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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. JOLTER: Joint Learning of Topics, Entities, Events and Relations

    SBC: LANGUAGE COMPUTER CORPORATION            Topic: DTRA152005

    In Phase II of JOLTER, we will develop several extensions and improvements upon the probabilistic graphical models developed in Phase I for discovering topics, entities, and relations jointly. The system will be able to (1) Discover and extend hierarchies of topics, entities, and relations; (2) Discover categories for events, multiway relations, and their roles; (3) Conditionalize the topics, ent ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  2. Knowledge Exploitation and Population for Event Reasoning (KEPLER) Phase II

    SBC: LANGUAGE COMPUTER CORPORATION            Topic: DTRA143005

    In Phase II of KEPLER, we will develop a prototype Knowledge Base (KB) expansion system that employs rich common-sense knowledge resources to perform high-quality scalable inference over a KB. The system will be able to (1) extract event parameters, event constructs, ontological relationships, definitional effects and inferences, and quantitative expectations from open text and structured resource ...

    SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  3. 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
  4. 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
  5. 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
  6. Plan Learning Across Textual Observations (PLATO)

    SBC: LANGUAGE COMPUTER CORPORATION            Topic: DTRA162004

    In Phase I of PLATO (Plan Learning Across Textual Observations ), Language Computer Corporation will explore how best to migrate state-of-the-art plan recognition techniques to the more complex genre of textual data addressing such issues as varied textual inputs, diverse subject matter domains, changes in agent plans and goals, unclear or underspecified temporal relationships between actions, an ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
  7. 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
  8. Portable, Fieldable, Non- Helium-3 Based Neutron Multiplicity Counter

    SBC: PROPORTIONAL TECHNOLOGIES, INC.            Topic: DTRA162007

    Neutron coincidence counters are currently based on 3H technology. A worldwide 3He shortage plus the need for significant improvements in performance necessitate the development of a new class of neutron detectors. We propose the use of boron-coated straw (BCS) detectors, consisting of 4 mm diameter copper tubes lined with 10B-enriched boron carbide (10B4C). Previous studies have shown that BCS de ...

    SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
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