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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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. Advanced Electromagnetic Modeling with High Geometric Fidelity Using High-Order Curved Elements

    SBC: VIRTUAL EM INC.            Topic: N20BT028

    Virtual EM is proposing a method to achieve orders of magnitude improvement in computational efficiency in full-wave CEM codes by using high-order curved elements. Virtual EM’s own commercial product VirAntenn™ will provide the CEM setting for both developing and implementing the new capability in Phase I and Phase II, respectively. Using multi-wavelength long cells with high-order basis forms ...

    STTR Phase I 2020 Department of DefenseNavy
  3. 1 Micrometer Integrated Transmitter for Balanced Radio-Frequency-Over-Fiber Photonic Links

    SBC: N.P. PHOTONICS, INC.            Topic: N20BT030

    NP Photonics proposes to design and develop a compact and integrated radio frequency (RF) -to-optical transmitter at 1060 nm for balanced RF-over fiber photonic links by taking advantage of our mature single-frequency laser technology, multicore fiber fabrication technology, and substantial heterogeneous packaging experience and capability in fiber laser products. In this Phase I program, we will ...

    STTR Phase I 2020 Department of DefenseNavy
  4. 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
  5. Accelerated Burn-In Process for High Power Quantum Cascade Lasers to Reduce Total Cost of Ownership

    SBC: ADTECH PHOTONICS, INC            Topic: N20BT029

    Quantum Cascade Lasers (QCLs) are one of the most versatile sources of radiation in the mid-infrared range and have found applications in a variety of fields. Despite their widespread adoption, one of the main hurdles holding QCLs back from large volume manufacturing is the large cost of ownership. While QCLs, like most semiconductor devices based on III-V compounds, can leverage the economies of ...

    STTR Phase I 2021 Department of DefenseNavy
  6. 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
  7. 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
  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. 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
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