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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. High Power Density Dual Rotor Permanent Magnet Motor with Integrated Cooling and Drive for Aircraft Propulsion

    SBC: Advanced Magnet Lab, Inc.            Topic: 1

    There is a critical need for electrification of transportation systems. The proposed technology enables the development of very high-power density permanent magnet motors, which when coupled to an integrated SiC drive allows for an overall specific power beyond 12 kW/kg. The proposed concept relies on the tight integration of a high-power density dual-rotor permanent magnet motor, high power densi ...

    STTR Phase I 2020 Department of EnergyARPA-E
  2. Circulating Diagnostic Markers of Infectious Disease

    SBC: PATHOVACS INCORPORATED            Topic: CBD18A001

    The focus of this STTR phase I component is on proof-of-concept studies demonstrating applicability of technical approaches for identificationof circulatory diagnostic markers for infectious disease. Therefore, the primary objective of this project is to determine feasibility of one suchtechnical approach called Proteomics-based Expression Library Screening (PELS), for identification of pathogen-d ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  3. Algorithms for Look-down Infrared Target Exploitation

    SBC: Signature Research, Inc.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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