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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. Data-driven RANS Turbulence Modeling Approach for Hypersonic Vehicles

    SBC: CORVID TECHNOLOGIES, LLC            Topic: N22AT016

    Corvid and NCSU, with the support of Leidos, will develop a machine learning-based framework to enhance RANS turbulence modeling at hypersonic conditions. We will start with the interrogation of existing LES databases from NCSU for model form identification and initial training, followed by a closed-loop iterative calibration procedure that will incorporate experimental data to further refine the ...

    STTR Phase I 2022 Department of DefenseNavy
  2. Rapid Personal Protective Equipment Simulation Environment (RAP-SIM)

    SBC: S.A.R. HUMAN PERFORMANCE, LLC            Topic: N22AT017

    Human-centric physics-based models are a key component in the design and analysis of personal protective equipment (PPE) for both commercial and military applications.  Research and development (R&D) related to new materials and component designs for different PPE including novel designs of body armor has yielded substantial success, but the returns in this area are diminishing relative to invest ...

    STTR Phase I 2022 Department of DefenseNavy
  3. Wide-area Advanced Synthetic Skin with Enhanced Sensory Perception for Low-visibility Undersea Environments

    SBC: PHYSICAL SCIENCES INC.            Topic: N22AT018

    Physical Sciences Inc. (PSI), in collaboration with Michigan State University (MSU), proposes to design, fabricate and evaluate a wide-area synthetic skin device to enable tactile sensing of various shaped objects placed in low-visibility undersea environments. A multi-angular spatial sensing capability will be implemented to identify patterns and 3D objects. This will be possible by the use of a ...

    STTR Phase I 2022 Department of DefenseNavy
  4. Ceramic Fabrication with Control of Micrograin Structure via Nano Additives

    SBC: Applied Sciences Inc.            Topic: N22AT019

    A multidisciplinary team led by Applied Sciences, Inc. (ASI) will incorporate Integrated Computational Materials Engineering (ICME) functionalities to create a predictive design tool to control the formation of unique micrograin structures with a Ceramic Matrix Composite.  Initiation of the structures will be the result of using nanomaterials as nucleation seed crystals in the matrix rather than ...

    STTR Phase I 2022 Department of DefenseNavy
  5. Ceramic Matrix Composites With Novel Additives For Gas Turbine Engine Applications (22-RD-363)

    SBC: UES INC            Topic: N22AT019

    Light weight SiC-based ceramic matrix composites (CMCs) are currently being considered for application as components in high temperature gas turbine engines. However, the effect of engine environment affects their service life. In this STTR Phase I proposal, UES, Inc. in collaboration with Virginia Tech proposes to utilize novel additives to enhance the service life of the CMC components. Models b ...

    STTR Phase I 2022 Department of DefenseNavy
  6. SiC based CMCs with improved properties

    SBC: LYNNTECH INC.            Topic: N22AT019

    Silicon carbide (SiC) based ceramic matrix composites (CMCs) are now being introduced as ultra-high temperature materials in gas turbine engines or hypersonic applications due to their high thermal conductivity and excellent stability at such temperatures.  However, compared to the superalloy materials that they are targeted to replace, these CMCs are much less understood due to a much more compl ...

    STTR Phase I 2022 Department of DefenseNavy
  7. Lidar-like 3D Imaging System for Accurate Scene Understanding

    SBC: ENGENIUSMICRO LLC            Topic: N22AT020

    The Department of Navy (DON) needs an inexpensive lidar-like 3D imaging sensors that have high depth and lateral resolution, have a large field-of view for reliable object detection, respond in real time, and work at medium to long ranges in indoor and outdoor environments. This need can be met by combining stereovision with an adaptive laser range finding array that can selectively increase the r ...

    STTR Phase I 2022 Department of DefenseNavy
  8. Aquatic Soft Robotic Kit

    SBC: TRITON SYSTEMS, INC.            Topic: N22AT023

    Triton Systems, Inc., an SBA Tibbetts Award Winner for Success in Commercializing SBIR derived technologies, in collaboration with Harvard University, will leverage expertise in soft robotics, material science, and STEM education to develop a next-generation STEM education aquatic robotics kit (grades K-12). The kit will have two main goals: 1) engage children’s critical thinking skills with cha ...

    STTR Phase I 2022 Department of DefenseNavy
  9. Aquatic Soft Robotic STEM Education Kit

    SBC: MAXENTRIC TECHNOLOGIES LLC            Topic: N22AT023

    There is a need to increase the number of highly motivated and qualified K-12 students particularly in regards to the future workforce in Naval technologies. Research has shown that K-12 students are more engaged and develop stronger critical thinking skills when building hands-on projects around specific applications with specific design criteria. Novel STEM education toolkits centered around ...

    STTR Phase I 2022 Department of DefenseNavy
  10. Low-Cost, Low-Power Vibration Monitoring and Novelty Detection

    SBC: FATHOM5 CORP            Topic: N22AT026

    The maintenance strategy of the Navy and Marine Corps is transforming from time-based and reactive maintenance to condition-based maintenance. The goals of this transition are to achieve increased asset availability and to lower maintenance costs by decreasing unplanned downtime through optimally planned condition-based scheduling.   Recent advances in artificial intelligence and machine learning ...

    STTR Phase I 2022 Department of DefenseNavy
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