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Award Data

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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.

  1. Ultrafast Electron Microscopy Module to Upgrade Existing Commercial Electron Microscopes

    SBC: Niowave, Inc.            Topic: 11a

    This project will develop a flexible longitudinal electron optical system based on high-precision radio-frequency cavities for short and intense electron bunch compressions, both in the energy and time domains. The proposed system is designed to be insertable into an existing transmission electron microscope column to upgrade its temporal resolution. Active phase-space control enables broad ranges ...

    STTR Phase I 2018 Department of Energy
  2. Novel Sulfonated Block Copolymers for Efficient Electrochemical Hydrogen Compression

    SBC: Sustainable Innovations, LLC            Topic: 17d

    According to a report by the Hydrogen Council, a global lobby set up in January 2017 by Toyota and Air Liquide that includes 27 members such as automakers Audi, BMW, Daimler, Honda and Hyundai, and energy firms Shell and Total, increasing the use of hydrogen in power, transport, heat and industry could deliver around one fifth of the total carbon emissions cuts needed to limit global warming to sa ...

    STTR Phase I 2018 Department of Energy
  3. Plasma Catalyst Coupling for Improved Conversion of Methane to Liquids

    SBC: HiFunda, LLC            Topic: 22c

    The discovery of large shale gas reserves in recent years has resulted in the reduction of natural gas price and a need to develop new applications for the available resource. Upgrading shale gas to liquid fuels which are more easily transportable and have greater economic value can result in significant benefits to the US. Coupled with this challenging problem the DOE has a goal of further develo ...

    STTR Phase I 2018 Department of Energy
  4. Algorithms for Look-down Infrared Target Exploitation

    SBC: Signature Research, Inc.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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