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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Ultra-Wideband, Low-Power Compound Semiconductor Electro-optic Modulator

    SBC: Freedom Photonics LLC            Topic: N13AT005

    Freedom Photonics is proposing to develop a novel modulator concept. The overall objective of this program is to develop a novel compound-semiconductor electro-optic modulator that simultaneously exhibits 100-GHz operation, optical/microwave velocity matc

    STTR Phase II 2015 Department of DefenseNavy
  2. 100GBit/s Nanowire Low Drive Voltage Modulator

    SBC: Freedom Photonics LLC            Topic: N13AT005

    In this Phase II Small Business Innovation Research project we will be developing extremely efficient (40G), and compact modulators suitable for microwave analog links, next generation radar and other military applications. III-V semiconductor nanowires a

    STTR Phase II 2015 Department of DefenseNavy
  3. LCS Radar Modeling for Training (LRMT)

    SBC: Intelligent Automation, Inc.            Topic: N14AT012

    We propose the design and development of LCS radar modeling for training a radar modeling engine that capture the effects of environment, weather, jamming/interference and operator actions on radar display. The purpose of this engine is to reduce or eli

    STTR Phase I 2015 Department of DefenseNavy
  4. LEARNING-BASED APPROACH FOR RELEVANT DATA EXTRACTION (LARDE)

    SBC: ROBOTIC RESEARCH OPCO LLC            Topic: N13AT016

    Robotic Research, LLC (RR) and Southwest Research Institute (SwRI) are creating a prototype Learning-based Approach for Relevant Data Extraction (LARDE). The LARDE framework is a data extraction and handling framework that can intelligently reduce the volume of raw data from on-board sensors, and organize and persistently store the reduced relevant dataset.

    STTR Phase II 2015 Department of DefenseNavy
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