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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. Quantifying Uncertainty in the Mechanical Performance of Additively Manufactured Parts Due to Material and Process Variation

    SBC: TECHNICAL DATA ANALYSIS, INC.            Topic: N16AT004

    TDA has teamed up with Lawrence Livermore National Laboratory as its research institution collaborator to address the target STTR topic objective of quantifying the uncertainties in the mechanical behavior of the AM parts. To quantify uncertainties by minimizing both the computational burden and expensive testing and also overcoming the IP concerns, we propose a novel approach with three layered i ...

    STTR Phase I 2016 Department of DefenseNavy
  2. Microstructure Informatics for Propagating Uncertainty in Material and Processing to Performance Predictions of AM Titanium Parts

    SBC: MRL MATERIALS RESOURCES LLC            Topic: N16AT004

    During AM of metallic alloys, a material exhibits several complex physical phenomena that impact the spatial distribution of heterogeneous material properties within a built component. Subsequent post-processing alters the already heterogeneous location-specific material properties. This project is to develop a novel methodology for linking the time and length scales of the various physical phenom ...

    STTR Phase I 2016 Department of DefenseNavy
  3. Advanced, nanostructred low-friction coatings for foil air bearings

    SBC: MesoCoat            Topic: N16AT005

    During Phase I, we propose to develop nanostructured, low friction thermal sprayed coatings that are able to withstand high dynamic loadings. Additionally, the novel coatings will possess a low friction coefficients in humid air, dried conditions and various greases and lubricants. These novel nanostructured coatings will be manufactured by HVOF spraying of solid lubricants based nanostructured po ...

    STTR Phase I 2016 Department of DefenseNavy
  4. Novel Separator Materials for Achieving High Energy/Power Density, Safe, Long-Lasting Lithium-ion Batteries for Navy Aircraft Applications.

    SBC: OCEANIT LABORATORIES INC            Topic: N16AT008

    Oceanit proposes to develop and demonstrate novel, tailored, designer separator materials with optimized properties to maximize lithium-ion cell/battery performance, life, safety and reliability.

    STTR Phase I 2016 Department of DefenseNavy
  5. Medium Voltage Direct Current (MVDC) Fault Detection, Localization, and Isolation

    SBC: IAP RESEARCH, INC.            Topic: N16AT009

    In this phase I we propose to extend our work on MVDC isolation device to include fault detection, and fault localization circuitry. We have previously developed under an SBIR a 6 kVDC, 2000A isolation device that was built and tested in MVDC ship distribution system laboratory at FSU CAPS. In this phase I we propose to use rogowski coils and hall effect probes to detect faults and we propose to a ...

    STTR Phase I 2016 Department of DefenseNavy
  6. Medium Voltage Direct Current (MVDC) Grounding System

    SBC: HEPBURN AND SONS LLC            Topic: N16AT012

    Hepburn and Sons LLC teamed with Florida State University (FSU) Center for Advanced Power Systems (CAPS) propose to develop an affordable, general method for grounding Medium Voltage Direct Current (MVDC) zonal electrical power systems for naval warships. The grounding system concept developed in Phase I will evaluate the incorporation of electric weapons and high power sensors while accounting fo ...

    STTR Phase I 2016 Department of DefenseNavy
  7. Forensic Integrated Security Toolkit

    SBC: MISSION SECURE INC            Topic: N16AT013

    Cyber security forensic functions depend on highly structured conformance to log formats for generation and transmission capabilities including identity, network time stamps and event message formats. Without this structure there is no effective way to reconstruct the time sequencing patterns that reveal the presence of unauthorized actions and actors inside of a network. Limitations in the capaci ...

    STTR Phase I 2016 Department of DefenseNavy
  8. Low-cost Thermal Management Technology for Combat Systems Computers

    SBC: Engineering And Scientific Innovations Inc.            Topic: N16AT014

    Using a fluid dynamic energy separation technique, in combination with thermoelectric generators (TEGs), a unique hybrid cooling system using low grade waste heat is proposed. This system uses the concept of fluid structure interactions and vorticity redistribution to produce large levels of vorticity within working fluid and thereby generate large temperature gradients in the working fluid which ...

    STTR Phase I 2016 Department of DefenseNavy
  9. Thermal Barrier Coatings for Long Life in Marine Gas Turbine Engines

    SBC: Directed Vapor Technologies International, Inc.            Topic: N16AT019

    The marine environment is extremely corrosive to turbine engine components due to the large amount of salts from the sea coupled with the fuel impurities and the high temperatures experienced. To cope with future operational requirements, a strong need exists to develop novel, protective coatings to provide environmental protection from hot corrosion and oxidation conditions across a wide range of ...

    STTR Phase I 2016 Department of DefenseNavy
  10. SCOUT: Smart Communication Of Unexpected Threats

    SBC: Commonwealth Computer Research Inc            Topic: N16AT020

    The Navy needs to fuse and distill time-stamped data sources as varied as overhead imagery and Twitter feeds into actionable intelligence such as alerts, on-demand reports about entities of interest, and search capabilities. In order to enable such analytics, it is effective to learn fixed dimensional vectors (embeddings) representing the entities present in these heterogeneous data sources, which ...

    STTR Phase I 2016 Department of DefenseNavy
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