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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. STability and Resilience Analysis Technology for Urban Systems analysis (STRATUS)

    SBC: Systems & Technology Research LLC            Topic: ST17C003

    The unique scale, population density, complexity, and connectedness of megacities requires new tools for detecting and assessing risks related to civil unrest, rule of law, terrorism, and other sources of instability, and for understanding the underlying dynamics. In addition, gray zone operations pose a new and strategically important class of threats to the stability of nation states and cities ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  2. REsilience & Stability In DENse Terrains (RESIDENT)

    SBC: BOSTON FUSION CORP            Topic: ST17C003

    Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of u ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  3. Underwater Blast Injury Monitoring

    SBC: TRITON SYSTEMS, INC.            Topic: DHA17C002

    Triton Systems, Inc. proposes to develop a piezo-textile that can capture underwater explosion pressure wave patterns to ultimately establish and monitor for injury risk severity. We propose to use a state-of-the-art piezo-textile to which we will apply our own proprietary treatments.We will assess our textiles pressure detection performance and durability against a non-textile piezoelectric array ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  4. Brain Targeting Nanoparticle for Drug Delivery in Traumatic Brain Injury

    SBC: WEINBERG MEDICAL PHYSICS, INC.            Topic: DHA18A001

    There is an urgent need to bypass or cross the blood brain barrier (BBB) to deliver drugs for TBI treatment. This project aims to develop targted intranasally delivered, magnetically propulsed, and targted nanoparticles for traumatic brain injury (TBI). In Phase I, we will demonstrate the design, fabrication, and in vitro characterization of proposed drug laden magnetic nanoparticles as well as co ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  5. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  6. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. Multi-Physics Models for Parachute Deployment and Braking

    SBC: CMSOFT, INC.            Topic: AF18AT004

    The main objective of this STTR Phase I effort is two-fold. First, to develop a robust approach for coupling the flow solver Kestrel with the multidisciplinary software tool AERO Suite in order to enable the physics-based modeling and simulation of the dynamics of Aerodynamics Decelerator Systems (ADS) such as parachutes from deployment to terminal velocity or terminal descent and touchdown, and t ...

    STTR Phase I 2018 Department of DefenseAir Force
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