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 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. 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
  2. Functional Engineering of a Photosynthetic Desalination Pump Circuit

    SBC: Phytodetectors, Inc.            Topic: G

    Phytodetectors will design and engineer a synthetic biological pump circuit to increase the volume of water produced via photosynthetic desalination. This project builds off previous technology designed by Phytodetectors: a mangrove-inspired ultra-filter that allows plants to purify salt water as well as secrete water with properties comparable to bottled water. The partnership seeks to demonstrat ...

    STTR Phase I 2020 Department of EnergyARPA-E
  3. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  4. Vertical GaN Substrates

    SBC: Sixpoint Materials, Inc.            Topic: N/A

    SixPoint Materials will create low-cost, high-quality vertical gallium nitride (GaN) substrates using a multi-phase production approach that employs both hydride vapor phase epitaxy (HVPE) technology and ammonothermal growth techniques to lower costs and maintain crystal quality. Substrates are thin wafers of semiconducting material needed for power devices. In its two-phase project, SixPoint Mate ...

    STTR Phase I 2014 Department of EnergyARPA-E
  5. Vertical GaN Substrates

    SBC: Sixpoint Materials, Inc.            Topic: DEFOA0000941

    SixPoint Materials will create low-cost, high-quality vertical gallium nitride (GaN) substrates using a multi-phase production approach that employs both hydride vapor phase epitaxy (HVPE) technology and ammonothermal growth techniques to lower costs and maintain crystal quality. Substrates are thin wafers of semiconducting material needed for power devices. In its two-phase project, SixPoint Mate ...

    STTR Phase II 2014 Department of EnergyARPA-E
  6. Retrofittable and Transparent Super-Insulator for Single-Pane Windows

    SBC: NANOSD, INC.            Topic: DEFOA0001429

    NanoSD, Inc. with its partners will develop a transparent, nanostructured thermally insulating film that can be applied to existing single-pane windows to reduce heat loss. To produce the nanostructured film, the team will create hollow ceramic or polymer nanobubbles and consolidate them into a dense lattice structure using heat and compression. Because it is mostly air, the resulting nanobubble s ...

    STTR Phase II 2016 Department of EnergyARPA-E
  7. Vertical GaN Substrates

    SBC: Sixpoint Materials, Inc.            Topic: DEFOA0000941

    SixPoint Materials will create low-cost, high-quality vertical gallium nitride (GaN) substrates using a multi-phase production approach that employs both hydride vapor phase epitaxy (HVPE) technology and ammonothermal growth techniques to lower costs and maintain crystal quality. Substrates are thin wafers of semiconducting material needed for power devices. In its two-phase project, SixPoint Mate ...

    STTR Phase II 2017 Department of EnergyARPA-E
US Flag An Official Website of the United States Government