that work well for a given location based on the properties of the water, the properties of the lures, and the visual capabilities of fish in that environment. The proposed project will measure the optical properties of (a) lakes and rivers. First-generation photometers would be constructed to estimate the sub-surface transmission and light-levels at three wavelengths and capture relevant water quality data. The project also proposes new methods to accommodate the selection of fluorescent pigments on lures. Algorithms will use the data to estimate the visual contrasts as perceived by certain species of fish and determine which lures have the highest probability of success for that species - bass in the first instance. The novelty of this approach is that it relies on estimating critical lighting parameters at three wavelength bands. Traditional methods rely on spectrometers that estimate spectra with thousands of data points and are not feasible for anglers. This project directly tests whether 3 well-spaced data points can accurately estimate lighting environments, visual signals, and their transmission in diverse water bodies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Belmont Scientific Inc.
SBIR Phase I: Development of Safe, Energy Dense, High Performance Lithium Ion Batteries
Contact
633 Trapelo Road, Suite 105
Waltham, MA 02452–7921
NSF Award
1940056 – SBIR Phase I
Award amount to date
$225,000
Start / end date
10/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the ability to detect and prevent fires in lithium-ion batteries. Lithium-ion batteries have become the preferred mode of energy storage and reuse in numerous applications ranging from mobile phones to aircraft. The low safety of current Li-ion batteries has led to a number of accidents in various applications ranging from computers to electric vehicles and aircraft. Excessive heat release from one cell can compromise the safety of the entire battery pack and the host system. By eliminating the potential for fires in each cell, the proposed technology will enable the construction of larger format cells to reduce the battery integration costs. Improved safety also will usher in the move towards higher energy density cells and open new applications that can benefit from Li-ion batteries. The projects potential societal impacts include significant revenues if successful, increased safety and even lives saved, increased penetration of energy storage and associated environmental impacts. This SBIR Phase I project proposes to develop an innovative technology to improve the safety of Li-ion batteries and prevent fire due to manufacturing defects, abuse and abnormal use. In today's batteries, these failures trigger exothermic reactions that can transition into uncontrolled thermal runaway. The resulting fires have impacted the safety of various systems ranging in scale from small (mobile phones and computers) to very large (aircraft). The objective of this effort is to develop a technology embedded in a compact sleeve that slides over the cells in a battery pack to passively detect the conditions and isolate the failing cells to prevent their thermal runaway. The Phase I research consists of designing the safety sleeves for select Li-ion battery chemistries and geometries, then demonstrating their effectiveness in detecting and preventing thermal runaway in both individual cells and in battery packs. The results from Phase I research will be used to design prototype sleeves for additional battery sizes, shapes and chemistries that will be tested further in Phase II. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BioAmp Diagnostics, Inc.
SBIR Phase I: Development of point-of-care diagnostics to direct the appropriate use of antibiotics for the treatment of high-risk urinary tract infections
Contact
845 Sutter Street
San Francisco, CA 94109–6109
NSF Award
2014629 – SBIR Phase I
Award amount to date
$224,996
Start / end date
05/01/2020 – 04/30/2021
Abstract
This Small Business Innovation Research Phase I project will provide critical development of a rapid diagnostic test capable of delivering the antibiotic resistance profile of a sample collected from patients suspected of suffering from urinary tract infections (UTIs). In the US there are approximately 8 million UTIs, and an increasing number of are caused by drug-resistant bacteria that significantly complicate the treatment of these infections. In general, patients suffering from a drug resistant UTI take longer to receive appropriate treatment, resulting in a greater risk of disease progression and onset of secondary comorbidities. Diagnostic tests that can rapidly identify drug-resistant UTIs will have a strong and positive impact on the treatment of these infections. The proposed work aims to optimize and expand the diagnostic capacity of a first-generation diagnostic assay to create a fully comprehensive test that can detect a drug-resistant UTI in minutes. The proposed SBIR Phase I project will advance the development of a dual-enzyme trigger-enabled cascade technology (DETECT), developed to detect low-abundant beta-lactamases produced by uropathogens to hydrolyze beta-lactamase antibiotics, rendering them ineffective. The presence of beta-lactamase-producing uropathogens can greatly complicate clinical decision-making because these pathogens are regularly resistant to the first-line antibiotics considered for treatment of urinary tract infections (UTIs). DETECT, applied as a diagnostic system, holds the potential to significantly improve the care of UTIs because it enables rapid identification of beta-lactamase-producing uropathogens directly from urine samples. The clinical feasibility of the technology has been demonstrated previously using clinical urine samples, first targeting a subset of beta-lactamases known as CTX-Ms. The proposed work aims to tune and optimize the first-generation system to offer a comprehensive diagnostic test that can accurately identify all of the clinically important beta-lactamases. This technology provides a simple, low-tech, and cost-effective way to inform patient treatment without the need of processing, urine sedimentation or centrifugation, or sophisticated instrumentation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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BioLum Sciences, LLC
SBIR Phase I: BioSense AMD - A Point-of-Care Device for Monitoring Airway Inflammation
Contact
2450 Holcombe Blvd Ste J
Houston, TX 77021–2041
NSF Award
2015081 – SBIR Phase I
Award amount to date
$224,808
Start / end date
05/01/2020 – 12/31/2020
Abstract
This Small Business Innovation Research (SBIR) Phase I project aims to develop a point-of-care biomedical device for the rapid and quantitative measurement of airway inflammation. Currently, methods to measure airway inflammation and disease control are difficult. Recent innovation in breath analysis has provided opportunity to better understand airway disease. However, the reach of these innovations has been limited due to cost and availability. Chronic lower respiratory diseases including asthma, chronic obstructive pulmonary disease (COPD), emphysema, and pulmonary hypertension are the fourth leading cause of death in the United States and a leading cause of death worldwide across all countries and income levels. There is an urgent need for methods to better monitor and manage these chronic lower respiratory diseases to improve survival and patients’ quality of life. Using an advanced chemical system, the proposed technology will measure a biomarker of inflammation in exhaled breath condensate (EBC). Success of this project will deeply impact fundamental pulmonary research and create broad societal value by improving health and reducing burdens on the healthcare system. This will be particularly valuable to underserved urban communities where poor air quality leads to increased severity of respiratory diseases. This product also has significant commercial potential, with the ability to reduce costs and streamline treatment in an industry valued over $100 B annually. This Small Business Innovation Research (SBIR) Phase I project aims to develop and implement an advanced proprietary automated chemiluminescent reagent mixing and detector system for instantaneous measurement of airway inflammation by real-time breath analysis. Hydrogen peroxide reports on airway inflammation, which is a critical factor in respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD), but is difficult to accurately measure at the point-of-care. The current methods of choice include highly invasive bronchoalveolar lavage (BAL), time-consuming and costly laboratory hydrogen peroxide assays, or fractional exhaled nitric oxide (FeNO), which provides an incomplete picture of airway inflammation. This project will fill this analysis gap and provide a valuable solution to monitoring airway inflammation in patients at the point-of-care. The proposed aims for developing a system to measure exhaled hydrogen peroxide in Phase I will include: a cartridge-based reagent delivery and mixing designed to optimize limit of detection and reproducibility; a robust and compact reader equipped with optimized photon detection technology and built-in vortex mixer; and careful analysis of sensitivity and selectivity for hydrogen peroxide versus potentially interfering analytes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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Bioinfoexperts, LLC
SBIR Phase I: RAPID Integrated and automated genomics platform for hospitals responding to COVID-19
Contact
PO BOX 693
Thibodaux, LA 70301–4904
NSF Award
2027424 – SBIR Phase I
Award amount to date
$256,000
Start / end date
05/01/2020 – 03/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be a user-friendly and scalable infection control surveillance software platform using advanced biotech and data analytics for monitoring the COVID-19 pandemic. The COVID-19 pandemic highlights the need for rapid testing, analysis, and tracking. The innovation provides access to next-generation sequence technologies to healthcare facilities, as well as a centralized system to integrate and share hospital-level data with microbial information to be shared on any geographic scale. The platform automates the analysis of bacterial and viral data, delivering simplified and clinically relevant results via interactive web interfaces. The proposed technology offers important data to clinicians and other experts. The intellectual merit of this SBIR Phase I project is to generate the largest collection of SARS-CoV-2 whole genomes with matched respiratory microbiomes for clinicians to rapidly test medical hypotheses for diagnostic and prescriptive use. Our project has three major objectives: 1) incorporate an automated analytical pipeline to process whole genomes of infecting strains of SARS-CoV-2; 2) integrate viral genomes with patient microbiomes and clinical records, and; 3) deliver clear, easy-to-interpret results via an interactive web interface. The infection control cloud-based software platform solution enables “precision epidemiology” integrating pathogen genomics with clinical and patient demographics to improve patient outcomes and enhance the capability of the health system for infection control and surveillance. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Biomineral Systems LLC
SBIR Phase I: Broad Spectrum biorational bio- and synthetic insecticides and mosquito repellents
Contact
3315 Bremen Hwy
Mishawaka, IN 46544–9346
NSF Award
1938569 – SBIR Phase I
Award amount to date
$224,982
Start / end date
02/01/2020 – 10/31/2020
Abstract
The broader impact/commercial potential of this SBIR project proposing a novel broad spectrum insecticide safe for humans, expected to be safer than synthetic insecticides. It will be used in conventional and organic farming, as well as personal protection/mosquito repellent products, costing significantly less than the products currently on the market. Crop losses due to insect pests cost billions of dollars and the limited classes of insecticides are vulnerable to the constant threat of resistance. In addition, the lack of specificity creates broad risks due to pesticide residues polluting food and water and causing environmental damage. In particular, organic farming needs effective bioinsecticides for economically sustainable yields. The proposed product will have applications to other mosquito-borne diseases without adverse effects on human health. This SBIR Phase I project proposes to combine an effective insect protein target with a new class of molecules. In particular, a single molecule and its analogs derived from easily produced and cheaply priced natural products create new options for cost-effective and scalable de-novo synthesis for mass production. A few separate molecules from this general class have been shown to possess the right mechanism of insecticidal activity specific to insects (not humans). The specific protein target has a well conserved active site across arthropods (insects). Preliminary technical feasibility has been established and the Phase I work plan will validate proof-of-concept for the proposed solution. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Bitome, Inc.
SBIR Phase I: Automated microfluidic reaction monitoring via miniaturized NMR spectroscopy
Contact
90 Forest Hills St, Unit 3
Boston, MA 02130–2935
NSF Award
2002683 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader/commercial impact of this Small Business Innovation Research Phase I project is to develop a commercially-viable miniaturized nuclear magnetic resonance (NMR) spectrometer for automated small molecule monitoring and analysis. The project aims to address major obstacles preventing widespread adoption of NMR spectroscopy. The proposed innovation is a miniaturized, cost-effective, and user-friendly NMR system, thus addressing major obstacles preventing widespread adoption of this powerful analytical method. It will be suitable for placement in industrial manufacturing environments to provide chemometric insights on complex solutions, resulting in reduced manufacturing costs for a wide range of high-value biochemical products. The proposed innovation constitutes a platform technology with a broad range of applications. The proposed SBIR Phase I project will be to advance the development of NMR spectroscopy. The proposed point-of-need, microfluidic, push-button NMR spectrometer presents technical challenges in the areas of hardware miniaturization for mass production, automated turnkey design, multidimensional pulse sequence design, and assisted post-processing annotation. The proposed project will explore the trade space defined by low instrument sensitivity, as a compromise due to permanent magnets with limited magnetic field strengths. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Bloomlife, Inc.
SBIR Phase I: A noninvasive, low-cost, point-of-care wearable electronic patch for continuous pregnancy monitoring
Contact
1931 MCALLISTER ST Unit D
San Francisco, CA 94115–4330
NSF Award
1843361 – SBIR Phase I
Award amount to date
$224,890
Start / end date
02/01/2019 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve high-risk pregnancy care and preterm labor detection by developing a noninvasive, low-cost, point-of-care wearable electronic patch for pregnancy monitoring in both clinical and home environments. Each year, 4 million women give birth in the US. More than one in ten of pregnancies is considered high-risk, where the mother, fetus, or newborn has elevated risk of experiencing an adverse health condition. The proposed platform will allow doctors to remotely monitor and manage high-risk pregnancies and intervene, as needed, upon detection of labor or other potential complications. By enhancing early detection of fetal well-being and increasing access to care, the device will allow for improved healthcare delivery, thus increasing mother and infant safety, preventing maternal and neonatal morbidities, and lowering healthcare costs. By applying machine learning to what could become the largest and most comprehensive dataset on maternal and fetal health, the proposed platform could become a valuable resource to researchers to identify underlying causes and biomarkers of preterm birth. Primary end users are women with high-risk pregnancies, and elevated risk of preterm birth. Target customers are hospitals, health care providers and insurance companies. This Small Business Innovation Research (SBIR) Phase I project seeks to develop an unprecedented means to support advances in maternal and fetal health: a state-of-the-art miniaturized mobile monitor that discretely sticks onto the mother's abdomen and uses sensors to noninvasively monitor fetal heart rate (FHR) and other physiological parameters in home and clinical environments. The device communicates to a smartphone, which acts as gateway to send data to a cloud-based platform, where the data is collected, stored and analyzed, with doctors able to set notification thresholds. For this project, patch technology, proven to effectively measure uterine activity and fetal movement will be leveraged to develop a disruptive product capable of detecting FHR as early as 25 weeks gestation. Miniaturization, power consumption and cost levels necessary for deployment in remote settings will be achieved. A usability study of the prototype monitor will then be conducted in expectant women in hospital settings, followed by an equivalency study to validate accuracy of the prototype compared to cardiotocogram, the current clinical gold standard. This solution will increase specificity of FHR testing, and improve interpretation of monitoring data, as well as aggregate data to train AI models to predict adverse events such as preterm birth. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Boston Microtechnology LLC
SBIR Phase I: CMOS-Integration of Isolated AC/DC conversion with Integrated Powerline Communication
Contact
1500 District Avenue
Burlington, MA 01803–5069
NSF Award
1913881 – SBIR Phase I
Award amount to date
$224,631
Start / end date
06/15/2019 – 05/31/2021
Abstract
The broader impact/commercial potential of this project is that it will revolutionize AC-DC convertors that are present in nearly all existing and future residential and commercial electronic devices. Reduced convertor complexity and increased power efficiency will result in extreme cost savings for both the manufacturers of these devices as well as the end consumers, enabling adoption to all corners of society. This dramatically different integrated convertor will also bring powerline communications into these electronic devices, a game changer that will enable electronics developers to add intelligence to their products across numerous markets such as home and office IoT devices, AC powered medium-wattage (~5W) electronics, power-over-ethernet, and smart LED lighting. This Small Business Innovation Research (SBIR) Phase I project will create an alternative integrated AC-DC converter architecture. Existing converters have numerous bulky, expensive, and unreliable discrete magnetic components that will be replaced with this integrated circuit (IC) based solution. The result of this project will be a reduced footprint, reduced BOM count, efficient converter for medium wattage (~5W) electronic loads. This project will additionally support low wattage loads (<1W) with an even smaller footprint and even lower BOM count, showcasing the scalability of this technology which is not an option with existing fly-back AC-DC convertor solutions. Validation of the Phase I IC-based converter performance will provide a foundation for Phase II, and incorporation into powerline communications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Boydston Chemical Innovations, Incorportated
STTR Phase I: Metal Free-Ring Opening Metathesis Polymerization
Contact
510 SW 295th Place
Federal Way, WA 98023–3531
NSF Award
2002330 – STTR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will be a technology enabling 3D printing of high-performance materials. A rapid and versatile ability to fabricate 3D parts that are lightweight, heat-resistant, biocompatible, and chemically inactive would yield improved manufacturing capabilities across a range of potential commercial applications, such as medical devices, implants, dental materials, automotive parts, aircraft, and spacecraft materials. This project will advance the development of new materials for the 3D printing community. This Small Business Technology Transfer Phase I Project will advance a technology based on a new chemical reactivity recently discovered for producing high-performance plastics and composites. This unique catalyst-resin system will be developed for use in 3D printing. The photoredox catalyst will be redesigned for efficient curing, within seconds per layer without a need for solvents. The resin systems will be formulated for rapid crosslinking, low volatility, and high-resolution 3D printing. Finally, the complete catalyst-resin combination will be optimized for use with commercial vat photopolymerization 3D printing equipment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CATHBUDDY, INC.
SBIR Phase I: Development of a Sterilization-based Reusable Catheterization System
Contact
841 E Fayette Street
Syracuse, NY 13210–0000
NSF Award
2021595 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to improve the process of intermittent urinary catheterization while decreasing the risk of associated infection For individuals who cannot empty their bladder due to anatomic or physiologic causes, single-use intermittent catheterization is the safest method for bladder emptying. Despite this, typical catheterization methods produce an annual 40-60% risk of complicated urinary tract infection, leading to over $4 billion of avoidable healthcare costs and patient morbidity. Some catheterization tools are safer than standard disposable catheters (e.g. no-touch catheters), but these are more costly and rarely used. To address this cost, some individuals attempt to sterilize their single-use catheters and reuse them in an off-label manner, increasing the risk of urinary tract infection to 70-80% per year. This project aims to develop a safe reusable catheter with the benefits of a no-touch catheter, allowing for an at-home sterilization device; this innovation will allow for a decrease in urinary tract infection risk, improvement in catheter usability, decreased catheter spending, and a 99% reduction of catheter-associated waste. This Small Business Innovation Research (SBIR) Phase I project will focus on the technical sterilization abilities of this novel purpose-built catheter sterilization device, especially when dealing with anticipated formation of bacterial biofilms. This research will involve exposing catheter samples to pathogen-inoculated urine, performing the anticipated cleaning and sterilization methodologies, and utilizing previously-validated fluorescence imaging techniques to document the presence and location of surviving bacteria and biofilm formation. It is expected that the intended sterilization techniques inherent in this novel device will provide adequate sterilization assurance for safe catheter reuse. This project will also focus on the feasibility of the laboratory-validated cleaning and sterilization protocol for anticipated users to perform without medical supervision. This research will examine cleaning and sterilization protocols by individual catheter users to determine points of potential risk to inform design of the device and the protocol. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CAZA HEALTH LLC
SBIR Phase I: A Powerful Clinical Aid in the Diagnosis of Vaginitis to Prevent PTB and Stop STI Transmission
Contact
379 REAS FORD RD STE 1
Earlysville, VA 22936–2407
NSF Award
2026102 – SBIR Phase I
Award amount to date
$249,726
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide fast, accurate diagnosis of vaginal infections. Vaginitis results in 10 million office visits a year representing 10% of all US women’s health visits, is known to dramatically increase susceptibility to sexually transmitted infections. External testing is expensive and can take from a day to weeks for results. For current in-office tests, 40% of all yeast infections and 30% of bacterial infections are misdiagnosed and require further visits. More importantly, vaginitis can lead to a large fraction of spontaneous preterm births - a major cause of neonatal mortality, emotional distress and lifelong disability worldwide. In the US, PTB results in healthcare costs of $26 B/year, motivating a fast and accurate test. This project will develop an advanced test that uses artificial intelligence (AI) to study samples quickly and accurately in the doctor's office. This Small Business Innovation Research Phase I project advances a novel test for vaginitis upon clinical presentation. This project leverages Artificial Intelligence (AI) image analysis with a high-quality fluorescence microscope to rapidly scan specimens in the doctor's office for fast diagnosis. This project will validate preliminary studies suggesting higher image accuracy compared to viewing similar samples under a microscope. Phase 1 of this project will examine prepared samples from diverse patient populations of up to 500 women to optimize analysis and characterization of VHA automated digital pathology system. All samples will be compared to manual assessment currently used clinically. Additionally, user testing in multiple types of clinical research environments, such as medical schools and health networks, will be undertaken to diversify patient sample populations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CELADYNE TECHNOLOGIES, INC.
SBIR Phase I: Nanocomposite Ionomers and Proton Exchange Membranes
Contact
1017 Harwood Place
Austin, TX 78704–2613
NSF Award
2014453 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact of this SBIR Phase I project advances the translation of hydrogen technologies in heavy duty and ultra-duty applications. The hydrogen economy could generate an estimated $2.5 T in economic value in the manufacturing, transportation, energy storage, and building energy, sectors. Current membranes that require high humidity levels and low temperatures for operation complicates fuel cell thermal and water management components in heavy duty fuel cell systems. The proposed solution advances the development of a new membrane serving as a drop-in replacement to enable low humidity and elevated operating temperatures. This SBIR Phase I project will use porous polymer supports to translate a nanocomposite material that exhibits both low humidity and elevated temperature proton conductivity into a standardized solution for a proton exchange membranes. Furthermore, the composite materials will be added at high volume fractions to confer additional benefits in mechanical stability and lower gas permeability. The project activities include material translation into supported membranes, membrane composite formulation optimization, measurements of key membrane properties, and demonstration in a fuel cell stack. If successful, the project would yield new proton exchange membranes that enable operation under low humidity – elevated temperature conditions to simplify fuel cell systems while extending system durability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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 – 04/30/2021
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.
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CEREVU MEDICAL, INC.
SBIR Phase I: A Wearable for Remote Monitoring of the COVID-19 Patient Population
Contact
688 MISSOURI ST
San Francisco, CA 94107–2839
NSF Award
2031714 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 02/28/2021
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 real-time monitoring of COVID-19 symptoms toward public health objectives. This project will provide healthcare systems the ability to remotely manage patients during quarantine, protecting hospitals and healthcare workers from unnecessary visits that can quickly overwhelm the healthcare system. This remote monitoring will allow for early identification of patients requiring hospitalization by continuously monitoring key symptoms and notifying patients, caregivers, and loved ones when urgent care is required. This Small Business Innovation Research (SBIR) Phase I project is to integrate a forehead patch, smartphone/tablet app, firmware, and cloud-based data portal to continuously assess and monitor COVID-19 patients. The first step will be to develop firmware to measure and display key COVID-19 symptoms, such as changes in SpO2/hypoxia, heart rate, respiration rate, and body temperature. The system will also monitor vital signs including dyspnea, myalgia, coughing frequency, and coughing intensity. The monitor user interface will capture non-measurable patient inputs, such as consumption of fluids and food, gastric problems, changes in smell and taste capabilities, and medication usage. Rule-based alert algorithms will be developed to provide notifications to healthcare professionals when critical condition thresholds have been triggered. A datahub and physician dashboard will be developed to remotely monitor large groups of COVID-19 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.
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CHOSEN DIAGNOSTICS INC
SBIR Phase I: Absolute protein quantitation in in vitro diagnostics for gut inflammation
Contact
1441 Canal Street
New Orleans, LA 70112–2714
NSF Award
2015077 – SBIR Phase I
Award amount to date
$224,758
Start / end date
05/15/2020 – 03/31/2021
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.
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CL CHEMICAL COMPANY
STTR Phase I: Scalable thermochemical conversion of carbon dioxide to commodity chemical intermediates
Contact
17815 GREEN WILLOW DR
Tampa, FL 33647–1382
NSF Award
1913722 – STTR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this STTR project is to chemically recycle carbon dioxide, which would otherwise be released to the atmosphere, to useful fuels and products thus providing a closed loop for production and emissions for many common products. Virtually every industry uses petroleum and/or natural gas, either through transportation or plastics (e.g., packaging), and there is no current commercial CO2 /carbon recycling process. The current routes for CO2 conversion are crippled by one or more of the following challenges: (a) very low rates of CO2 conversion, (b) high temperature of operation, (c) non-selective product formation, and (d) issues with scalability of the process. This STTR Phase I project proposes to re-purpose CO2 from a pollutant to a feedstock for fuels and chemicals. Recent research has achieved a proof-of-concept on reverse water-gas shift chemical looping (RWGS-CL). Carbon monoxide (CO), a major component of synthesis gas, is selectively produced, which can be used as the backbone to any chemical or fuel through existing processes. Preliminary performance results and literature findings indicate that this process operation could contribute to unprecedented efficiencies and potential scalability within a small footprint compared to other futuristic technologies that convert CO2. The RWGS-CL process operates at reasonable temperatures with high CO2 conversion rates and highly selective towards CO formation. The RWGS-CL process is thus, unique and transformative in that it addresses all of the major challenges and paves the way for a sustainable generation of greener hydrocarbon fuels at industrial scale. This project aims to enable prototype construction of the technology at 100 x scale of lab tests using formed materials (pellets) capable of operating at industrial scale, a reactor model to capture the performance and size of the RWGS-CL unit, and a techno-economic 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.
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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 – 04/30/2021
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.
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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 – 07/31/2021
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.
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COAGULO MEDICAL TECHNOLOGIES, INC.
SBIR Phase I: Development of a rapid, point-of-care coagulation test for the investigation and treatment of COVID-19-related coagulopathy.
Contact
327 COMMONWEALTH AVE APT 1
Boston, MA 02115–1900
NSF Award
2030771 – SBIR Phase I
Award amount to date
$253,210
Start / end date
09/01/2020 – 02/28/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a rapid, point-of-care device that allows for the precision management of blood clotting (coagulation) disorders and therapies. The proposed technology will support the development of a fully-automated reader system, along with single-use disposable cartridges, to enable clinical testing of COVID-19 patients with blood clotting issues. Due to the severe inflammation that occurs during COVID-19 disease, these patients often require frequent testing for blood clotting disorders. The proposed technology will rapidly identify patients that are more likely to form blood clots, and it can help evaluate the effectiveness of their current regimens; this will have impact beyond the current pandemic. This Small Business Innovation Research (SBIR) Phase I project allows for the determination of coagulation factor-specific inhibition and/or deficiency and real-time monitoring of response to treatment. The development of a point-of-care, portable, small volume coagulation assay that can be used for anticoagulant management using a precision-medicine approach would enable the identification of coagulation factor-specific inhibition, and, therefore, prove to be an essential tool in the diagnosis and treatment of coagulation disorders. This diagnostic would also be able to be used in non-COVID-19 anticoagulant management, aiding the identification and quantification of anticoagulants in an emergency and surgical setting and in other high-risk patients, such as neonates. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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CODON LEARNING, INC.
SBIR Phase I (COVID-19): Developing a comprehensive and customizable science courseware grounded in evidence-based teaching and learning practices
Contact
607 10th Street
Golden, CO 80401–5817
NSF Award
2015112 – SBIR Phase I
Award amount to date
$224,960
Start / end date
08/01/2020 – 01/31/2021
This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to advance the state of practice of STEM courses. Certain techniques, known as evidence-based teaching (EBT), can improve performance for all STEM learners and narrow the achievement gaps, but 80% of STEM classrooms are still primarily lecture-based. This project will develop a digital course design tool enabling an instructor to quickly create and implement an exciting STEM course course. It will create and scale a plug-and-play library of high-quality assessment items and instructional resources in a way that instructors find empowering, easy to use, and valuable. This will be valuable during a period of remote learning, such as that created by the social distancing of the COVID-19 situation. This Small Business Innovation Research (SBIR) Phase I project will support the development and testing of a system to distribute EBT course structure and content at scale. Active learning and high-structure courses produce better outcomes, and therefore this project focuses on dissemination of EBT curricula and course structures. The research objectives are to automate course design, and explore user requirements for the system to scale, and produce real-time feedback on student 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.
Errata
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Addenda
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COLLAMEDIX INC.
SBIR Phase I: Biofabrication of a collagen fabric by scaled-up electrochemical compaction
Contact
16500 PARKLAND DR
Cleveland, OH 44120–2539
NSF Award
1913847 – SBIR Phase I
Award amount to date
$250,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in the development of a highly biocompatible implant material made from collagen that can be used to treat a variety of medical conditions, including stress urinary incontinence, pelvic organ prolapse, hernias, and orthopedic injuries. Many people suffer from these conditions, but the current treatments are suboptimal. Most current implants for the repair or support of these soft tissue problems are made from polypropylene, which has significant clinical problems, including chronic inflammation and pain. The FDA recently ordered the removal of all synthetic implants for pelvic organ prolapse from sale in the US due to patient safety issues. Stress urinary incontinence affects 22% of women aged 45-64 years, and an estimated 9.2 million women in the US alone will have pelvic organ prolapse by 2050. These women have life-altering disorders, often limiting them from working, caring for their families, exercising, traveling, etc. New technology to safely treat these disorders is urgently needed. The current project will advance the development of a safe, natural, and effective implant material presently not available to these women. Reimbursement for these procedures under Medicare and private insurance are in place. This Small Business Innovation Research (SBIR) Phase I project seeks to advance the manufacturing of electrocompacted collagen threads which can be used for a variety of medical implants. The existing lab-scale manufacturing process for the production of the collagen threads will be developed into a scaled-up commercial ready process. Key goals include speeding up the thread production, decreasing the need for operator intervention, and improving the efficiency of converting the collagen feedstock into thread, all while maintaining thread strength and process repeatability. This is critical to ensuring that products developed from this technology can be produced in commercial volume and will be priced within existing medical insurance reimbursements. Achieving these goals will greatly de-risk this technology, enabling the attraction of further investment capital and the continuation of product development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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COMBPLEX, INC.
SBIR Phase I: Precision Lasers for Controlling a Major Agricultural Parasite
Contact
1191 ELLIS HOLLOW RD
Ithaca, NY 14850–2947
NSF Award
2026082 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
Abstract
This Small Business Innovation Research (SBIR) Phase I project aims to develop and validate a novel solution for specific pests affecting honey bees. Beekeepers around the globe consistently cite Varroa mites as a leading cause of honey bee colony loss and, in the United States, attribute to these mites an estimated $2 B in agricultural damages every year. Since arriving in the U.S. in the late 1980s, Varroa mites have developed resistance to most known chemical pesticides, leaving beekeepers with few treatment options that do not also negatively impact the colony or contaminate honey. This project will develop a year-round, automatic, and chemical-free method for controlling Varroa mites, effectively mitigating the existing honey bee decline and resolving the chief problem facing beekeepers across North America and Europe, improving global food and agriculture supplies. The intellectual merit of this project is the interdisciplinary application of selective photothermolysis technology combined with in-depth understanding of honey bee behavior to remotely detect and destroy a harmful apicultural pest. This project is investigating the field efficacy and cost effectiveness of employing a computer vision-driven identification algorithm to identify the Varroa mite, a serious honey bee parasite, and then introduce a high-power laser burst to immediately destroy the mite while it remains attached to the infested bee but without harming the host. The research objectives include quantifying the negative effect on mite population growth during the growing season and determining the number of laser/detector devices required to maintain permanent year-round control of Varroa mites in a standard colony. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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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
$255,993
Start / end date
10/01/2020 – 09/30/2021
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.
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CONFLUENCY LLC
SBIR Phase I: Human-Centered, Augmented Intelligence Software for Water and Wastewater
Contact
4601 N MALDEN ST APT 3
Chicago, IL 60640–4810
NSF Award
2004275 – SBIR Phase I
Award amount to date
$224,936
Start / end date
07/01/2020 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from development of augmented intelligence software improving planning and operational decisions for water and wastewater systems. The most challenging issues for water utilities include addressing aging infrastructure, adapting complex systems to changing regulations, and addressing the impacts of environmental change. They arise from interconnected infrastructure networks that interface with both the built and natural environment. Current artificial intelligence and machine learning solutions for water are narrowly defined for specific use cases. The proposed intelligence software will enable transformative changes in water management by seamless composition of hybrid models from simulators and data-driven models to overcome data and information silos, enabling decision-makers to integrate data in a system model that increases resilience at reduced customer costs. These improvements can lead to significant reductions in the roughly $4.7 B annual energy spend for water/wastewater, $50 B in combined sewer system programs, and up to $1 T in aging infrastructure needs. This Small Business Innovation Research (SBIR) Phase I project will develop methods for combining multi-fidelity simulation models and data-driven models to support decision-making for both long-term planning needs and real-time operational decision support for water and wastewater systems. Meta-modeling techniques for embedding physical system understanding from high-fidelity physics-based simulators to low-fidelity models will be evaluated. Accuracy and runtime tradeoffs will be evaluated for multiple reduced-order methods (e.g. linear and non-linear equations, projection-based methods) to enable more efficient optimization of large solution spaces. Domain applications include reduced-order versions of the St Venant equations for one-dimensional flow, and analytical solutions of biological, physical, and chemical processes in secondary wastewater treatment. The project will evaluate multiple machine learning methods, including deep neural networks, reinforcement learning, random forest, support vector machines, and boosted learning algorithms, to detect patterns in observed data for near-term predictive power toward operational real-time decisions. Expert elicitation techniques will be used to quantify human expertise for subjective decision criteria, integrating valuable tacit human knowledge into the decision process. Meta-analysis of alternative hybrid modeling workflows will be evaluated to identify computationally efficient pathways to optimize complex planning 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.
Errata
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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 – 07/31/2021
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.
Errata
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CORDANCE MEDICAL INC.
SBIR Phase I: Transcranial Dynamic Focused Ultrasound for the Non-Invasive Opening of the Blood-Brain Barrier (BBB)
Contact
2483 OLD MIDDLEFIELD WAY STE 205
Mountain View, CA 94043–2330
NSF Award
2014262 – SBIR Phase I
Award amount to date
$224,986
Start / end date
05/15/2020 – 12/31/2020
Abstract
This SBIR Phase I project aims to develop technology designed to provide physicians with a new capability to manage patients with brain diseases such as brain cancers, Alzheimer’s or Parkinson’s. One reason brain disease is difficult to treat is the existence of the blood-brain barrier (BBB) that prevents almost all therapeutic agents from reaching diseased tissue from blood. The proposed technology enables opening the BBB in a non-invasive manner with a system that is portable and may be deployed in an out-patient or a clinic setting. This system could impact the cost burden of managing patients with brain diseases and provide better quality of life. The proposed project develops methods to accurately direct focused beams of ultrasound to therapy targets within the patient’s brain from an array of ultrasound transducers embedded in a cap-like device conformed comfortably to a patient’s head. In the last several years, focused ultrasound with microbubbles (an FDA approved ultrasound contrast agent) has been used to transiently open the BBB to administer drugs or provide therapy. The proposed cap-like device includes mechanisms both to conform to the patient head and to measure the resulting alignment to the patient anatomy. The envisioned method is to acquire information on cap placement and MR and CT images of the specific patient in advance so that the therapeutic ultrasound can then be directed accurately to targets within the patient's brain. The proposed work includes a) developing beamforming algorithms applicable to a range of patient head sizes, with transducer elements arranged on the conforming cap; and (b) understanding and mitigating potential sources of errors limiting the performance. The project will conduct simulation and analysis using MR and CT images from real patients, obtained from the U.S. National Library of Medicine Visible Human Project, resulting in specifications suitable for construction of a laboratory device for verification and validation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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CORELESS TECHNOLOGIES, INC.
SBIR Phase I: Large Scale Synthesis of Hollow Metal Nanospheres: Conversion of Batch Synthesis to Continuous Flow
Contact
312B MYRTLE ST
Santa Cruz, CA 95060–4942
NSF Award
1940608 – SBIR Phase I
Award amount to date
$269,999
Start / end date
10/15/2019 – 12/31/2020
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is rooted in the development of a large-scale synthesis for the manufacture of highly uniform hollow metal nanospheres for use by the military in potentially contaminated zones of operation, in rural settings with limited access to healthcare laboratories, or in the agricultural field for faster and more affordable detection of lower levels of food-based toxins and pathogens. Furthermore, establishing a source of these next-generation metal nanoparticles at commercially relevant levels of quality and quantity with consistent and predictable performance would pave the way for their expansion into other industries that could also benefit from their advantages, such as photocatalysis, water purification, and photomedicine. This Small Business Innovation Research (SBIR) Phase I project will scale-up the production of hollow metal nanoparticles from the existing small-batch syntheses to a large-scale continuous flow process, with strict standards for the control of their size, shape, and optical response. Large-scale synthesis of highly uniform hollow metal nanospheres with controllable size has not been achieved to date, hampering the use and study of these advanced materials. A high-quality, high-volume production method will position hollow metal nanospheres for rapid commercial adoption in applications where they markedly outperform their solid counterparts, such as in color reporting for lateral flow assays (LFAs), where hollow gold nanospheres can offer a 10-fold improvement in assay sensitivity. The primary objective of the proposed work is to determine the parameters necessary for a high-quality, high-throughput synthesis based on continuous flow, including reactor materials, chamber dimensions, precursor concentrations, flow rates, and reaction times. The major technical hurdle lies in the identification (within a very large parameter space) of suitable conditions for a successful and controlled synthesis; accordingly, a major component of this project is in-depth analysis and characterization of synthesized nanoparticles by optical spectroscopy and electron microscopy. Characterization results will be used to inform iterative reactor improvements. The resulting high throughput reactor will both advance the state of the art of nanomaterial synthesis and enable new research by creating a consistent supply of commercially available hollow nanoparticles with reproducible physical properties. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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COUTURE TECHNOLOGIES LLC
SBIR Phase I: Using Automation to Deliver Photo-Realistic Clothing Simulations for Virtual Fittings
Contact
350 ODOMS BEND RD
Gallatin, TN 37066–6205
NSF Award
2026135 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to demonstrate the feasibility of the virtual garment creation and try-on system. As businesses increase their e-commerce presence, they face a major challenge: the high rate of returns in e-commerce. The return rate for online purchases exceeds that of in-store purchases by roughly 4 to 1, with customers (52-74%) citing dissatisfaction with the garments’ fit as the primary reason for returns. A reduction in returns as small as 1% could keep over 50 million pounds of goods out of the landfill and return $2.3 B to fashion retailers. This Phase I project is aimed at developing a sophisticated process using 3D modeling and fabric simulation technologies to enable customized fit and sizing visualizations prior to purchase. This Small Business Innovation Research (SBIR) Phase I project will demonstrate the feasibility of the virtual garment creation system by using machine learning, numerical simulations and 3D graphic rendering to generate virtual garments based on (i) images and text that describe the garment and (ii) a minimum set of measurements of the customer's body. This process will advance the translation of novel approaches to combining artificial intelligence and 3D representation of a deformable shape in a computationally efficient manner. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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COVID COUGH INC
SBIR Phase I: COVID-19 Cough Classifier Using Artificial Intelligence
Contact
6400 S FIDDLERS GREEN CIR STE 25
Greenwood Village, CO 80111–5075
NSF Award
2029591 – SBIR Phase I
Award amount to date
$255,974
Start / end date
09/01/2020 – 02/28/2021
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 COVID-19 diagnostic tool using artificial intelligence. The proposed Cough Detector and Cough Classifier is able to “listen” to sounds in a given environment, then detects and classifies coughs. When a cough related to COVID-19 is identified, the individual and relevant personnel in a potential germ circle can be immediately notified. Functioning as an early warning system, the tool will work on a mobile device or laptop, and can be embedded in other technology, such as infrared cameras with microphones or other sound detection equipment. The tool will support ongoing outbreaks and mitigation of social distancing considerations. This Small Business Innovation Research (SBIR) Phase I project will utilize deep learning and transfer learning to develop a COVID-19 cough classifier. The unique features of a COVID-19 cough require distinguishing between characteristics of widened airway, narrowed airway, fluid filled air sacs, airflow patterns of spirometry, stiff lungs, and others. The unique characteristics or features are learned while classify cough types on a training data set. A tuned deep learning model is able to distinguish COVID-19 cough from other types of cough in real-time. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CREATHADH ENERGIES, LLC
SBIR Phase I: Vibration Energy Harvesting-Based Sensor System
Contact
1142 NIELSEN CT APT 2
Ann Arbor, MI 48105–1968
NSF Award
1951480 – SBIR Phase I
Award amount to date
$250,000
Start / end date
01/01/2020 – 03/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to use novel energy harvesting techniques to benefit the expanding wearables market and improve the lives of patients who use prosthetics and orthotics. New integrated circuit technology enables vibration energy harvesting from a physically much smaller vibration harvester. These smaller harvesters enable multiple applications. For example, battery life in wearables to track heart rate and steps walked could be extended. Also, fabric-based vibration energy harvesting applications could be realized in military and first responder uniforms to power communication devices. Similarly, for commercial markets clothing-integrated sensors for digital health applications could be powered by vibration harvesting. Finally, first markets will be explored for vibration harvesting systems integrated in prosthetics or orthotics to improve the quality of life for patients. A sensor system in orthotics could detect medical complications in patients suffering from diabetic neuropathy. These new energy harvesting circuits could potentially also power sensors integrated into prosthetics that could identify structural and mechanical problems. This Small Business Innovation Research (SBIR) Phase I project develops a vibration energy interface circuit that allows cold start-up from record low voltages and low currents using novel CMOS (Complementary Metal Oxide Semiconductor) design techniques. These CMOS design techniques use only one vibration harvester input to charge large loads such as 100µF capacitors without the use of a transformer or Schottky diodes. Lowering the minimum start-up voltage in a vibration harvesting interface circuit has been a significant area of circuit research in integrated circuit design over the last decade. The innovation proposed for this SBIR Phase I project uses a classic Cockcroft-Walton charge pump with large off-chip 100µF capacitors. The charge pump's rectification is designed in CMOS to allow leakage-based signals to form and switch the charge pump's rectification from cold start-up. In this project there will be continued research into integrated circuit techniques and solutions to lower the minimum start-up voltage in a circuit interface to a vibration harvester. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CROSSLINK COMPOSITES, INC.
SBIR Phase I: Tailored Carbon Fiber Technology for High Volume Industrial Applications
Contact
1540 Riggs Chapel Road
Harriman, TN 37748–0000
NSF Award
2025333 – SBIR Phase I
Award amount to date
$255,917
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is technology that encompasses the development of customizable carbon fiber products and package formats at a low cost. Lack of suitable raw materials and corresponding processes has largely stymied the development and manufacturing of many high-volume industrial composite applications. The current advanced material reinforcement knowledge base is built on technology developed to serve space/aerospace composite material applications, which are relatively low-volume and cost-insensitive markets. This project focuses on creating a new platform designed specifically for high-volume, cost-sensitive industrial composite applications. The resulting carbon fiber products from this advanced material delivery platform can be tailored to facilitate a broad range of industrial composite applications currently unmet or underserved, such as automotive, wind energy and infrastructure applications. This will potentially enable sizable performance and efficiency gains in those industries. This SBIR Phase I project proposes to demonstrate proof-of-concept for a new carbon fiber format technology platform. The proposed technology platform entails delivering carbon fiber with customizable tow linear densities produced from a universal conversion feedstock while seeking to maintain requisite and optimal physical properties of the carbon fiber. Physical properties of multi-level samples will be analyzed iteratively to determine acceptable linear density boundaries. Prototype mechanical devices will be developed to explore multiple viable approaches to optimize processes for the target product formats. The project also will determine the material handling viability of the resulting products for downstream composite uses. The project will explore the trade space of carbon fiber production economics, application requirements, and product 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.
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CURATED NETWORKS, INC
SBIR Phase I: Software Defined Networking with Partially Ordered Multipath Routing
Contact
1855 ENCINA DR
Santa Cruz, CA 95062–1988
NSF Award
2014153 – SBIR Phase I
Award amount to date
$217,973
Start / end date
06/01/2020 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be a new network architecture to improve the internet. Its original connectionless, packet-switched architecture was a departure from the traditional circuit-switched model and involved significant risks. To manage these risks, the original design focused on a simple network with smart endpoints. The result was scalable, robust and supported a wide range of communications technologies; however, it is limited in its ability to meet the performance, security, and policy needs of many modern network applications. Overprovisioning and expensive, complex, and fragile add-on technology are required to meet the needs of these new applications and these solutions may not scale This project will provide an enhanced, smart network that is scalable and robust, supporting performance and policy control while making efficient use of network resources. This will improve the next generation of internet applications. This Small Business Innovation Research (SBIR) Phase I project explores the translation of networking with constraints. In this architecture, performance requirements are expressed as performance constraints, and policy requirements for security, multi-tenancy, and traffic differentiation as Boolean constraints on the resources used for an application. Routing with constraints computes the best set of paths per destination that provide the full range of performance and policies supported by the network, allowing traffic to be sent over paths that meet the needs of applications, and distributing the load more evenly over the network (simulations show a 10x increase in capacity). This approach is more robust because it is implemented as a part of the routing function, directly responding to network changes, and more efficient because it runs on the "native internet," eliminating overlays. Lastly, it improves security by implementing a default-deny communication model and is easier to configure based on its declarative, "what" configuration model. This project is focused on characterizing and mitigating risks remaining in this architecture and demonstrating the feasibility of this approach through the development of an operational proof-of-concept. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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CYPRIS MATERIALS, INC.
SBIR Phase I: Paintable Solar Reflective Coatings for Cool Roof Retrofits
Contact
626 BANCROFT WAY STE A
Berkeley, CA 94710–2262
NSF Award
1940383 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will bring a new family of "structural color" coatings to the commercial marketplace as an alternative to toxic pigments and dyes, as well as a new paradigm for controlling the flow of light. This project aims to improve the energy efficiency of buildings through a coating that can be applied to residential roofing materials during installation or at the original equipment manufacturer level. The technology is a bottoms-up approach to the formation of reflective materials offering significant advantages over state-of-practice cool-roofing alternatives by retrofitting without changing the facade's appearance. The resulting product will rapidly increase adoption of cool-roof technologies due to improved performance without aesthetic loss, a key homeowner concern, leading to substantial energy savings. This Small Business Innovation Research (SBIR) Phase I project addresses key risks and technical challenges associated with commercializing brush block copolymer based photonic crystals. This forms an ideal advanced materials platform for large-area dielectric mirrors due to the low costs of the raw materials and the simplicity of "bottoms-up" fabrication by macromolecular self-assembly. To realize commercial applications, the chemistries for these reflective organic materials need to be optimized for exterior coating applications to resist degradation from natural weathering conditions such as ultraviolet radiation, rain, thermal cycling; furthermore, the formulation must be optimized for standard application. This proposed activity will develop new synthetic routes, stabilization strategies, and the first manufacturing processes to demonstrate these unique advanced materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Capacitech Energy, Inc
STTR Phase I: Self-Powering Textiles for Electronic Wearables
Contact
3259 Progress Drive
Cross City, FL 32628–3230
NSF Award
1914035 – STTR Phase I
Award amount to date
$224,905
Start / end date
06/15/2019 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is the integration of energy conversion and energy storage technologies into a single ribbon called the Solar Supercapacitor (SolarCap). The innovative aspect of SolarCap technology is that it is a self-powering ribbon which can be weaved along with cotton fibers to make a fabric. Batteries are currently being employed for powering wearable electronics used in remote places during multiple day trips with limited supplies and resources. However, most batteries are heavy, have a short life span, and are expensive, and transporting them to hostile locations can be difficult and dangerous. The SolarCap ribbons will have a considerable commercial impact since it can be used to charge the wearable electronics devices while woven on the user's backpack, clothing, etc. The proposed study will answer several key scientific questions including energy storage capability, stability, charge-recharge cycle life and durability of the SolarCap ribbons. The core value of the proposed SolarCap is that it can provide soldiers, firefighters, first responders, and outdoor personals increased mobility, comfort, flexibility, and peace of mind concerning device's electrical power while in the field. It can also reduce the physical load carried by the user. This Small Business Technology Transfer (STTR) Phase I project eliminates the requirement of distinct devices for energy harvesting and storage. Using distinct devices for energy harvesting and storage can be a significant issue for those who are working at remote outdoor places. This is because, once the battery power of a device is drained, the outdoor personnel should find a place to charge the battery. The objective of this proposal is to develop a wearable self-powering SolarCap ribbon by integrating solar cells and supercapacitors on a ribbon. To accomplish this goal, a flexible perovskite solar cell (PSC) will be developed on a conductive ribbon. A hybrid supercapacitor device will be integrated with the PSC to store the harvested energy. These two devices will be so integrated that a direct electric charge transfer can take place from solar cell to the storage device. The proposed SolarCap ribbons are anticipated to deliver more than 8% solar power conversion efficiency and an energy density of more than 20WhKg -1. The size of the ribbons will be so designed to weave along with cotton filaments to make a self-powering fabric. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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CatalyzeH2O LLC
SBIR Phase I: Anti-Microbial Graphene Oxide Nanofiltration Membrane
Contact
249 Alexandra Loop
Elkins, AR 72727–3707
NSF Award
1913598 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project results from the ability to design a reusable nanofiltration membrane platform for wastewater treatment. Energy-efficient and effective wastewater treatment for water purification and reuse remains a tremendous challenge because safe and reliable approaches are often capital and energy intensive. The production of clean water from wastewater for municipal or industrial reuse requires the removal of a wide range of organic and inorganic contaminants, including many hazardous and toxic substances (e.g., pesticides, heavy metals, pharmaceuticals, etc.). Energy costs are driven even higher by the high fouling propensity of polymeric membranes with the wide array of water contaminants. Preventing fouling and enabling high contaminant rejection with low energy requirements remain the two core challenges of membrane filtration for wastewater treatment. The proposed technology will address the two core challenges through the use of an anti-fouling surface chemistry. The low energy requirements, contaminant rejection, and anti-fouling properties of the proposed membrane make it a disruptive innovation that can easily penetrate the market, providing a cost-effective solution that is lacking in current membrane purification systems. This SBIR Phase I project proposes to develop a nanofiltration technology utilizing surface chemistry modification for the creation of an anti-fouling membrane for the rejection of pesticides. The United States spends nearly $9 billion a year on pesticides, which account for 16% of the world pesticide market. Out of the 25 most common active ingredients in pesticides, 76% are water soluble, which leads to contaminated soil, groundwater, and nearby bodies of water. The objectives of this project are to remove common commercial pesticides from water while investigating the advantageous effects of an anti-fouling membrane surface. Performance of the membrane will be investigated through cross flow filtration experiments to identify rejection, stability, and anti-fouling properties. The vision is to create a nanofiltration membrane with a broad contaminant rejection while decreasing energy requirements and fouling. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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Cell Reprogramming & Therapeutics LLC
SBIR Phase I: Generation of Dopaminergic Neurons from Fat
Contact
4404 S 113 str
Greenfield, WI 53228–2565
NSF Award
1819574 – SBIR Phase I
Award amount to date
$294,999
Start / end date
09/01/2018 – 05/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be functional neuronal cells derived from human adult adipocytes that will have applications in regenerative medicine. The goal is to develop dopaminergic (DA) neural progenitor cells (NPCs) from transdifferentiated human adult adipocytes using a DA cell induction cocktail. This will have application in cellular therapeutics and research tools for Parkinson's Disease (PD), and other neuronal diseases. In addition, these studies will impact the field of stem cell research and regenerative medicine, since this will be the first demonstration that functional neuronal cells, the main building blocks of brain, spinal cord, and peripheral nervous systems, can be produced from mature fat cells that can be used as cellular therapeutics for several neurological disorders. This SBIR Phase I project proposes to develop new technology for generation of midbrain dopaminergic (DA) neural progenitor cells (NPCs) from adult adipocytes (fat cells), which will used as a platform to develop cellular therapeutics for Parkinson's Disease (PD), and PD research tools. Recently, using a chemical genetics approach (chemical approach or small molecule approach), engraftable midbrain DA neuronal progenitor cells (DA NPCs) from human bone marrow derived mesenchymal stem cells (BM-hMSCs) have been generated. Additionally, DA neuronal progenitor-like cells also had been produced from de-differentiated fat cells (DFAT cells) that have several advantages over BM-hMSCs such as homogeneity of DFAT cell cultures, ease of isolation and low immunogenicity. The goal of Phase I project is to validate and optimize the DA induction protocol for generation of midbrain DA NPC from DAFT cells. Phase II will focus on clinical grade manufacturing of these DA cells and testing their therapeutic effect in several preclinical animal models of PD. Commercial products emerging from Phase I/II work include cellular therapeutics for PD and research tools for PD. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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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 Drive
Madison, WI 53719–1266
NSF Award
2015010 – STTR Phase I
Award amount to date
$225,000
Start / end date
08/01/2020 – 07/31/2021
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.
Errata
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Central Inventions, Inc.
SBIR Phase I: Stackmaps: A Metacognitive Learning Support Tool To Empower Students In STEM
Contact
14 Spring St
Waltham, MA 02451–4429
NSF Award
1843795 – SBIR Phase I
Award amount to date
$224,995
Start / end date
02/01/2019 – 10/31/2020
Abstract
This SBIR Phase I project will study and develop methods to provide adult professionals and young adult students with the skills and self-confidence to pursue studies and careers in Science, Technology, Engineering, and Math (STEM) fields. Today, a large segment of society identifies as being underrepresented in the technology sector. Some individuals experience low technology-related self-confidence as a result. At a time when the United States has an increasing demand for technology workers, the country needs contributions from all segments of society, and not simply those segments which have been privileged in the past, to meet this demand and maintain U.S. competitive advantage in the global innovation economy. Engaging people from the full spectrum of the United States population will enable innovative companies to leverage more diverse sources of creativity, build better solutions to today's problems, and create more jobs. When people see themselves as future practitioners of a technical skill, it is possible to learn topics in a deeper, more fulfilling, and more enduring manner. Commercializing this invention will increase online learning platform retention rates, driving revenue not only within educational companies but within the companies who hire the resulting talent. The proposed technology is innovative because no commercially-available software tools exist which support metacognitive development in tandem with technical skill acquisition. This innovation is risky because no one has proven that having a positive influence on metacognition through automated software is even possible during single learning session. The goal of this research is to deliver techniques for enhancing the self-efficacy of STEM learners within the context of online learning platforms. The project combines best practices in digital personalization and educational psychology research to deliver customized content responsive to learner preferences and learner attitude attributes. The proposed research will demonstrate, via a random trial, increased levels of motivation and engagement in students who receive targeted interventions as compared with a control population. Using survey instruments, the researchers will measure changes in self-efficacy, challenge-seeking, and goal-setting behavior. Because the research team has unique experience in developing proven educational interventions which enhance self-efficacy across a variety of learning domains, the algorithms and methods inside the proposed technology will be difficult for competitors to replicate. This SBIR project will deliver algorithms and automated, web-based interventions to help all STEM learners experience personal engagement with STEM topics and find empowerment in the task of learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Choosito!
STTR Phase I: Simplification AI for Workforce Upskilling
Contact
462 Ballytore Rd
Wynnewood, PA 19096–2309
NSF Award
1914104 – STTR Phase I
Award amount to date
$224,743
Start / end date
08/01/2019 – 07/31/2021
Abstract
This STTR Phase I project addresses the challenge of upskilling the workforce by developing novel personalized content simplification technology. It will build a novel digital binder tool with an AI empowered content selection and simplification capability. The magnitude and urgency of the workforce upskilling problem require an immediate and robust solution. Corporations are desperate to find and nurture appropriately skilled workers to fill emerging roles. Beyond big high-tech corporations, the need for retraining is expanding in the trades and manufacturing space. An estimated 300-600 million people will need to be retrained between now and 2030. The proposed breakthrough solution utilizes state-of-the-art deep learning and natural language processing algorithms to automatically generate training materials appropriate for the level of familiarity that trainees have with the content and skills they need to acquire. This is facilitated by three core technologies: a content simplification solution with the capability of searching and identifying collections of digital resources by identifying key concepts. The applied algorithms consider the current background of the learner and include documents needed to comprehend those key concepts. The second technology addresses the open problem of text simplification by proposing a hybrid approach of traditional text simplification techniques like word substitution and a novel information retrieval approach that identifies concepts critical for the comprehensibility of advanced documents. The third technology is a personalized content simplification engine tailored to the needs and capacities of each trainee who can continue to use the technology for continuous retraining, upskilling and lifelong learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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Circle Optics LLC
SBIR Phase I: A novel parallax-free, 360 degree panoramic camera system
Contact
2632 Skillman Avenue
Long Island City, NY 11101–0000
NSF Award
2026054 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to advance long-form panoramic content capture at reduced cost. While content creators and producers seek panoramic content capture to create immersive viewing experiences, current approaches integrate many shots that consequently require expensive and time-intensive post-production. This project will save costs and labor by enabling seamless real-time capture of cinematic-quality panoramic content. Potential applications include security, risk and asset management, robotics, mapping, and live event capture; sectors that can benefit include navigation, aviation, tourism, construction, manufacturing, and entertainment. This Small Business Innovation Research (SBIR) Phase I project will develop an innovative camera system that fuses images captured through a camera array at the level of the lenses, rendering a perfect 360° image instantaneously. Minimizing overlapping image capture reduces the problems of parallax error and perspective errors, while valuable camera resolution is not lost on redundancy. This project will: 1) develop software; and 2) validate opto-mechanical alignment and assembly concepts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Clairways LLC
SBIR Phase I: Medical Device for Monitoring Respiratory Disease
Contact
1 South St
Hanover, NH 03755–2186
NSF Award
1843658 – SBIR Phase I
Award amount to date
$269,999
Start / end date
02/01/2019 – 03/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be a novel wearable device for unobtrusively detecting changes in the lung health of patients with chronic respiratory disease. This Passive Unobtrusive Lung function Monitor (PULMO) will be the only device that can automatically measure a patient's lung health information without requiring any active engagement from the clinician, and without imposing any obtrusive changes to the patient's daily routine. The PULMO is useful in a broad range of respiratory disease applications, such as lung transplant post-operative care, asthma management and respiratory therapy research, that require continuous, objective and unobtrusive monitoring of lung function change. Since PULMO technology is compatible with low-cost microcontrollers, it has the potential to dominate the spirometry market and respiratory clinical trials space with high-volume production. The spirometry market has an expected CAGR of 9.4 % from 2018 to 2025, reaching a $1.4 billion market value by 2025, while clinical trials expenditures on new respiratory therapy drugs is forecast to reach $1.7 billion in 2025. This Small Business Innovation Research (SBIR) Phase I project addresses the major drawback of the state-of-the-art in continuous monitoring of respiratory disease, which is that it demands daily discipline, effort and proper technique of the patient, resulting in missing, invalid or fabricated data. In this project, a manufactured PULMO test device will be implemented with an intelligent event detection unit combined with a low power microcontroller, and the total average power consumption will be less than 300 microWatts. The measurement error of the PULMO will be within +/- 5 %, which is necessary for detecting changes in lung impairment. The intelligent event detection unit will be implemented as a nonlinear dynamical system in a custom integrated circuit. A gated recurrent neural network that is optimized for embedded low resource systems will be implemented in the low power microcontroller and will be used to detect respiratory disease symptoms. Controlled tests will be performed with a silicone phantom chest to evaluate the measurement accuracy of the PULMO device. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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CoreMap, Inc.
SBIR Phase I: The Development of Signal Sensing, Processing and Mapping Technology to Enable Curative, Patient-Specific Treatment of Atrial Fibrillation
Contact
197 Moonlight Ridge
Colchester, VT 05446–7797
NSF Award
2026029 – SBIR Phase I
Award amount to date
$251,134
Start / end date
09/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a diagnostic technology capable of identifying the drivers of Atrial Fibrillation (AF), which promises to enable new therapeutic options for a large population of under-served patients. AF is the most common and complex cardiac arrythmia. AF patients are at severe risk of complications including stroke, heart attack and death. AF patients have limited treatment options and medications are only effective approximately half of the time. Ablation is highly effective at treating other arrythmias, but current diagnostic mapping technologies are limited in the ability to provide customized treatment for chronic AF. This project will test concepts of a new device to measure AF. This Small Business Innovation Research (SBIR) Phase I project will validate the ability of a novel micro-electrode array to accurately measure AF in an animal. This is important because conventional intra-cardiac catheters lack the spatial resolution to adequately resolve discrete, closely spaced activations. Accurate resolution of cardiac tissue activations is essential to deduce the properties of diseased tissue and to plan effective patient-specific ablation therapy. Optical mapping is a gold standard for measuring electrical activation of tissue and therefore provides a trusted platform for comparative validation. The expected results are to observe complex activation patterns on an ovine heart model using the novel micro-electrode array, and for those electrical patterns to be corroborated by optical mapping 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.
Errata
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Addenda
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Cruz Foam, Inc.
SBIR Phase I: Sustainable Packaging Foam
Contact
2851 Mission St
Santa Cruz, CA 95060–5756
NSF Award
1938479 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the reduction in single use plastics contributing to landfill waste and ocean pollution by replacing them in packaging with a fully biodegradable and naturally sourced alternative. With its water-based proprietary technology, the material developed in this project will transform shrimp shells into foam to replace conventional single-use packaging. The advantages of this material include mechanical properties competitive with non-sustainable alternatives at cost-competitive production. This Small Business Innovation Research Phase I project will develop the basic technology to scale the production of a compostable and recyclable foam made of chitin. Chitin is a polysaccharide derived from shrimp shell waste. The material has the same mechanical properties and thermal insulation as polystyrene foam. Currently, this material is made with a hot molding process that creates high-quality foam, but it is challenging to scale for mass production of the volumes required to service the packaging industry. With this project, the company will develop a process that is fully scalable and uses existing equipment for the production of polystyrene foam for quicker adoption. The goals of the new process are to generate the same mechanical strength, thermal insulation, and density as polystyrene foam. The team will vary the foam composition and processing parameters to achieve the desired properties. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Cryoocyte Inc
SBIR Phase I: High Throughput Cryopreservation of Aquaculture Seed
Contact
97 Chicopee Dr
Hubbardston, MA 01452–1565
NSF Award
1913772 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be to advance cryopreservation technologies for the development of a seed banking product for commercially important aquaculture species. Genetic banking of plant cells, tissues, seeds, and embryos is common practice in agriculture to ensure important genetic lines are not lost due to disease outbreak or environmental catastrophe. However, genetic banking of embryos and larvae within the aquaculture industry is nonexistent to date, and the investments made toward genetic improvements are susceptible to catastrophic loss without a proper seed banking product. The inability to reliably preserve seed for long periods of time is currently a barrier to the formation of an aquaculture seed storage product. This research will enhance scientific and technological understanding for the cryopreservation of aquatic organisms and be a transformative step to protect genetic resources vital to the commercial aquaculture industry. These technological advancements also can be adapted for the conservation of threatened or endangered aquatic organisms important to food security and ecosystem health domestically and abroad. This SBIR Phase I project proposes to develop a technology to implement a genetic banking product that allows aquaculture facilities to "cryobank" thousands of seeds from family lines developed over years of selective breeding programs. Recent advancements in rapid cooling for storage at liquid nitrogen temperatures (-196 degrees C) and ultra-rapid rewarming (~107 degrees C/min) have led to major breakthroughs in cryopreservation research. These advancements will be utilized to develop a low throughput, high efficacy strategy for the successful cryopreservation of an important aquaculture species, Litopenaeus vannamei or Pacific white shrimp. Protocol optimization for cryoprotective agent loading/unloading, vitrification, and ultra-rapid warming will result in high revival, survival, and grow out to post larval stages. Once proven, the technique will be scaled up to develop a high throughput process to successfully cryopreserve >10,000 samples per day. This technology will enable the commercial aquaculture industry to conserve important genetic strains and stockpile cryopreserved seed at the levels necessary to avoid interruptions to food supply commonly caused by disease outbreaks and environmental catastrophe. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Cytocybernetics
STTR Phase I: Developing a platform for superior predictive analysis of HERG Ion Channel-Drug Interactions for the Comprehensive In-vitro Proarrhythmia Assay (CiPA)
Contact
5000B Tonawanda Creek Rd N
North Tonawanda, NY 14120–9536
NSF Award
1913793 – STTR Phase I
Award amount to date
$269,900
Start / end date
07/01/2019 – 09/30/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project will be to improve the safety testing of new drugs for approval by the FDA. By decreasing the time and costs associated with safety testing, the product will make all classes of new drugs safer, less expensive and available to patients sooner. All new drugs must demonstrate that they are safe. One common and critical point at which new candidate treatments fail is because they have the serious side effect of promoting sudden cardiac death through lethal arrhythmias. This product combines advanced biological techniques with advanced computing to develop a system that will enable pharma and biotech companies to more rapidly and accurately identify pro-arrhythmic drugs earlier in the development process, thus saving drug companies significant costs associated with drug development. Drugs that ultimately fail cardiac safety screening need to be eliminated as soon as possible from the development pipeline, and certainly pre-clinically. A drug that makes it to clinical trials before cardiac side effects are identified can result in significant wasted costs, in addition to the human cost. Conversely, a drug incorrectly eliminated also can be costly, both in terms of lost revenue and benefit to society. This STTR Phase I is a proposal to improve the extraction of key data from experiments on the HERG ion channel and its interpretation through computational modeling in the new FDA CiPA initiative. Preclinical safety testing currently focuses on two interdependent questions: 1) Does the drug block the HERG channel? and 2) Does the drug prolong the action potential? The CiPA initiative proposes to integrate this process systematically, through screening of a defined set of cloned ion channels in high throughput systems and combing this with action potential modelling through the qNet index. The HERG channel is handled separately using a complex state-dependent block model that due to its complexity requires very difficult and time consuming manual measurements. This proposal will automate this process by using a real-time interface to computer model block and evaluate the information coming from voltage clamp experiments as they occur. As such it will be an artificial intelligence that will substitute for the judgement of a human experimenter by focusing only on protocols and exposure times that define the kinetics of a particular drug. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DARCY SOLUTIONS INC.
SBIR Phase I: Innovative Advection-Enhanced Geothermal Heat Pump Fieldloop Demonstration
Contact
5451 ZUMBRA CIR
Excelsior, MN 55331–7758
NSF Award
1938497 – SBIR Phase I
Award amount to date
$249,971
Start / end date
12/01/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to address the high costs associated with building heating and cooling in a sustainable fashion. Heating/cooling constitute approximately 48% of building energy consumption. Ground-source or geothermal heat pumps (GSHPs) represent an energy-efficient and environmentally sustainable heating and cooling solution, but their high upfront capital costs have significantly limited deployment. This project takes a fundamentally different approach to GSHP heat transfer, with the expected result that installation costs are decreased by up to 50% and operating costs by 20% compared to conventional GSHP systems. This project will thoroughly field test and analyze the performance of the GSHP innovation, advancing the technology design and installation parameters, and readying it for commercial deployment. This Small Business Innovation Research (SBIR) Phase I project addresses the problem of the high installation cost and large, disruptive footprint of GSHP systems, with the objective to provide a cost-effective, widely-deployable, renewable solution for building heating and cooling. This project will advance an innovative GSHP field loop technology from numerical and laboratory analyses to manufacturing and field testing. The overall research objective is to determine the performance of the innovative GSHP field loop under real-world conditions. The research program includes: 1) development of a comprehensive numerical model of the innovative GSHP system for field sites; 2) field testing, including final design, installation, and operation of equipment at a field site; 3) numerical model and equipment design refinement following initial field testing; 4) installation and testing of modified equipment; and 5) development of a comprehensive cost, energy use and emissions model. It is anticipated that the project will result in a commercially-ready GSHP product, with design and installation guidelines, that substantially (by up to 50%) reduces the installation cost of GSHPs while improving their performance. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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DEEPCONVO INC.
SBIR Phase I: Voice-based telehealth interface for symptom monitoring and screening for chronic and acute respiratory diseases, including COVID-19
Contact
317 CORNWALL DR
Pittsburgh, PA 15238–2643
NSF Award
2032220 – SBIR Phase I
Award amount to date
$255,984
Start / end date
09/01/2020 – 02/28/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is a novel smartphone-based method for symptom monitoring and screening for chronic and acute respiratory diseases, including COVID-19. Current methods of evaluating respiratory diseases are not easily accessible or do not scale to screen large populations. The proposed technology will enable detection and monitoring of respiratory diseases to anyone with access to an internet-connected microphone (e.g., smartphone), using voice as an indicator. The technology will administer simple tests in minutes and deliver results in seconds, without requiring specialized user training. The anticipated outcome is a widespread, real-time screening, monitoring and exacerbation warning system that remotely analyzes voice signals for patients with chronic and acute respiratory diseases, including COVID-19. This Small Business Innovation Research (SBIR) Phase I project seeks to develop voice-based classifiers that diagnose COVID-19 and monitor the severity of the disease. Existing algorithms that detect vocal biomarkers in breath and speech indicative of lung function and respiratory disease will be extended to incorporate COVID-19 signatures. Audio recordings from patients receiving a positive COVID-19 test will be collected to extract micro -signatures and develop algorithms to automatically recognize and map patterns to clinical findings and reported symptoms. The research objectives include developing: (1) A binary classifier that differentiates symptomatic and asymptomatic patients; (2) A multi-class classifier that correlates (in future predicts) changes in the severity of a patient’s symptoms when provided a series of voice samples (3) Developing a dashboard for physicians that provides up to date reports and visualizations of the cross sectional and longitudinal analytics (4) An API giving lung function metrics and classifiers available for integration into 3rd party IT 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.
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DENTUIT IMAGING LLC
STTR Phase I: A Machine Learning Framework for Comprehensive Dental Caries Detection
Contact
651 N BROAD ST STE 205 #677
Middletown, DE 19709–6402
NSF Award
2013846 – STTR Phase I
Award amount to date
$224,999
Start / end date
07/01/2020 – 03/31/2021
Abstract
The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project will be the development of an artificial intelligence software solution that enables automated detection of dental cavities in digital X-rays. Routine misdiagnosis of dental cavities (tooth decay) is a global challenge; cavities alone account for over 5% of healthcare costs in developed countries, with dental care focused on repairing rather than preventing tooth decay. This project will develop an add-on solution for software already in use by 200,000 dentists nationally. The technology resulting from this project will allow non-expert assistants to automate the triaging, screening, and tracking of patients, increasing access to oral care for underserved communities nationally and throughout the world. This Small Business Technology Transfer (STTR) Phase I project will demonstrate the feasibility of two key innovations: (1) a novel software framework using an innovative neural network algorithm for the detection of cavities in X-rays, and (2) the world’s largest database of dental radiographs annotated by specialists in oral radiology. The goals of R&D are to achieve high sensitivity and specificity in cavity detection and to ensure consistent high-quality annotations. Outcomes include: (1) achieving state-of-the-art performance in cavity detection, (2) outperforming domain experts in detecting all stages of cavities, and (3) enabling professionals and non-experts alike to interpret pathologies using a visual heatmap of prediction confidence. The proposed technology features an innovative neural network structure for learning visual representations of dental radiographs that jointly characterize the data while highlighting their most salient attributes. Using a new and original training procedure, the technology will maximize the benefit of existing unlabeled data. Technical challenges include scaling performance while maintaining a minimal false-negative rate, establishing interoperability under various calibration settings, and achieving the desired level of results on the types of machines used by customers with reasonable resource costs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DESIGN THERAPEUTICS, INC.
SBIR Phase I: Development of a genomic targeting drug delivery platform
Contact
6005 HIDDEN VALLEY ROAD, SUITE 2
Carlsbad, CA 92011–4225
NSF Award
1914294 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is a technology that enables the development of novel therapeutics to treat a range of serious genetic neurodegenerative diseases. The proposed drug delivery platform would help improve the understanding of the root cause of certain genetic neurodegenerative diseases. Further, new therapeutics to treat the root cause of severe neurogenerative disorders would have strong commercial potential. Currently, patients have limited treatment options and require significant and costly supportive care. New therapeutics would both improve the lives of patients and create value for insurance providers by reducing the need for costly care. This SBIR Phase I project proposes to demonstrate proof-of-concept for a genomic targeting drug-delivery platform. Unstable nucleotide repeats in the genome have been identified as the root cause of over 20 neurodegenerative conditions. These are debilitating disorders with high disease burden impacting millions of lives. Most nucleotide repeat expansion diseases are caused by a toxic gain-of-function mutation in a single allele. These diseases show dominant inheritance where most patients have a normal, unaffected copy. Silencing expression of the disease allele would address the root cause of the disease, completely halt progression of degenerative symptoms, and likely enable patients to regain lost function. The proposed effort seeks to develop a proof-of-concept allele-specific gene modulator that silences the mutant allele in myotonic dystrophy 1 (DMPK). Using this drug delivery platform, the objective is to synthesize molecules that would target transcriptional repressors specifically to the diseased DMPK allele. Using patient cells, the plan is to test for molecules that silence expression from the repeat containing diseased DMPK allele without impacting the healthy copy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DIGITOUCH HEALTH LLC
STTR Phase I: Smartphone-based blood pressure monitoring via the oscillometric finger pressing method
Contact
7 DANA RD STE 111
Valhalla, NY 10595–1554
NSF Award
1843514 – STTR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to drive hypertension awareness and control rates around the world, through the availability of low-cost, portable blood pressure monitoring. High blood pressure (BP) is a major cardiovascular risk factor that affects up to 1 billion people worldwide. It is treatable, yet hypertension awareness and control rates are low. Ubiquitous BP monitoring technology could improve hypertension management, but existing devices require an inflatable cuff and therefore do not afford anytime, anywhere measurement of BP. The market for a portable, cuff-less blood pressure monitor is estimated in the tens of billions of dollars. Successful completion of this project via demonstration of measurement accuracy across a broad range of blood pressures will provide the company with a strong position in this large market. Ultimately, the success of this project could translate to much greater awareness and control of hypertension, helping reduce the incidence and burden of cardiovascular disease around the world. This Small Business Technology Transfer (STTR) Phase I project aims to develop a technology for cuff-less and calibration-free measurement of blood pressure via a button on a smartphone. Existing automated cuff-based monitors are bulky and do not enable anytime, anywhere measurement of BP. The 'oscillometric finger pressing method'is an emerging approach that uses the same measurement principle that is employed by most automatic cuff devices, but instead of inflating a cuff, the user presses his or her finger (and the underlying artery) against a combination of optical and pressure sensors to determine the blood pressure. The objectives of this program are to shrink the current prototype design and validate its accuracy. The proposed R&D plan includes miniaturization of the circuit components to mount them on a single board and optimization of the sensing technology and algorithm to work in a broad range of normotensive and hypertensive individuals. This work will be followed up by a clinical test of the monitor. The resulting device is expected to be small and thin enough to mount to the back of a smartphone and demonstrate clinical-grade accuracy for the measurement of blood pressure. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DOCUGAMI, INC.
SBIR Phase I: Authoring Assistance via Contextual Semantic Labeling
Contact
150 LAKE STREET S
Kirkland, WA 98033–6460
NSF Award
2012993 – SBIR Phase I
Award amount to date
$216,917
Start / end date
07/01/2020 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to advance Natural Language Processing (NLP) to improve productivity, compliance and insight for businesses. Documents are the underlying fabric of business as they hold detailed agreements, obligations, requirements and terms central to business operations with customers, suppliers, partners and regulators. However, documents still represent "dark data", separate and inaccessible to automated business processes. Businesses like commercial real estate, insurance, professional services, financial services, legal firms and many others produce and consume many documents containing similar patterns with innumerable variations. Authoring and executing these agreements is laborious and error-prone, but it is difficult to automate the use of this semi-structured information. This project develops a series of sophisticated steps to discern structure and information from narrative text, applying the latest techniques from several schools of thought in artificial intelligence. This project will enable knowledge workers to gain the assistance of artificial intelligence to author and execute commercial agreements with greater ease, efficiency, precision, confidentiality, compliance and insight. This Small Business Innovation Research (SBIR) Phase I project is to enhance unstructured human-centered text with a structured computer-optimized version, a "shadow" representation of each document that uses XML and database technology to enable innovative software assistance for users and organizations. The research takes a multi-faceted approach, applying computer vision and then creating a pipeline of new algorithms using techniques from Deep Learning, Bayesian, Evolutionary, Symbolic and Classic NLP. The process operates on "small" datasets (10-30 documents) with high accuracy as well as large datasets. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DRIVEABILITY VT, LLC
SBIR Phase I: Neurocognitive and behavioral detection of THC impairment
Contact
71 CRESCENT BEACH DR
Burlington, VT 05408–2608
NSF Award
2014649 – SBIR Phase I
Award amount to date
$224,472
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to develop a reliable tool for law enforcement for the detection of cannabis-related driving impairment. Impaired operation of equipment costs the nation hundreds of billions of dollars annually. Our detection tool is a software application designed to be presented on a mobile tablet device. It will utilize a combination of neurocognitive, behavioral, and physiological indicators of cannabis intoxication to make an informed determination of impairment. This detection tool may be used as a roadside device by law enforcement, as a screening tool by employers of transit companies, or by an individual user. This Small Business Innovation Research (SBIR) Phase I project is to develop a portable mobile device and software to perform a roadside cannabis detection test. The software will perform a rapid sequence of neuropsychological tests. Combined with an infrared camera to track eye movement and pupillary reflex during driver evaluation, this system can potentially detect driving impairment due to tetrahydrocannabinol. A machine learning algorithm will be used to both assess physical and neurological test results and to present a progressive testing architecture. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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DYNAMIC ENTROPY TECHNOLOGY, LLC
STTR Phase I: Development of an Intranasal Vaccine for COVID-19
Contact
4923 KENTON LK
San Antonio, TX 78240–5404
NSF Award
2032325 – STTR Phase I
Award amount to date
$256,000
Start / end date
10/01/2020 – 09/30/2021
This is a COVID-19 award.Abstract
The broader impact /commercial potential of this Small Business Technology Transfer (STTR) Phase I project is development of a novel, safe and effective, non-invasive, vaccine for the COVID-19 pandemic. Currently there is no approved vaccine for SARS-CoV-2, and some candidates are administered intramuscularly. The proposed intranasal vaccine directly interacts with the respiratory tract and may provide improved protection and virus clearance. The proposed vaccine is non-invasive, easy to administer, and may be effective in a single dose, thus impacting future social distancing needs. This Small Business Technology Transfer (STTR) Phase I project will develop an intranasal coronavirus vaccine and determine the most promising formulation, with tasks including: 1) synthesis of novel coronavirus antigens and formulation of intranasal vaccine using liposome nanoparticles, including antigen discovery, liposome nanoparticle formulation, and in vitro characterization; 2) preclinical testing of intranasal coronavirus vaccine in an animal model, including intranasal vaccination, serum antibody analysis, virus challenge and analysis of protection efficacy. The outcome of this Phase I study is to obtain an optimized nanoparticle intranasal vaccine formulation for induction of robust T and B cell responses specific to SARS-CoV-2 S and N protein. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Dascena
SBIR Phase I Machine Learning for Screening Acute Respiratory Distress Syndrome in General and COVID-19 Patient Populations
Contact
1135 Martin Luther King Dr.
Hayward, CA 94541–4399
NSF Award
2014829 – SBIR Phase I
Award amount to date
$225,000
Start / end date
08/15/2020 – 01/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to improve early and accurate acute respiratory distress syndrome (ARDS) detection. ARDS detection is vital due to the recent COVID-19 outbreak and the propensity for individuals testing positive for COVID-19 to develop ARDS as a serious complication, as well as the 140,000 patients per year in the United States admitted with ARDS. The ARDS diagnostic market in the US was an estimated $154 million in 2018. This project will advance a machine-learning algorithm to accurately predict ARDS onset in the COVID-19 patient population. These systems will monitor patient electronic health records and automatically provide ARDS prediction alerts for both general and COVID-19 patient populations, thereby enabling appropriate intervention and prevention methods in advance of ARDS onset to improve patient outcomes. This Small Business Innovation Research (SBIR) Phase I project will use semi-supervised machine learning (SSL) to develop and validate an ARDS prediction screening tool. The goals and anticipated technical results are as follows: Aim 1 will employ semi-supervised deep learning to develop a model for the prediction of ARDS up to 48 hours prior to onset. Because SSL will improve generalized performance, the tool can be applied in settings where many clinical features are not available, including a lack of radiographic data. Aim 2 will validate and optimize the semi-supervised model across external datasets. Validation on external datasets will evaluate the algorithm across a variety of hospital-specific measurement frequencies, demographics, and care practices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ECO-SHELTER, LLC
STTR Phase I: A non-woven bamboo-based strand composite process to manufacture low-cost roofing
Contact
2650 NW 58TH ST APT 4
Seattle, WA 98107–5307
NSF Award
1914284 – STTR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this STTR Phase I project is the stimulation of a new economy for natural fiber composites, allowing wood manufacturers and other industries an opportunity to expand into a profitable and sustainable venture, improving livelihoods. Developing a suitable replacement to asbestos cement corrugated sheets can drive new industry and work opportunities for the 125 million people in the world who are exposed to asbestos in the workplace. Further, a safe and affordable alternative will reduce millions of families future exposure to the harmful and toxic substance. Providing a cost-effective, energy-efficient roof will have both an environmental and health impact at a household level and lead to increases in energy savings and productivity while also reducing heat-related stress and illnesses. Demonstrating the potential of natural fiber composites as structural construction materials will promote a low-energy production process and sequestration of carbon dioxide through sustainable and renewable grasses and fibers, which can be scaled in resource-limited settings throughout Asia and Africa. This Small Business Technology Transfer Phase I project seeks to develop a commercially viable and scalable process to manufacture a bamboo-based strand composite for application in low-cost roofing globally. The intellectual merit of the proposed project resides in undertaking technical objectives to (i) determine ideal feedstock characteristics to produce suitable bamboo strands for formation into three-dimensional (3D) panels (ii) developing proper resin application systems to effectively consolidate and bond bamboo strands into durable panels and (iii) produce a prototype sandwich panel and evaluate its structural performance as well as resistance to moisture uptake and dimensional stability, and thermal conductivity. This new knowledge is expected to significantly advance the field of natural fiber composites by addressing several existing technical challenges for long-term construction applications that can withstand hot and humid climates, including ideal distribution of particulate geometry and moisture content, biodegradation, and effective binders for functionality. A prototype of the process to manufacture a non-woven bamboo-based strand composite for a roofing application will be designed and built to ensure it can be deployed at scale for industrial production in resource-limited 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.
Errata
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ECOCLOSURE LLC
STTR Phase I: High Performance Microalgae Building Enclosures for Energy Efficient Retrofitting Application
Contact
5530 BALLANTYNE COMMONS PKWY
Charlotte, NC 28277–0566
NSF Award
2012157 – STTR Phase I
Award amount to date
$225,000
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is in the sustainable and economic retrofitting of low-performing older buildings toward improved economic, social and ecological impacts of built environments. More than half of all commercial buildings were constructed before the 1980s with lower energy standards. The owners and occupants of these buildings now often seek better energy management and air quality technologies. The microalgae window developed in this Phase I project is an energy-efficient, easy-to-install, adaptable modular unit for different retrofitting applications, able to compete with conventional windows due to its good air quality and renewable energy potentials. Gains in worker productivity from microalgae window retrofit are estimated to be substantial and building values at sale or rental are expected to increase significantly due to building envelope improvement. This Small Business Technology Transfer (STTR) Phase I project seeks to develop an innovative, cost-effective microalgae window for retrofitting low-performing commercial windows. Microalgae are an effective biological system for carbon capture and biomass production from photosynthesis. The microalgae window incorporates a network of screens filled with microalgae within a window assembly to replace or add to older windows for energy-efficient retrofitting. The microalgae screen within a window assembly is able to balance multiple functions of thermal insulation, daylight transmission, solar shading efficacy, and views to outside. Research objectives are to: 1) characterize the optimal microalgae window system for pre-1980 office retrofitting applications; 2) verify environmental performance using computer simulations and lab experimentation in accordance with industry standards; and 3) conduct field testing to evaluate building energy savings, indoor air quality improvement and renewable energy production potentials. The new microalgae window mitigates energy transfer between indoor and outdoor environments, subsequently reducing heating, cooling, lighting, and ventilation demands. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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EDGETENSOR TECHNOLOGIES INC.
STTR Phase I: A Self-Learning Approach for In-Vehicle Driver and Passenger Monitoring Through a Sensor Fusion Approach
Contact
6708 ALCOVE LN
Plano, TX 75024–6320
NSF Award
1950249 – STTR Phase I
Award amount to date
$225,000
Start / end date
03/01/2020 – 11/30/2020
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project will result from the introduction of a state-of-the-art driver monitoring system using artificial intelligence to detect distracted driving or poor driving practices. It can also be used for driver coaching and education, as well as to improve driver attention. The system will help minimize accidents and create safer roads and work environments. End users include automotive original equipment manufacturers (OEMs), commercial fleet operators, taxi and ride-sharing companies, heavy machinery and crane operators, rail and aviation operators, and operators of specialized transportation systems, such as school bus services and charter vehicles. This Small Business Technology Transfer (STTR) Phase I project will exploit data from different camera and inertial sensors inside a vehicle to monitor and assess the attention of the driver. The driver’s gaze and upper body pose will be evaluated separately using artificial intelligence (AI) methods and the results combined to generate an overall estimate of the level of driver distraction. The proposed framework is expected to generate reliable results even in cases of high face occlusion. The technical objectives of the project include to: 1) Explore supervised and unsupervised methods to track the driver's body movement using depth and RGB sensors, addressing the challenges and drawbacks of current vision-based algorithms in real-world driving conditions; 2) Design a novel deep learning framework to integrate the driver's body pose with his/her attention level to infer driver's activities (e.g., such as using portable devices, eating, drinking, and other activities); 3) Develop new models of driver visual attention to obtain confidence levels in the estimated driver's gaze, estimated shoulder pose and joints positions; 4) Develop multi-modal end-to-end deep learning frameworks that integrate multiple sensors to provide important features for monitoring and assisting the driver; 5) Implement the system on low-power commodity hardware that is cost-effective and scalable. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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 – 06/30/2021
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.
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EMANATE WIRELESS, INC.
SBIR Phase I: Utilization, Condition, and Location Tracking for Clinical Assets
Contact
11145 WINDSOR ROAD
Ijamsville, MD 21754–8911
NSF Award
2025873 – SBIR Phase I
Award amount to date
$255,221
Start / end date
08/01/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to improve the quality of healthcare in the United States by reducing the costs to maintain clinical equipment. US hospitals spend $93 billion yearly on medical equipment life cycle costs (second only to personnel). Large inefficiencies exist; a typical hospital has 25% over-inventory of equipment, resulting in $1 M annually in unnecessary capital and operational expense. Current monitoring systems use wireless tags to locate equipment but these do not reduce equipment maintenance costs. This proposal will develop a new tag with sensors and software to monitor not only equipment location but also utilization and condition to optimize inventory levels. This system will generate further savings by optimizing equipment service intervals based on usage and condition rather than simply elapsed time. Most importantly, this system will improve patient outcomes by detecting faults requiring immediate service, such as drops and failing mechanical components. This Small Business Innovation Research (SBIR) Phase I project will advance development of technology enabling hospitals to optimally manage clinical equipment. The solution mounts small battery-powered wireless tags (with sensors and machine learning algorithms) on equipment for monitoring. The research plan will address three main technical challenges: applicability, scalability and readiness as follows: 1) Applicability: Measure a wide variety of device types, analyze collected sensor data, identify algorithms mapping sensor data to context, and test performance under real-world scenarios; 2) Scalability: Develop procedures and tools to create an algorithm library for the thousands of device-type/make/models in the hospital market; and 3) Readiness: Characterize the cost-size-battery life trade space, with a goal of tag life of 10 years, including exploring battery alternatives,sensors with deep-sleep modes, and adaptive algorithms maintaining device context with maximum sleep intervals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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EMERALD TUTU INC, THE
SBIR Phase I: The Emerald Tutu
Contact
189 HAMILTON ST
Cambridge, MA 02139–3923
NSF Award
2016199 – SBIR Phase I
Award amount to date
$255,999
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide a nearshore (just offshore of inhabited coastal land, in shallow water) solution to reduce coastal flooding. The proposed project addresses a need to lessen heavy flood protection solutions based on carbon-intensive concrete in the form of seawalls and other barriers. This project will prototype an interconnected network of floating growth mats, made to seed marsh grass above the water and seaweed below. The heavy biomass of these mats and their network properties as a large interconnected group provides wave and storm surge reduction. A proposed turnkey kit offers a low-cost system, readily deployable and expandable over time. Additionally, as a floating park-like marine landscape, it has many co-benefits to the surrounding communities. As plant-based infrastructure, it serves as a site for native marsh grasses and local seaweeds to populate, providing new habitats and improving water quality. This SBIR Phase I project is a natural coastal resilience technology designed to be pre-fabricated, modular, and easy to implement for a variety of coastal environments and communities. The technology consists of robust vegetated mats linked in a network and deployed in the nearshore. The mats are colonized by local varieties of semi-aquatic marsh flora above the water line, and aquatic seaweeds below. Research objectives to validate this approach include comparing mat network performance in a range of flow conditions, including extreme waves, to inform mat design. A second research thrust will measure biomass accumulation and ecological performance through in situ deployments of mat structures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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 – 06/30/2021
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.
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ENKOAT LLC
SBIR Phase I: Composite Coatings for Improving Energy Efficiency of Building Envelope Systems
Contact
661 N CASTLEDALE AVE
Casa Grande, AZ 85194–6500
NSF Award
2015128 – SBIR Phase I
Award amount to date
$249,996
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of energy efficient building coatings that have the potential to significantly reduce greenhouse gas emissions. The market for energy efficient coatings is experiencing accelerated growth due to government and rapid rise in demand for Leadership in Energy and Environmental Design certified structures. With these recent developments, building developers are actively seeking solutions which are technologically robust and cost-effective for meeting energy mandates. These novel architectural coatings not only provide the aesthetics and textured finish as traditional architectural coatings, but also provide the added benefit of decreasing heating and cooling related costs for the building owner. This Small Business Innovation Research (SBIR) Phase I project is focused on developing an optimized blend of phase change materials for incorporation in architectural building envelope coatings such as paint, plaster and stucco, to provide them with insulative properties. The optimized blend will consist of phase change materials (PCMs) with different phase transition temperatures in specific volume proportions to maximize energy savings in a specific climate zone in terms of heating and cooling costs. Preliminary lab work has shown promise that PCMs can be utilized in coatings to reduce temperature swings and shift the peak load to off-peak hours, which can lead to significant cost savings. This project will develop protocols to maximize incorporation of PCMs in these coatings without compromising their aesthetics. Energy modeling and experimental work including micro- and macro- scale material characterization will be carried out to verify the laboratory and small field-scale performance of these 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.
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ENVIRONMENTAL PROTECTIVE COATINGS LLC
SBIR Phase I: Durable Omni-Phobic Coatings
Contact
23255 BELLWOOD DR
Southfield, MI 48034–5155
NSF Award
2014801 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to advance the development of a self-cleaning coating technology for applications in household products, automotive, sensors and aerospace. Fluorinated materials have been widely used in self-cleaning applications due to their excellent wear characteristics, and super-hydrophobicity, but their environmental impact motivates new solutions. Attempts to date have typically resulted in materials that are cloudy, non-durable and/or too expensive for commercial relevance. This project will advance a new coating that adheres well to substrates, offers high abrasion resistance similar to glass, and exceptional weather resistance. This Small Business Innovation Research (SBIR) Phase I project will allow the advancement of a durable, non-fluorinated, super omniphobic, optically clear coatings for industrial applications. The proposed work is focused on enhancing the performance of nonfluorinated omniphobic coatings in three specific ways. First, the adhesion of omniphobic coatings will be improved such that they will be able to withstand submersion in water for months without showing swelling/delamination. This will be achieved by using water stable urethane polymers and/or prior surface treatment of the substrate. Second, the abrasion resistance of the coating will be enhanced by using a combination of urethane precursors and fillers. Finally, the weatherability will be increased by using UV stabilizers along with UV stable urethane polymers such that the coatings will have improved performance in outdoor 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.
Errata
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Addenda
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ENVIROTRONICS, LLC
STTR Phase I: Self-powered underwater light system for photosynthetic cultures
Contact
8000 INNOVATION PARK DR BLDG 310
Baton Rouge, LA 70820–7400
NSF Award
1843399 – STTR Phase I
Award amount to date
$211,834
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this project is to transform the culture of photosynthetic aquatic microorganisms. Although microalgae and cyanobacteria have high volumetric productivities, the cultures cannot be too deep, due to restrictions of light penetration. This proposed technology removes the light penetration limit inherent in current technologies. The results of this project will allow the production of medical and food grade biomass in controlled conditions, as the light source will not be connected to the exterior of the culture reactors. This approach will provide the advantages of a fermentation production using phototrophic species, without the need to supply organic carbon. The photosynthetic biomass production makes use of carbon dioxide and light for growth. This project will result in a microalgal/cyanobacterial biomass production in areas where it is not currently feasible and with higher productivity. The increase of the depth of the cultures two, five or more times of what is currently possible, practically reduces the area required for biomass production. A reduction of cost will improve the economic outlook for microalgal-based commodity products, including feed, food, fuels, nutraceuticals and pharmaceuticals and lower the environmental impact. This Small Business Technology Transfer (STTR) Phase I project addresses one of the most significant problems found in achieving the promise of microalgae and cyanobacteria as source of food, fuels and other products is the limitation of light penetration. Most outdoor cultures are limited to less than 60 cm depth. In reactors with artificial light, besides the light penetration high electrical costs limit their use to high value products. This project will result in a light system that takes advantage of the water movement in cultures to generate electricity for LED lights in untethered units that move with the culture. The proposed generator uses methods more efficient and lighter that traditional electromagnetic and piezoelectric generators. The developed energy harvester can be used in other applications such as power for water quality monitoring and other sensing equipment. In this phase, a unit with a miniaturized energy harvester coupled with passive switching, charging, discharging and rectifying modules in the same substrate, in a waterproof casing will be developed. Data proof of the suitability of these units to support photosynthetic microorganisms? biomass production will be obtained. The results will inform further development of the units in a future phase. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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ENVISION ENDOSCOPY, INC.
SBIR Phase I: Endoscopic Patient Mask to Limit Aerosolization During Endoscopic Procedures During COVID-19 Pandemic
Contact
15 FAIRFAX ST APT 2
Somerville, MA 02144–1107
NSF Award
2030942 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to help manage COVID-19 transmission in hospitals with a novel patient face mask to limit transmission of SARS-CoV-2 virus during endoscopic procedures. All endoscopic procedures are considered aerosol-generating procedures because of the possibility of coughing and retching during upper endoscopy, and the passage of flatus during colonoscopy. The proposed patient endoscopic mask limit the spread of microdroplet and aerosols from the patient. This project proposes to develop an endoscopy mask which will be disposable, single use, with an oral opening for the introduction of an endoscope to the gastrointestinal tract. The proposed solution will allow most type of endoscopes, probes, and tubes to be inserted through the mask and enter the mouth or nose, while providing a seal between the mask and scope to limit leakage during the procedure. In addition, it will reduce the post-procedure wait time needed for air circulation in the endoscopy room to remove aerosols for the safety of patients and gastrointestinal health care givers. The solution will be useful for managing transmissions of any airborne infections. This Small Business Innovation Research (SBIR) Phase I project will develop a novel technology that seals between the mask opening and an endoscope, while allowing the endoscope's advancement inside the gastrointestinal tract. The challenge with sealing the mask comes from the scope, which must have significant freedom of motion when it is inserted into the mouth of a patient. The proposed mask will have an access for suction to clear airway secretions and to remove aerosol and micro-droplets generated during endoscopic procedures. If successful, this seal technology can be utilized in other aerosol-generating clinical applications, such as reducing spread of aerosolized droplets of blood in laparoscopic surgery procedure. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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EPIImaging, LLC
SBIR Phase I: A Passive Alternative to LiDAR for Automotive 3D Ranging
Contact
414 Paco Drive
Los Altos, CA 94024–3827
NSF Award
2015152 – SBIR Phase I
Award amount to date
$224,850
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will advance the development of detection systems for autonomous vehicles. The proposed technology takes advantage of trends in price, performance, and quality of imagers and processors driven by the proliferation of these devices in smartphones. The technologyalso provides key capabilities such as integrated color information, detection over extended depths, scene segmentation and tracking, and better performance in inclement weather or under poor visibility. This leads to improvements in three-dimensional (3D) vision and object modeling that will have significant commercial impact in accelerating the development and deployment of autonomous and semi-autonomous vehicle navigation and assistance. This will lead to higher commuting efficiency, reduced traffic fatalities, reduced traffic congestion, and reduced pollution. This Small Business Innovation Research (SBIR) Phase I project will establish the technical capabilities and advantages of passive sensing image-based multi-camera EPI Epipolar-Plane Imaging (EPI) analysis for autonomous vehicle (AV) ranging. The research objective is to advance the development of EPI analysis and compare it to Light Detection and Ranging (LiDAR) systems. The research will extend an existing EPI-based module to incorporate new hardware and software to achieve these results, including accuracy and precision comparable to LiDAR at distances of 200 m and beyond, feature discernment superior to LiDAR, higher levels of semantics in presented range information, and operation in inclement weather and discrete obscuration. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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EQO, INC.
SBIR Phase I: Investigation of a Bioengineered Immunotoxin for Use as a Biopesticide for the Control of Aquatic Invasive Mussel Infestation
Contact
6101 HIGHLAND CAMPUS DR # 2250
Austin, TX 78752–6000
NSF Award
1938619 – SBIR Phase I
Award amount to date
$225,000
Start / end date
10/01/2019 – 01/31/2021
Abstract
The broader impact & commercial potential of this Small Business Innovation Research (SBIR) project is the ability to control zebra & quagga mussel infestations with a cost-effective and target-specific biological treatment. In addition to the estimated $7 billion economic impact, mussel infestation causes substantial ecological impacts. Currently, there is no treatment option available following infestation by quagga or zebra mussels functional at the scale of commercial reservoirs without significant disruption of native species. The successful development of an efficient and specific treatment has the potential to improve the ability to restore and protect native aquatic ecosystems, water infrastructure, power production infrastructure, and native fisheries. Additionally, the approach has the potential to lower production cost, and require a lower effective dose when compared to current treatment options. This SBIR Phase I project proposes to develop a biopesticide comprised of the enzymatic portion of a toxin for the mechanism of action and the binding domains from antibodies for targeting zebra and quagga mussels. Control of infestation by chemical means is largely restricted to enclosed systems, and requires additional remediation prior to water use. Biopesticides, however, can be considered a reduced risk treatment option. The use of ScFv (single chain variable fragment regions) from mAbs (monoclonal antibodies) has become common place in pharmaceuticals like Herceptin and MT-3724 and can be used here, resulting in a treatment product with anticipated high specificity, high efficiency, known mechanism of action, limited half-life, no expected long-term environmental impact, and limited to absent off-target impact. This work is believed to be novel as biopesticides utilizing immunotoxin technology for the remediation of aquatic nuisance species are not well developed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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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 – 06/30/2021
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.
Errata
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ESTAT ACTUATION, INC.
SBIR Phase I: Rotary Electroadhesive Clutch for Lightweight and Energy-Efficient Actuators in Next-Generation Robots
Contact
5540 HOBART ST
Pittsburgh, PA 15217–1967
NSF Award
1941405 – SBIR Phase I
Award amount to date
$225,000
Start / end date
12/15/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research project will be to enable new robotics systems with actuator hardware that is substantially lighter and less expensive than the current state-of-the-art. The high cost and limited performance of actuators are the greatest problems for engineers developing products for mobile applications, such as package delivery, security, disaster recovery, and wearable assistive devices, causing the market to bifurcate into low-cost robots with extremely limited functionality or versatile robots costing tens or hundreds of thousands of dollars. Clutches are an important way to reduce actuator requirements and costs, but conventional clutches are large, heavy, and power-hungry, ultimately negating potential improvements. In this project, we will develop an electro-adhesive clutch that is 10x lighter and uses 1000x less power than conventional clutches. This hardware innovation allows robotics engineers to use clutches with almost no mass or power consumption penalties. Removing this constraint will have a substantial impact on the commercial viability of robots that are both capable and affordable. This Small Business Innovation Research (SBIR) Phase I project will consist of the design and characterization of a compact rotary electro-adhesive clutch. This work will build on recent accomplishments in creating and characterizing the linear electro-adhesive clutch design to move toward a rotary design integrating with existing robotic joints with minimal required hardware changes. The objectives of this work are to experimentally optimize the effect of materials and design choices on the performance of the rotary electro-adhesive clutch, and to establish performance metrics to evaluate the feasibility of commercial use. Design work will include simulation, mass optimization, and exploration of fabrication techniques. The experimental work will characterize the system in terms of maximum torque, power, and speed testing, response time and dissipation testing, and preliminary fatigue and wear experiments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ETALYC, Inc.
SBIR Phase I: Information fusion-driven adaptive corridor-wide traffic signal re-timing
Contact
2711 S Loop Dr
Ames, IA 50010–7146
NSF Award
1914219 – SBIR Phase I
Award amount to date
$224,737
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from a significant reduction in traffic delays, crashes, and fatalities by implementing a fully adaptive traffic signal re-timing solution. The most recent National Traffic Signal Report Card gave a failing grade of D+ to traffic signal operations in the United States. These failing grades are despite the fact that agencies spend approximately $2 billion every year on signal operation, maintenance, and capital improvements. If the US supports its signals at an "A" level, the public would see: (i) a 15-40% reduction in traffic delay, travel time savings up to 25%, and a 10-40 % reductions in stops; (ii) a 10 % or more reduction in fuel consumption resulting in nationwide savings of almost 170 billion gallons of motor fuels per year; and (iii) up to 22% reduction in harmful emissions. From a science and technology perspective, this effort will be an impactful success story for artificial intelligence and machine learning. As the small business is a product of Iowa State University start-up factory, the project is expected to involve students looking for industry experiences in the project leading to a more comprehensive education for them. This Small Business Innovation Research (SBIR) Phase I project will develop and demonstrate proof-of-concept of a fully adaptive traffic signal re-timing solution. The key intellectual merit of this effort will be developing deep learning models to extract abstract features from a range of heterogeneous information sources to perform feature-level fusion. Upon feature extraction, the proposed solution will use scalable deep reinforcement learning models to obtain re-timing decisions. The reinforcement learning process will help the system adapt to changing traffic scenarios at different time-scales without the need for significant manual interventions. The solution will be flexible for both onboard and cloud-based computing, depending on the availability of such platforms. Overall, the proposed system will reduce implementation time and capital and maintenance expenditures. These advantages will encourage cities around the US and internationally to adopt such a re-timing strategy and will dramatically transform the current landscape of this market. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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EVOLUTION DEVICES, INC.
SBIR Phase I: 3D Markerless Motion Capture Technology For Gait Analysis During Rehabilitation
Contact
2150 SHATTUCK AVE FL PH
Berkeley, CA 94704–1370
NSF Award
2014869 – SBIR Phase I
Award amount to date
$224,990
Start / end date
07/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance diagnosis and treatment of walking disorders and associated rehabilitation. An estimated 50 million Americans experience gait (walking) impairment due to injury, disease, and age, and more than 38,800 physical therapy clinics treat these patients. This project will develop an artificial intelligence system to extract gait metrics from video data from cameras surrounding a small area. A new diagnostic tool will track nuanced gait metrics throughout rehabilitation treatment. This technology will enable new and faster ways for physical therapists to precisely diagnose gait abnormalities and track treatment. This Small Business Innovation Research (SBIR) Phase I project could result in a system to diagnose gait deficiencies for people who suffer from neurological impairments. The proposed project will develop a markerless three-dimensional motion capture system to accurately diagnose gait pathologies in a time- and cost-efficient manner for clinicians. The project will: validate of the markerless motion capture system to ensure accurate measurement of raw kinematic metrics within 10% error of standard methods and potentially expand the system metrics; and conduct verification and validation 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.
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EWPanel LLC
STTR Phase I: Powerless, Flexible Sensor Subfloor Mats from Natural Materials
Contact
326 W Gorham Street
Madison, WI 53703–2017
NSF Award
1843965 – STTR Phase I
Award amount to date
$224,590
Start / end date
07/15/2019 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project involves a low-cost, convenient, anonymous floor occupancy analysis. This will be achieved by developing a powerless, flexible subfloor sensor mat that can integrate with regular flooring products. If implemented in buildings, the sensor mat will help raise space utilization, improve occupant productivity and satisfaction, and inform dynamic layout planning for organizational agility. This sensor mat will address the needs from different parties in the small building ecosystem, including flooring manufacturers, building system integrators, work space system providers, architects and interior designers, and cooperations and businesses in commercial buildings. Additionally, this thin film with high electrical output, if successfully achieved in this project, will find great commercialization potential in other applications, such as self-powered, wireless adhesive wearable electronics, and implantable medical devices. This proposal also has an environmental impact in that it reduces carbon footprint, promotes use of green natural materials and generation of renewable energy. The proposed project has the intellectual merits of addressing two key questions that could determine the technical and commercial feasibility of the occupancy sensor mat. First, how to create a sufficiently thin and flexible sensor mat that has no impact on flooring installment and walking performance. Second, how to raise the electrical output and energy generated from the sensor mat to the level that is high enough to meet the requirements of signal resolution and wireless transmission? Specific research tasks and methods include: natural cellulosic materials chemical functionalization for electric property engineering towards high power output; sensor mat design to effectively convert footsteps to electricity within a confined mat thickness; integration of wireless transmission units tailored for the sensor mat towards a self-powered sensor with wireless connectivity. The final goal is to develop a powerless sensor from which the electrical output and the energy generation will be sufficient to sustain itself and to provide discernible 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.
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EXOTANIUM, INC.
SBIR Phase I: Intelligent, real-time migration of software containers to optimize cloud computing resources
Contact
350 Duffield Hall Suite N
Ithaca, NY 14853–2700
NSF Award
2025878 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve usage of computing cloud resources to minimize waste. Increasingly, businesses are running IT infrastructure and operations in the cloud to reduce server expenses. However, leasing equivalent cloud space from major providers can cost companies as much as 50% of their revenue. This is in part because businesses must overprovision to accommodate potential surges in server use and to ensure that applications that cannot tolerate any downtime are not interrupted. This overprovisioning causes as much as 60% of unused/idle cloud space and an estimated $14 Billion in wasted spending annually. This project will enable users to reduce their cloud spend by up to 90% by taking advantage of deeply discounted server space available in spot markets, and it will further enable users to optimize their workloads by consolidating virtual machines, further reducing cost. This Small Business Innovation Research (SBIR) Phase I project will focus on the development of two novel intelligent-automation-based solutions. The first technology will dramatically improve the usability of discounted virtual machine (VM) instances (Spot Instances) for critical applications by spawning containers on discounted Spot Instances and dynamically relocating containers between such instances based on availability and price. The second technology will address idle resource waste in the cloud by packing idle containers onto a small number of VMs during the idle period, minimizing the number of active VMs and thus reducing the cost of keeping services online. When the workload increases, the technology will relocate containers onto different VMs, without any service interruption. To establish feasibility, a prototype for each element will be designed and developed. Objectives include: 1) optimize network and storage for supporting the company’s patented container architecture for secure isolation of containers in the cloud; 2) develop a resource scheduler for both proposed solutions 3) develop a user interface for workload monitoring and configurations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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EYEDEA MEDICAL, INC
SBIR Phase I: Development of a novel, highly efficient Descemet's Membrane Endothelial Keratoplasty preparation device expands the donor pool
Contact
3361 CHESTNUT AVE
Baltimore, MD 21211–2623
NSF Award
1938552 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2020 – 12/31/2020
Abstract
The broader/commercial impact of this SBIR Phase I project will study and improve the process of corneal graft preparation in eye banks for use in vision-restoring transplant procedures to treat corneal diseases, affect more than over 4 million people in the United States. Descemets membrane endothelial keratoplasty (DMEK) is an advanced procedure involving transplantation of a thin layer of the cornea with outstanding clinical outcomes. However, this places a significant burden on eye banks as they use a difficult, time- and cost-intensive process to isolate the thin layer of the donor cornea (DMEK graft), subsequently provided to a surgeon for transplantation. The proposed research will enable development and evaluation of a novel to decrease the difficulty of DMEK graft preparation, reduce the time required, and expand the eligible donor pool. Improving the graft preparation process will result in increased economic efficiency within eye banks, and help enable greater access to vision-restoring DMEK procedures to individuals in the United States. This project seeks to develop and evaluate a novel, first-in-class graft preparation device that standardizes, de-skills, and improves the viability of the liquid bubble technique (LBT) for DMEK graft preparation. The proposed device overcomes the major barriers to LBT adoption: (1) consistent needle insertion into the correct tissue plane and (2) endothelial cell loss (ECL) due to high pressure in the cornea. It does so via a stabilizing corneal base in conjunction with a needle insertion system to allow for simple, standardized DMEK preparation in under 5 minutes with less than 5% failure rates at appropriate graft viability, even in diabetic and obese donor corneas. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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EarthSense, Inc.
STTR Phase I: Autonomous Disinfecting Robot for Crowded Spaces
Contact
60 Hazelwood Drive
Champaign, IL 61820–7460
NSF Award
2027693 – STTR Phase I
Award amount to date
$256,000
Start / end date
06/01/2020 – 05/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to respond to the COVID-19 pandemic. The proposed work will rapidly create new autonomous robots for sanitization in hospitals and other high-traffic areas with high risk of surface-borne pathogen transmission. The autonomous sanitizing system produced by this effort would fill a crucial void in ensuring hospital spaces are kept sanitized as the health care system scrambles to respond to the evolving COVID-19 crisis. In addition, the solution will be widely applicable in controlling Hospital Acquired Infections, affecting over 2 million people in the US annually, with an overall economic impact of $45 B. The proposed autonomous high-dexterity robots are projected to successfully keep the high-touch areas in about 10,000 square feet of commercial space reliably sanitized and could be applicable to the over 50 billion square feet of public commercial space (office, industrial, healthcare, hospitality, retail, etc.) in the US. Faster, more efficient, and targeted santization has potential to dramatically reduce downtime of these spaces and the labor required for sanitization. This STTR Phase I project, in response to the ongoing COVID-19 crisis, will rapidly develop new robotic systems and algorithms for robots capable of precisely navigating surfaces in crowded environments. This new system will be capable of selective sanitization in the proximity of humans, removing the key limitation of existing full-room single-source UV radiation based robots requiring the room to be unoccupied. UV light technology has tremendous promise in improving sanitization at hospitals and reducing costs by minimizing chemical use, but the technology has had limited application due to ill effects on mammalian cells. The selective exposure capability with the use of the robotic arm and focused lighting will alleviate that limitation, opening up further uses of UV lighting in hospital sanitization. Toward this goal, this project will advance key areas of robotics, including Simultaneous Localization and Mapping (SLAM) algorithms in the presence of dynamic obstacles, and the control of arms over surfaces with varied objects and in the vicinity of humans. These efforts will advance the science and practice of robotics for applications in healthcare and other 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.
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Electro Magnetic Applications Inc Denver
SBIR Phase I: Design and Development of a Dynamic Spacecraft Charging Test Chamber and Combined Spacecraft Charging Effects Simulation Environment
Contact
7655 W Mississippi Ave
Lakewood, CO 80226–4356
NSF Award
1938315 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will offer the space industry a timely and cost-effective means for accurately quantifying and evaluating the effects of space radiation on their materials and products. Companies will have the capability to understand the performance of their materials and products in dynamic, realistic space radiation environments, which will lead to advances in materials, longer lifespans, and fewer accidents/failures. The capability to study subsystem response in a realistic simulated environment and inform complex models will enable faster optimization and design iterations at lower costs. The proposed project will develop a simulation tool coupling the drastic timescale differences of surface and internal charging in a user-friendly interface, and pairing this tool with a dynamic space radiation testing chamber. A simulation tool with these capabilities addresses the usability gap in the state of practice and enables the solution of the complete spacecraft charging problem in a single simulation. The ability to produce broad spectrum energies and alter these sources in-situ allows for materials and objects to be exposed to realistic environmental changes without the approximations and extrapolations currently required due to the limitations in capability, scheduling, and size at appropriate facilities. The proposed system will offer a new capability for testing and modeling of subsystems such as human radiation protection devices, satellite materials and components, solar panels, and others; this will enable design advances that are faster, more accurate, and more effective than those currently available. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Eye-Predict
SBIR Phase I: Visuotactile tests of mental domains
Contact
3400 Ben Lomond Pl
Los Angeles, CA 90027–2955
NSF Award
2014693 – SBIR Phase I
Award amount to date
$225,000
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I is better outcomes and lower costs for people with major neurological or psychiatric conditions. The proposed technology will offer a set of tests for assessment of cognitive function. Millions of Americans suffer persistent emotional, cognitive, or sensorimotor dysfunction after experiencing traumatic brain injury. The proposed system will operate on standard mobile devices to facilitate easy diagnosis and treatment. This Small Business Innovation Research (SBIR) Phase I project will establish the feasibility of developing a battery of visuotactile tests to assess mental domains. The proposed study will yield stimulus-response data (psychometric functions) based on novel visuotactile measures and compare them to analogous functions based on gold-standard measures that are much less accessible. Personalized testing will maximize interpretability by customizing stimulus parameters for each individual and testing session, thus minimizing the likelihood of floor and ceiling effects. The feasibility aims will be achieved if psychometric trends for the proposed measures match those found for analogous gold-standard 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.
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Eyes in Synch LLC
SBIR Phase I: Eyes in Sync
Contact
6775 Moore Drive
Oakland, CA 94611–0000
NSF Award
2014229 – SBIR Phase I
Award amount to date
$225,000
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to advance technologies for vision improvement. Many suffer from undetected problems with moving their eyes for reading, and current technologies do not reveal this in school screenings or sometimes, even in doctor's offices. This product will be an app designed for smartphones to engage children in games that build skills for optimally using the two eyes together, a critical element in reading ability and visual performance. The innovation will enhance scientific and technological understanding by integrating in one app eye movement, psychophysical, and reading fluency assessment. The technical result will be an all-in-one, portable, easy and fun-to-use solution for improving visual skills and reading in children. It will provide data to learning technologists to improve solutions customized to address conditions, such as dyslexia and autism. This Small Business Innovation Research (SBIR) Phase I project addresses the issue of “functional binocular vision” or FBV. When the eyes do not look at exactly the same place, or when they cannot move across a page of text accurately and efficiently, discomfort often occurs. This discomfort causes children in particular to stop reading, affecting their learning. The project aims to develop and test an approach less expensive and more appealing than solutions available today. The proposed app will test existing visual skills (convergence and tracking) and reading fluency, then track the eyes as they move while the user plays games. Users receive points for being able to identify targets; they can only perceive the targets if their eyes are working together correctly. The technology will enable users to get immediate feedback on how they performed in the games (their visual skill level) and how their reading speed (fluency) improves. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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FLATCAM LLC
STTR Phase I: FlatCam: Inexpensive, Compact Lensless Cameras for IoT Applications
Contact
5214 La Branch St
Houston, TX 77004–5840
NSF Award
1914252 – STTR Phase I
Award amount to date
$224,995
Start / end date
07/15/2019 – 12/31/2020
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is the development of a new imaging platform technology that has the potential to affect many areas including consumer imaging, medical imaging, spectroscopy, astronomy, surveillance, and defense. Transitioning this technology into real applications will mean this technology can be used for personalized experiences, improved quality of life, and increased safety. The STTR Phase I proposed project will develop inexpensive, lensless imaging devices (contrary to the current state-of-art cameras, that rely on lenses to form a focused image), that can be integrated with internet-of-things (IoT) devices to gather visual data. Since the lens in a camera accounts for the vast majority of the cost and the weight, these devices can provide order of magnitude reductions in cost, allowing cameras to be integrated into a much larger array of home, auto, and city-scale smart devices. The research tasks in this project are: (1) developing fast, real-time algorithms for image reconstruction exploiting advances in optimization and machine learning (2) developing face detection, recognition, and tracking algorithms that operate with the lensless imaging platform for IoT applications like personalization, and (3) improving data communication (wired or wireless) to meet current and future IoT needs by exploring end-to-end system integration and optimization. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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FLUXMAGIC, INC.
SBIR Phase I: High Precision Coaxial Magnetic Gear
Contact
2828 SW CORBETT AVE STE 214C
Portland, OR 97201–4815
NSF Award
2015163 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to investigate applications of a new high-performance mechanical gearbox. Electric motors account for approximately 23 percent of electricity consumed in the United States and roughly 63 percent of manufacturing sector electricity. An improvement in geared motor technology can help realize energy savings. A magnetic gear creates speed change without any physical contact, requires no gear lubrication, has inherent overload protection, has low acoustic emissions and low starting torque. Due to its contact-free torque production, a magnetic gear has the potential for a long lifetime while operating at high efficiency. This project will advance the development of a magnetic gearbox, with many potential applications. This Small Business Innovation Research (SBIR) Phase I project explores the trade space of magnetic gearboxes with regard to efficiency, thermal stability, and torque density and the potential trade-offs with respect to cost. Multiphysics-based numerical and analytic modeling co-design techniques will be utilized to explore the thermal and mechanical sizing trade-offs impacting the efficiency of the magnetic gears while mitigating magnet demagnetization. The proposed designs will utilize a unique laminated magnet array combined with the laminated slotted modulator. The project will explore the design trade-offs with respect to stack length and mechanical deflection in the context of the magnetic and thermal design. The project will demonstrate the efficiency and performance capabilities of a magnetic gearbox compared with an equivalently sized mechanically geared motor. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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FOLI RESEARCH, LLC
SBIR Phase I: High-speed, precision wire plotting for electromechanical sensors and actuators
Contact
7604 S 650 W
Crawfordsville, IN 47933–8802
NSF Award
2014996 – SBIR Phase I
Award amount to date
$224,700
Start / end date
06/01/2020 – 11/30/2020
Abstract
The broader impact/commercial potential of this SBIR Phase I project is to increase performance and simplify the development of electric motors. This project develops additive manufacturing technology for the electromagnetic and electronic components necessary for new high-performance motors for applications such as commercial aviation. The global electric motor market was estimated at $100 B in 2017. The proposed technology allows more efficient utilization of rare earth materials, and could eliminate the conventional trade-offs between motor efficiency and cost, enabling reduced energy intensity by cost-driven applications, like heating, ventilation, and air conditioning (HVAC), to significantly reduce their energy intensity. The proposed SBIR Phase I project will explore translation of a novel manufacturing process allowing printing of high-density wire windings with the same design freedom and streamlined manufacturing associated with printed circuit boards today. Because the upstream wire manufacturing and coating processes have such tight tolerances, a relatively modest plotting machine can produce electromagnetic devices at speeds of several meters per second. Further, by incorporating electronics directly into the plotted windings, devices which would conventionally require integrating multiple manufacturing processes can be made in a single step. In this project, we will advance the development of an end-to-end workflow for this manufacturing process and use it to prototype a novel high-performance electric motor design. Gravimetric power densities of over 20 kW/kg may be possible with this approach, representing a 4X improvement over state-of-the-art in the 100kW class and potentially enabling electric aviation. In this project, we will advance and validate the performance of a new motor 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.
Errata
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FROSTDEFENSE ENVIROTECH, INC.
SBIR Phase I: Budbreak Delay Gel Technology for Frost Management and Mechanization of Vineyards
Contact
509 S GARFIELD AVE
Champaign, IL 61821–3831
NSF Award
1938235 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to create value for grape farmers by reducing crop damage from frost by delaying the time when the buds break in spring. The innovation proposed will reduce the costs of frost management, decrease yield loss, and improve quality. Delaying bud break will also assist in labor management by increasing the operating window for optimal shoot removal. Grapes are the highest value fruit crop in the U.S. and the sixth largest crop globally. Grape production is highly influenced by the weather, with frost damage among the top weather hazards. Success in the grape market opens the door to deployment with many other fruit crops. This Small Business Innovation Research (SBIR) Phase I project will allow grape growers to reduce frost damage and maximize resources for mechanization. This approach integrates many studies, including: biophysical and biochemical factors influencing the endogenous regulation of bud break, resistance to cold injury, and polymer sciences. Preliminary studies indicate the ability to resist wet conditions and regulate bud break by 10 to 14 days. If the aims of this project are achieved, the technology will contribute significantly to farmers’ abilities to cope with present and future threats of spring frost, with current mechanization and available labor limitations, and will be the foundation for continued innovation in tools that address current and emerging challenges of climate change. The project will demonstrate the feasibility of the spray through a series of in situ applications with partners in Washington and Illinois. In addition, the project will launch data analytics studies to guide the application timing of bud break delay technology by testing sensors for farm microclimate data acquisition and gaining access to critical data sources. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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FULL CIRCLE MICROBES, INC.
SBIR Phase I: A Microbial Inoculant for the Degradation and Recycling of Hemp Waste into a Nutrient-Rich Fertilizer
Contact
265 TAPROOT FARM LN
Hinesburg, VT 05461–9740
NSF Award
2014792 – SBIR Phase I
Award amount to date
$224,935
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this SBIR Phase I Project is to increase the advance a technology to transform leftover plant matter into a fertilizer to support the agricultural industry. The proposed project will develop a microbial inoculant that will rapidly and efficiently transform post-harvest leftover plant matter into a nutrient-rich bioavailable fertilizer used to nourish future crops, particularly in the emerging hemp industry. The findings from this research project are potentially applicable to the degradation of other common agricultural crops, such as corn, and the conversion of feedstock into biofuels. The technology will add value to farms, save farmers money, and prevent further environmental harm through the production and use of synthetic fertilizer. This SBIR Phase I project advances a cooperative, synthetic microbial inoculant that degrades lignin, a polymer in hemp that is highly resistant to degradation, into a nutrient-rich fertilizer that increases hemp yield. This innovation will be achieved by developing and performing assays that quantify the efficiency with which microbes degrade lignin and produce peroxidases, the family of enzymes that degrade lignin. After identifying microbes with lignin-degrading capabilities, these microbes will be incorporated into a plant growth promoting co-culture, at which point the inoculant will be optimized to achieve the maximum lignin degradation efficiency at a wide range of temperatures and conditions. This will be achieved through lab-scale adaptation, i.e. a natural forced microbial evolution. Finally, the output of the optimized microbial inoculant will be evaluated for its ability to increase hemp seed germination and decrease the harmful effects of plant pathogens. These characteristics will be examined using seed germination assays and microbial plate competition assays. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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FloraPulse Co
SBIR Phase I: Models to predict soil and plant water status from continuous in-plant measurements
Contact
170 Louise Ln
Davis, CA 95618–4869
NSF Award
2026205 – SBIR Phase I
Award amount to date
$255,544
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to help fruit and tree nut growers minimize environmental impacts and improve profitability. This project will use data from implantable microchip sensors that directly measure tree hydration to develop precision models of tree and vine needs for water. These models require no hardware installation and are packaged in a user-friendly format. They will automatically provide growers with affordable advice tailored to their field and crop, enabling accurate 24/7 water status data, forecasts, and recommendations for large-scale improvements in irrigation management of tree crops. This SBIR Phase I project will explore plant health via continuous variation of water status or drought stress within the tissues. This data stream will be used to build dynamical models of plant water stress. The project's technical aims are to: 1) Characterize the spatial (due to plant position in the field) and temporal variations; 2) Develop a framework for iterative development of predictive models of water stress dynamics from the single-plant to the whole-field scale; and 3) Develop a system optimized for industrial modeling of the spatial and temporal dynamics of water across the full orchard or vineyard, diagnostics of high- and low-performing cultivars, irrigation blocks, and decision support to optimize field design and crop management. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Foresight Science & Technology Incorporated
SBIR Phase I: Masking Agents to Promote Ingestion of Organic Pest Ant Bait
Contact
34 Hayden Rowe St
Hopkinton, MA 01748–1889
NSF Award
2025718 – SBIR Phase I
Award amount to date
$210,876
Start / end date
10/31/2020 – 10/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase I project is the development of an environmentally neutral product for control of red imported fire ants (RIFA), aggressive pests that occur in high densities and are specialists of urban, rural, and agricultural habitats, particularly in southern states. The RIFA affects many economic sectors and cause billions of dollars in damage and control costs annually. Their large numbers and potent sting disrupt the quality of life for millions of Americans and 5-10% of these may develop hypersensitivity to their venom, creating significant medical costs. The RIFA reproductive system lead to rapid re-infestation of treated areas; therefore, continuous use of control measures is required, with associated environmental risk. This project will enable commercialization of a new bait that is environmentally neutral and cost competitive. It will be the first new active ingredient for RIFA control in 20 years. Our novel application of masking agents for RIFA control is expected to have a general impact on the discovery of new pest control active ingredients. This SBIR Phase I project will advance the translation of novel active ingredients for effective RIFA pest mitigation. Prior testing has indicated that additives are needed for this type of pesticide. This project will test additives and optimize formulations for field use of the new ingredients. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Forest Devices, Inc
SBIR Phase I: Hemorrhagic Stroke Detection with Electrochemical Impedance Spectroscopy ;
Contact
544 Miltenberger St.
Pittsburgh, PA 15219–5971
NSF Award
2014760 – SBIR Phase I
Award amount to date
$224,385
Start / end date
05/15/2020 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to investigate an affordable prehospital hemorrhagic stroke (HS) detection device. The current state-of-the-art technology for prehospital HS detection is a computed tomography ambulance (i.e. mobile stroke unit). Mobile stroke units have high upfront and operating costs, and a lower-cost device could revolutionize healthcare for stroke patients in two ways. First, prehospital identification allows these patients to be triaged to hospitals equipped to treat them (neurosurgical centers), resulting in faster care and better outcomes. Second, the ability to rule out HS prehospital will allow earlier treatment of another condition, ischemic stroke, to improve outcomes and reduce long-term healthcare costs. The proposed SBIR Phase I project will use electrochemical impedance spectroscopy (EIS) to differentiate HS and ischemic stroke. EIS involves injecting an alternating current signal and measuring the resulting impedance across a spectrum of frequencies. The impedance spectrum of materials often differ, allowing EIS to be useful in a variety of applications including examination of corrosion, antibody binding, body composition, and disease diagnosis. This work will advance the use of EIS, to date used experimentally in detecting intracranial pathologies, to detect hemorrhagic tissue within the brain. This work will explore the development of a fast-acquisition EIS HS detection device. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Fortiphyte, Inc.
SBIR Phase I: Identification of disease resistance traits to improve the productivity and sustainability of soybean cultivation
Contact
663 Colusa Ave
Berkeley, CA 94707–1517
NSF Award
1844088 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the productivity and environmental sustainability of soybean cultivation. Soybean is the most widely grown crop in the United States with nearly 90 million acres under cultivation. Soybean is a key part of the food system and generates $22 billion in export revenue each year. One of the greatest threats to soybean production is the fungal pathogen known as Asian Soybean Rust. Current commercial soybean varieties have no resistance to this pathogen and over $2 billion is spent annually on fungicides to control this disease. While soybean is highly susceptible to this disease, many wild plant species have natural resistance to this pathogen. This project seeks to identify the naturally occurring mechanisms of disease resistance in wild plant species that can be used to develop disease-resistant soybean varieties. Adoption of these varieties is expected to bring more than $4 billion in value to the soybean industry while improving productivity and reducing fungicide use. The intellectual merit of this SBIR Phase I project is to identify plant immune receptor proteins that confer disease resistance to Asian Soybean Rust, which is caused by the fungal pathogen Phakopsora pachyrhizi. A key determinant of whether or not a plant is resistant to a particular pathogen is whether the plant has an appropriate immune receptor protein capable of recognizing the presence of the invading pathogen. Once activated, plant immune receptors trigger plant defense responses that typically result in immunity. This project will use reverse genetic and biochemical approaches to identify plant immune receptor proteins that confer resistance to Asian Soybean Rust. Preliminary work identified several molecules from Phakopsora that elicit an immune response in non-host plant species. The goal is to identify the cognate immune receptors and test them for sufficiency to enable immune activation in response to Asian Soybean Rust elicitor molecules. This research will enable future work to the development soybean varieties with resistance to Asian Soybean Rust. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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
$225,000
Start / end date
08/01/2020 – 01/31/2021
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.
Errata
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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
8 MARKET PL STE 300
Baltimore, MD 21202–4113
NSF Award
2015009 – SBIR Phase I
Award amount to date
$224,980
Start / end date
08/01/2020 – 07/31/2021
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.
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GENERATE LLC
SBIR Phase I: A Digital Design-Delivery System for the Large-scale Deployment of Mass Timber Building Technologies
Contact
4 LONGFELLOW PL APT 1603
Boston, MA 02114–2813
NSF Award
1938111 – SBIR Phase I
Award amount to date
$225,000
Start / end date
10/15/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to democratize mass timber systems, rendering them accessible across the architecture, engineering, and construction (AEC) industry. Buildings account for 40% of all greenhouse gas emissions, indicating an urgent need for energy-intelligent building prototypes. Mass timber buildings require less energy for production than competitive technologies and were approved in 2019 by the International Building Code for structures of up to 18 stories in the US. Yet, they remain inaccessible as a technology, in part because developers, architects and manufacturers remain unfamiliar with mass timber and its benefits. This proposal seeks to unlock a latent market of development potential on sites to which mass timber offers unique advantages. Because our technology integrates adaptable-to-site building solutions into the industry's supply chain, it is designed to improve adoption by reducing risks, barriers, and costs usually associated with innovative technologies. By giving designers, engineers, and builders access to cutting-edge mass timber building systems, our proposal aims to encourage the use of a sustainable and profitable technology for the rapid urbanization of North American cities. This Small Business Innovation Research (SBIR) Phase I project will focus on developing adaptable mass timber building solutions that are replicable and commercializable. This will be achieved by designing a variety of rigorously tested and cost-effective building solutions in mass timber and developing a generative design system that can generate and deploy optimal building proposals using these pre-designed building solutions. The first component of our technology comprises the development of pre-approved structural building solutions across a range of building scales (3-18 stories) and mass-timber technologies, including novel hybrid structural solutions developed with support from manufacturers and engineers. The second component the generative system will handle different development scenarios from large urban blocks to small urban infill sites. The tool will generate a wide variety of potential compliant options, analyze and test these for user-specified performance metrics, and sort among them to find a best-case building proposal. The tool will incorporate the structural solutions developed in the first component of the work and deploy them within their constraints to test real-world building solutions against the constraints of each development project. The tool will also seamlessly integrate with existing BIM (Building Information Modeling) project-delivery platforms for easy interoperability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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GENIPHYS, LLC
SBIR Phase I: Biologic Filler for Regenerating Tissue Following Breast Conserving Surgery
Contact
10307 OAK RIDGE DR
Zionsville, IN 46077–8313
NSF Award
1913626 – SBIR Phase I
Award amount to date
$224,873
Start / end date
07/01/2019 – 12/31/2020
Abstract
This SBIR Phase I project will address key hurdles for commercialization of an injectable breast tissue replacement for use immediately following breast conserving surgery, otherwise known as lumpectomy. Surgeons using this procedure today have limited options for predictably restoring normal breast size, shape, and consistency following tumor removal. Because of this, many women are left with breast deformities or must undergo multiple surgical procedures. These issues compromise their psychological well-being and quality of life and increase healthcare costs. With these challenges in mind, this project will evaluate the ability of a patented, liquid, fibril-forming collagen to serve as an injectable, breast tissue replacement. Upon injection, this liquid biopolymer self-assembles into a physically stable and persistent natural fibrillar scaffold, meaning it can be used to fill patient-specific tissue voids. Project results will provide early-stage preclinical evidence of this biopolymer's effectiveness for filling and regenerating breast tissue in a large animal lumpectomy model. If successfully translated to the clinic, this therapy would provide breast cancer surgeons with a much-needed regenerative breast tissue solution. This in turn, would boost surgeons' confidence when working to achieve complete tumor removal, improve quality of life for breast cancer survivors, and decrease overall costs of care. The liquid collagen polymers evaluated in this proposal preserve several natural features of the collagen protein as it exists in the body, thus giving rise to three key advantages. First, this biomaterial has the ability to rapidly transition from liquid to solid, forming natural collagen-fibril scaffolds just like those in the body's tissues. Second, it is amenable to customization and advanced biofabrication with tailorable geometries, fibril architectures, and mechanical properties. And finally, these scaffolds stably integrate and persist in vivo, inducing site-appropriate tissue generation without evoking immune or inflammatory response. This project seeks to overcome technical hurdles associated with identifying compatible and scalable sterilization and manufacturing processes for this unique, liquid biomaterial. Additionally, project activities will seek to specify biopolymer formulations that support surgeon ease-of-use, provide efficacy for breast tissue replacement, and do not interfere with standard clinical practices (e.g. radiation and re-excision procedures). The outcomes of this proposal will provide valuable proof-of-concept for a viable medical-grade manufacturing process and early preclinical validation that these collagen polymers can address breast cancer patient-specific needs. Finally, this project will lay the foundation for this natural collagen polymer to serve as an enabling tool for next generation personalized regenerative medicine therapies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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GEOMETRIC DATA ANALYTICS
SBIR Phase I: IM3UNE: A Platform for Integrated Monitoring, Mapping, Modeling and Understanding of Novel Epidemics Like COVID-19
Contact
636 ROCK CREEK ROAD
Chapel Hill, NC 27514–6716
NSF Award
2029153 – SBIR Phase I
Award amount to date
$255,631
Start / end date
08/01/2020 – 04/30/2021
This is a COVID-19 award.Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to assist with preparedness and decision-making for situations like the COVID-19 pandemic. This health crisis has been exacerbated by a lack of real-time information or predictive information about the extent, location, and spread of the disease. This Phase I project ingests data streams from government agencies, healthcare providers, and the general public, returning real-time, actionable information to assist in guiding a broad and coordinated response. While this platform is particularly relevant in the COVID-19 pandemic, it is disease agnostic, and will have utility for seasonal influenza and other infectious diseases, positively impacting public health. This Small Business Innovation Research (SBIR) Phase I project will create a platform aimed at providing real-time identification of infectious disease outbreaks and predictions of disease spread, with an initial focus on COVID-19. Among the gaps in the response to the COVID-19 pandemic is capability to accurately track the magnitude, location, and spread of infectious agents. This project aims to assess and demonstrate the value of leveraging multiple modalities and sources of data for early detection and prediction of disease outbreaks, with focus on COVID-19. The approach will combine data fusion methods and epidemiological modeling approaches with continual input from subject matter experts in an effort to generate actionable information and predictive models related to disease spread. A variety of data streams providing information on disease incidence, transportation data, and sub-population interaction data will be used to construct progressively more sophisticated SEIR models. These efforts will result in an improved understanding of the utility and applicability of various data streams to epidemiological monitoring and forecasting, as well as platform for users of various levels of technical expertise. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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GRAYMATTER ROBOTICS INC.
SBIR Phase I: Smart Robotic Sanding Cells for Composite Parts in High-Mix Applications
Contact
1019 22ND ST
Santa Monica, CA 90403–4517
NSF Award
2026159 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impacts of this SBIR Phase I project are in improving the quality of life of the manufacturing workers, helping U.S. manufacturers remain cost-competitive in the global market, and improving consistency in the quality of the manufactured parts. The proposed robotic cells will reduce the need for workers to perform ergonomically challenging sanding tasks and reduce the risk of worker injuries on sanding lines. The proposed technologies will enable the human operators to focus on high-level decision making and the creative aspects of the manufacturing tasks, while the robotic assistants will perform the low-level tedious tasks. This would allow human operators to collaborate more as a team and thereby improve worker productivity. Currently, there are more than 3000 companies in the U.S. alone doing composite fabrication. Most of them face challenges due to a shortage of workers and high labor churn leading to longer delivery times. The proposed work will enable manufacturers to improve quality and lower costs. Moreover, it will enable manufacturers to reduce time to part delivery by reducing reliance on human labor and easily scale production capacity with changes in demand by adding or removing robotic cells. The overall goal of the proposed effort is to develop a robotic sanding process for high-mix applications. The technology will enable robots to program themselves by automatically generating and safely executing trajectories based on the task description, accounting for the uncertainties present in the environment. The robotic tools will reduce cycle time by fast execution of safe and efficient execution of sanding project related to the fabrication of composite materials. A robotic sanding cell will be developed by incorporating appropriate sensors and tools, developing algorithms for fast and safe workpiece localization in the robotic cell, and assessing the post-sanding surface quality and the state of the abrasive media. The sanding instrumentation will provide recommendations to the human operator for initiating another robotic sanding pass or changing the abrasive media. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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GREEN MAGIC HOMES, INC.
SBIR Phase I: Integration of innovative materials into a modular system of semi-permanent construction.
Contact
18851 NE 29TH AVE STE 700
Miami, FL 33180–2845
NSF Award
2014704 – SBIR Phase I
Award amount to date
$224,975
Start / end date
05/15/2020 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of a new modular construction that is easy to assemble and cost-effective for a variety of semi-permanent and permanent uses. There is a great need among disaster relief organizations, the military, local government in rural and remote areas. and emergency response teams for sturdy, portable structures that are quick and easy to assemble and provide shelter from the elements. This project will expand the capabilities of a unique construction system using technically advanced materials and integrating them into a kit. The system will be environmentally friendly, employ special insulation to reduce internal temperature variation, and will maintain a hygienic environment. The proposed project will demonstrate the technical and commercial feasibility of this system and fulfill unmet needs of the estimated $1 B global market for modular construction. This SBIR Phase I project is to integrate advanced materials into an existing system of modular construction. The project will focus on the integration of components made from recycled polymers, advanced thermal insulation materials, and antimicrobial coatings. The technical focus is to combine these advanced materials without compromising the underlying performance of the system. The project will develop prototype wall panels in the form factors of the building system’s components. These prototype wall panels will then undergo structural, loading, and wind and fire resistance testing. The panels will be tested for the preservation of component functionality. The project will develop a full-scale 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.
Errata
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GRID7 LLC
SBIR Phase I: Taekion Defense-hardened Blockchain File System using aBFT Consensus
Contact
7136 PETURSDALE CT
Boulder, CO 80301–3831
NSF Award
1940349 – SBIR Phase I
Award amount to date
$224,646
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project include the ability to enhance the security and trust of critical infrastructure networks for applications including defense, electric grids, health care, and emerging autonomous systems (i.e., self-driving vehicles and robotics). As billions of internet connected things are added to our existing infrastructure, providing a trusted data layer will rise in importance to maintain reliability and security of our critical infrastructure, as many of these systems are mission and life-critical. Our proposed innovation will allow highly distributed and autonomous systems the ability to make decisions based on highly trusted data sources. Our innovation will enhance the practical applications of distributed computing fault tolerance and consensus (agreement) mechanisms by applying them to real-world, critically needed defense networks initially and to other critical infrastructure areas later. The commercial opportunity is to provide a missing piece of the puzzle to support a trusted data layer in the next generation, or Internet evolution. This SBIR Phase I project proposes to prototype a novel, next-generation Distributed Ledger Technology (DLT) consensus algorithm to be plugged into open source DLTs to enhance the data and transaction integrity aspects under asynchronous (disconnected, flaky, or malicious) networking scenarios. The challenge is to provide the ability to maintain agreement and decision finality (or integrity) among consensus nodes operating in asynchronous (network partition, crash fault, byzantine fault) networking environments. In simpler terms, this means the ability to keep and store a file or update within a DLT node, even though the fault keeps the DLT update from taking place over an extended period of time. This capability is highly important when running DLTs in critical infrastructure networks. The research objectives are to combine local, hash-chained write-ahead journaling methods with state-of-the-art asynchronous byzantine fault tolerant (aBFT) consensus to prototype high data integrity (ability to retain all transactions, provide liveness guarantees, maintain local node state integrity, and maintain data ordering and timestamps) under asynchronous network 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.
Errata
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Addenda
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GROTTHUSS, INC.
SBIR Phase I: Rechargeable Zn Metal Battery with Long Life and Low Cost
Contact
14526 SE LYON CT
Happy Valley, OR 97086–4296
NSF Award
2012221 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2020 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to explore translation of a rechargeable zinc-metal battery for large-scale energy storage. Renewable but intermittent energy sources require cost-effective storage. The proposed battery essentially converts a primary alkaline battery to a rechargeable form with novel chemical components. This project will demonstrate the long cycle life of zinc-metal batteries under conditions amenable for applications such as backup power for data centers, grid-level needs, and household energy storage use. This SBIR Phase I project proposes to develop Zn-metal batteries in use-inspired battery configurations and cell dimensions. This project is to translate the fundamental understanding of Zinc-salt-based water-in-salt electrolytes that strengthen the inertness of both water molecules of the electrolytes and Zn metal anode. The proposed technology offers stable cycle life with excellent power output in an appropriate footprint. The project will advance the development of new electrolytes that greatly mitigate the hydrogen evolution reaction and eliminate dendrite formation on the Zn metal anode. The new electrolytes address the challenges of both anode and cathode, where the cathode capacity fading issues will be addressed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Gamdan Optics, Inc
SBIR Phase I: A novel AR on LBO
Contact
2362 Qume Drive
San Jose, CA 95131–1841
NSF Award
1840843 – SBIR Phase I
Award amount to date
$224,667
Start / end date
02/01/2019 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is as diverse as the laser technology itself. Lasers have become the true facilitator of the data-based society. It is tool of choice for future smart factories and on-demand manufacturing. It serves as the fundamental building block of optical sensing systems used to collect large volumes of critical data to be used for decision making in every facet of society. The myriad of new applications for laser systems echoes the same demand ? higher power. The bottleneck in the power generation is often the capability of optical components of the laser to withstand the power without degradation. So the greater potential of lasers can be unleashed if there would be a way to break through the power handling capability of laser components starting with the nonlinear optical crystals indispensable in creating these powerful energy sources. This research project is precisely designed to address this need and the successful completion of this project would enable the next generation of miniaturized electronic devices, expand our horizon of biological imagery and precision surgery, and explore our universe with instruments that are currently confined to our laboratories. The proposed project targets the most common material used to generate high power visible and UV light ? Lithium Triborate (LBO) crystal. Able to handle power density up to 45GW/cm2, LBO is currently the material of choice for high energy industrial lasers. However, optical surfaces where the light enter and exit LBO often get damaged well before the actual bulk material. Traditional dielectric anti-reflective (AR) coatings on these surfaces are typically made using a limited selection of materials of lower damage threshold in a process highly susceptible to contamination, resulting in significantly lower damage threshold than the bulk LBO crystal. In this proposal, state-of-the-art surface-texturing processes on LBO will be developed to eliminate the use of these dielectric films while still providing the necessary AR functionality. A variety of processes and materials on LBO surfaces will be attempted and studied with resulting surfaces tested for absorption and damage threshold. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Gel4Med
SBIR Phase I: Tunable Mechanical and Functional Properties of Peptide Films
Contact
15 Waverly St
Brighton, MA 02135–1200
NSF Award
1843682 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 01/31/2021
Abstract
This SBIR Phase I project focuses on developing chemically cross-linked synthetic nanomaterials to address the unmet clinical need in promoting infection free tissue regeneration in surgical, traumatic, ocular, burn, and chronic wounds. While small wounds heal naturally, larger chronic wounds demonstrate delayed wound healing with infections, and affect over 6.5 million patients costing over US $25 billion annually in treatments. In addition, annually, 2 million Americans suffer from serious infections due to drug resistant bacteria resulting in severe morbidity, serious complications, huge economic losses with an estimated 23,000 deaths. As conventional antibiotics are failing, our ability to fight drug resistant pathogens is diminishing and the pipeline of new potential antibiotic drugs is very skim. Thus, there is an urgent need to develop a product that can fight multiple pathogens through a mechanism against which bacteria are less likely to develop further resistance. Hence, the current project evaluates the feasibility of developing a novel, easily handleable dry film with potential to eliminate a variety of infectious pathogens while improving wound healing in a single application. This product is pliable, easily rehydratable, has intrinsic tissue scaffolding properties and is inherently antimicrobial against a broad range of pathogens without the use of any additional agents. This SBIR Phase I project will demonstrate the feasibility of developing a shape retaining, pliable, easily handleable antimicrobial cell-scaffolding gel matrix into a product that is simultaneously toxic to antibiotic-resistant bacterial strains, while remaining conducive to tissue regeneration. This current product has a nano-porous gel matrix that promotes cellular infiltration and attachment along with utilizing a charge-based mechanism to lyse bacterial membranes upon contact. Although there is on-going research on such self-assembled hydrogels, the formation of films using these nanofibers has never been assessed before and stands to be the key technological advancement. Thus, this current proposal explores two methods for making films such as i) solvent casting methods relying on non-covalent crosslinking - where the hydrogel is applied to a surface and then allowed to dry into a film overnight, and ii) Covalent crosslinking by - incorporating cysteines by oxidizing using H2O2 or crosslinking using Schiff base formation followed by reductive deamination. The films so formed will be structurally and functionally evaluated for their ability to eliminate infections and biocompatibility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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GenEdit Inc
SBIR Phase I: A block copolymer delivery system for the Cpf1 ribonucleoprotein
Contact
140 Hearst Mining Bldg
Berkeley, CA 94720–1760
NSF Award
1844019 – SBIR Phase I
Award amount to date
$225,000
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to bring curative gene editing therapies using CRISPR to patients with genetic diseases. CRISPR-based therapeutics have the potential to be next generation therapeutics, particularly for genetic diseases due to their ability to cut DNA with sequence specificity. However, this type of targeted genome editing has not yet been successfully demonstrated for human therapeutics with existing methods. The translation of CRISPR-based gene editing to the clinic remains a significant unmet need and the most difficult aspect of translating CRISPR-based gene editing into therapeutics is the lack of safe and effective delivery methods to the target the tissues. Existing viral-based delivery systems have limitations that include immunogenicity, pre-existing antibodies against them, broad tropism, off-target effects, restricted DNA cargo packaging capacity, and manufacturing challenges. As a result, non-viral methods that employ synthetic materials are being widely investigated as potential alternatives. Developing non-viral delivery vehicles that can effectively deliver CRISPR components to target tissues will improve the ability to broadly use CRISPR-based therapeutics for many genetic diseases. The intellectual merit of this SBIR Phase I project is to develop a non-viral delivery system for the CRISPR enzyme Cas 12a (Cpf1) for delivery to target muscle tissue, and, potentially, enable the development of a novel gene editing treatment for Duchenne muscular dystrophy (DMD). The approach involves proprietary CRISPR-nanoparticles that are composed of peptide PEG-PAsp(DET) complexed to Cpf1 RNP, which possess good biocompatibility and high gene editing efficiency with the potential to manufacture and scale up under GMP for use in clinical trials. Preliminary data demonstrate that PEG-PAsp(DET) complexed to Cpf1 RNP can efficiently deliver Cpf1 RNP to the muscle tissue and can induce the expression of the dystrophin protein by deleting exon23 with a mutation. Under this proposal, the specific experiments will focus on improving the biocompatibility, stability, and muscle-targeting ability of the CRISPR-nanoparticles. The experimental plan is to synthesize various Peptide-PEG-PAsp(DET), followed by screening in primary myoblasts and reporter mouse system. This technology using CRISPR-nanoparticles will be the first example of a delivery vehicle that can simultaneously deliver Cpf1 protein and gRNA via intravenous injection and achieve gene editing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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General Probiotics Inc
SBIR Phase I: Antiviral and Anti-inflammatory Live Biotherapeutics (COVID-19)
Contact
1000 Westgate Dr., Ste. 122
St. Paul, MN 55114–1964
NSF Award
2031154 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of new therapeutics against coronavirus SARS-CoV-2 and associated COVID-19. Few broad-spectrum antivirals exist, and vaccines are effective but strain-specific and require development time for each new strain. This project will engineer probiotics native to the upper respiratory tract of humans to serve as antiviral and antibacterial agents. These probiotics will inhibit viral entry inside human lung cells and stop lung inflammation that causes lethal severe acute respiratory distress in COVID-19 patients. This development will be enabled by modern synthetic biology techniques and an agile research and development paradigm. This Small Business Innovation Research Phase I project will advance the development of new probiotics. These benign, non-virulent microbes will be equipped with defensins, protegrins and compstatins. Defensins are peptides known to inhibit critical steps in viral infection, including the antagonistic binding of angiotensin converting enzyme 2, the human cell receptor thought to facilitate Covid-19 entry inside lung epithelial cells. Protegrins are broad spectrum antimicrobials, with strong activity against bacteria, such as pneumonia-causing Klebsiella spp. and viral particles, including enveloped viruses like SARS-CoV-2. Compstatin is a complement system inhibitor that modulates the overactivation of inflammatory responses, which in the case of a coronavirus infection results in severe acute respiratory syndrome. At the end of this project, a library of live biotherapeutics will be developed that can exhibit antiviral, antibacterial and anti-inflammatory activity when expressing and secreting combinations of peptides. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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H Quest Vanguard, Inc.
STTR Phase I: Building with Carbon: Improving Construction Materials with Nanocarbon Additives from Natural Gas
Contact
750 William Pitt Way
Pittsburgh, PA 15223–8133
NSF Award
1914147 – STTR Phase I
Award amount to date
$225,000
Start / end date
06/15/2019 – 03/31/2021
Abstract
The broader impact/commercial potential of this project is the improvements to the strength, durability, and longevity of concrete infrastructure and construction materials with novel graphene-rich carbon nanomaterial additives. Advancement of this technology area (advanced materials/nanomaterials for infrastructure applications) will directly reduce the costs of construction and maintenance ($165B/year in public spending) while supporting the nation's core economic activities ($14T/year in transported goods). The enhanced strength and longevity of nanocarbon coatings and concrete composites will reduce the amount of raw material required to meet specifications resulting in a net reduction of greenhouse gas emissions (concrete production is responsible for 7% of global GHG emissions). The innovation will enhance scientific understanding of the effect of graphene-rich additives on the permeability and strength of concrete and coating composites using both advanced analytical techniques (x-ray tomography) and industry standard procedures (ASTM testing). It will also enhance understanding of the processing required (e.g. functionalization and dispersion) to integrate graphene-rich additives into polyurethane materials and concrete. Additionally, the project will help refine the plasma-based process conditions to produce carbon materials optimized for these applications. This Small Business Technology Transfer (STTR) Phase I project will demonstrate enhancement of mechanical properties and impermeability of construction materials' concrete and concrete coatings using graphene-rich nanocarbon additives derived from microwave plasma conversion of natural gas. The permeability of concrete is its primary pitfall and is responsible for the two most common causes of failure: carbonation and chloride contamination. Sealants can extend concrete's lifespan but are expensive to apply and often deteriorate rapidly due to environmental effects (UV, chemicals, mechanical abrasion). Graphene additives can enhance the barrier properties and mechanical strength of concrete and sealants, but are currently too costly for construction and infrastructure applications. The objective of this project is to enhance the barrier and mechanical properties of concrete and sealants using a novel graphene-based carbon nanomaterial produced using a cost-effective, scalable, plasma-based process. Carbon nanomaterials will be produced at varied process conditions and, following post-treatment and functionalization, will be incorporated into polyurethane formulations and concrete mixtures. Water and chloride penetration into composites will be examined using advanced x-ray tomographic 3D imaging. Composites will undergo further testing in accordance with AASHTO/ASTM-standards. The anticipated results will establish the technical benefits of using graphene-based nanocarbon additives in concrete and sealants. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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HABITAWARE, INC.
SBIR Phase I: New Wearable for Body Focused Repetitive Behavior Detection
Contact
6465 Wayzata Boulevard
Saint Louis Park, MN 55426–1733
NSF Award
1914175 – SBIR Phase I
Award amount to date
$269,695
Start / end date
07/01/2019 – 11/30/2020
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from providing an accurate real-time awareness solution for those who suffer from body-focused repetitive behaviors. Over 4% of Americans suffer from skin picking, hair pulling, and nail biting, the majority of whom resort to covering up the problem with makeup, gloves, wigs, and even tattoos due to treatment cost barriers and lack of effective tools to facilitate behavior change. While behavior therapy, and in particular habit reversal training, has shown efficacy, this method is traditionally burdened by unreliable journaling, a lack of access to treatment, and difficulty for patients to perform in real-time because of a lack of awareness. While real-time awareness devices do exist, there is room for improvement in detection accuracy. This project will examine feasibility of a novel sensor system within a wearable device that can significantly improve detection accuracy of BFRB-related behaviors. This Small Business Innovation Research Phase I project will develop and validate a novel wearable sensing system used to detect subtle movements associated with BFRBs that is suitable for large-scale manufacturing. We believe the proposed wearable system can improve the efficacy of leading behavior therapy methods. To accomplish these goals, early studies will focus on three main objectives. First, the team will investigate the best electrical and spatial configuration of the proposed sensors in a tightly controlled test setup. Second, the team will integrate the optimal configuration into a device suitable for testing and validate the integrity of the sensor output on individuals. Finally, the team will develop a proof-of-concept BFRB recognition algorithm under ideal, low-noise 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.
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HALOMINE INC.
SBIR Phase I: HaloFilm – a spray-on, rechargeable, reapplicable antimicrobial coating
Contact
1411 HANSHAW RD
Ithaca, NY 14850–2730
NSF Award
2014378 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop an antimicrobial surface coating with unique application and efficacy features. As many as one-third of Healthcare-Associated Infection (HAI) cases can be attributed to environmental surfaces, particularly hospital “high touch” surfaces (e.g., bed rails, machine buttons, equipment). In the US, an estimated 1.7 million HAI occur in hospitals each year, resulting in 99,000 deaths and an estimated $20 billion in healthcare costs. The proposed project will advance the development of a solution offering continuous protection from bacteria, fungi and viruses, as well as food-borne pathogens and even mold. The current disinfecting paradigm relies on killing pathogens daily or less frequently, leaving surfaces vulnerable to new contamination. The proposed antimicrobial coating maintains surface integrity, potentially serving hospitals, long-term care facilities, outpatient centers, and other applications such as home health, food safety, mass transit safety, mold abatement, and schools. The proposed project will investigate the translational utility, efficacy and safety of a spray-on, re-chargeable, re-applicable antimicrobial surface coating. The proposed technology is a spray-on solution that leaves a thin transparent film on a surface. The film is a polymer composed of one monomer adhering to the surface and a second another monomer that stabilizes chlorine. The coating converts the surface into a chlorine battery such that even a commercially available sanitizer leaves the surface covered with chlorine in a form that can last for more than two weeks without toxic effects upon contact. The proposed coating has excellent efficacy against pathogens because it relies on chlorine; it has enjoyed decades of use because of its broad-spectrum efficacy without generating resistance in pathogens. The proposed work is to advance the development of a formulation that includes anti-fouling monomers. The goal for this Phase I effort is to demonstrate efficacy against Clostridium difficile, a particularly concerning pathogen for hospitals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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HALOMINE INC.
SBIR Phase I: HaloFilm as a virucide against COVID-19 infection
Contact
1411 HANSHAW RD
Ithaca, NY 14850–2730
NSF Award
2028187 – SBIR Phase I
Award amount to date
$256,000
Start / end date
06/01/2020 – 02/28/2021
This is a COVID-19 award.Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop an antiviral surface coating with unique application and efficacy features. Evidence suggests that the COVID-19 virus strain can remain live on stainless steel and plastic for as long as three days, a potentially harmful situation in environments with high traffic, such as subway turnstiles, buses, and high-touch surfaces in hospitals. Furthermore, even in hospitals, cleaning and disinfecting can be insufficiently comprehensive than desired, with surfaces that may easily be recontaminated until disinfectants are reapplied. The proposed technology enables chlorine-based disinfectants to be effective for as long as 4 weeks. The coating keeps chlorine in a physical and chemical state that is active against viruses, but remains safe and does not cause skin irritation upon contact. The coating can turn any surface into an antimicrobial, and antiviral, surface. The proposed SBIR Phase I project will assess the utility, efficacy and safety of a spray-on surface coating that is rechargeable and can be reapplied, such that it can be used as an antimicrobial surface coating, particularly to prevent transmission of coronaviruses. The state-of-the-art is to regularly use liquid spray disinfectants to kill viruses on surfaces. However, typical active ingredients, such as chlorine, quaternary ammonium compounds, alcohol, peracetic acid or hydrogen peroxide, are active against viruses for a matter of minutes and certainly less than an hour, leaving a surface that can potentially be recontaminated. The technical aims of the proposal focus on 1) assessing the virucidal activities of the coating at specific times after application; 2) determining the half-life of coronaviruses on the coating for comparison to other materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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HARVEST THERMAL, INC.
SBIR Phase I: Very-Low Emissions Heating, Cooling and Hot Water System
Contact
663 COVENTRY RD
Kensington, CA 94707–1329
NSF Award
1938079 – SBIR Phase I
Award amount to date
$224,738
Start / end date
12/01/2019 – 02/28/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be the reduction in home energy costs, electric grid system costs, and environmental impacts from electricity generation. The proposed research project will advance the state of the art in residential combined heating and hot water technology. The research project will resolve the technical risks associated with operating a high-efficiency CO2 heat pump in combined heating and hot water applications, and with implementing efficient load shifting in these applications. The project has the potential to reduce user energy costs, grid system costs, and environmental impacts by: shifting electrical load from peak demand times to off-peak demand times, reducing the need for costly and highly polluting peak power generation resources, and integrating variable renewable energy resources, such as wind and solar at times of low demand. This will put downward pressure on electric rates, as well as provide immediate user bill savings through lower demand and by shifting electricity demand to the cheapest times. The proposed system has the potential for large-scale commercial deployment due to its significantly lower operating costs and lowered initial fixed investments. This Small Business Innovation Research (SBIR) Phase I project aims to resolve technical challenges associated with the commercial deployment of high-efficiency CO2 heat pumps in combined heating and hot water applications. CO2 heat pumps have demonstrated high efficiency in hot water applications with coefficients of performance up to 5. However, they typically operate much less efficiently in combined systems due to a lack of advanced controls. The research will develop a thermal stratification model of a hot water tank based on customer use and charging conditions, a predictive thermal demand model, and a simulation model of the whole system integrating heat pump performance, tank stratification, and predictive customer demand. The project will then develop new controls (hardware and software) to optimize for user and grid costs and emissions and validate the effectiveness of the resulting control system by integrating it into the existing prototype. This assessment will demonstrate the commercial viability of CO2-based combined heat and hot water systems with load shifting. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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HEALING INNOVATIONS INC
SBIR Phase I: Development of a Novel, Cost-Effective Gait Training Device Utilized at Home for the Neurological Patient Population
Contact
41 PEABODY ST
Nashville, TN 37210–2125
NSF Award
2014635 – SBIR Phase I
Award amount to date
$223,370
Start / end date
08/15/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation (SBIR) Phase I project would be the development of a neurorehabilitation technology with a total addressable market of $54B and the opportunity to increase access to advanced care for the 5.2 million people in the US living with paralysis and the 1.3 million people each year that experience an extreme neurological injury or diagnosis that can lead to severe gait impairment. This technology will encourage a proactive approach to care, eliminate the need for a clinician to be physically present in the rehabilitation experience, and introduce software solutions to increase motivation and connectivity. Clinically, if successful, this technology could dramatically decrease secondary complications, help people regain the ability to walk, and ultimately reduce costs associated with neurological diagnoses. This Small Business Innovation Research (SBIR) Phase I is to develop an at-home gait trainer for rehabilitation and physical therapy of individuals with neurological injuries or neurological conditions using a patient-centered approach. This project integrates at-home advanced medical technology with telemedicine physical therapy. This will enable continued rehabilitation and physical therapy without clinical oversight via training videos. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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HEAT INVERSE, LLC
SBIR Phase I: Passive Cooling Materials for Transparent Applications in Refrigerated Trucking and Solar
Contact
119 WESTHAVEN RD
Ithaca, NY 14850–3098
NSF Award
1914454 – SBIR Phase I
Award amount to date
$250,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to overcome the barrier to transparent passive radiative cooling materials that are applicable to commercial environments. The project develops a transparent passive cooling thin-film applicable to situations that lose efficiency when heated, and where both mechanical and thermal stress are involved, for example, over advertisements on refrigerated trucks, or on the front face of solar panels. It will provide the simultaneous qualities of transparency in visible wavelengths, durability to withstand the elements, flexibility for ease of application, high cooling power to address customers' pain points, and manufacturability in a roll to roll format to minimize costs. The technology has the potential to provide a 25-80% increase in fuel efficiency via application of the thin-film to the outside of refrigerated truck trailers. The benefits to customers include: fuel cost savings, reduced emissions, allowing regulatory requirements to be met, decreased maintenance and replacement costs compared to refrigeration units and in-truck insulation in truck, as well as temperature maintenance in maximum heat. This Small Business Innovation Research (SBIR) Phase I project seeks to develop a thin-film product that could revolutionize cooling technologies across a number of industries. The demand for temperature-sensitive goods is expected to continue to grow significantly. To address the need for refrigeration with reduced fuel costs and emissions, the project is developing selective photonic emitters in thermal wavelength windows such that instead of heat being effectively enclosed in an insulating thermos (the atmosphere), they are exposed to a vast cold sink of space. The result is a revolutionary method of entirely passive heat management. This approach will be optimized in a thin-film photonics material that provides significant cooling to refrigerated truck trailers, saving refrigeration fuel costs. Phase I research objectives will establish proof of feasibility and include producing and testing promising material combinations at wafer-scale, testing to ensure that the material's qualities transfer to a commercially relevant size, and performing a small-scale test with potential customers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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HELIPONIX, LLC
SBIR Phase I: Plant Photomorphogenesis using Adaptive Multispectral LED Arrays in a Rotary Aeroponic Cultivation Chamber (RACC)
Contact
800 S SAINT JAMES BLVD
Evansville, IN 47714–2437
NSF Award
2025920 – SBIR Phase I
Award amount to date
$256,000
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide a sustainable method to grow healthy produce for individuals at a residential consumer level independent of location, climate, or season of the year. This project will develop new systems to grow produce in spaces with a small footprint, reducing food waste and consumption of potable water and energy. This can provide the capability to enhance cost-effective production in a small space with limited resources. The intellectual merit of this SBIR Phase I project is a new plant cultivation technology, called rotary aeroponics. coupled with a tunable irradiance growth efficiency research light designed to examine how light wavelength and timing can impact plant photomorphogenesis. Rotary aeroponic cultivation is the method of growing plants on a rotating cylindrical tower that is affixed vertically within a controlled environmental chamber. The tower design provides a larger surface area for growing plants in comparison to traditional vertical farming methods, thereby increasing the number of plants grown in a smaller space with less power consumption. The goal of this project is to successfully grow a healthy polyculture assortment of leafy green vegetables in a food-safe environment. The multi-spectra light will be used to learn how to maximize plant yields, minimize food safety risks, and enhance the taste profiles of different plant types. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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HEN NOZZLES LLC
SBIR Phase I: High efficiency nozzles for fire fighting
Contact
3650 PINON CANYON CT
Castro Valley, CA 94552–5430
NSF Award
2014176 – SBIR Phase I
Award amount to date
$225,000
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is advance the development of technologies for fire control. In recent years, California and other locations have experienced wildfires in millions of square acres of land, displacing thousands of people and forcing millions to breathe unhealthy air. Better fire control technologies, particularly fire hose nozzles, help address this need. The annual North America market for fire hose nozzles is $250 M. The proposed high efficiency nozzles would enable faster fire suppression, preventing billions in dollars of property damage, reducing risk to first responders, and conserving water. This SBIR Phase I project will advance the development of a fire hose nozzle to enable higher fire suppression rates. Enhancing capabilities of fire hose nozzles without changing operational protocols requires development of non-conventional transition regions in the flow pathway to simultaneously allow increasing flow rate, range and surface area. In this project, the nozzle flow pathway will be optimized to eliminate features causing backflow and non-uniformities. A flow modulation mechanism will be developed for the optimized nozzle to allow changing stream width without sacrificing range or fire-control rates. Fire suppression rates of the optimized nozzles will be measured and compared to the existing state-of-the-art nozzles. An empirical model will be created to estimate both the duration and potential water savings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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HERA GLOBAL TECH INC.
SBIR Phase I: Volition With An App
Contact
1120 SAVANNAH AVE
Pittsburgh, PA 15218–1319
NSF Award
2026010 – SBIR Phase I
Award amount to date
$255,880
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to decrease the number of overdose deaths in the U.S. by making an AI-driven mobile app to those suffering from substance use disorder (SUD). There were more than 67,000 drug overdose deaths in the U.S. in 2018. This project will potentially alter the existing behavioral health marketplace through its ability to save lives and reduce the $740 billion spent annually treating SUDs. The app, freely available to anyone with a mobile phone, uses an expert artificial intelligence (AI) system to suggest an appropriate evidence-based recovery plan to those in need. Medically recognized contingency-based therapy processes are incorporated to help individuals follow their recovery plans. This Small Business Innovation Research (SBIR) Phase I project will develop an expert system to develop an evidence-based personalized recovery program to individuals affected with SUD. To do this, the company is developing SUD self-directed recovery while enhancing compliance and motivation through a novel, salient reward system. Increasing recovery plan compliance is a major addition to current healthcare industry functions. The project will utilize a positive feedback loop via the novel use of value-based payment for individuals with substance use disorder with or without clinician oversight. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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HERMES LIFE SCIENCES LTD
SBIR Phase I: Pre-diagnostic Blood-Plasma Separation at the Point-of-Care
Contact
124 HOY RD
Ithaca, NY 14850–9378
NSF Award
1938096 – SBIR Phase I
Award amount to date
$269,996
Start / end date
01/01/2020 – 06/30/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this project will explore the development the High Efficiency Rapid Magnetic Erythrocyte Separator (H.E.R.M.E.S), a highly translational blood-plasma separation system enabling the decentralization of commercial blood testing. Blood testing is currently limited to centralized testing labs due to the requirements of centrifugation, a key first step in the majority of diagnostic testing. However, centrifuges are not suitable for use at the point-of-care and have created a bottleneck in the translation of bench-to-bedside testing. H.E.R.M.E.S is a unique magnetic bead-based separation method to quickly obtain plasma free of red blood cells. The technology is a low-cost and standalone platform with the potential to augment the testing efficiency and translational ability of existing blood-based diagnostic tests. Specifically, this effort will examine the potential for H.E.R.M.E.S to augment Human Immunodeficiency Virus (HIV) diagnostic and viral load quantification testing in finger-stick and whole blood, when used with standard lab-based and rapid diagnostic assays. Access to higher quality HIV tests will have a major impact for public health and improved diagnostic outcomes. H.E.R.M.E.S will address the lack of availability of low-cost and efficient sample processing technologies and help introduce the next generation of robust point-of-care blood tests. This Small Business Innovation Research (SBIR) Phase I project will enable the implementation of a magnetic-bead based separation assay to achieve low-complexity and rapid blood-plasma separation in point-of-care testing environments. The technology will enhance current blood-testing capabilities at the point-of-care and has the potential to enable the development of highly robust diagnostic tests. This Phase I effort will demonstrate the feasibility of the underlying technology for companion use with commercially existing laboratory-based and rapid diagnostic HIV assays. The compatibility of the separation assay will be verified by comparing the performance of the diagnostic assay with different sample types: blood, centrifuged plasma and H.E.R.M.E.S plasma. This proposal will explore the potential to use the unique sample type generated by H.E.R.M.E.S to enhance HIV diagnostic testing outcomes by providing earlier detection. The end result is a device that can process blood into a sample that will augment the performance of blood-based diagnostic 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.
Errata
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Addenda
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HEROWEAR, LLC
SBIR Phase I: Mechanized clothing to enhance productivity and low back health in the logistics industry
Contact
600 ANDREW RUCKER LANE
Nashville, TN 37211–7322
NSF Award
1913763 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 06/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop mechanized clothing technology to reduce physical disability, healthcare costs and missed work for material and package-handlers in the logistics industry. Workers in this industry are at high risk of developing low back pain (LBP) due to the physical demands of repeated leaning and lifting. There are currently no solutions for this occupation that are effective, affordable, practical and unobtrusive. This project is focused on mechanized clothing, a game-changing new device to reduce fatigue and incidence of low back pain amongst material/package-handlers and other occupations that involve repetitive lifting and leaning. For employers, mechanized clothing creates the potential for a happier, healthier and more productive workforce with reduced employee turnover, medical costs and understaffing issues. For workers, mechanized clothing means the potential for less low back pain, fatigue and missed work. For society, it means the potential to improve well-being for millions of individuals worldwide and to reduce the burden on the healthcare system and reliance on painkillers. This SBIR Phase I project proposes to develop an exoskeleton that is able to integrate into the normal workflow of material/package-handlers. Mechanized clothing has been shown in lab tests to reduce loading on the low back. The key to demonstrating commercial feasibility is proving to logistics companies that their workers can be assisted in a real world environment without interfering with daily workflow. The SBIR project plan is to (i) design a multi-stage clutch to prepare for real-world testing; (ii) use a robotic emulator system in the lab to quantify optimal assistive spring stiffness for leaning and lifting biomechanics, to inform spring selection in the new mechanized clothing prototype; and (iii) demonstrate feasibility of device integration into a real-world package-handling environment by testing users with the mechanized clothing prototype and assessing the degree to which it can assist users without hindering workflow. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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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 – 07/31/2021
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.
Errata
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Addenda
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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 – 11/30/2020
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.
Errata
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HOUR 72, INC.
SBIR Phase I: A multi-armed and customizable polymer adhesive for expending lifetimes of active ingredients in topical products
Contact
325 E 72ND ST
New York, NY 10021–4685
NSF Award
2014765 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 01/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will develop a new solution to help prevent insect-borne diseases, such as malaria, Zika, dengue, and chikungunya. Over half the world’s population is at risk of contracting an insect-borne disease, and the global mosquito repellent market is expected to grow to $11 billion by 2021. Use of personal repellents is a promising solution to prevent insect-borne diseases, but challenges include adherence because products may only be effective for a few hours (and less when rubbed or washed off). The proposed technology is a material to serve as a platform for insect repellents in a costly and effective fashion. The proposed material enables ultra-long-lasting efficacy and will be customizable, waterproof, not absorbed into the bloodstream, and imperceptible to the touch when applied to the skin. The technology could be extended to other applications, such as antimicrobial use and sunscreen. This SBIR Phase I project proposes to develop a platform technology to extend the life of functional skin products. Phase I aims are to: 1) Optimize a skin formulation for repelling insects with performance goals: 99%+ efficacy for at least 3 days, waterproof, not absorbed into the bloodstream, containing zero synthetic repellents, and imperceptible to touch when applied to skin; 2) Explore the parameter space for manufacturing the polymer and insect repellent formulation at scale; 3) Conduct testing to determine efficacy of the insect repellent formulation compared to a reference formulation; 4) Demonstrate extended life of a variety of active ingredients for utilization in topical sunscreen and antimicrobial products. Phase I work will establish feasibility of the proposed platform, while meeting a recognized need in the area of protection from vector-borne illnesses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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HUMANGO INC
SBIR Phase I: HumanGo, the Artificial Intelligence based Health Coach Assistant
Contact
210 CACTUS CT
Boulder, CO 80304–1001
NSF Award
2014828 – SBIR Phase I
Award amount to date
$223,525
Start / end date
08/01/2020 – 01/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from helping individuals achieve higher levels of wellness. The proposed system will collect data from a user’s wearables and other devices (smart watch, wifi scale, sleep tracker…) for a novel solution. The proposed project will develop an artificial intelligence (AI) coach monitoring fatigue and fitness to continuously optimize an integrated fitness, diet, and sleep plan. This Small Business Innovation Research (SBIR) Phase I project will use advanced AI and Deep Reinforcement Learning methods to develop a system that automatically builds and updates a training plan integrating workouts, diet and recovery subject to real-life conditions such as work, sickness, etc. Through advanced data preparation leveraging deep learning techniques, the system will cleanse the data to ensure high quality input data to the digital avatar. This avatar uses Reinforcement Learning to learn by exploration the best individualized courses of action for pre-specified goals. This system will form a novel personalized, predictive, proactive solution for monitoring health in real time 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.
Errata
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HUXLEY MEDICAL, INC.
SBIR Phase I: Single wearable patch for cost-effective, reliable, and accurate home sleep apnea testing
Contact
3344 PEACHTREE RD NE UNIT 3005
Atlanta, GA 30326–4815
NSF Award
2016158 – SBIR Phase I
Award amount to date
$224,998
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will investigate the feasibility of novel wearable sensor techniques to provide a complete diagnostic assessment for obstructive sleep apnea (OSA) with a single wireless patch worn on the chest. An estimated 25-30 M adults in the United States have OSA, but 80% of OSA-positive patients are undiagnosed while the highest volume clinics can only conduct around 5,000 sleep tests annually. Low diagnosis rates result partly from the challenge of sleep clinics managing an inventory of expensive and complex home sleep testing devices. To date, all home sleep tests require patients to wear bulky sensors that attach to multiple (3-5) regions of their body via a network of wires, tubes, and probes. This project will explore novel, unobtrusive, cost-effective sensors to reliably detect apnea and hypopnea during sleep. The project outcomes will strengthen fundamental understanding of how physiological signals are altered during sleep apnea and how to reliably measure these signals using simple wearable patches. The proposed SBR Phase I project will advance the development of a sensor platform for a wireless device to diagnose obstructive sleep apnea. The project will explore the feasibility of new sensing modalities to provide sufficient diagnostic information with a single wireless patch. The innovation stems from: (1) use of novel cardiorespiratory sensing modalities and machine learning to determine respiratory events and arousals from disordered breathing, and (2) integration of multiple sensing modalities into a chest-worn patch to provide a complete assessment of sleep apnea severity according to established clinical guidelines. This project will: conduct functional tests of sensor modalities relative to the clinical standard wired technologies; identify digital signatures of disordered breathing using advanced digital signal processing techniques; and assess the diagnostic capability of the complete single patch sensor relative to the clinical gold standard sleep 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.
Errata
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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
College Station, TX 77840–5241
NSF Award
2015016 – SBIR Phase I
Award amount to date
$249,966
Start / end date
05/15/2020 – 01/31/2021
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.
Errata
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Health Technology Innovations, LLC.
STTR Phase I: CryoDiscovery? : An integrated cryo-EM intelligence solution
Contact
4640 SW Macadam Ave
Portland, OR 97239–4243
NSF Award
1939142 – STTR Phase I
Award amount to date
$224,949
Start / end date
03/01/2020 – 10/31/2020
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project will be to accelerate discoveries of new molecular structures using cryogenic electron microscopy ("Cryo-EM"). Cryo-EM produces high-resolution 3D images at microscopic levels and is used by researchers in many fields including life sciences, materials science, nanotechnology, semiconductors, energy, environmental science, and food science. Microscopy advancements enable molecular image capture at unprecedented levels of resolution, but the data produced are growing exponentially and subsequent processing of those images into visible 3D structures is both challenging and time consuming. Each project can produce more than 100,000 images and take weeks to arrive at one viewable 3D structure. Current image processing and data analysis solutions are not well-integrated, requiring extensive manual user involvement and long wait times before assessing image quality. We will apply machine learning to automate cryo-EM image processing to improve researcher productivity and accuracy. We will also design the system to reduce user training time. The result will improve access to cryo-EM and accelerate new breakthroughs in many areas of science. This Small Business Technology Transfer (STTR) Phase I project automates image processing for single particle analysis by developing new machine learning models that recognize particles with repeatable accuracy levels and integrates them into the cryo-EM workflow for easy deployment. Images generated by cryo-EM are highly noisy, and the goal is to process them to build recognizable 3D molecular structures. Many steps in the cryo-EM workflow require manual intervention and analysis that can take several weeks and result in errors due to user bias, time waiting and user fatigue. The objectives of this research are to produce a prototype that consistently and accurately predicts particles and is easily integrated into the cryo-EM workflow. The approach will be to increase the training and validation datasets from a wide range of applications and utilize existing convolutional neural network frameworks. We will develop new techniques for running experiments to optimize the models, integrate the prototype into established cryo-EM workflows for end-to-end processing, and produce a delivery method for easy 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.
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Heliobiosys, Inc.
STTR Phase I: Purification of Mycosporine-like Amino Acids using Aptamers
Contact
112 Foxwood Road
Portola Valley, CA 94028–8113
NSF Award
1940352 – STTR Phase I
Award amount to date
$225,000
Start / end date
02/01/2020 – 01/31/2021
Abstract
The broader impact of this STTR Phase I project is to harvest a natural sunscreen for broader distribution. This project will use a group of fast-growing microorganisms that make these ingredients. The challenge will be to harvest enough of the material to make effective and affordable sunscreens. The problem is akin to trying to collect all the "needles in a haystack". New tools that incorporate reusable analogues to "magnets" for capturing and releasing the sunscreen compound will provide a novel way to get the material out of a complex mixture of broken open cells and into the sunscreens. There is a lack of genuinely non-toxic, environmentally safe sunscreens in the U.S. market today. Melanoma, the most common cancer in the U.S., is a deadly form of skin cancer directly attributable to sun damage to skin, and conventional sunscreens are under pressure because of human health concerns and possible impacts on coral reefs. This work will provide a new class of sunscreens safer for people and marine life. Unlocking the potential of this nature-designed sunscreen will improve human health and the environment. This STTR Phase I project will evaluate the technical feasibility of using aptamers (small nucleic acids) to isolate mycosporine-like amino acids (MAAs) from a complex mixture of compounds derived from cyanobacteria. Small molecules present challenges for aptamer development because they can be: difficult to immobilize, have multiple three-dimensional conformations, and few chemically distinguishing features. MAAs present unique challenges due to the similarity of their chemical structure with other cell lysate materials and wide variety of amino acid substitutions. This innovation entails the isolation and identification of the specific MAAs being produced, isolation of aptamers that are highly specific, and assessing process scalability. MAAs are not commercially available so reference standards will be derived from the culture broth. These materials will be utilized as targets in aptamer selection using a proprietary single-stranded DNA library of aptamer sequences to identify suitable candidates by next-generation sequencing and bioinformatics analysis. Those aptamer candidates will then be screened and evaluated using an affinity purification workflow and absorbance-based microplate assay. The end result of this work will be to establish if this is a robust and scalable affinity purification method for MAAs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Helios Applied Science Inc
SBIR Phase I: Utilization of a Combustion Process to Rapidly Solidify a Photocuring Composite Structure
Contact
1 Westinghouse plz, Ste D157
Hyde Park, MA 02136–2196
NSF Award
1843840 – SBIR Phase I
Award amount to date
$224,973
Start / end date
02/01/2019 – 01/31/2021
Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project will be the research and development of a new class of extremely portable deployable structures that allows easier transportation and simplifies the deployment of bulky structure. This fundamental technology covers a wide variety of potential commercial products including large easily transported rescue equipment and large tents for earthquake and other widespread humanitarian disaster scenarios; large space satellite structures such as antennas and optical arrays; large deployable UAV wings; large volumes for habitation or material storage; piping for water, sewage, oil or gas. This technology can help save lives during disasters, ease the transportation of potable water, sewer and energy with lower construction and deployment costs. This Small Business Innovation Research (SBIR) phase I project will entail the systematic analysis and development of a novel highly compact, rapidly deployable composite tube technology. The challenge is to harness and combine the extremely energy dense properties of chemical combustion with a photocuring high-performance structural composite material to create an easily transported structure that can be rapidly deployed. The project will entail experiments to better understand the polymer material properties and tailor them to the electromagnetic spectrum emitted by the combustion. Customization of an adhesive that will combine the necessary viscosity, structural and curing properties. A multiphysics simulation, validated with laboratory experiments, will be used to predict the technology's limitations. The qualifying components will be utilized in a refined design and evaluated by manufacturers for large scale production. These efforts will culminate in scale prototype construction 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.
Errata
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Howe Industries LLC
SBIR Phase I: ThermaSat - A Solar Thermal CubeSat Propulsion System
Contact
1435 E University Dr Ste C-108
Tempe, AZ 85281–0000
NSF Award
1936152 – SBIR Phase I
Award amount to date
$249,966
Start / end date
12/15/2019 – 11/30/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I Project addresses the need for small, low-cost satellites in space to have on-board propulsion capabilities. The advent of small satellites is opening space to entrepreneurs and researchers to improve telecommunications, monitor climate patterns, and conduct other activities. Unfortunately, many of these small satellites have no method of maneuvering in space, and so their capabilities are limited. Satellite propulsion allows for small satellites to achieve three major goals. First, they can reach their preferred orbit without diverting the launching spacecraft. Second, they can make minor adjustments to their orbits for many years, ensuring they do not re-enter the atmosphere prematurely. And third, at the end of the mission they can de-orbit themselves and avoid becoming dangerous space debris. An onboard propulsion system will be necessary for the satellite infrastructure of the future. By developing this technology now, we can overcome a major obstacle in space exploration and assist humanity in expanding to the stars. This Small Business Innovation Research (SBIR) Phase I Project is to develop a green, inexpensive, and effective small satellite propulsion system. Equipping CubeSats and other small spacecraft with onboard propulsion will drastically improve their technological capabilities and ensure they deploy, function, and de-orbit safely. The system functions by selectively filtering sunlight to heat water to high temperatures by limiting radiative heat emissions. The high-temperature steam is exhausted through a nozzle and can control the satellite with high efficiency. The major goal of this effort will be to experimentally and computationally model optical system performance. Other goals will be to validate that the thermal and structural systems are suitable for ground launch and operation in space. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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Hyphae Design Lab
SBIR Phase I: Ecosystem Design Tool
Contact
942 Clay St.
Oakland, CA 94607–3906
NSF Award
1938665 – SBIR Phase I
Award amount to date
$224,851
Start / end date
02/01/2020 – 01/31/2021
Abstract
The broader impact of this SBIR Phase I project is to enable tools to inform methods to reduce air pollution. Air pollution increases the risk of cancer, stroke, heart disease, respiratory infections; further, it may play a role in Alzheimer's disease and diabetes, resulting in trillions of dollars of health care costs globally each year. Half of these costs may be attributed to roadway traffic sourced pollution. Traffic sourced pollution is possibly intercepted by trees, although improperly configured roadside trees do not produce these benefits and creating the opportunity for improved health via targeted engineering of roadside tree placements. This project will develop analysis and design tools to make sure that such tree plantings optimize benefits for ecosystem designers, health insurance companies, governments, and local businesses. This SBIR project will develop a system to optimize high-resolution site-specific tree placement for pollution reduction. Trees are known to reduce air pollution by acting like filters as their high surface area attracts pollutants. Tightly packed trees of a type with high surface area placed on the leeward side of a busy roadway can intercept > 30% of traffic sourced pollutants. This project will perform ground-based, high-resolution vegetation analysis on neighborhoods under study. These data will be used to train an algorithm to infer high-resolution vegetation properties from widely available, low-cost data streams. These inferred vegetation metrics will be integrated with a geospatial ecosystem design automation pipeline to create a software tool. To accurately predict the capture, high-resolution vegetation surface area measurements, tree crown spacing information, wind speed, wind direction and roadway traffic volumes will be aggregated in a comprehensive 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.
Errata
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Addenda
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IASO THERAPEUTICS, INC.
SBIR Phase I: Development of Bacteriophage Qbeta and Mutants as Carriers for Next Generation Vaccines
Contact
325 E GRAND RIVER AVE STE 300
East Lansing, MI 48824–4384
NSF Award
1913654 – SBIR Phase I
Award amount to date
$225,000
Start / end date
06/01/2019 – 05/31/2021
Abstract
This SBIR Phase I project aims to develop an anti-cancer vaccine. A successful vaccine against cancer can potentially revolutionize cancer treatment and prevention by providing durable protection to patients and preventing relapse, without the harmful side effects commonly associated with chemo- and radiation- therapies. One of the major challenges in anti-cancer vaccine development is the low immunogenicity of cancer antigens, in particular tumor associated carbohydrate antigens. In order to overcome this, in this project, a new carrier system based on bacteriophage Qbeta will be developed. A representative carbohydrate antigen GD2 will be linked with bacteriophage Qbeta, which can elicit superior titers of antibodies that can kill cancer cells. Successful commercial development of such vaccines will greatly benefit cancer patients not only in the US, but also throughout the world. In addition to cancer vaccines, the bacteriophage Qbeta based carrier is a new platform technology to elicit powerful antibody responses. Biotechnological companies interested in vaccine development can adapt Qbeta as the carrier to target infectious diseases and chronic diseases. Furthermore, the Qbeta platform can provide an excellent starting point for the generation of monoclonal antibodies, which are among the top agents developed for therapeutics and diagnostics. Thus, the availability of a superior carrier can potentially address a wide range of biomedical needs. This SBIR Phase I project proposes to design new bacteriophage Qbeta based carriers for next generation vaccines. Vaccines have had tremendous impacts on public health. Traditional vaccines commonly incorporate attenuated or killed bacteria or viruses as immunogens. With the enhanced requirements on safety, the field is focusing more on well-defined subunits as epitopes for vaccine design. As subunits tend to have lower immunogenicity, immunogenic carriers are critical to deliver the desired antigen to the immune system and to enhance the immune responses. However, there are only a few carriers available that have been validated in clinical studies. The limited choices of carriers can significantly reduce vaccine efficacy due to interferences from anti- carrier antibodies. This project develops a new class of immunogenic carrier based on bacteriophage Qbeta capable of eliciting superior levels of IgG antibodies to the target antigen compared to gold standard carrier proteins. Novel mutants of Qbeta will become available to elicit high levels of IgG antibodies against the target antigen. The utility of the new Qbeta carrier will be demonstrated in delivering a tumor associated carbohydrate antigen, i.e., ganglioside GD2 derivative, to induce potent anti-cancer IgG antibodies. When successful, the GD2 based vaccine will be a quantum leap for the field as it will be the first ever carbohydrate based anticancer vaccine. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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ICTERO MEDICAL, INC.
SBIR Phase I: High Surface Area (HSA) Intraluminal Cryoablation for the Treatment of High-risk Patients with Gallstone Disease
Contact
2450 Holcombe Blvd Suite 88
Houston, TX 77021–2039
NSF Award
1938608 – SBIR Phase I
Award amount to date
$223,729
Start / end date
01/15/2020 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop a safer alternative to gallbladder surgery for elderly patients at higher risks of complications due to the effects of general anesthesia. Approximately 200,000 Medicare patients undergo surgery to remove their gallbladders every year. Unfortunately, 24% of these patients will experience a perioperative complication due to the effects of general anesthesia, totaling $500 M in cost annually to the US healthcare system. As the population ages and management of chronic disease improves, the need for alternatives to gallbladder surgery increases. This project will develop a process to affect the entire surface of the gallbladder ("ablation"), inducing a healing response that will defunctionalize the gallbladder and obviate the need to remove it. This is the first technology designed to conduct this process within a tube via a minimally invasive approach. Ultimately, this technology could be adapted to create more effective devices for other high surface area tissue targets. The proposed project is a significant improvement over current state-of-practice ablation devices due to its ability to deliver high-surface area ablation within a closed lumen or organ, such as the gallbladder. Existing conductive devices are designed for targeted ablation of discrete lesions rather than therapeutic delivery to large tissue targets, such as the gallbladder. The aim of this project is to develop a new process using open lumen instillation of cryogen to achieve high surface area cryoablation of tissues. This raises several unique engineering challenges, including the design of a delivery mechanism for the uniform distribution of cryogen across a closed lumen and development of a pressure management system to properly evacuate the cryogen gas and prevent an increase in intraluminal pressure. Initial optimization of the cryogen distribution and pressure management system will be conducted using a benchtop thermal load model of the gallbladder to approximate the in vivo thermodynamics. Optimized designs will then be tested in acute and chronic animal models to demonstrate the safety and efficacy of open lumen instillation of cryogen for high surface area intraluminal cryoablation of the gallbladder. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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IGNEOUS IP HOLDINGS, LLC
SBIR Phase I: 3-D printing of high strength-to-weight closed-cell polymer foam with gyroid lattices
Contact
53 FULTON STREET STE 1
Boston, MA 02109–1415
NSF Award
1938466 – SBIR Phase I
Award amount to date
$225,000
Start / end date
10/15/2019 – 09/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the state of the art of additive manufacturing, through development of a novel foam resin technology for rapid 3-D printing of ultra low-density parts with high strength-to-weight ratios. The demand for lightweight, high-strength printed parts is growing across all sectors of the manufacturing industry. The additive manufacturing market is expected to more than double by 2026, with high resolution vat photopolymerization as its largest market segment (>$1 B). By accelerating production speeds and overcoming size limitations that have limited manufacturing output to small products, the technology also opens the doors for general manufacturing. Within the automotive, aviation and shipping industries, for example, the technology will support lightweighted designs, thus increasing efficiency, while lowering energy consumption, material consumption, and greenhouse gas emissions, resulting in lightweight printed parts. This Small Business Innovation Research (SBIR) Phase I project will develop a novel method to modify the high resolution vat photopolymerization process, to enable 3D printing with resin that is foamed using a patent-pending process. Because the proposed technology can be adapted for use on most vat photopolymerization systems, industries can apply it to their existing resins, machines, and processes. The technology will allow for the manufacture of lightweight parts with up to 75% gas fractions, translating to parts that are 75% lighter and less expensive to produce compared to traditional additive manufacturing processes. In order to establish proof-of-concept and progress the technology toward commercialization, several critical objectives must be met. Materials that can produce strong, lightweighted products using this technology will be identified. Different types of materials will be investigated in experiments designed to vary the gas fraction in the cured foam, and at least 3 resin formulations will be selected to generate foams for further evaluation of their mechanical properties. The results of three types of tests (compression, impact, and 3-point bending) on foams printed using the proprietary PrintFoam process will be compared to other materials to demonstrate that the technology delivers materials with improved strength-to-weight ratios. In addition, plans for scale-up of the machine and technology will be generated. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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IKONA, INC.
SBIR Phase I: Using Immersive Virtual Reality For High-Quality Training to Caregivers Working With Seniors
Contact
50 W 34TH STREET APT 17C6
New York, NY 10001–3089
NSF Award
2026134 – SBIR Phase I
Award amount to date
$255,901
Start / end date
09/01/2020 – 08/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be significant for helping senior caregivers optimally understand and respond to cognitive changes in older adults through a new Virtual Reality (VR) The project will result in a high-quality, effective training module for helping senior caregivers optimally understand and respond to cognitive changes in older adults. This will enhance the competence, confidence, and motivation of their nursing staff, and help reduce staff turnover. The solution will empower caregivers to effectively attend to the needs of the elderly in a way that enhances seniors’ quality-of-life and facilitates ‘aging in place,’ hence contributing towards increasing well-being among the elderly population and alleviating the societal costs of aging. This Small Business Innovation Research (SBIR) Phase I project addresses the technical challenge of developing VR content that effectively promotes caregiver knowledge acquisition, skill development, and motivation increases, while keeping the training experience relatively brief and efficient. Unlike simple memorization of information, positive psychological outcomes like enhanced motivation are challenging to generate. This project will strategically employ cinematic directing techniques at key points in the VR training - a new approach to VR training. The solution leverages principles from the cognitive neuroscience of learning to deliver innovations in VR content design, analysis and delivery. Research objectives include: (1) building an engaging VR training module centered around teaching empathy and communication skills, which is enhanced with cinematic directing elements, (2) assessing the usability and feasibility of the developed content for achieving the desired outcomes in the short- and long-term, (3) building and assessing a VR training module centered around teaching observation and behavioral skills to senior caregivers, which includes embedded interactive testing elements. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Addenda
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IMAGINAG TECH, LLC
SBIR Phase I: COWculator: Automated Cattle Counting and Bovine Temperature Screening from Aerial Feedlot Images
Contact
2495 DEBORAH DR
Beachwood, OH 44122–1664
NSF Award
1913609 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from the development of a quick, easy, and accurate way to count cattle and detect bovine illnesses on feedlots and ranches via Unmanned Aerial Vehicles (UAVs). Current methods for counting cattle are extremely time-consuming or inaccurate, and sometimes both. Additionally, bovine illnesses are often diagnosed too late, leading to 50% of cattle mortalities on feedlots and yielding a $1.9 billion economic loss to the cattle industry. The proposed technology will leverage aerial images to (a) count cattle accurately and efficiently and (b) identify ill cows up to one week before clinical symptoms appear without the need to install expensive health-monitoring equipment on each cow. Ultimately, the proposed technology promises to more broadly impact the way wildlife and endangered species are tracked by automating wildlife counting on aerial images. This Small Business Innovation Research (SBIR) Phase I project proposes to develop an imaging-based solution for feedlot accountants, nutritionists, and auditors to monitor cattle. The project will leverage aerial photos of feedlot pens to automatically count all cattle breeds - regardless of season and ground conditions - using a combination of deep learning and traditional image processing tools. Additionally, this project will leverage aerial thermography to measure bovine temperatures; machine learning tools will be developed to differentiate between elevated body temperatures associated with illness and those associated with normal confounding factors. The goals of this Phase I project are to develop and fully validate the technology for cattle counting on feedlots and to establish the technical feasibility of leveraging aerial thermographic imaging for prediction of cattle 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.
Errata
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IMPRESSIO INC
SBIR Phase I: Mimicking Metatarsophalangeal Joints Using Tailored Ultra-Dissipative Liquid-Crystalline Elastomers to Treat Hallux Rigidus
Contact
12635 E Montview Blvd, Ste 214
Aurora, CO 80045–7335
NSF Award
2014661 – SBIR Phase I
Award amount to date
$249,999
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to treat arthritis in joints. This project will advance the use of special materials for joint repair, which permit devices to mimic the naturally soft tissues of the body and provide anatomically correct support. These materials also offer the advantages of minimally invasive surgery, development of patient-specific devices. It will offer the ability to arthritis in joints in the foot, hand, knee (e.g. total knee replacement), spine (e.g. total disc replacement), and repair of any load-bearing orthopedic tissue, such as meniscus. The proposed project focuses on advancing the translation of Liquid-Crystalline Elastomers (LCE) as a cartilage replacement device for the metatarsophalangeal (MTP) joint to treat hallux rigidus. Hallux rigidus is a joint disorder at the base of the big toe. This project will be the first to investigate LCEs for orthopedic applications and develop an MTP joint repair using LCEs. LCEs have vastly superior energy dissipation properties relative to traditional elastomers, such as silicone or hydrogels. This project will demonstrate LCEs for treatment of degenerated joints by drawing from the disciplines of liquid-crystal elastomer science, viscoelasticity, and bioengineering. LCEs are known for behavior that is similar to biological tissues. This proposed project will accomplish: 1) synthesizing an LCE to mimic mechanical properties of natural joint to minimize wear rate under simulated physiological conditions; and 2) validation of biomechanical performance and biocompatibility of LCEs in comparison to the state of practice. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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IMVELA CORP.
SBIR Phase I: Harnessing Untapped Food-borne Microbial Diversity to Rationally Engineer Novel Healthy Foods
Contact
19 Morris Ave Bldg 128
Brooklyn, NY 11205–1095
NSF Award
1940409 – SBIR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader/commercial impact of this SBIR project is to validate the technical and commercial viability of developing a novel fermented food to address underlying mechanisms associated with Irritable Bowel Syndrome (IBS). IBS is a highly disruptive and prevalent disease afflicting approximately 32 million Americans. Technically, the ability to rationally design a novel fermented food with defined strain content and specific health and nutritional benefits will be validated for the first time. Commercially, the taste and acceptability for consumers will also be verified to ensure strong market demand for the product. If successful, this proposal will more broadly validate a novel platform for designing rationally fermented foods with a variety of desirable properties, including improved health and nutritional qualities, more robust preservation, and targeted removal of specific compounds/toxins. Although the initial disease target is IBS, there are many other chronic diseases with strong associative links to the microbiome; these now constitute 90% of U.S. health care spending (nearly $4 trillion) and present an urgent area for innovation that this platform could powerfully impact, both domestically and abroad. This Small Business Innovation Research (SBIR) Phase I project proposes to develop a new platform to precisely engineer novel fermented foods with defined microbial and metabolite content to improve human health. Fermented foods have great promise to impact the host gut and microbiome through a variety of established mechanisms, and have the advantage of high, metabolically active doses of microbes and the ability to deliver multiple strains along with their associated bioactive metabolites. However, a key technical hurdle is that it is not currently possible to precisely define the strain and metabolite content of a fermented food. This proposal addresses this challenge by leveraging recent advances in microbial strain isolation, genomic characterization and high throughput screening. First, next-generation strain isolation techniques will be applied to food-borne microbes to develop a large and deeply characterized biobank of previously inaccessible microbial strains. The strains will then be screened for activity on specific host and microbiome mechanisms. Lead strains will then be formulated into a food at commercial scale, and the presence of the strains as well as retention of their associated health properties will be confirmed. Finally, the taste profile will be validated. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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IN CONTEXT REPORTING INC
SBIR Phase I: Development of a fully annotated corpus for the training of a Clinical Question Answering System for critical results delivery at the Point of Care
Contact
6540 SEWANEE AVE
Houston, TX 77005–3748
NSF Award
2014686 – SBIR Phase I
Award amount to date
$224,961
Start / end date
06/01/2020 – 02/28/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from improving the quality of healthcare and streamlining its delivery. The accumulation of clinical data has become a potentially valuable resource for clinical practice, as Electronic Medical Records (EMRs) contain information on day-to-day patient care. Latest Natural Language Processing (NLP) techniques applied to EMR data enable the development of health Intelligent Virtual Assistants (hIVAs) to assist healthcare professionals in incorporating evidence-based decision support, reducing errors and improving efficiency. Current most promising NLP approaches are underdeveloped for the clinical domain given the lack of high-quality annotated clinical data required for training, testing and validating the machine learning algorithms. As most EMR data is available as unstructured free text, software developers in Artificial Intelligence (AI) struggle to find these annotated texts. The proposed project will inform the production of high-quality hIVAs - from voice-based clinical AI chatbots for assisting physicians at the point of care to Question-Answering systems for clinical decision-making. This Small Business Innovation Research (SBIR) Phase I project addresses the technical challenge of exploiting different combinations of Deep Learning (DL) structures for developing a novel set of annotation tools and an expert adjudication methodology to optimize the development of annotated corpora, specifically tailored for the clinical domain. The lack of these standard and annotated data sets is a major bottleneck preventing progress in clinical Information Extraction. Without these corpora, individual Natural Language Processing applications abound without the ability to train different algorithms, share and integrate modules, or compare performance. The company is leveraging the latest DL techniques to develop a unique architecture, able to identify a comprehensive set of context modifiers within unstructured clinical texts. This approach will boost the semi-automatic annotation of clinical corpora; produce accurate and robust annotated corpora; and reduce corpora production time and cost. The project objectives include: (1) adapting the existing in-house algorithm for automatic clinical text pre-annotation; (2) integrating a hybrid algorithm into a multi-user operable software platform for obtaining a minimum viable semi-automatic annotation product; (3) conducting a small pilot study to validate the performance of the resulting software platform and a Minimum Viable Product of an annotated corpus for diagnostic imaging reports. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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INFOCUS NETWORKS
SBIR Phase I: Scaling Cluster Computing Fabrics with Optical Networking
Contact
3957 30TH ST UNIT 406
San Diego, CA 92104–3080
NSF Award
1842768 – SBIR Phase I
Award amount to date
$224,993
Start / end date
02/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from developing technology to enable enterprise, cloud, academic, and government network operators to cost-effectively scale computer clusters to support the growing demands on these systems. Computer clusters underpin an increasingly broad range of services that businesses, researchers, and society have come to rely on, from machine learning systems to online social media platforms. Companies increasingly use computer clusters to gain a competitive advantage and accelerate product development. Today's networking technologies improve in performance by a factor of two every two years, but the demand placed on cluster computing systems is growing more than twice that fast in some market segments. The technology developed through this project is well-positioned to exceed the cost and performance scaling limitations of current networking technology, enabling business and scientific end-users to find solutions to more complex problems more quickly. This Small Business Innovation Research (SBIR) Phase I project demonstrates the feasibility of a network interconnect for computer clusters that routes traffic through transparent optical switches. Optical switches remove communication bottlenecks in the network fabric but require fundamental changes in how distributed applications communicate information across the network compared to present-day technologies. The commercial success of the technology depends on its ability to accelerate the execution of common distributed applications while providing the interoperability, reliability, and manageability expected by network operators. This project aims to demonstrate a 2x improvement in the execution speed of network-bound applications compared to today's technologies. The proposed research to reach this goal includes developing and optimizing the software stack necessary to interface commodity applications with the fabric, quantifying the performance of those applications subject to the constraints imposed by optical switching, and optimizing the optical switch design to maximize application performance at a system level. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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INFORMAI LLC
STTR Phase I: Artificial Intelligence Tool to Optimize Organ Transplantation Outcomes (Transplant-AI)
Contact
2450 Holcombe Blvd.
Houston, TX 77021–0000
NSF Award
2014827 – SBIR Phase I
Award amount to date
$225,000
Start / end date
08/15/2020 – 07/31/2021
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project will be to improve solid organ transplantation outcomes. Few significant clinical or technological advancements have been made within the last two decades to improve organ matching success, and the accuracies of current models predicting survival outcomes are diminishing. There is a great need for clinicians to have better decision-making support tools. Every 12 minutes, a new person is added to the organ transplant waiting list, a number growing by about five percent each year. Within a single day, 21 people die waiting for a kidney, liver, or other organ match. Although 36,500 kidney and liver transplants are performed each year, the patient demand for donor organs far outweighs supply by four to one, so the need to improve donor-recipient matching is urgent. Optimizing the donor organ-patient match is a key determining factor for improving transplant success and patient survival. This project's artificial intelligence (AI) model will guide transplant surgeons, physicians, and other healthcare professionals will deliver precise, accurate, quantitative information for real-time predictions. This Small Business Technology Transfer (STTR) Phase I project proposes artificial intelligence to predict outcomes after solid organ transplantation procedures. Clinicians currently consider several factors when determining organ allocation and candidate patient ranking on the recipient waitlist, including extent of disease pathology, functional status of the recipient, and intrinsic donor and recipient compatibility factors. Measures, indices and functional status scores have been designed to predict specific outcomes but are not easily combined into one optimized decision to guide organ allocation decisions. To date, no organ-matching predictive outcome model has comprehensively synthesized all available patient- and donor-specific variables at the time of transplantation. This project will train an artificial intelligence (AI) algorithm to comprehensively integrate all information available at the time of transplantation procedures (hundreds of variables) into a predictive model. An AI model of this nature would be a substantial improvement from linear models able to synthesize only a modest number of parameters (approximately 15) to date. It is expected that the proposed technology will predict both pre- and post-transplant survival more accurately than currently accepted 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.
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INHERENT BIOSCIENCES, INC.
SBIR Phase I: Using patient specific DNA methylation to predict COVID-19 clinical prognosis
Contact
2725 E Parleys Way #100
Salt Lake City, UT 84109–1648
NSF Award
2034014 – SBIR Phase I
Award amount to date
$255,959
Start / end date
09/01/2020 – 02/28/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of an onsite, clinical test to screen incoming patients potentially infected with COVID-19 and prioritize hospital resources and personnel based on a predicted infection severity and treatment response. The benefits of a test that can predict COVID-19 infection severity are enormous. In addition to the millions of infections and hundreds of thousands of dealths, it costs hospitals an average of roughly $2,500 per day per patient for inpatient care. This project will develop a test for COVID-19 screening to accurately identify patients at risk. This Small Business Innovation Research (SBIR) Phase I project is establishing the use of DNA methylation patterns for personalized screening and treatment for COVID-19. The variation in symptoms and outcomes for COVID-19 progression make it challenging for healthcare workers to triage accurately. The development of a DNA methylation-based test to predict the severity of COVID-19 infection will help manage the pandemic. This project will: 1) generate a comprehensive dataset of white blood cell DNA methylation patterns, health history, and clinical data for patients infected with COVID-19; 2) generate a predictive model for COVID-19 infection severity and treatment response. The anticipated technical results of this project are a testing method and a computer algorithm for predicting infection severity and treatment response based on a patient’s unique DNA methylation pattern. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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INITIUM AI INC.
SBIR Phase I: Natural Language Processing for Enhanced Sales Communication
Contact
245 HUNTERS TRL
Ann Arbor, MI 48103–9525
NSF Award
1938438 – SBIR Phase I
Award amount to date
$224,847
Start / end date
11/01/2019 – 10/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from revolutionizing the way businesses approach sales, by directly and positively impacting sales communication. This, in turn, will lead to increased sales efficiency and increased customer satisfaction, while facilitating the acquisition of new customers and the retention of existing ones. These aspects will directly impact a company's bottom line and improve profitability. While the focus of this project is to build AI technology that can assist sales representatives in their communication, the lessons learnt here and the methods developed will be applicable to other areas where communication is essential, including the medical domain, counseling, or interviews. Furthermore, the goal of this project is to maintain significant involvement of women and under-represented minorities in this woman-owned company. This Small Business Innovation Research (SBIR) Phase I project focuses on building an intelligent sales platform expected to positively transform the sales process in business-to-business interactions. This will be achieved by creating technology that assists sales agents by increasing the effectiveness of their communication. Building on recent advances in Natural Language Processing and Machine Learning, novel methods and tools will be developed to measure and ensure sales agent responsiveness, accuracy, professionalism, and empathy in relation to customer communication. This project will leverage a proprietary large-scale dataset of sales emails and associated outcomes as a basis for the machine learning process. By the end of the Phase I project, this research will enable a direct and data-driven understanding of outcome-oriented sales communication and a quantified assessment of potential leads. This will be paramount to the future development of the project and to its impact and success in the marketplace. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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 – 07/31/2021
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.
Errata
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INNATRIX, INC.
SBIR Phase I: Directed protein evolution: Creating high affinity protein ligands for controlling economically detrimental plant pathogens and pests
Contact
250 BELL TOWER DR
Chapel Hill, NC 27599–0001
NSF Award
2014621 – SBIR Phase I
Award amount to date
$249,594
Start / end date
06/01/2020 – 05/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to create next generation crop products. Crop loss due to pathogens has been estimated to be approximately 20-40% of total possible yield. The proposed technology is an environmentally-friendly way to combat pests, even if they evolve to be resistant to conventional methods. This technology can be used for other life sciences applications, including special cancer treatments. The proposed project is to generate new and durable resistant crops by producing ligands that can bind to virulence factors of plant pathogens to make them malfunction. The novel protein evolution technology is a rapid and automated platform for developing high-affinity protein ligands. It comprises a self-sustaining, iterative bacterial culture system that drives the emergence of new protein and peptide sequences expressed by the M13 bacteriophage. Once pathogens or pest develop resistance for the ligands we generate, new and stronger binding ligands could be quickly evolved to control them. The technology is broadly applicable to developing optimized protein sequences for virtually any affinity interaction. Other applications include protein purification, antibody optimization as well as engineering novel receptors for cancer immunotherapy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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INOON, LLC
STTR Phase I: Multiple Eye Disease Detection Using a Smartphone
Contact
2104 MAIN ST APT 7
Lubbock, TX 79401–5920
NSF Award
2015102 – STTR Phase I
Award amount to date
$225,000
Start / end date
08/15/2020 – 07/31/2021
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.
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INSIGHT SENSING CORPORATION
STTR Phase I: A Novel Approach to Manage Nitrogen Fertilizer for Potato Production using Remote Sensing
Contact
1000 WESTGATE DR
Saint Paul, MN 55114–1416
NSF Award
1913435 – STTR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 04/30/2021
Abstract
The broader impact/commercial impact of this Small Business Technology Transfer Research (STTR) project is to reduce the environmental impact of agricultural production while optimizing net income to producers. Over-application of nitrogen fertilizer contributes to groundwater contamination via nitrate-nitrogen leaching, and puts substantial financial burden on rural municipalities and private well owners who are required to install and pay for treatment of their drinking water. An estimated 1% of global energy consumption is attributed to the production of synthetic nitrogen fertilizer. Producers operate under tight margins, and face pressure to maximize crop yields to remain profitable and sustain their business. The proposed technology aims to optimize nitrogen application and minimize the susceptibility of loss to the environment, while accounting for the year to year weather variability that poses the largest production challenge. The technology not only determines the optimum nitrogen rate for achieving maximum profit, but it also provides transparency in nitrogen management and can serve as a means for demonstrating compliance with incentive or regulatory programs. This STTR Phase I project proposes to refine and test a novel algorithm for making real-time nitrogen fertilizer recommendations during the growing season using remote sensing. The need for this technology is rooted in the issue that producers are not satisfied with current methods for in-season nitrogen management because of lack of accuracy and poor temporal and spatial resolution. The research objectives of this project are to: (i) predict crop nitrogen concentration using multispectral information, (ii) compare the algorithm to conventional methods, (iii) calibrate and validate a crop growth model for prediction of above-ground biomass, (iv) develop predictive algorithms for radiation use efficiency, and (v) optimize the algorithm and develop a software application suitable for use by producers. The algorithm needs to account for yearly variability in crop growth dynamics caused by climatic conditions, crop variety, and nitrogen management practices. A field experiment will be conducted to collect data necessary to evaluate these objectives. It is anticipated that this technology will perform with reasonable accuracy and have similar or superior performance to existing N management methods, making it a vast improvement over current practices because of its ability to consider spatial and temporal variability in a scalable manner. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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INSILICA, LLC
SBIR Phase I: Advanced Cancer Analytics Platform for Highly Accurate and Scalable Survival Models to Personalize Oncology Strategies
Contact
2736 QUARRY HEIGHTS WAY
Baltimore, MD 21209–1069
NSF Award
2012214 – SBIR Phase I
Award amount to date
$224,454
Start / end date
08/15/2020 – 07/31/2021
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.
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INTACT THERAPEUTICS
SBIR Phase I: A thermogel-based drug delivery platform for the upper gastrointestinal bleeding treatment
Contact
3944 TRUST WAY
Hayward, CA 94545–3716
NSF Award
2014730 – SBIR Phase I
Award amount to date
$224,999
Start / end date
08/15/2020 – 04/30/2021
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.
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INTELLIGENT DOTS LLC
STTR Phase I: BedDot: A Contactless Sensor Device for Sleep Activity Monitoring
Contact
3425 RIVER FERRY DR
Johns Creek, GA 30022–5936
NSF Award
1940864 – STTR Phase I
Award amount to date
$225,000
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impacts of this Small Business Technology Transfer (STTR) Phase I project include the technology advancement of smart sensing and the improvement of the quality of life and care of seniors, by providing real-time safety, activity and health monitoring during sleep; and sending alerts, reports and analysis to their loved ones and caregivers. The growth of this demographic segment, the reduction of family size, and increased mobility bring significant challenges to senior care. According to U.S. Census Bureau projections, the number of Americans 65 and older will increase to 55 million in 2022, and to 70 million by 2030; of this group, the population over 85 years of age is the fastest growing segment. Seniors and caregivers will benefit from the new sensor technology developed in this project, whether they live in their own homes or in assisted-living facilities, contributing to healthcare quality improvement and cost reduction. The advanced signal processing and machine learning techniques developed in this project will advance the field of data analytics and smart sensing. The proposed project is the first to develop a real-time contactless sleep monitoring device based on vibration sensing. The sensor will provide reliable monitoring of sleep activities and vital signs while placed under mattresses in various building environments. This project will mark the first attempt to develop a contactless blood pressure monitoring function. The advanced signal processing and machine learning algorithms will be refined and validated regarding vital sign estimation (heart rate, respiration rate, and blood pressure) and sleep activity recognition (entry/exit of the bed, movement, posture change). A key challenge of data analytics algorithm development is to self-adapt to changes in the physical and noise environment. Various algorithms and functions will be integrated into one device with a user-friendly graphic interface; then the product's advantages and limitations will be evaluated systematically in different relevant environments and compared with other 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.
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INTELLIGENT FINANCIAL MACHINES LLC
SBIR Phase I: Predictive and Computational Technologies for the Mortgage Industry
Contact
315 HIGHLAND TER
Woodside, CA 94062–3520
NSF Award
2015154 – SBIR Phase I
Award amount to date
$223,820
Start / end date
07/01/2020 – 12/31/2020
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from providing mortgage market participants such as lenders, servicers, insurers, investors, rating agencies, government sponsored enterprises, and regulators with integrated deep learning systems that offer actionable predictions of borrower, portfolio, security, and market behavior of unprecedentedly high accuracy and low latency at scale. The systems will enable these organizations to identify valuable opportunities, reduce losses, and improve staff utilization while dramatically lowering compute costs in a $2 billion annual mortgage decision and risk analytics market. Wide adoption will boost the performance of the American housing-finance system, benefiting homeowners and the broader population through lowering borrowing costs, expanding access to credit, and reducing the risk of future financial crises. The Phase I project focuses on developing transformative computational algorithms that make comprehensive deep learning predictions available in real time, at a fraction of the cost of existing computational technologies. It yields new insights into how computational algorithms can significantly enhance the benefits of AI prediction systems. This Small Business Innovation Research (SBIR) Phase I project seeks to address the core technical challenge associated with the development of powerful deep learning systems for measuring risk and identifying opportunities in the mortgage industry. This challenge is the construction of novel and transformative asymptotic-approximation algorithms to run in real time, rather than the hours or days prior technology requires. Examples of such applications include measuring the risks of large pools of mortgages over long horizons and the risks of mortgage securities backed by such pools. The dramatic running time gains offered by these algorithms are the key to harnessing the unprecedented predictive accuracy of deep learning models of individual borrower behavior. The key objectives of the proposed project are to develop a large-pool asymptotic approximation approach that offers run-time guarantees for deep learning models, and to construct efficient numerical schemes for implementing the resulting algorithms in a cloud environment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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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
$224,988
Start / end date
07/01/2020 – 06/30/2021
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.
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IQ BIOTECH LLC
SBIR Phase I: Development of a novel bioprotectant with fungicidal and biostimulant properties
Contact
8208 NW 30TH TER
Miami, FL 33122–1914
NSF Award
1951282 – SBIR Phase I
Award amount to date
$219,075
Start / end date
02/01/2020 – 03/31/2021
Abstract
The broader impact of this SBIR Phase I project will be in developing a crop protective agent that reduces negative environmental impacts and improves overall crop yield. Many common food crops, including tomatoes and peppers, are highly susceptible to fungal contamination; these organisms are rapidly developing resistance to the chemical pesticides widely used today. The objective of this project is to develop and test a new biofungicide consisting of beneficial fungi to protect plants from variety of diseases and plagues. This solution does not cause harm to the environment and offers a way to manage pesticide-resistant pathogens, which cost approximately $10 billion in the farming market. The proposed project will optimize the biofungicide for the many types of soils, crops and pathogens common across the country. A series of laboratory tests will be conducted to determine the optimal composition of the solution. The proposed project involves designing an effective bioprotectant and biostimulant, consisting of two different Trichoderma strains, to provide enhanced protective effects against harmful fungi and bacteria, with the added benefit of boosting plant health and improving overall crop yield. This project will develop new formulations of the blended strain biofungicide to provide maximum flexibility in their application, stability for storage and delivery, as well as testing and optimizing their efficacy in new and unproven combinations of plants, soils and growing conditions. The merits of the bioprotectant anti-fungal have already been demonstrated in preliminary experiments, but only for limited combinations of crops and soils. Relevant environments will be tested in this project. Additionally, previous tests have been conducted with dry formulations of Trichoderma, and thus the proposed research will focus on the two key objectives of (i) proving efficacy in new contexts and (ii) developing stable liquid formulations. To this end, a wide matrix of formulations will be tested with a variety of soils, crops and pathogens. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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ITERATIVE METHODS, LLC
SBIR Phase I:Ground-Loop Heat Exchanger Solution for Low Cost Ground-Source Heat Pumps
Contact
810 VICKERS AVE.
Durham, NC 27701–3143
NSF Award
1938260 – SBIR Phase I
Award amount to date
$224,807
Start / end date
01/01/2020 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is that it will significantly lower the initial cost of residential and commercial ground-source heat pump (GSHP) systems, while expanding the existing market through broadening GSHP applicability. This project will demonstrate the feasibility and performance under real-world conditions of a novel in-ground heat exchanger that is both inexpensive and easy to install, even on space-constrained lots, with little landscape disruption. The technology will lead to increased adoption of energy-efficient heating/ventilation/air conditioning (HVAC) technology, increasing the “electrification” of the energy economy and reducing air polluting emissions. These GSHP systems will impact the national market of heating and cooling systems, with potential annual energy savings of over 6.4 quadrillion BTUs, end-user savings of $77. B in annual energy costs, and reduced peak electricity demand by 144 GW. This SBIR Phase I project proposes to further develop a technology addressing the applicability, desirability and cost-competitiveness of GSHP systems. The chief technical objective of the project is to optimize system components and architectures by increasing fundamental understanding of in-ground heat exchanger performance and installation methods through digital and physical prototyping across a range of real-world conditions. A second technical objective is to improve fundamental understanding of the energy storage capability of the technology and how it can be leveraged through operational cycling to further increase the performance-cost ratio. Studies of physical prototyping, installation and thermal properties will be conducted, in addition to computational fluid dynamic (CFD) simulations. The primary goals are to demonstrate significant benefits in installed performance-to-cost and an installation time of under 8 hours for a typical residential 3-ton system, compared to the current state-of-the-art of 16 hours. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Infecho Scientific LLC
STTR Phase I: Implementation of an ultrasound technology for continuous in-situ monitoring of lubricant viscosity
Contact
1340 Ashland Rd
Columbia, MO 65201–8213
NSF Award
2013639 – STTR Phase I
Award amount to date
$224,770
Start / end date
07/01/2020 – 06/30/2021
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.
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Innerspec Technologies Inc
SBIR Phase I: PORTABLE EMAT PHASED ARRAY FOR CORROSION MAPPING
Contact
2940 Perrowville Road
Forest, VA 24551–2225
NSF Award
1842797 – SBIR Phase I
Award amount to date
$224,048
Start / end date
02/01/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide a better and safer alternative to conventional piezoelectric ultrasonic instruments that use liquid-coupled transducers for the inspection of pipelines, tanks, and other structures used in power generation and liquid process industries. This new instrument does not require the use of liquid coupling, and can work on rough, coated, or contaminated surfaces that cannot be inspected with conventional liquid-coupled techniques unless the part is subjected to costly and time consuming part preparation. By not using liquids, this instrument can also be used on components that are very hot, very cold, radioactive, or in a vacuum. A high-resolution ultrasonic instrument that does not use couplant and has comparable performance to a piezoelectric instrument will save inspection time, reduce inspection costs, and permit inspections while in-service, which will result in millions of dollars in savings for plant operators. Society as a whole will also benefit from improvements in safety and performance of the plants, and by reducing the amount of waste and contaminants released into the environment as direct sub-product of the inspection, or from failures in facilities and equipment. The proposed project consists of the development of a portable, high-resolution, ultrasonic phased array instrumentation, software, and transducers based on non-contact Electro Magnetic Acoustic Transducer (EMAT) technology to substitute or complement the tens of thousands of conventional piezoelectric instruments in the market. For the instrumentation, the research will revolve around the development of a high-power and compact 16-channel pulser/receiver with a very small dead zone that permit inspection near the surface of the part. This instrumentation will also require custom software with signal-enhancing algorithms that compensate for the small amplitude of EMAT signals. The 16-channel phased-array EMAT transducers will involve multi-physics simulation of electrical and magnetic components to develop very small and high-density coil elements that can produce enough signal amplitude at high-frequencies while handling the pulsing rates required for effective inspection, and the high-power generated by the custom instrumentation. All these components will need to be enclosed in a battery-powered package that can be used in the harsh conditions typically found in field inspections. The expected result is a portable instrument that can compete in performance with conventional piezoelectric instruments, especially in applications and inspection environments where a conventional instrument is not practical or very costly to use. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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InnovBot LLC
SBIR Phase I: Robotic Inspection and Data Analytics to Localize and Visualize the Structural Defects of Civil Infrastructure
Contact
2254 Sultana Drive
Yorktown Heights, NY 10598–3703
NSF Award
1915721 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/15/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that the proposed innovative research has the potential to be developed into a self-contained robotic inspection tool with vertical mobility that carries an RGB-D camera and ground penetrating radar (GPR) to detect and characterize both surface flaws and subsurface defects. The software algorithms and functions will be integrated into this wall-climbing robot to automate the data collection and analysis process, especially at critical locations that are difficult to access by human operators. The use of the robotic inspection tool will allow the evaluation and condition health monitoring of human-built concrete structures to be performed significantly faster, more thoroughly and at a lower cost by eliminating the need for scaffolding and blocking traffic. It will also improve inspection safety and speed which leads to more frequent and on-demand inspections, thus making the national infrastructure (bridges, tunnels, dams, buildings) more secure. This Small Business Innovation Research (SBIR) Phase I project focuses on developing innovative methods and software algorithms for 3D GPR imaging of subsurface defects, vision-based accurate positioning and surface flaw detection, characterization and mapping. The software functions will be integrated into this wall-climbing robot to evaluate the performance and validate the feasibility of the innovation. The intellectual merit of this project includes the 3D GPR imaging method that combines robot control and vision-based accurate positioning with GPR signal processing to locate the subsurface defects and embedment (rebar, pipes, fractures, voids, delamination, etc.) in concrete structures that will revolutionize the way GPR data is collected, interpreted and displayed. This method enables the GPR-Rover to scan the surface in arbitrary and irregular trajectory rather than move along grid lines to locate subsurface targets and discover the areas of delamination. The proposed robotic visual inspection and machine learning algorithm is novel because it can not only detect and characterize surface flaws but also precisely register them on 3D map for better localization and visualization. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Intelinair, Inc.
SBIR Phase I: Using Aerial Imagery Analysis to Manage Stress in Coffee Production
Contact
1807 S. Neil St.
Champaign, IL 61820–7215
NSF Award
1913969 – SBIR Phase I
Award amount to date
$225,000
Start / end date
07/01/2019 – 11/30/2020
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is significant. Based on the company's experience with the willingness of farmers to pay for such services, the potential commercial market for the envisioned solution for coffee alone would amount to USD 1 billion, based on the estimated 27 million acres currently in production around the world. The commercial potential for additional specialty crops would exceed several times this amount. The company's agronomy team believes that the proposed solution would result in yield improvements of the order of 5% to 10% and a reduction in combined fertilizer and water costs in the range of 3% to 8%. Moreover, the solution would result in higher-quality coffee beans which would improve the commercial viability of small coffee farms in emerging economies. This would have the potential of lifting hundreds of thousands of sub-tropical farmers and their families out of poverty while sustainably protecting soil and water resources. Precision agriculture techniques developed in this project will also enable coffee producers to address the effects of climate change by identifying destructive patterns and prescribing effective ways to maintain or improve yield and quality. This Small Business Innovation Research (SBIR) Phase I project seeks to develop novel deep learning algorithms and computer vision methods for coffee and for specialty crops in general, and thereby identify, through analysis, signatures of critical coffee tree stress conditions. To date, image analysis algorithms developed in academia typically focus on lab environments or controlled research plots. The tasks outlined in this project focus on real world coffee orchards with more demanding conditions. Challenges from the imagery point of view include managing the effects of clouds and the sun angle on the canopy, capturing tree foliage at an angle and identifying individual trees. Challenges from the deep learning area include identifying with confidence anomalous areas of stress or increasing stress for varying coffee strains, soil and topographical conditions within the orchard using multispectral and thermal imagery. From an agronomy standpoint, the project will seek to assist and/or correlate the deep learning findings with soil moisture sensors and other ground truth data. These elements will form the core of a low-cost commercial remote sensing and alerting system that is expected to be available to coffee-growing communities in the near future. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Interphase Materials, Inc.
SBIR Phase I: Advanced fouling detection for district cooling facilities treated with a novel nano-engineered surface treatment
Contact
370 William Pitt Way
Pittsburgh, PA 15238–1329
NSF Award
2001669 – SBIR Phase I
Award amount to date
$249,675
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will reduce the energy demands of district cooling (DC) plants via state-of-the-art monitoring and analysis of system operations. District cooling systems are a more efficient, cost-effective way to produce chilled water across campuses compared to traditional building air conditioning units. Fouling accumulation in DC systems is an inevitable byproduct of environment, water source, and operating conditions; it contributes to inefficiencies that lead to increased power costs. This project’s aim is to improve the understanding and analysis of fouling using a machine learning, algorithm-based system performance indicator (SPI) in conjunction with a nanomaterial that reduces fouling accumulation and improves heat transfer. The SPI will provide value to DC operators by enabling them to be proactive instead of reactive in their maintenance protocols, which will improve the efficiency of their cooling systems and reduce their operating costs. Together, this innovative technology package will optimize DC operations and contribute to reduced energy demand and emissions. An average size DC plant can realize an estimated savings of $300,000 annually. This SBIR Phase I project proposes to improve the efficiency of district cooling (DC) systems by increasing their system analysis capabilities through the following activities: 1) Integrate machine learning techniques into DC system data analysis to generate a system performance indicator (SPI). Instead of signaling that fouling has already occurred, the SPI will predict fouling onset to signal the need for retreatment with the nanomaterial and conduct other maintenance. 2) Optimize a system by integrating additional sensors for system performance diagnostics. The proposed project will conduct verification and validation for a system that could retrofit a single diagnostic sensor in the absence of a full sensor suite. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Isolere Bio, Inc
SBIR Phase I: Non-Chromatographic Method for the Purification of Monoclonal Antibodies
Contact
701 W. Main St.
Durham, NC 27701–5013
NSF Award
1843074 – SBIR Phase I
Award amount to date
$269,999
Start / end date
02/01/2019 – 02/28/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to improve manufacturing technology for the purification of monoclonal antibodies, which are important therapeutics as well as valuable tools in research and diagnostics. Approximately four new antibody drugs are approved every year, and while they can have tremendous clinical outcomes and are sometimes heralded as "magic bullets," they often come with a significant price tag. This puts a strain on patients and insurance companies, limiting the accessibility of antibody-based drugs. Furthermore, antibodies are critical research tools that enhance the understanding of biology. The technology developed in this research project will provide a completely novel method for the purification of antibodies from cell culture that will lower cost, increase manufacturing throughput, and accelerate the time to market for new therapeutics. Commercially, this technology will disrupt the current gold standard - Protein A resin - making antibody purification simpler, faster, and cheaper at all scales: research, clinical, and industrial. The intellectual merit of this SBIR Phase I project is to develop technology for improved purification of monoclonal antibodies. Although upstream production of antibodies in cell culture has improved dramatically, downstream purification has not kept pace, resulting in a production bottleneck and a major market opportunity. The objectives of this SBIR Phase I project are to demonstrate technical and commercial feasibility of a new technology that combines affinity with liquid-liquid phase separation to separate antibodies from cell culture contaminants. It involves an antibody-binding domain fused to a biopolymer with stimulus responsive phase behavior. When this fusion protein is added to cell culture harvest, it binds the antibody and, after triggering the phase separation with salt, pulls the antibody out of solution. The purified antibody can then be eluted from the fusion by lowering the pH. This project aims to 1) optimize regeneration conditions so that the fusion can be reused, 2) evaluate long-term stability, and 3) validate the technology at scale and conduct a head-to-head comparison to the industry gold standard, Protein A resin. The goal is to identify storage conditions that provide a long shelf life for a product that can be reused 10-100 times without compromising antibody yield or purity. The focus of the project is to demonstrate promising capabilities of the technology for use in industrially manufactured monoclonal antibodies, replacing conventional chromatography steps with a simpler and more cost-effective method. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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JAQ ENERGY LLC
STTR Phase I: Wirelessly Enabled and Distributed Energy Storage Systems Technology
Contact
720 2nd St #134A
Tuscaloosa, AL 35401–0000
NSF Award
1843319 – STTR Phase I
Award amount to date
$250,000
Start / end date
02/01/2019 – 12/31/2020
Abstract
The broader impact/commercial potential of this project includes the development and proof-of-concept prototype demonstration of a new wirelessly-enabled and distributed battery energy storage system technology which can result in significant contributions to wide range of applications that critically depend on energy storage systems and energy availability. These applications include electrification of transportation via Electric Vehicles (EVs) and Electric Aircraft (EA), off-power-grid homes, green homes, and other buildings. This technology seeks to and supports the adoption increase of EVs, EA, and renewable energy sources. As a result, the project contributes to the increase in energy efficiency, the reduction in greenhouse gas emissions and the reduction in the dependence on foreign oil imports. The project enhances scientific and technological understanding by demonstrating the visibility, robustness, and stability of distributed wireless control methods and power electronics architecture for the wirelessly enabled and distributed energy storage system. The results of the project will be used to evaluate and determine the technical and commercial feasibility of the wirelessly enabled and distributed battery energy storage systems. This Small Business Technology Transfer (STTR) Phase I project will focus on conducting research and development tasks that will address key technical challenges that are crucial to successful commercialization of the wirelessly-enabled and distributed energy storage system such as robust and stable controller realization, wireless communication link realization for continuous wireless control, realization of efficient light-weight multi-link wireless power transfer, high-density light-weight power electronics with high-efficiency, and electrical and mechanical integration of the overall system. A proof-of-concept prototype for Electric Vehicles application will also be developed under this project and used for several demonstrations to potential partners, customers, and investors. This proof-of-concept demonstration prototype will be used to demonstrate the feasibility of the system and related desired functionalities such as fast, easy and safe exchange of modules in the system without the need for specialized personnel and distribution 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.
Errata
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JUPITER THERAPEUTICS, INC.
SBIR Phase I: Cell-derived vesicles loaded with novel anti-inflammatories for treatment of severe COVID-19
Contact
11241 WALLINGSFORD ROAD
Los Alamitos, CA 90720–3026
NSF Award
2030602 – SBIR Phase I
Award amount to date
$255,961
Start / end date
09/15/2020 – 08/31/2021
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 a novel treatment option for COVID-19 patients with life-threatening medical complications. Coronavirus infection causes inflammatory reactions leading to acute respiratory distress syndrome, lung and organ failure. This project builds on new methods to generate cell-derived drug delivery vehicles that, when combined with special molecules, specifically target inflamed tissues and modify the disease course. This drug candidate could also impact the outcome of many diseases where runaway inflammation underpins disease pathology, such as emerging viral and/or bacterial threats, neurological conditions such as Alzheimer’s and Parkinson’s disease, stroke and heart attack, autoimmune disease including lupus and arthritis, and various cancers. This Small Business Innovation Research Phase I project uses new technology that harnesses both physical and chemical forces applied to cultured cells to generate cell-derived vesicles. Compared to state-of-the-art techniques, this technology generates vesicles with substantial improvements in product yield, generation rate, and homogeneity, and allows control over vesicle size. Moreover, vesicles can be generated from any cell line to optimize vesicle tropism for specific tissues in the body. When loaded with molecules that induce inflammation-resolution such as resolvins, these vesicles could yield a new treatment. The proposed work will optimize vesicle production, perform vesicle characterization, and develop efficient resolvin-loading procedures. Tissue-specific delivery and functionality in cells and animal models of lung injury will subsequently be assessed. The in vitro assays will measure the ability of vesicles to specifically bind cognate receptors and block neutrophil migration and macrophage production of pro-inflammatory mediators. The disease model will monitor the capacity of resolvin-loaded vesicles to block and reverse inflammation in the lung. This potential triple activity could generate an alternate treatment modality. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Julia Computing Inc
SBIR Phase I: Neural Component Architecture to Accelerate Modeling & Simulation
Contact
20 Garland Rd
Newton Center, MA 02459–1709
NSF Award
1938400 – SBIR Phase I
Award amount to date
$224,676
Start / end date
02/01/2020 – 01/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from enabling significant cost and time savings in developing new, more efficient designs in broad fields such as engineering and healthcare. If successful, the project will enable simulations of everything from automobiles to aerospace components and pharmaceuticals to run up to 100 times faster by representing a physical component of a system with an advanced digital analogue. To date, software incompatibilities have limited the development of this kind of modeling. This project will solve this problem through advanced computational and compiler techniques, and thereby demonstrate the feasibility of a new kind of design process with significant cost reductions. This Small Business Innovation Research Phase I project will demonstrate the feasibility of using neural components in a modular system. We will combine the successes of surrogate model optimization and neural ODEs to allow for component-based differential-algebraic equation models with automated model order reduction through a latent diffeq. The idea is to build complex models as an assembly of modular pre-designed simulation components using our recent advances in differential programming and learning software to allow for automated training of neural model order reduction for accelerating the solution of large acausal models. Two machine learning methods have promising prospects for accelerating traditional mechanistic modeling workflows: surrogate optimization and neural differential equations. In this project, we will integrate these components into 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.
Errata
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Addenda
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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 – 07/31/2021
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.
Errata
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KOYA INC.
SBIR Phase I: Active Smart Wearable Compression Technology for Treating Breast Cancer Related Lymphedema
Contact
357 TEHAMA ST STE 1
San Francisco, CA 94103–4192
NSF Award
2013825 – SBIR Phase I
Award amount to date
$224,957
Start / end date
08/01/2020 – 07/31/2021
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to address needs related to lymphedema. Lymphedema is a common and lifelong side-effect of cancer surgery that occurs from injury or damage to lymphatics, affecting approximately 10 million patients in the US. When it occurs in the extremities, this condition causes swelling that can restrict patient motion, cause discomfort, damage skin, and untreated it can lead to cellulitis, ulceration and infection/hospitalization. Depending on the disease stage, standard treatments include garment wraps, manual drainage/massage, pneumatic compression and complete decongestive therapy. This project will develop an ambulatory compression solution that is programmable, calibrated, and quiet. This Small Business Innovation Research (SBIR) Phase I project supports the development of a next-generation wearable therapeutic platform for treating chronic venous and lymphatic diseases using sequential compression therapy. The project will develop a shape-memory electromechanical actuator platform and system architecture to achieve precise and remote control over compression therapy to stimulate the body’s lymphatic and venous system. The wearable system will comprise of a controller and a segmental garment with multiple, programmable, individualized compression channels. The device will be powered with a lithium-ion battery and microprocessor control integrated in a wearable solution the size of a smartphone and enabled for remote monitoring. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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KRNC INC.
SBIR Phase I: Asymmetric Sybil Resistance via Proof-of-Balance
Contact
1738 BRIDGEPORT AVE
Claremont, CA 91711–2518
NSF Award
2015162 – SBIR Phase I
Award amount to date
$225,000
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is upgrading the public’s existing electronic U.S. dollars to match and exceed the capabilities of private cryptocurrencies. Distributed-ledger technology has the potential to transform every sector of the economy, but today’s blockchains require users to purchase specific assets before sending payments or using related applications. This has delayed mainstream adoption of blockchain technology and raised concerns that a transition to decentralized commerce could threaten the value of savings held in traditional currency. The proposed project will develop a new technology for protected digital transactions. This SBIR Phase I project proposes to develop a decentralized blockchain that will eliminate the need for cryptocurrencies by allowing the owners of U.S. dollars to unlock fiat-derived tokens at zero cost. By adapting recent advancements in biological signaling theory to computer science, the project aims to advance new methods in distributed computing. It will replace symmetric Proof-of-Work and Proof-of-Stake vote-weighing mechanisms with a new technology, Proof-of-Balance, that can deliver significant enhancements to security and performance. The proposed work will explore application of the formal mathematical models by developing and deploying an operational Proof-of-Balance 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.
Errata
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Kaizen Technologies, Inc
SBIR Phase I: Air Quality Analysis by Unmanned Aerial Vehicles
Contact
2339 N. Kildare Ave
Chicago, IL 60639–3655
NSF Award
1842686 – SBIR Phase I
Award amount to date
$224,653
Start / end date
02/01/2019 – 03/31/2021
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be to bring to the market a faster and cheaper means of gathering highly accurate local air quality. This will be done through the use of miniaturization of chemical sensors that are carried by UAVs. Not only will there be technical hurdles that will be overcome through the implementation of this means of gathering data, the use of UAVs in this manner pushes the boundaries of their use in urban areas in a way that has not been done before. The societal and commercial impact will be to reduce cost and time in obtaining air quality at a point in time and space, thereby making air quality measurements less of a financial and technical burden to governments, organizations and corporations. This progress will help ensure that communities can address air quality concerns through the data gathered. This STTR Phase I project proposes to implement a novel means to couple a low-cost technology to detect when chemical components reach a given threshold in the air with the use of Unmanned Aerial Vehicles as a means of delivering the sensors to a specified location. The sensor technology utilizes colorimetric detection of chemicals. Off-the-shelf colorimetric sensors, combined with a unique algorithm, produce color difference maps for toxic industrial chemicals at their permissible exposure level (PEL) concentrations. The objective of the research is to determine if the proposed approach will allow for accurate chemical sensing for a precise location. It is anticipated that the technology to be utilized will allow for an accurate capture of a broad range of pollutants and chemical compounds along with concentration levels. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Kampanics, L.L.C.
STTR Phase I: Development of resonators on high temperature piezoelectric materials for harsh environment sensor and oscillator applications
Contact
7545 Haw Meadows Drive
Kernersville, NC 27284–6700
NSF Award
2014804 – STTR Phase I
Award amount to date
$249,999
Start / end date
05/15/2020 – 04/30/2021
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to address the need for accurate devices capable of operating in extreme environments exceeding 250 °C. Many sensors have key components made of quartz, known for its high sensitivity, accuracy, and stability; but it cannot operate at temperatures exceeding 250 °C. The applications requiring sensitive components operating at these high temperatures include interplanetary spacecraft, nuclear reactors, deep drilling, enhanced geothermal systems, and hypersonic aircrafts and missiles. The proposed project will develop new sensors using advanced material technologies. This Small Business Technology Transfer (STTR) Phase I project aims to develop a novel resonator on piezoelectric materials optimized for performance at high temperature and pressure. The proposed dual-mode resonators are expected to exhibit much higher stability and accuracy. They are also expected to have significantly less need for systemic recalibration. The three main objectives in this project are to optimize the cut angles of the piezoelectric material; develop wafer-level fabrication processes, for size and cost reduction; and to develop a wafer bonding process for eventual wafer-level packaging of the resonators. The effort address translation challenges in device structure, synthesis, modeling and optimization, wafer level fabrication and packaging, to make highly sensitive, accurate, small footprint, low-cost resonators. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Kintsugi Mindful Wellness, Inc.
SBIR Phase I: Scaling Mental Healthcare in COVID-19 with Voice Biomarkers
Contact
2737 Garber Street
Berkeley, CA 94705–1346
NSF Award
2031310 – SBIR Phase I
Award amount to date
$256,000
Start / end date
09/01/2020 – 08/31/2021
This is a COVID-19 award.Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to use voice as a real-time measurement of mental health. Transforming voice intonations into biomarkers could enable disease diagnosis and progression, supporting the $13 B virtual health care sector that was growing 27% annually prior to COVID-19. Furthermore, peer support for mental health increases engagement in self-care decreases substance use and depression, particularly for vulnerable populations. The project will advance the use of machine learning for voice mental health biomarkers in a group setting. This Small Business Innovation Research (SBIR) Phase I project will define voice biomarker features for a deep reinforcement learning based system. This project will advance a voice biomarker technology that can serve as fast behavioral health diagnostic, potentially superseding the current paper-based PHQ-9 and GAD-7 tests. The priority is to scale the optimal mix of individuals and activities for group therapy based on reward functions that maximize improvements in depression and anxiety scores. The major technical challenges include: (1) capturing nonverbal cues in a video; (2) interpreting multi-speaker audio processing; (3) creating deep reinforcement learning models to serve relevant group matches and follow-up exercises; and (4) building engaging visual feedback of progress from group meetings. The anticipated technical result of this innovation will be to define voice biomarker features and reward functions for a deep reinforcement learning based system in clinically relevant settings to improve depression and anxiety treatment outcomes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Errata
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Koliber Biosciences Inc.
SBIR Phase I: Artificial Intelligence Platform for Peptide Drug Discovery
Contact
6760 Top Gun St.
San Diego, CA 92121–4152
NSF Award
2014327 – SBIR Phase I
Award amount to date
$225,000
Start / end date
06/01/2020 – 05/31/2021