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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. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: KRTKL INC.            Topic: SOCOM23B001

    krtkl (“critical”) will conduct a Phase I Feasibility Study to identify the best approach for reducing aviator cognitive load by optimizing information delivery and decision-making based on a thorough analysis of existing platforms, sensors, data sources, and onboard compute resources. This information will be used to identify Artificial Intelligence and Machine Learning based algorithms for p ...

    STTR Phase I 2023 Department of DefenseSpecial Operations Command
  2. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: PARRY LABS, LLC            Topic: SOCOM23B001

    Existing airborne defense systems integrate a wide variety of sensors necessary to provide operators with situational awareness across the visual, thermal, signals, and electromagnetic spectrums. To date, individual sensor systems have been largely stove-piped, as have Artificial Intelligence/Machine Learning (AI/ML) and advanced, Size, Weight, and Power (SWaP)-optimized data processing systems. T ...

    STTR Phase I 2023 Department of DefenseSpecial Operations Command
  3. Hypersonic Seeker Window Attachment for Hypersonic Flight Systems

    SBC: FIRST RF CORPORATION            Topic: MDA22T011

    The harsh environment posed by hypersonic flight makes antenna design challenging due to extreme temperature exposure coupled with often competing mechanical/aero and RF performance requirements. FIRST RF proposes an advancement to its numerous conformal antenna technologies utilizing additive manufacturing of dielectric materials. This approach will decouple the competing RF and mechanical requir ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  4. Additive Manufacturing of Structural Insulators

    SBC: ADVANCED CERAMICS MANUFACTURING, LLC            Topic: MDA22T012

    There is a need for a lightweight, high-performance, insulation to protect the internal systems in hypersonic vehicles. A passive thermal protection system (TPS) design would be simple and reliable. As designs evolve, there is a need for TPS insulation materials that can be additively manufactured. Our Phase I approach will additively manufacture pre-ceramic scaffolds that are used to create low d ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  5. Low-Cost In-Situ Rapidly Carbonized Carbon-Carbon Composite Material

    SBC: EOS ENERGETICS, INC.            Topic: MDA22T013

    Estes Energetics and Battelle Memorial Institute will apply a fast, affordable manufacturing technology—proven to Technology Readiness Level (TRL) 4 and Manufacturing Readiness Level (MRL) 4—that manufactures a layer of carbon-carbon directly on composite structures without requiring use of an autoclave or densification process holds, resulting in reduced manufacturing time while improving com ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  6. Low Cost Carbon-Carbon Development for Hypersonic Flight Systems

    SBC: M4 ENGINEERING, INC.            Topic: MDA22T013

    The innovation proposed here is a novel carbon-carbon composite (CCC) manufacturing method based on polymer infusion and polymerization (PIP) using a novel precursor polymer with exceptionally high char yields. This results in a material that has the promise of excellent quality and mechanical properties, while offering the breakthrough advantages of (1) greatly reduced or eliminated need for back ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  7. Paratemporal Simulation with Uncertainty Quantification

    SBC: WARPIV TECHNOLOGIES, INC.            Topic: MDA22T001

    This topic identifies the need creating a Modeling and Simulation (M&S) development and execution environment that significantly decreases the time to execute statistically significant batches of stochastic simulation runs for the purpose of estimating scenario output and outcome distributions while improving statistical knowledge of the outcome distributions. The strategy sought by this topic is ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  8. Reactive Jet Interactions with Multifidelity Turbulence and Tailored Finite-Rate Combustion Modeling

    SBC: ATA ENGINEERING, INC.            Topic: MDA22T005

    To advance simulation techniques, such as high-fidelity computational fluid dynamics (CFD), to accelerate maturation of DACS design through design-time trade studies, there is a need for new, test-validated models that improve both computational performance and the accuracy of the reacting jet in hypersonic crossflow simulations. ATA and CUBRC (a research institution with leading expertise in aero ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  9. Paratemporal Simulation with Uncertainty Quantification

    SBC: RTSYNC CORP            Topic: MDA22T001

    We propose to develop Para-DEVS, an extension of the existing modeling and simulation (M&S) environment overcome two major hurdles that must be overcome to implement paratemporal simulation techniques for application to execution of large stochastic models. We propose to develop techniques to achieve scalability, the ability to overcome the combinatorial explosion of branching arising from multipl ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  10. Artificial Intelligence-based Recommender for Model-Based Systems Engineering (ARMS)

    SBC: NEXCEPTA INC            Topic: MDA22T002

    There is a critical need for innovative recommendation technology for digital data engineering artifacts and tools. To address this need, we propose design and implement the Artificial Intelligence-based Recommender System for Model-Based Systems Engineering (ARMS) software as a user-personalized context-aware content recommender system solution for Model Based Systems Engineering (MBSE) applicati ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
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