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 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. Improving Analysis of Large Multidimensional Data through Parallel Processing & Explorative Visualization

    SBC: Frontier Technology Inc.            Topic: MDA18T001

    Using a combination of parallel processing and explorative visualization, a new and exciting solution for high-performance visual analysis of large multidimensional data is proposed. Steady volume flows are selected to demonstrate the strategy, methodology, techniques, and functionalities. Virtual Reality (VR) and Augmented Reality (AR) platforms will be adopted to unleash the power of explorative ...

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  2. Storable Clean Ethane/ethylene Nitrous Engine (SCENE)

    SBC: PIONEER ASTRONAUTICS            Topic: MDA18T005

    he Storable Clean Ethane-ethylene Nitrous Engine (SCENE) is a proposed technology designed to provide upper stages and spacecraft with non-toxic, liquid, non-cryogenic, high-performance propulsion with an Isp on the order of 300 seconds. The propellant components are stored as liquids under their saturated vapor pressures. With the SCENE, nitrous oxide is used as an autogenously pressurized oxidiz ...

    STTR Phase I 2019 Department of DefenseMissile Defense Agency
  3. Multi-Physics Analysis Tool for High-Energy Gas Lasers

    SBC: Material Flow Solutions, Inc.            Topic: MDA16T001

    Based on the results of our Phase I work, one significant barrier to optimizing battery performance lies in understanding the relationship between bulk solids and particle flow properties and the flow into the die. Our hypothesis: an increase in quality batteries production can be achieved if powder preparation process can be optimized and the die filling process controlled. We feel that control o ...

    STTR Phase II 2019 Department of DefenseMissile Defense Agency
  4. Innovative Methodologies for Manufacturing of Lethality Test Articles

    SBC: MRL MATERIALS RESOURCES LLC            Topic: MDA17T001

    Metallic additive manufacturing (AM) is an attractive technology for the production of lethality test articles due to the potential for significantly reduced lead time and manufacturing cost. However, in order to be effective in providing accurate lethality data, the properties of the AM material have to match closely the properties of conventionally manufactured alloys found in real threat target ...

    STTR Phase II 2019 Department of DefenseMissile Defense Agency
  5. TRACE – Target Recognition with the Assistance of Artificial Intelligence

    SBC: Intelligent Automation, Inc.            Topic: N18BT033

    Intelligent Automation Inc. (IAI) proposes the design and implementation of the Target Recognition with the Assistance of Artificial Intelligence (TRACE) system that incorporates classical model-based target classification and identification approaches with data-driven machine learning solutions to improve the target classification accuracy. The outcome of the TRACE systems is a set of machine lea ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Comprehensive Surf Zone Modeling Tool

    SBC: Dynamic Dimension Technologies, LLC            Topic: N19AT010

    The littoral and specifically surf zone regions with breaking waves, bathymetry, weather, currents, tides, obstacles, etc. create a dynamic environment that can be very challenging for conducting operations. Systems are being developed to increase situational awareness in this region, however expensive physical testing to verify performance is limited to specific areas and conditions. To supplemen ...

    STTR Phase I 2019 Department of DefenseNavy
  7. High Speed Spinning Scroll Expander (HiSSSE)- Organic Rankine Cycle for Increased Naval Ship Power Density and Fuel Efficiency

    SBC: Air Squared, Inc.            Topic: N19AT013

    Waste heat from Naval diesel generators provides significant opportunity to introduce organic Rankine cycles (ORC) to increase their fuel efficiency. The objective of the proposed effort is to design and demonstrate a high-speed, spinning scroll expander (HiSSSE) ORC as a power dense waste heat recovery system for diesel generators on ships. The system will leverage Air Squared’s spinning scroll ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Measuring Manipulation in Audiences Targeted by Coordinated Social Media Dissemination Tactics

    SBC: Intelligent Automation, Inc.            Topic: N19AT024

    The information environment has become a new battlefield for adversaries of the United States and its allies. Coordinated campaigns have been waged to radicalize, incite division, inflame, influence elections and public opinion on a variety of issues. These campaigns have weaponized social media by forming networks of synthetic accounts (botnets) which spread mis/disinformation, polarize groups an ...

    STTR Phase I 2019 Department of DefenseNavy
  9. REVAMP: REcommendation, Verification, and Analysis for Mission Planning

    SBC: Intelligent Automation, Inc.            Topic: N19BT029

    Effective and efficient data-driven mission support is crucial for achieving readiness and superiority in warfighting enterprises. Leveraging machine learning (ML) and artificial intelligence (AI) in mission planning would not only minimize the human-error factors and increase accuracy, but also improve speed in planning, execution, and evaluation of a mission. REVAMP will improve the next generat ...

    STTR Phase I 2019 Department of DefenseNavy
  10. SLACA: Self-Learned Agents for Collective Aerial Video Analysis

    SBC: Intelligent Automation, Inc.            Topic: AF18BT002

    For this STTR Intelligent Automation, Inc. teams with researchers from University of Maryland, College Park to develop SLA, a self-learned agent system for collective human activities and events in aerial videos. Aerial video analytics often faces challenges such as low resolution, shadows, varied spatio-temporal dynamics, etc. The traditional methods depending on the object detection and tracking ...

    STTR Phase I 2019 Department of DefenseAir Force
US Flag An Official Website of the United States Government