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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. A GREEN AND UNIQUE THERMOSETTING-THERMOPLASTIC POLYCARBONATE

    SBC: INSTRUMENTAL POLYMER TECHNOLOGIES, LLC            Topic: 16NCER2B

    Of the 300 million tons of plastic produced per year most will require 500 years to biodegrade. Currently only 9% is recycled, and 50 million tons of thermoset plastic produced annually that can't be recycled. _x000D_ _x000D_ This project will develop a sustainable and easily biodegradable polycarbonate plastic that is uniquely a recyclable thermoset resin. We call it a thermosetting thermoplastic ...

    SBIR Phase II 2018 Environmental Protection Agency
  2. Development of Innovative Broad-Spectrum Analysis Methods for PFAS

    SBC: SEACOAST SCIENCE, INC.            Topic: 17NCER3A

    This SBIR addresses EPA’s need for improved sampling and analysis technologies to detect Per- and Polyfluoroalkyl Substances (PFAS). PFAS are used in firefighting sprays, at airports, and for wild fires, and have been used in textile treatments (e.g., it is a component in Scotchgard). It is estimated that 65 million Americans are at risk of PFAS exposure in their drinking water. Seacoast propose ...

    SBIR Phase I 2018 Environmental Protection Agency
  3. Greener Plastics with High Heat Tolerance for Additive Manufacturing

    SBC: INTELLIGENT OPTICAL SYSTEMS, INC.            Topic: 17NCER5B

    Advances in materials and automation are rapidly reshaping the American manufacturing economy. These advances must be embraced to sustain a strong manufacturing sector in the United States. Additive manufacturing is possibly the fastest growing example of this trend, growing at an astonishing compound annual growth rate of 25.7%. The plastic materials market for additive manufacturing, valued at $ ...

    SBIR Phase I 2018 Environmental Protection Agency
  4. Renewable Bioplastics Production

    SBC: ALTEX TECHNOLOGIES CORPORATION            Topic: 17NCER5A

    Altex’s Renewable Bioplastics Production (RBP) technology meets the Greener Plastic Manufacturing needs; to eliminate harmful-petrochemical feed sources, to accomplish toxic-free, low-energy, low cost bioplastics production, to reduce Green House Gas (GHG) emissions, and to have environment friendly-biodegradable bioplastics. Altex’s proposed RBP technology combines a novel feeding-sizing-pret ...

    SBIR Phase I 2018 Environmental Protection Agency
  5. Bioinformatics: Data Integration for Biomonitoring Applications

    SBC: Arete Associates            Topic: DTRA162002

    Aret Associates and Oak Ridge National Laboratory (ORNL) propose an interdisciplinary effort to further develop and validate a robust, operational biomonitoring application that can process soil microbiome data to reliably detect episodic and low-level chronic contamination while maintaining low false alarm rate.The Phase II SBIR work will build upon the successful Phase I proof-of-concept demonst ...

    SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
  6. DNC-GD: Deep Neural Network Compression for Geospatial Data

    SBC: Intelligent Automation, Inc.            Topic: NGA181009

    Following technology advances in high-performance computation systems and fast growth of data acquisition, a technical breakthroughnamed Deep Learning made remarkable success in many research areas and applications. Nevertheless, the progress of hardwaredevelopment still falls far behind the upscaling of deep neural network (DNN) models at the software level. NGA seeks to apply neuralnetwork minia ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181010

    The National Geospatial-Intelligence Agency (NGA) ingests and analyzes raw imagery from multiple sources to form actionable intelligenceproducts that can be disseminated across the intelligence community (IC). To effectively meet these demands NGA must continue to improveits automated and semi-automated methods for target detection and classification. Of particular concern is furthering NGA's abil ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. 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
  9. Generalized Change Detection to Cue Regions of Interest

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181006

    Toyon Research Corporation proposes to research and develop algorithms for generalized change detection, by leveraging and exploringexisting and proven effective traditional and deep learning methods, with a unique 3D reconstruction component. The vast majority of themassive amounts of imagery data will have small pixel level differences due to a multitude of unimportant changes: minor misregistra ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Variational Object Recognition and Grouping Network

    SBC: INTELLISENSE SYSTEMS INC            Topic: NGA181005

    To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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