You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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.

  1. Multiphysics Modeling of Dynamic Combustion Processes Using Pareto-Efficient Combustion Framework

    SBC: STREAMLINE NUMERICS, INC.            Topic: AF18BT010

    The objective is to develop zonal multi-physics capability for turbulent combustion simulations. The foundation of the proposed work is a novel Pareto-Efficient Combustion (PEC) framework for fidelity-adaptive combustion modeling. The PEC model utilizes a combustion submodel assignment, combining the low-cost flamelet-based models with the more expensive finite rate chemistry models where necessar ...

    STTR Phase I 2019 Department of DefenseAir Force
  2. Vibration imaging for the characterization of extended, non-cooperative targets

    SBC: Guidestar Optical Systems, Inc.            Topic: AF19AT006

    Locating objects that vibrate is a way to discern potential threats and locate targets. However, current vibrometry technology typically measures only the global vibration of target and cannot create an extended spatial measurement of the vibration profile of the target. These solutions cannot identify what the target is, nor can they locate potential weak spots on the target, because they lack sp ...

    STTR Phase I 2019 Department of DefenseAir Force
  3. 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
  4. 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
  5. 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
  6. Tunable bioinspired spatially-varying random photonic crystals

    SBC: Electro Magnetic Applications, Inc.            Topic: AF19AT017

    Metamaterials and photonic crystals are engineered composites that exhibit novel and interesting properties not found using ordinary materials. They have been shown to allow extraordinary control over the electromagnetic field, including molding the flow of energy, amplitude profile of the field, phase of the waves, intermodal coupling, and more. To achieve such control, a set of tools and procedu ...

    STTR Phase I 2019 Department of DefenseAir Force
  7. Eliminating Ransomware Attacks with Program Access Control (PAC)

    SBC: MARC PEREZ            Topic: AF19BT001

    In the wake of ransomware reaching epidemic proportions and the current anti-ransomware products’ inability to stop its march, there is a great deal of urgency in creating effective countermeasures. Our proposal is to design and subsequently develop a technology called Program Access Control (PAC), that can positively protect data on both consumer and enterprise systems. If successfully dep ...

    STTR Phase I 2019 Department of DefenseAir Force
  8. Open Call for Science and Technology Created by Early-Stage (e.g. University) Teams

    SBC: Semicyber, LLC            Topic: AF19BT001

    There are numerous ongoing research and development efforts on SansEC technology for applications to enhance warfighter and commercial technologies. Two major SansEC applications of interest are (1) the detection of damage on composite airframes, (2) the measuring of the shape of morphing airframes actively in-flight, and subsequently feeding this information back to a flight control system in rea ...

    STTR Phase I 2019 Department of DefenseAir Force
  9. Terahertz cyber security testing using artificial intelligence (FA-002)

    SBC: Electronics of the future, Inc..            Topic: AF19BT001

    The focus of this proposal is FA-002 - artificial intelligence (AI), which will be used for the hardware cyber security. AI will link the THz and sub-THz responses at the pins to the defects and deviations from design of the integrated circuits under test. An increasing complexity of digital and mixed-signal systems makes establishing the authenticity of a chip to be a key problem. New rapid, inex ...

    STTR Phase I 2019 Department of DefenseAir Force
  10. Open Call for Science and Technology Created by Early-Stage (e.g. University) Teams

    SBC: Exosonic, Inc.            Topic: AF19BT001

    Exosonic is developing a quiet Mach 1.8, 4500 nmi range supersonic civil aircraft that uses aerodynamic shaping techniques to mute its sonic boom. Exosonic is teamed up with Stanford University Prof. Juan Alonso's Aerospace Design Lab to apply the lab's low boom shape optimization tools to design this aircraft to meet future low-boom regulatory standards. The aircraft's primary customers are comme ...

    STTR Phase I 2019 Department of DefenseAir Force
US Flag An Official Website of the United States Government