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. Provably Unclonable Functions on Re-configurable Devices

    SBC: Potomac Research LLC            Topic: A18BT001

    Physically uncloneable functions (PUFs) have the potential to revolutionize cybersecurity by forming the basis for next-generation secure networks and trusted computing environments. During Phase I, Potomac Research and OSU evaluated of three physically uncloneable function (PUF) designs that can be implemented on COTS FPGAs. One design based on hybrid Boolean networks (HBN-PUFs) emerged as the cl ...

    STTR Phase II 2020 Department of DefenseArmy
  2. Predictive Graph Convolutional Networks

    SBC: METRON INCORPORATED            Topic: N19AT017

    Increased availability of graph-structured military data and recent technical advances in neural network design and training methods has led to an opportunity to advance the state of the art while simultaneously establishing and improving the ability:(1) to monitor a platform or force, (2) to predict capabilities and limitations of the force, and (3) to suggest opportunities and vulnerabilities. ...

    STTR Phase II 2020 Department of DefenseNavy
  3. Multi-Modal Sensing of Sensitization and Stress Corrosion Cracking Susceptibility in AA5xxx Alloys

    SBC: Luna Innovations Incorporated            Topic: N18AT010

    In order to travel faster, travel longer, and carry larger payloads, new Navy ships are being designed with light weight alloys and composite materials. High magnesium AA5xxx series alloys provide a high strength to weight ratio and excellent corrosion resistance, but suffer from sensitization as anodic ß precipitates (Al¬3Mg2) are form along grain boundaries due to a combination of elevated tem ...

    STTR Phase II 2020 Department of DefenseNavy
  4. Machine Learning of Part Variability for Predictive Maintenance

    SBC: EXPERIMENTAL DESIGN & ANALYSIS SOLUTIONS, INC.            Topic: AF20ATCSO1

    High Cycle Fatigue (HCF) characterization and maintenance accounts for a significant portion of the overall life cycle cost of most military propulsion systems.  A key variable that drives HCF margin is dynamic response which is directly related to the geometry of each part.  This is especially true of integrally bladed rotors (IBRs, or blisks).  It has been well established that HCF is a proba ...

    STTR Phase II 2020 Department of DefenseAir Force
  5. Machine Learning of Part Variability for Predictive Maintenance

    SBC: EXPERIMENTAL DESIGN & ANALYSIS SOLUTIONS, INC.            Topic: AF20ATCSO1

    High Cycle Fatigue (HCF) characterization and maintenance accounts for a significant portion of the overall life cycle cost of most military propulsion systems.  A key variable that drives HCF margin is dynamic response which is directly related to the geometry of each part.  This is especially true of integrally bladed rotors (IBRs, or blisks).  It has been well established that HCF is a proba ...

    STTR Phase II 2020 Department of DefenseAir Force
  6. Local Stochastic Prediction for UUV/USV Environmental Awareness

    SBC: APPLIED OCEAN SCIENCES, LLC            Topic: N19AT022

    This project delivers a compact system to assess and reduce local uncertainties that impact routing and sensor operation decisions while tracking the evolution of the maritime environment around unmanned platforms at sea (UUV/USV). The system runs both at control centers and on-board the UUV/USV’s, subject to different network bandwidth and computing environments Size, Weight and Power (SWaP) co ...

    STTR Phase II 2020 Department of DefenseNavy
  7. Laser Surface Modification and Galvanic Protection of 5XXX

    SBC: Luna Innovations Incorporated            Topic: N18AT016

    Exfoliation corrosion of 5XXX series aluminum alloy is an issue related to sensitization of the aluminum substrate wherein internal stresses drive delamination of highly elongated outer layers due to preferential corrosion paths and volumetric expansion. The Navy is interested in preventing this corrosion to decrease lifetime costs on Littoral Combat Ships, Ship-to-Shore Connector vessels, and Tic ...

    STTR Phase II 2020 Department of DefenseNavy
  8. Hot Filament CVD Technology for disruptive, high throughput SiC epitaxial growth reactors

    SBC: TRUENANO INC            Topic: N18AT004

    TrueNano, Inc. will in collaboration with the University of Colorado and industry partners, produce a novel single wafer, high throughput, cold wall Hot Filament CVD (HF-CVD) reactor prototype for the growth of high-quality silicon carbide (SiC) epitaxial layers, suitable for the next generation of power electronic devices and systems. This includes the design and simulation of the reactor chamber ...

    STTR Phase II 2020 Department of DefenseAir Force
  9. Freeze Casting of Tubular Sulfer Tolerant Materials for Solid Oxide Fuel Cells

    SBC: MILLENNITEK LLC            Topic: A14AT011

    Solid oxide fuel cells have long suffered from degradation due to impurities in the fuel and complexities associated with dissimilar materials and high operating temperatures. This degradation lowers the usable cell power output and requires ancillary equipment for fuel sulfur removal and reformation. A unique microstructure for a tubular anode-supported SOFC is being developed using a novel freez ...

    STTR Phase II 2020 Department of DefenseArmy
  10. Detection Rate Improvements Through Understanding and Modeling Ocean Variability--- Phase II-- MP-18-103

    SBC: METRON INCORPORATED            Topic: N18AT002

    Transmission loss (TL) is a key input to the sonar equation for predicting the ability of an active sonar system to detect and track a target of interest. The proposed technical effort centers on developing physics-based models to interpret and predict TL variability. The concept under development consists of a model that consumes modeled and in situ oceanographic information, estimates the likeli ...

    STTR Phase II 2020 Department of DefenseNavy
US Flag An Official Website of the United States Government