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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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. Fully Metallic Self-Fragmenting Structural Reactive Materials Using Composites and Alloys Comprised of Aluminum, Lithium, and Magnesium

    SBC: Adranos Energetics LLC            Topic: DTRA16A002

    While aluminum casing materials provide some enhanced performance and thermal loading to explosive ordinance, their overall effectiveness is highly limited by incomplete combustion and long residence times. In order to reduce these problems, the casing material must be designed to facilitate rapid fragmentation through either specialized casing geometries or greatly refined initial particle sizes. ...

    STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency
  2. Multimode Organic Scintillators for Neutron/Gamma Detection

    SBC: Radiation Monitoring Devices, Inc.            Topic: DTRA19B003

    There is significant interest in multi-functional materials enabling gamma-ray spectroscopy, neutron/gamma pulse shape discrimination (PSD), ultra-fast response, and time-of-flight (TOF) neutron detection. These materials would be used in a variety of mission scenarios for the localization and monitoring of special nuclear materials. Commercial inorganic scintillators offer some of these character ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  3. Semantic Models for the Identification of Laboratory Equipment (SMILE)

    SBC: Charles River Analytics, Inc.            Topic: DTRA19B002

    Military operators must identify and catalogue the equipment they find when inspecting laboratory facilities. This information is used to determine the lab’s capabilities, including the lab’s potential for building weapons of mass destruction. Currently, operators use computer vision algorithms to help them classify equipment in pictures of laboratory environments. Unfortunately, current image ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
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