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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Molecular Shape Detection for Chemical Analysis

    SBC: RYON TECHNOLOGIES, INC            Topic: A07T012

    Mass spectrometry is a technology with wide-ranging applications in defense and homeland security. The technique is widely applicable and exceedingly sensitive, but for many molecules there can be ambiguities regarding the isomeric and conformeric form. As the number of atoms in a molecule increases, the number of stable isomers raises dramatically. Recent research has shown that the binding en ...

    STTR Phase I 2007 Department of DefenseArmy
  2. Environmental Sensor for Autonomous UAVS

    SBC: ANASPHERE, INC            Topic: A07003

    Improved observations of the battlespace are of key and growing importance in today’s combat environment. UAVs are making key contributions in this area, and sensor improvements are a key part of increasing UAV capabilities. However, all sensors are subject to degradation under detrimental environmental conditions. Adding a sensor system to UAVs that enables the in-situ identification and qua ...

    SBIR Phase I 2007 Department of DefenseArmy
  3. Learning-Based Source Separation Methodologies Applicable to the Multiple Target Problem

    SBC: Coprime            Topic: N/A

    "Coprime proposes to investigate the applicability of learning-based source separation methodologies to the problem of multiple targets in a complex acoustic environment. The Phase I effort will focus on identifying viable learning-based source separationalgorithms specifically tuned to the multiple combat vehicle scenario. A prototype architecture will be developed and numerical software rapidly ...

    SBIR Phase I 2002 Department of DefenseArmy
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