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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. 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
  2. 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
  3. Recommendation Technology for Digital Engineering Artifacts

    SBC: NOU SYSTEMS INC            Topic: MDA22T002

    Utilizing our current applications and data models supporting the MDS digital test planning and anlaysis ecosystem (currently deployed to MDA's EWS system), the nSI team will develop methods for artifact recommendations for system engineering data to aid MDS personnel in finding data relevant to their tasks. The team will extend our current data model (currently supporting the digital M&S) and tag ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  4. Deep Reinforcement Learning (DRL) Enabled Warfighter Assistant

    SBC: NOU SYSTEMS INC            Topic: MDA22T004

    State spaces are enormous, the operation is real time, the outcomes are uncertain, the consequences of suboptimal actions are dire. The BMDS is a carefully crafted system with many moving parts. As with all complicated systems, there are many tradeoffs to make when operating them. In a world with finite resources, decisions on how to allocate interceptors during a raid could be the difference betw ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  5. 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
  6. 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
  7. Quantum Material Design

    SBC: QUOHERENT, INC.            Topic: MDA22T007

    Computational Materials Design offers a potential alternative to trial-and-error experimentation in the quest for improved materials. Under this paradigm materials design is driven by input requirements – the desired properties of the material – and result in the output of one or more potential material formulations that can provide the desired properties. The use of relationships between mate ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  8. Deep Reinforcement Learning (DRL) Enabled Warfighter Assistant

    SBC: TOYON RESEARCH CORPORATION            Topic: MDA22T004

    The U.S. missile defense system (MDS) includes various assets located at sea, on land, and in space that provide global coverage against missile threats to the U.S. and its allies. Elements of the MDS create a layered defense capability providing detection, tracking, discrimination, and intercept capabilities against missile threats. As the MDS and its elements continue to grow and evolve to keep ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  9. High-Resolution Modeling of Plume Exhaust Shock-Boundary Layer Interactions

    SBC: QUADRUS ADVANCED MANUFACTURING LLC            Topic: MDA22T005

    A thruster jet emerging laterally from a missile surface into a hypersonic external crossflow produces a complex environment which poses a significant effect on the vehicle control. A good understanding of the phenomenon can be achieved only with highly accurate physics computations. Our innovation offers to greatly enhance prediction qualities in a high-performance framework. This effort will be ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  10. Methodologies to Develop Radiation Testing Environments for Survivable Microelectronics

    SBC: INNOSYS, INC.            Topic: MDA21T001

    We will investigate the radiation effects on microelectronics due to gamma-rays and beta-rays and compare the effects on electrical and material properties between the two radiation types to formulate a quantitative mapping of radiation types (gamma and beta) and effects. The purpose is to: 1) Develop an overall physics-based strategy; 2) Define the experimental design, guided by analytical calcul ...

    STTR Phase I 2022 Department of DefenseMissile Defense Agency
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