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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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. Advanced Electromagnetic Modeling and Analysis Tools for Complex Aircraft Structures and Systems

    SBC: Hypercomp, Inc.            Topic: N20BT028

    Under this STTR solicitation N20B-T028, the goal is to build on the strengths of HyPerComp’s development in the HDphysics suite of tools to meet NAVAIR’s requirements in solving large-scale problems in electromagnetics.  One area that will receive a major attention in this effort is the development of high order curved meshes for arbitrary geometries with small- and large-scale features that ...

    STTR Phase I 2020 Department of DefenseNavy
  2. Geometry-Perfect CEM Design and Analysis Software for Aircraft Systems

    SBC: IERUS TECHNOLOGIES, INC            Topic: N20BT028

    Performing accurate simulations of large- and multi-scale electromagnetics problems has far-reaching implications in a variety of engineering and scientific disciplines. The same physics governs a diversity of applications including problems of importance for NAVAIR such as complex radome-antenna and antenna-platform interactions.  Such simulation problems involve complex materials, multiple feed ...

    STTR Phase I 2020 Department of DefenseNavy
  3. 1um heterogeneously integrated transmitter for balanced links

    SBC: Freedom Photonics LLC            Topic: N20BT030

    In this program, we propose to adapt a new, high-performance integration platform for RF photonics to operation at 1um, and to realize integrated optical transmitters that meet the requirements of the program.

    STTR Phase I 2020 Department of DefenseNavy
  4. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  5. Investigation of Radiation Effects in Advanced Microelectronic Devices for developing predictive models of degradation

    SBC: CFD Research Corporation            Topic: 20A001

    Radiation effects in microelectronic components are a significant concern for the reliability of DoD systems that operate at high altitudes or in outer space. Typical characterization efforts focus on macroscale degradation signatures from electrical measurements at device terminals. However, a comprehensive analysis of radiation-induced physical defects is not possible based solely on terminal me ...

    STTR Phase I 2020 Department of DefenseDefense Microelectronics Activity
  6. PARTEL: Periscope video Analysis using Reinforcement and TransfEr Learning

    SBC: MAYACHITRA, INC.            Topic: N20AT007

    We propose a suite of video processing algorithms utilizing the machine learning (ML) techniques of artificial intelligence (AI) reinforcement learning, deep learning, and transfer learning to process submarine imagery obtained by means of periscope cameras. Machine learning (ML) can help in addressing the challenge of human failure of assessing the data of periscope imagery. Though pre-tuned blac ...

    STTR Phase I 2020 Department of DefenseNavy
  7. Frequency and Phase Locking of Magnetrons Using Varactor Diodes

    SBC: Calabazas Creek Research, Inc.            Topic: N20AT015

    Magnetrons are compact, inexpensive, and highly efficient sources of RF power used in many industrial and commercial applications. For most of these applications, the requirement is for RF power without regard to precise frequency or phase control, and noise riding on the RF signal is not important. For many accelerator, defense, and communications applications, however, these characteristics prev ...

    STTR Phase I 2020 Department of DefenseNavy
  8. Machine Learning for Transfer Learning for Periscopes

    SBC: Arete Associates            Topic: N20AT007

    Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop and demonstrate new approaches that improve the performance of in situ machine learning (ML) algorithms as they evolve over time, adapt to new environments, and are capable of transferring their learned experiences across platforms.  Technological advances that will be brought t ...

    STTR Phase I 2020 Department of DefenseNavy
  9. Machine Learning for Simulation Environment

    SBC: Arete Associates            Topic: N20AT014

    Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop an interactive scenario building tool capable of generating realistic synthetic 360° videos in real-time for use in training simulators for periscope operators .  We refer to this solution as RealSynth360.  This novel capability will be created by combining the latest advances ...

    STTR Phase I 2020 Department of DefenseNavy
  10. Transportable Rugged Crystalline Silicon Reference (TRuCR)

    SBC: Aosense, Inc.            Topic: AF20AT001

    Crystalline silicon cavities serve as ultralow-phase-noise optical local oscillators for optical atomic frequency standards and can support the realization of optical timescales.  While a JILA/PTB team has built and tested several silicon cavities over the past decade, similar cavities are not readily available to other potential users.  We propose to combine AOSense’s expertise in laser-frequ ...

    STTR Phase I 2020 Department of DefenseAir Force
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