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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. 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
  2. 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
  3. 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
  4. 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
  5. Quantum Algorithms for Advanced Antenna Technologies

    SBC: Semicyber, LLC            Topic: AF19BT001

    Our product solution is a quantum algorithm-based electromagnetic modeling and simulation software package to run on classical computers and quantum simulators and computers.

    STTR Phase II 2020 Department of DefenseAir Force
  6. Self-Calibrating, Conformal Nanomembrane based Pressure Sensors for Embedded Sensing Applications

    SBC: NANOSONIC INC.            Topic: AF18AT002

    This DOD Phase II STTR program would develop self-calibrating, conformal nanomembrane based pressure sensors for embedded sensing applications, using silicon on insulator techniques in combination with our pioneering nanocomposite materials. Such low-modulus, conformal nanomembrane sensor skins with integrated self-calibration, interconnect elements and electronic devices can be applied to new or ...

    STTR Phase II 2020 Department of DefenseAir Force
  7. Stable High Bandwidth AO Control with physical DM constraints

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT008

    Adaptive optics (AO) can compensate for the aberrating effects of atmospheric turbulence which degrade the performance of high energy laser (HEL) weapon systems and, as such, is an enabling technology for effective deployment of HEL weapon systems. A key component in an HEL AO system is the deformable mirror (DM). However, mechanical constraints in currently available DMs limits AO system performa ...

    STTR Phase II 2020 Department of DefenseAir Force
  8. Stable High Bandwidth AO Control with physical DM constraints

    SBC: Guidestar Optical Systems, Inc.            Topic: AF18AT008

    Adaptive optics (AO) can compensate for the aberrating effects of atmospheric turbulence which degrade the performance of high energy laser (HEL) weapon systems and, as such, is an enabling technology for effective deployment of HEL weapon systems. A key component in an HEL AO system is the deformable mirror (DM). However, mechanical constraints in currently available DMs limits AO system performa ...

    STTR Phase II 2020 Department of DefenseAir Force
  9. Systematic Fatigue Test Spectrum Editing Using Wavelet Transformations

    SBC: TECHNICAL DATA ANALYSIS, INC.            Topic: N18BT029

    Our Phase I effort showed that spectrum compression could be successfully achieved via Wavelet Transform (WT) based Fatigue Spectrum Editing (FSE) techniques for uniaxial HCF spectra cases. For example, 85% reduction in spectrum length can be achieved in the case of the original FELIX spectrum. However, the extension of the same FSE technique to multi-axial HCF cases showed less desirable results ...

    STTR Phase II 2020 Department of DefenseNavy
  10. Terahertz cyber security testing using artificial intelligence

    SBC: Electronics of the future, Inc..            Topic: AF19BT001

    The goal this work is to use AI to interpret the THz and sub-THz responses at the pins to the defects and deviations from design of the integrated circuits under test. The key application is work is identifying hardware security treats using artificial intelligence (AI) for cyber security applications. Our approach will provide a rapid, inexpensive, and non-destructive technology address this prob ...

    STTR Phase II 2020 Department of DefenseAir Force
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