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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.

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  1. Crested Tunnel Barriers for Fast, High Density, Nonvolatile Memory Devices

    SBC: ADVANCED FUEL RESEARCH, INC.            Topic: N/A

    Crested multi-layer tunnel barriers have been proposed, which offer a revolutionary solution to overcome density to speed trade-offs characteristic of present data storage technologies. Practical implementation of the proposed technology will involve useof thin film materials which are readily manufacturable and CMOS-compatible. A critical need exists for experimental verification of the theoret ...

    STTR Phase I 2001 Department of DefenseAir Force

  2. Crested Tunnel Barriers for Fast, High Density, Nonvolatile Memory Devices

    SBC: ADVANCED FUEL RESEARCH, INC.            Topic: N/A

    Crested multi-layer tunnel barriers have been proposed, which offer a revolutionary solution to overcome density to speed trade-offs characteristic of present data storage technologies. Practical implementation of the proposed technology will involve useof thin film materials that are readily manufacturable and CMOS-compatible. A critical need exists for experimental verification of the theoreti ...

    STTR Phase II 2003 Department of DefenseAir Force

  3. Storage Efficient Data Mining for High-Speed Data Streams

    SBC: SONALYSTS INC            Topic: N/A

    The Sonalysts Team's goal is to provide a cross-disciplinary, intelligent, efficient stream data mining and intelligent storage system that is highly portable and configurable for the plethora of systems that need to ingest huge data streams and decidewhat, when, where, and how to store data. Leveraging current algorithms, we will apply supervised and unsupervised learning approaches to streaming ...

    STTR Phase I 2003 Department of DefenseAir Force
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