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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. Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA)

    SBC: Luminit LLC            Topic: AF18BT004

    To address the U.S. Air Force need for Developing innovative wave-optics Propagation methods to model laser systems that are faster, efficient and more accurate, Luminit, LLC, and University of Southern California (USC) propose to develop Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA). The proposed algorithms will be based on cutting off redundant frequencies upon ...

    STTR Phase I 2019 Department of DefenseAir Force
  2. Carbon Nanotube FET Modeling and RF Circuit Simulation

    SBC: ELECTRONICS OF THE FUTURE, INC.            Topic: AF18BT006

    The project will develop and validate a geometry scalable CNTFET compact model for HF circuit design and extract the model parameters from the measured characteristics of the fabricated devices. The ballistic and quasi-ballistic transport, quantum and parasitic effects will be accounted for the predicted performance will be compared to 130 nm RF Si-CMOS to determine the conditions for breaking eve ...

    STTR Phase I 2019 Department of DefenseAir Force
  3. RAPID RECONSTITUTION FOR GROUND-BASED OPTICAL SSA CAPABILITY FOR GEO, HEO AND MEO

    SBC: J.T. MCGRAW AND ASSOCIATES, LLC            Topic: AF16AT05

    Commercially-derived telescope systems, consisting mostly of commercially available components assembled to optimally meet space surveillance goals, stand ready to temporarily replace, supplement and/or augment existing optical surveillance systems. In t...

    STTR Phase I 2016 Department of DefenseAir Force
  4. Bio-Inspired Bone, Wing, Tail, and Muscle Structures for Morphing Aircraft

    SBC: Prioria Robotics, Inc.            Topic: AF15AT01

    ABSTRACT: Our focus in this proposal is to perform basic research to create bio-inspired 3-D morphing mechanical structures which are a gateway technology to enable true 3-D morphing flight. Prioria and Virginia Tech University will team to perform basic research into bio-inspired structure such as artificial bones/wings/feathers and artificial muscles. Prioria will establish technical feasibility ...

    STTR Phase I 2016 Department of DefenseAir Force
  5. 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
  6. 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
  7. High Performance THz Detector Arrays Using Planar Metamaterial Absorbers

    SBC: DOLCE Technologies, LLC            Topic: AF09BT33

    DOLCE Technologies, LLC, in collaboration with Professor Rick Averitt’s research group at Boston University and Eric Shaner’s group at Sandia National Laboratories, will develop and deliver a high performance room-temperature Terahertz detector array solution based on metamaterial absorbers integrated with bi-material cantilevers. The metamaterial approach is frequency scalable and can operat ...

    STTR Phase I 2010 Department of DefenseAir Force
  8. Surface plasmon enhanced tunneling diode detection of THz radiation

    SBC: ITN ENERGY SYSTEMS, INC.            Topic: AF09BT33

    This Small Business Technology Transfer Research phase I program will develop a new class of uncooled THz detectors for the 1-10THz band with a novel design using surface plasmon resonant cavities with integrated metal-insulator-metal tunneling diodes as the detecting element. Tunneling diodes provide ultrafast broadband response, potentially into the visible (300THz), but demonstrated performanc ...

    STTR Phase I 2010 Department of DefenseAir Force
  9. Surface plasmon enhanced thin-film photovoltaic systems

    SBC: ITN ENERGY SYSTEMS, INC.            Topic: AF09BT39

    This Small Business Technology Transfer Research phase I program will develop a new class of surface plasmon enhanced photovoltaic devices that exhibit increased current collection. Photon management, the manipulation of the incident optical field to increase the probability that a photon is absorbed in the active region of the cell, is critical to the development of next generation thin film sol ...

    STTR Phase I 2010 Department of DefenseAir Force
  10. VLSI Compatible Silicon-on-Insulator Plasmonic Components

    SBC: ITN ENERGY SYSTEMS, INC.            Topic: AF08BT18

    This Small Business Technology Transfer Phase I project will develop ultradense, low-power plasmonic integration components and devices for on-chip manipulation and processing of optical signals. Both passive and active components will be studied. Detailed performance predictions will be obtained through finite element modeling (FEM) of the harmonic Maxwell’s equations. The FEM provides detai ...

    STTR Phase I 2010 Department of DefenseAir Force
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