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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  2. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  3. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  4. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  5. STTR Phase I: Development and Validation of Low-Cost Natural Gas Leak Detection Sensors and Analytics for Drone-Based and Handheld Deployments

    SBC: Nikira Labs Inc.            Topic: CT

    The broader impact/commercial potential of this project is the rapid, cost-effective detection of natural gas leakage to improve public safety, mitigate global climate change, and decrease product loss. Natural gas is the largest provider of power in the United States. However, more than 80 Tg of leakage occurs at well pads and pipelines during production alone. Such leakage poses a public health ...

    STTR Phase I 2018 National Science Foundation
  6. STTR Phase I: Rational design of highly sensitive and selective chemical sensors using structural color

    SBC: DrinkSavvy, Inc.            Topic: BT

    The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project will be the development of sensor-embedded "smart" drinkware (i.e., stirrers, straws and cups) to actively alert consumers prior to consumption of a "spiked" beverage, and thus provide a proactive way to prevent drug-facilitated sexual assault. This sensor technology is based on "smart" molecularly im ...

    STTR Phase I 2018 National Science Foundation
  7. STTR Phase I: Engineering Alternative Oxidation Activity in A. ferrooxidans For Enhanced Biohydrometallurgy Capabilities

    SBC: Ironic Chemicals LLC            Topic: BT

    The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project will be to develop engineered bacteria with the ability to oxidize the copper mineral chalcopyrite and gold. The majority of copper reserves are in chalcopyrite, which currently requires smelting. The US copper mining industry, due to regulatory restrictions, has a limited smelting capacity forcing US ...

    STTR Phase I 2018 National Science Foundation
  8. STTR Phase II: Autonomous Landing of Small Unmanned Aircraft Systems onto Moving Platforms

    SBC: PLANCK AEROSYSTEMS INC.            Topic: EW

    The broader impact/commercial potential of this project will enable Unmanned Aerial Systems (UAS or drones) to safely and reliably operate from moving vehicles and moving vessels at sea. There is an immediate need for this capability in many industries. In commercial fishing, drones will replace manned aircraft for fish-finding operations, radically reducing cost and risk. In maritime security, dr ...

    STTR Phase II 2018 National Science Foundation
  9. STTR Phase II: Nanostraw-mediated Immune Cell Reprogramming

    SBC: Navan Technologies, Inc.            Topic: BT

    The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project will be to develop a new tool to safely and nondestructively deliver genes and other materials into large numbers cells at the same time. New forms of therapies for cancer and other intractable diseases take advantage of a patient's own cells, re-engineered in the laboratory to target a tumor ...

    STTR Phase II 2018 National Science Foundation
  10. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
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