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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. Learner Engagement and Motivation to Learn Assessment and Monitoring System

    SBC: Design Interactive, Inc.            Topic: AF17AT009

    Training can now be delivered on a large scale through emerging platforms, but training must be engaging to be effectively utilized. Key to providing training that makes a difference in the field is an understanding of how to induce high levels of engagement during learning and the ability to objectively assess engagement in real-time so that interventions can be tailored during training to optimi ...

    STTR Phase II 2019 Department of DefenseAir Force
  2. Closed-Loop Feedback Control for Transcranial Direct Current Stimulation, Phase II.

    SBC: QUANTUM APPLIED SCIENCE & RESEARCH INC            Topic: AF17BT002

    Human analysts are presented with ever-increasing amounts of data to process, taxing the limitations of human cognitive capacity. This cognitive overloading leads to increased likelihood of errors and accidents, with costly consequences in mission critical operations. Consequently, there is a rising demand for more efficient processing of increasingly large amounts of intelligence. Transcranial di ...

    STTR Phase II 2019 Department of DefenseAir Force
  3. CIM-MIAS (Cyber Information Management and Mission Impact Analysis System)

    SBC: MODUS OPERANDI, INC.            Topic: AF18CT002

    The DoD lacks an multi-level security (MLS) cyber information management (CIM) system capable of collecting, sharing and disseminating cyber information containing threats, system vulnerabilities and mission impacts and risks for systems operating at multiple security levels. A system that can securely collect and persist this information from various systems operating at various security levels i ...

    STTR Phase I 2019 Department of DefenseAir Force
  4. Verification and Validation of Algorithms for Resilient Complex Software Controlled Systems

    SBC: XL SCIENTIFIC LLC            Topic: AF17CT05

    This effort seeks verification tools and techniques to ensure safety and stability of spacecraft Guidance, Navigation, and Control (GN&C) algorithms, particularly the attitude control system integrated with autonomy software. Advanced control algorithms and autonomy are increasingly necessary to enable responsiveness of fleets of vehicles to attitude constraints and object avoidance. Verus Researc ...

    STTR Phase II 2019 Department of DefenseAir Force
  5. Rapid Discovery of Evasive Satellite Behaviors

    SBC: DATA FUSION & NEURAL NETWORKS, LLC            Topic: AF17CT02

    The problem addressed in this effort is to automatically learn historical ephemeris space catalog time, position, and velocity entity track update error uncertainties (i.e., without track error covariances) and to automatically (e.g., without expert event labeling) produce: – unmodeled non-gravitational space catalog update flags – abnormal unmodeled catalog update flags with abnorma ...

    STTR Phase II 2019 Department of DefenseAir Force
  6. Nanomaterials-Enabled Electrochromic Eye Protection Device

    SBC: INNOSENSE CORPORATION            Topic: AF18BT003

    This project will address the U.S. Air Force needs for single-piece, electronically dimmable eye protection device (EDEPD). In Phase I, InnoSense LLC (ISL) will demonstrate feasibility of the approach by incorporating electrochromic layer on curved polycarbonate substrates. Phase I tests will include optical and physical characterizations regarding transmission range, switching speed, haze, unifor ...

    STTR Phase I 2019 Department of DefenseAir Force
  7. Autonomous Decision Making via Hierarchical Brain Emulation-- 19-009

    SBC: METRON INCORPORATED            Topic: AF19AT009

    The objective of this project is to develop human intelligence-inspired algorithms that exploit multi-modal sources of low and high quality data to achieve a series of objectives such as detection, localization, tracking, and classification. A Bayesian model-based hierarchical adaptive decision making (HADM) algorithm will be developed which includes multiple levels of decision making organized in ...

    STTR Phase I 2019 Department of DefenseAir Force
  8. Ultrahigh-Bandwidth Robust Performance Diagnostics for Rotating Detonation Engines

    SBC: SPECTRAL ENERGIES LLC            Topic: AF19AT011

    Spectral Energies proposes to design a multisensory diagnostic suite for measurements within elevated-pressure RDEs. This sensor will utilize tunable-laser absorption spectroscopy to measure temperature, pressure and H2O concentrations in the annulus of a rocket-RDE and background-oriented schlieren imaging system for flow density gradient imaging to provide time resolved information about the sho ...

    STTR Phase I 2019 Department of DefenseAir Force
  9. High Energy, Safe, and Long-Life Next Generation Batteries Using Liquefied Gas Electrolytes

    SBC: SOUTH 8 TECHNOLOGIES, INC.            Topic: AF19AT014

    The team at South 8 Technologies is the first to develop a novel and patented Liquefied Gas Electrolyte chemistry for rechargeable lithium metal batteries which meets these Air Force requirements. The proposed non-hazardous chemistry has already demonstrated world-record performance on the lithium metal anode (99.9% plating/stripping efficiency over hundreds of cycles) while maintaining high perfo ...

    STTR Phase I 2019 Department of DefenseAir Force
  10. Virtual Reality for Multi-INT Deep Learning (VR-MDL)

    SBC: INFORMATION SYSTEMS LABORATORIES INC            Topic: AF19AT010

    Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...

    STTR Phase I 2019 Department of DefenseAir Force
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