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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. Prognostic Capabilities for Field Effect Transistors (FET)

    SBC: RIDGETOP GROUP INC            Topic: N06007

    Shrinking semiconductor process geometries (130 nm and below) are increasingly subject to performance, lifetime, and reliability-limiting effects that can cause hard-to-diagnose intermittent failures. One of the most serious emerging reliability problems is called Negative Bias Temperature Instability (NBTI). NBTI is a p-MOSFET degradation mechanism that causes increasing threshold voltage (VT) ...

    SBIR Phase II 2007 Department of DefenseNavy
  2. Prognostic for Process-Related Integrated Circuits (IC)

    SBC: RIDGETOP GROUP INC            Topic: N06006

    This SBIR is to design, develop, fabricate and package a suite of Integrated Circuit (IC) sensors as an IC chip. The chip, referred to as IC Prognostics chip, will contain four groups of sensors to sense damage to the “canary” devices on the IC chip: a damaged canary indicates a high probability of similar damage to like devices on an electronic assembly. There are three variations of IC Pr ...

    SBIR Phase II 2007 Department of DefenseNavy
  3. Prognostics and Health Management (PHM) for Digital Electronics Using Existing Parameters and Measurands

    SBC: RIDGETOP GROUP INC            Topic: N05093

    With its SBIR Partners Boeing, University of Tennessee and HRL Laboratories, Ridgetop develops novel techniques to determine system State-of-Health, and predicting failures in Digital Processors before they occur, and develop improved Remaining Useful Life (RUL) predictions. This will employ the use of existing measurands and operands. Current Area Prognostic Health Management (PHM) Managers and A ...

    SBIR Phase II 2007 Department of DefenseNavy
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