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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. DIPAIN based assay for the T-2 Toxin

    SBC: L. C. PEGASUS CORP.            Topic: A10AT021

    This proposed project is to develop a rapid assay for T-2 Toxin. Under this project we will develop DIPAIN-derivative based test-strips that indicate the presence of trace quantities of trichothecene mycotoxins in aqueous solutions. The T-2 toxin will be used as a test case for this effort. We will use of 2-(diphenylacetyl)-l,3-indanedione-l-hydrazone (DIPAIN II) and its derivatives as reagents o ...

    STTR Phase I 2010 Department of DefenseArmy
  2. Decontamination storage bags for chemical and biological warfare agents

    SBC: MATERIALS MODIFICATIONS INC            Topic: A10AT003

    This STTR Phase I project will develop a novel toxic material storage bag with an inner liner capable of decontaminating chemical and biological warfare agents (CBWA’s).. The inner-liner technology would entail adsorption and decomposition of warfare agents without the release of toxic agents, and will result in a storage bag capable of being disposed of in an environmentally safe fashion. The ...

    STTR Phase I 2010 Department of DefenseArmy
  3. Topological Data Analysis and Wide Area Detection of Chemical and Biological Contamination MP 39-10

    SBC: METRON INCORPORATED            Topic: A10AT020

    Metron, Inc. and Stanford University propose to design, develop, test and demonstrate topological data analytic algorithms to analyze hyperspectral imagery. We propose to adapt the topological data analytic techniques, including Stanford’s successful Mapper algorithm, to the hyperspectral imagery domain. Using these algorithms we will identify topological and geometric features and properties ...

    STTR Phase I 2010 Department of DefenseArmy
  4. Non-destructive Exfoliation and Drying of Anisotropic Nanomaterials

    SBC: NANOSONIC INC.            Topic: A09AT021

    The overall goal of this proposed Army STTR is to demonstrate low-cost, non-destructive methodologies for non-agglomerating drying of anisotropic nanomaterials. NanoSonic and Virginia Tech will work in tandem to demonstrate novel approaches involving both high performance coatings and CO2 processing that facilitate gentle, simultaneous drying and exfoliation of nanoparticles, preventing agglomera ...

    STTR Phase I 2010 Department of DefenseArmy
  5. MEMS based thermopile infrared detector array for chemical and biological sensing

    SBC: New Jersey Microsystems, Inc.            Topic: A10AT004

    New Jersey Microsystems proposes to develop an economical thermopile array with sensitivity maximum in the long wave infrared region (LWIR). Current infrared detectors are too expensive to be widely deployed in large numbers. The proposed MEMS technology is simpler, more manufacturable, and therefore less expensive than bolometer and ferroelectric devices with competitive D* sensitivity. The th ...

    STTR Phase I 2010 Department of DefenseArmy
  6. Incremental Learning for Robot Sensing and Control

    SBC: SET ASSOC. CORP.            Topic: A09AT030

    SET Corporation, together with Carnegie Mellon University''s National Robotics Engineering Center (NREC), will develop a system that leverages state-of-the-art sensing, perception, and machine learning to provide trafficability assessments for UGVs for agricultural, security and military applications. It will consist of a set of proprioceptive and exteroceptive sensors that provide rich data about ...

    STTR Phase I 2010 Department of DefenseArmy
  7. Multi-input Multi-output Synthetic Aperture Radar with Collocated Antennas

    SBC: TRIDENT SYSTEMS LLC            Topic: A10AT005

    The enormous effort devoted to the data acquisition, signal processing, and automatic recognition of stationary targets has resulted in a generation of synthetic aperture radar (SAR) systems that are meeting the challenge of real-world conditions. However, in a practical battlefield, moving targets may pose a more severe threat than stationary targets. Many high value targets are only vulnerable w ...

    STTR Phase I 2010 Department of DefenseArmy
  8. Random Number Generation for High Performance Computing

    SBC: Silicon Informatics, Inc.            Topic: A10AT012

    Highly scalable parallel random number generators (RNGs) will be developed, evaluated and implemented for use in high performance computing on thousands of multi-core processors and general purpose graphics processing units. The main contributions are: (a) design and implementation of new parallel test methods that capture the inter-stream correlations exhibited in practice and complement the curr ...

    STTR Phase I 2010 Department of DefenseArmy
  9. Impact of Climate Change on Military Compounds in the Environment

    SBC: Environmental Quality Management            Topic: A09AT024

    This will facilitate the development of remedial approaches for existing facilities and assist in planning new facilities, logistics, and procedures to protect the environment without impairing critical mission functionality. The commercial application will include software distribution and updates.

    STTR Phase I 2010 Department of DefenseArmy
  10. Incremental Learning for Robot Sensing and Control

    SBC: Net-Scale Technologies, Inc.            Topic: A09AT030

    This proposal addresses key open challenges identified during the LAGR program for the practical use of adaptive, vision-based robot navigation in commercial settings. First, the adaptive vision system learns quickly, but forgets as quickly. This will be addressed by using an ensemble of "expert" classifiers, each of which specializes for a particular environment and can be quickly activated when ...

    STTR Phase I 2010 Department of DefenseArmy
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