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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. Flexible Low Temperature CO2 Capture System, E-CACHYS

    SBC: ENVERGEX LLC            Topic: 1

    This project focuses on the design, integration and optimization of a flexible natural gas combined cycle plant with carbon capture, capable of operating in a highly variable renewable energy environment. Renewable energy sources such as wind and solar power offer unique solutions in our quest to reduce global carbon dioxide (CO2) emissions. However, the increasing penetration of these high variab ...

    STTR Phase I 2020 Department of EnergyARPA-E
  2. 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
  3. Enabling Technology- Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors

    SBC: cambridge crops, Inc.            Topic: G

    Food production, and in particular animal-derived meat products, are a major source of green-house gases, compounded by the remarkable inefficiency in biomass conversion (grain to dense muscle tissue in meat), along with growing challenges with food safety, quality and nutrition. To address this growing problem, we propose to exploit the emerging field of cellular agriculture (tissue engineering o ...

    STTR Phase I 2020 Department of EnergyARPA-E
  4. 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
  5. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  7. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  8. 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
  9. Incident Surveillance Management System (ISMS)

    SBC: Geospatial Systems, Inc.            Topic: N/A

    Geospatial Systems and Rochester Institute of Technology (RIT) have teamed with Leica Geosystems to develop an Incident Surveillance Management System (ISMS) that can ingest data from remote sensing systems, reduce that data, and deliver information products to decision makers in near real time. The information products are consistent with accepted practice within the NIMS community and utilize st ...

    STTR Phase I 2006 Department of Homeland Security
  10. Botnet Analytics Appliance (BNA)

    SBC: MILCORD LLC            Topic: N/A

    As reported by Internet security threat reports, Bot networks are becoming the focal point for cybercriminals. Milcord and the University of Wisconsin, responds to this challenge with our proposal ¿ a ¿Bayesian Activity Monitor for Botnet Defense¿ (BAM-BD). In this proposal, we will research, design, and develop a botnet detection and mitigation tool that automatically classifies botnet behavio ...

    STTR Phase I 2006 Department of Homeland Security
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