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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. Standoff Detector using Large-Volume Advanced Scintillation Materials

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: DTRA152008

    From 1993 to 2013, sixteen incidents involving highly enriched uranium associated with illegal activity has been reported to the IAEA.A gun-type of weapon would require roughly 25 kg of highly enriched uranium (HEU), which is easily deployed.Part of the defense is layered detection using standoff detection.Though detection of HEU is difficult, RMD has developed a number of large-volume scintillati ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  2. Advanced Fast Shutter for Debris Mitigation

    SBC: HYPERION TECHNOLOGY GROUP INC            Topic: DTRA143007

    In an effort to development more robust optical system coatings DTRA, in collaboration with Sandia National Labs, is working to characterize the degradation of optical materials for space systems when exposed to high intensely EUV/ cold x-rays. The experiments utilizes the Double Eagle z-pinch facility which generates high current, high voltage arc pinch plasma to produce an intense EUV and cold x ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  3. MEMS Chip for Chemical Vapor Sampling and Analysis

    SBC: AGILTRON, INC.            Topic: DTRA143003

    Agiltron will develop a new class of chemical vapor analyzers by leveraging Agiltrons development and production of micro-electrical-mechanical systems (MEMS) products and expertise with surface-enhanced Raman scattering (SERS) analysis and film fabrication. Our approach capitalizes on integration of these separate technologies for the first time to generate a unique and novel functionality that f ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  4. Encapsulated HI3O8 Microparticles Phase II

    SBC: AKITA INNOVATIONS LLC            Topic: DTRA143002

    This Phase 2 project will further develop and scale a manufacturing process for the production of 5-25 kilogram quantities of encapsulated HI3O8 with a particle size of approximately 2 m and other sizes as desired by the sponsor. This project addresses the need to develop manufacturing processes and build a production capability for the manufacture of HI3O8 a halogen-containing chemical reagent f ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  5. Novel Munition Technologies to Attack and Defeat Weapons of Mass Destruction (WMD)

    SBC: HYPERION TECHNOLOGY GROUP INC            Topic: DTRA143004

    Traditional weapon systems often fail to meet the requirements of close combat typical of the previously discussed engagement, where insurgents often blend in or store weapon amongst friendly or non-combatant forces, to shield them from precision strike munitions of a technologically superior force. This type of warfare has led to an increased focus on the use of less-lethal weapons, to reduce let ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  6. Long-range SNM detection using alternative signatures

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: DTRA162003

    "Increasing the distance for standoff detection of nuclear materials, beyond that capable with direct radiation detection, using alternative signatures, such as the concentration of ionization in the surrounding atmosphere, improves the ability to locate, track and monitor this material. Ionizing radiation generates free elections, ions, and exited states in the nearby atmosphere, even when the s ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
  7. Data-Driven Technology Discovery Methodologies

    SBC: Systems & Technology Research LLC            Topic: DTRA162005

    We propose to develop Prediction of Emergent SCIENce & Technology (PRESCIENT), a system that mines a text corpus of scientific patents and publications to discovers emerging technologies that may impact WMD or CWMD. PRESCIENT will take as input a diverse corpus of patents and publications, including metadata about contributing authors and organizations, and will produce as output alerts with timel ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
  8. Compact Laser Drivers for Photoconductive Semiconductor Switches (16-RD-863)

    SBC: UES INC            Topic: DTRA16A004

    Compact Electromagnetic Pulse Module (EMP) capable of being arranged in series-parallel planar or cylindrical arrays is needed to simulate nuclear weapon effects. High gain optically triggered photoconductive semiconductor switches (PCSS) based on Gallium arsenide (GaAs) with low timing jitter enables the development of planar or phased arrays of modular EMP or High Power Microwave (HPM) sources. ...

    STTR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
  9. Machine Learning-based Capability for Radioactive and Nuclear Threat Detection and Identification

    SBC: PHYSICAL SCIENCES INC.            Topic: DTRA162001

    Physical Sciences Inc. (PSI) proposes to develop an Advanced Learning-Enabled Threat Search (ALERTS) software to significantly enhance detection range and source classification accuracy during search for Special Nuclear Materials and other radioactive threats. The software will implement Machine Learning algorithms for automated extraction of spectral and temporal features by training on sets of g ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
  10. Machine learning for standoff detection of Special Nuclear Material (SNM)

    SBC: CLOSTRA INC            Topic: DTRA162001

    "Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of t ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
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