You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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. Protocol Feature Identification and Removal

    SBC: P & J ROBINSON CORP            Topic: N18AT018

    Protocols used for communication suffer bloat from a variety of sources, such as support for legacy features or rarely used (and unnecessary) functionality. Traditionally, the Navy subscribes to a blanket adoption of a standard protocol "as is". Unnecessary features are active and can be accessed by both internal and external systems creating security vulnerabilities. PJR Corporation's (PJR's) Pha ...

    STTR Phase II 2019 Department of DefenseNavy
  2. Recovery of Rhenium from Superalloy Scrap

    SBC: LYNNTECH INC            Topic: OSD12T04

    Due to the limited amount of rhenium present in the earths crust (approximately 1-2 part per billion) there is a significant benefit to be realized in recovering for reuse the rhenium from scrap material, spent catalysts, or end-of-life superalloys. Rhenium is found in molybdenum-copper porphyry deposits. If rhenium is present in ore that is processed, it will show up in the resulting molybdenum ...

    STTR Phase II 2015 Department of DefenseOffice of the Secretary of Defense
  3. ARCHIMEDES

    SBC: SOAR TECHNOLOGY INC            Topic: N17AT004

    Evidence-based guidelines derived from the learning sciences literature can be applied to training-requirements decisions. However, accessing the state-of-the-art in the learning sciences and applying its lessons to specific training design and analysis questions can be difficult, especially for those not already familiar with the learning sciences. ARCHIMEDES, the software tool proposed in this e ...

    STTR Phase II 2019 Department of DefenseNavy
  4. Soliloquy Ph II

    SBC: SOAR TECHNOLOGY INC            Topic: N17AT010

    Automatic Speech Recognition (ASR) allows trainees to practice verbal communication skills in representative training environments without the need for human role players. However, these technologies have yet to become a feature of most training systems. Building on Phase I work, SoarTech along with our academic partners at UC Davis, proposes developing Soliloquy, a novel interface that allows non ...

    STTR Phase II 2019 Department of DefenseNavy
  5. Advanced Optically-driven Spin Precession Magnetometer for ASW

    SBC: POLATOMIC, INC.            Topic: N04T002

    This SBIR Phase II proposal describes the development of a breadboard Advanced Optically-driven Spin Precession Magnetometer (AOSPM), an ultra high-sensitivity scalar laser magnetometer for airborne ASW. The AOSPM is an innovative high-sensitivity instrument capable of measuring scalar DC and ELF magnetic fields with a sensitivity better than 10.0 fT/root-Hz. Since the high sensitivity AOSPM is a ...

    STTR Phase II 2006 Department of DefenseNavy
  6. Full Featured Low-Cost HMS for Combatant Craft

    SBC: QUALTECH SYSTEMS INC            Topic: N18AT015

    Qualtech Systems, Inc. (QSI), in collaboration with Vanderbilt University (VU) proposes to develop a state-of-the art Health Management System (HMS) system consisting of a small form factor GPS-enabled onboard computer, a small display for crew, and sensors for boat and engine vibration, OBD data, engine oil quality monitoring, and battery health monitoring. The HMS system will provide Wi-Fi and w ...

    STTR Phase II 2019 Department of DefenseNavy
  7. A Multiscale Modeling and Simulation Framework for Predicting After-Burning Effects from Non-Ideal Explosives

    SBC: REACTION ENGINEERING INTERNATIONAL            Topic: N10AT002

    The objective of the proposed Phase II STTR effort is to develop a validated computational tool to predict the afterburning of non-ideal munitions containing metal and hydrocarbon fuels. The activities outlined devise a well-coordinated collaboration among researchers from Reaction Engineering International (REI) and the State University of New York at Buffalo (UB). The activities proposed will bu ...

    STTR Phase II 2015 Department of DefenseNavy
  8. Additive Manufacturing for Naval Aviation Battery Applications

    SBC: Texas Research Institute, Austin, Inc.            Topic: N18AT008

    Texas Research Austin (TRI-Austin) will continue to partner with the University of Texas, Austin, to use additive manufacturing for fabricating and optimizing the lithium ion and electroactive metal electrode systems for which the team established proof of concept in the Phase I base period. The Aerosol Deposition Method (ADM) is a broadly applicable additive manufacturing technology that has been ...

    STTR Phase II 2019 Department of DefenseNavy
  9. Integrated learning-based and regularization-based super resolution for extreme MWIR image enhancement

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: N17AT016

    OKSI and Northwestern University propose to develop a single-image super-resolution (SR) methodology for mid-wave infrared (MWIR) imagery that combines learning-based and regularization-based approaches to produce extreme enhancement of low-resolution images. We will also develop a detector-limited imaging system specifically designed to be used with the SR methodology for which even higher levels ...

    STTR Phase II 2019 Department of DefenseNavy
  10. Cognitive Adaptation and Mission Optimization (CAMO) for Autonomous Teams of UAS Platforms

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: N17BT035

    The Navy needs cognitive control capabilities that enable an autonomous robotic team comprised of a ground control station node and a team of UAS platforms to operate independently (or with minimal human oversight) while carrying out complex missions. A cognitive control capability needs to be developed that concurrently optimizes the balance of mission risk / performance with respect to the Navyâ ...

    STTR Phase II 2019 Department of DefenseNavy
US Flag An Official Website of the United States Government