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Award Data

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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. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  2. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  3. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    This Phase II project aims to assemble the key set of sensor modalities that are needed to reliably view the key process anomalies and properties of laser powder bed fusion. The research team will down-select from the Phase I sensors investigated and integrate the sensors into a sensor fusion software package that facilitates data collection and synchronization, and eventually feedback control of ...

    STTR Phase II 2019 Department of DefenseDefense Logistics Agency
  4. Computerized Robotic Delayering and Polishing System

    SBC: SPECTRAL ENERGIES LLC            Topic: DMEA18B001

    The proposed research and technical objectives in this project deal with computerized automatic delayering and polishing system that would be applicable to both commercial and government semiconductor device research and development with applications including Failure Analysis (FA), Fault Isolation (FI), and Reverse Engineering (RE) of semiconductor microelectronic devices. This project could hel ...

    STTR Phase I 2019 Department of DefenseDefense Microelectronics Activity
  5. High Energy Density Micro-Ultracapacitors through Tunable Electrolyte Confinement and Directional Transport

    SBC: MAINSTREAM ENGINEERING CORP            Topic: DMEA13B001

    The increasing penetration of MEMs devices into the commercial market has lead to an increasing demand for micro-sized electrical energy storage devices to interface with a support them. Electrochemical double layer capacitors hold significant promise as

    STTR Phase I 2014 Department of DefenseDefense Microelectronics Activity
  6. 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
  7. Inhibiting Prolyl Hydroxylase to Mimic Natural Acclimatization to High Altitude to Improve Warfighter Performance at High Altitude

    SBC: Research Logistics Company            Topic: SOCOM17C001

    Acclimatization is the long-term adjustment that humans experience when exposed for weeks or months to high altitude. Acclimatization is important in this context because a warfighter who is acclimatized to high altitude is immune to high altitude illness, has superior work capacity, and has cognitive function approaching that found at sea level. In other words, the acclimatized warfighter is opti ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  8. Metrology of Thin Films on Sapphire Substrate

    SBC: OPTOWARES INC            Topic: DMEA16B001

    There is a lack of a non-destructive metrology tool to measure the thickness of thin films on sapphire substrates due to the transparency of the substrate. Leveraging our extensive experience building sensor systems combined with MIT Lincoln Laboratory’s expertise in theoretical modeling, we will design and build an innovative thin film measurement tool using Raman spectroscopy. Our metrology sy ...

    STTR Phase II 2019 Department of DefenseDefense Microelectronics Activity
  9. Small Team Command, Control, Communications and Situational Awareness (C3SA), SOCOM08-001

    SBC: CEEBUS TECHNOLOGIES, LLC            Topic: SOCOM08001

    SOF combat swimmers have a need for the continuous monitoring of each others relative position while diving and for the capability of being able to communicate with each other to help establish a common operational picture (COP).The C3SA system was previously developed under SBIR Topic SOCOM08-001 thru the receipt of both Phase I and Phase II SBIR awards.The C3SA established a stand-alone network ...

    STTR Phase II 2018 Department of DefenseSpecial Operations Command
  10. 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
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