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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. Paper Spray Mass Spectrometry Cartridges with Integrated Sampling and Enrichment

    SBC: Nano Terra, Inc.            Topic: A18BT020

    PS-MS is a simple and powerful method for rapid ambient sample preparation. However, its simplicity also means separation of undesirable components (particulates and molecular interferents) is not possible. Furthermore, samples must be collected by other means (e.g., dried blood spot cards) and placed on the ticket in liquid form before analysis. Although the technique is sensitive (nanograms to t ...

    STTR Phase I 2019 Department of DefenseArmy
  2. Multiple Hit Performance of Small Arms Protective Armor

    SBC: ENIG ASSOCIATES, INC.            Topic: A14AT017

    ENIG, in collaboration with SRI, proposes to develop a modeling methodology with predictive and inferential capabilities to address the challenges of designing body armor to resist realistic multiple impacts from burst fire events. Our toolkit will provide an end-to-end modeling capability, grounded in the statistics of realistic impacts from small-arms fire, which would address the final material ...

    STTR Phase I 2015 Department of DefenseArmy
  3. Population Behavioral Analysis at Scale, AOR Modeling

    SBC: DEEP LABS INC            Topic: SOCOM22DST01

    Deep Labs recognizes USSOCOM’s challenge to process multiple data and communications inputs for optimized decision making, and to support rapid on-the-move abilities to learn and communicate knowledge to enhance tactically relevant situational awareness in peer/near peer environments. Deep Labs has proven this capability across complex challenges in the world’s largest commercial enterprises a ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  4. Acoustically/Vibrationally Enhanced High Frequency Electromagnetic Detector for Buried Landmines

    SBC: White River Technologies Inc            Topic: A16AT004

    White River Technologies, Inc. (WRT) and University of Vermont (UVM) present this proposal, "Acoustically/Vibrationally Enhanced High Frequency Electromagnetic Detector for Buried Landmines". Among the primary gaps in our current landmine detection technology base is the ability to detect a wide range of buried explosive hazards including emerging low-metal mines and improvised explosive devices ...

    STTR Phase I 2016 Department of DefenseArmy
  5. Conductive Transmissive Coating for Enhanced-Absorption Thin Film Solar Cells

    SBC: AGILTRON, INC.            Topic: A15AT016

    Thin-film, lightweight, large-area flexible inorganic solar cells have shown promise to meet the militarys remote power needs on the battlefield. However, thin film solar cells normally have inferior conversion efficiencies due to limited absorption of sunlight by the thin active layer. Various approaches have been investigated to improve conversion efficiencies of thin film solar cells. Among the ...

    STTR Phase I 2016 Department of DefenseArmy
  6. Big Open Source Social Science (BOSSS)

    SBC: BOSTON FUSION CORP            Topic: A16AT013

    Boston Fusion Corp. and Arizona State University propose to research and develop Big Open Source Social Science (BOSSS). In BOSSS, we will create a unified approach that combines social and computer science methodologies to collect and interpret big open source data, yielding meaningful focused analysis of selected populations. We will develop a system framework that adaptively learns social behav ...

    STTR Phase I 2016 Department of DefenseArmy
  7. Biological Agent Detection Network

    SBC: PHYSICAL SCIENCES INC.            Topic: A17AT020

    Physical Sciences Inc. in cooperation with University of Notre Dame proposes to develop a method for the persistent surveillance and detection of aerosolized biological warfare agents using a distributed point bioaerosol detector network, local meteorological sensors, existing infrared surveillance cameras, and crowdsourced georeferenced network traffic and phrase monitoring. The proposed technolo ...

    STTR Phase I 2017 Department of DefenseArmy
  8. Vacuum Integrated System for Ion Trapping

    SBC: COLDQUANTA, INC.            Topic: A15AT009

    We propose to develop a compact, integrated ion trap quantum system for quantum sensor, timekeeping, and processing applications. To do so, we leverage ColdQuantas expertise in miniature ultra-high vacuum (UHV) and atom chip technology and Duke Universitys expertise in microfabricated surface ion traps and quantum information processing experiments. We will produce designs and implementation pla ...

    STTR Phase I 2015 Department of DefenseArmy
  9. sUAS Munition Teaming for Advanced Precision Strike

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: SOCOM21C001

    Precision-guided munitions have demonstrated dramatic effects with minimal collateral damage. New technology developed specifically to deny them accurate guidance information is now feasible, even for non-traditional adversaries. Further, digital communications are flooding the air with signals that interfere with communications many guidance methods rely on. Swarms of small, covert small Uncrewed ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  10. Bioaerosol Detector Wide Area Network

    SBC: ARETE ASSOCIATES            Topic: A17AT020

    Historically, the monitoring and detection of biological threats has been carried out via the deployment of high sensitivity / high complexity monitoring nodes to insure high probability of detection and low false alarm rate. Unfortunately, this detection strategy has inherent limits with respect to coverage and response due to its high deployment/support costs, mandating a new approach to environ ...

    STTR Phase I 2017 Department of DefenseArmy
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