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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. 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
  2. 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
  3. Soft Robotic Manipulators with Enhanced Perception using Multimodal Sensory Skins

    SBC: OTHER LAB, INC.            Topic: T1101

    We propose that the key to robotic automation in unstructured environments is compliant robotic manipulators that can tolerate, sense, and leverage contact in a feedback loop. We have demonstrated proof of concept of an instrumented end-effector capable of enhanced perception through observed and controlled contact in phase I. We will now expand the project to develop highly capable state and cont ...

    STTR Phase II 2017 National Aeronautics and Space Administration
  4. Properties Investigation of High-MON Oxidizers for Use in Deep Space Exploration

    SBC: Frontier Aerospace Corporation            Topic: T9

    Rocket propulsion for deep space applications typically use liquid propellants for axial stage and attitude control systems. The most common propellants are hydrazine (N2H4) and monomethylhydrazine (MMH) (CH3N2H3) for the fuels, and nitrogen tetroxide (NTO) (N2O4) for the oxidizer. The freezing points of both hydrazine and NTO approach room temperature and require on-board electrical heaters for t ...

    STTR Phase I 2018 National Aeronautics and Space Administration
  5. 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
  6. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. Automated Fiber Placement of Thin-Ply Composite Materials for Large Aerospace Structures

    SBC: NEXTGEN MATERIALS & PROCESSING LLC            Topic: T12

    Leveraging their prior experience working with automated fiber placement (AFP) of thin-ply composite materials, NextGen Materials & Processing LLC and the University of Massachusetts Lowell will utilize a Design of Experiments approach, combined with analytical modeling, to identify the critical material, slitting, spooling, and AFP parameters that influence the repeatable, high quality laydown of ...

    STTR Phase I 2018 National Aeronautics and Space Administration
  8. Bifunctional Regenerative Electrochemical Air Transformation for Human Environments

    SBC: SKYRE, INC            Topic: T6

    The proposed Bifunctional Regenerative Electrochemical Air Transformation for Human Environments (BREATHE) for life support and habitation is part of the atmosphere revitalization equipment necessary to provide and maintain a livable environment within the pressurized cabin of crewed spacecraft. Sustainable Innovations (SI) has developed a novel solid state technology for gas compression based on ...

    STTR Phase I 2018 National Aeronautics and Space Administration
  9. Efficient CO2 and H2O Removal with Novel Adsorbentsfor Life Support Applications on Mars

    SBC: MOSAIC MATERIALS, INC.            Topic: T6

    Very low CO2 concentrations that accumulate quickly from human respiration can have dramatic health effects, and thus in NASA’s history many technical removal strategies for CO2 from a confined atmosphere have been suggested and explored. A CO2 removal system that functions in a is a new area of research, as the primary CO2 removal component in the state-of-the-art system doesn’t have the adso ...

    STTR Phase I 2018 National Aeronautics and Space Administration
  10. Integrated Photonic Filters for RF Signal Processing

    SBC: OEWAVES, INC            Topic: T8

    In this Project, OEwaves Inc. and Georgia Tech team propose to research and develop a unique RF photonic receiver front-end enabling microwave signal processing at a heterogeneously integrated photonic platform. In particular, we propose to develop a new technology for photonic microwave filters based on the new advances in Si-based integrated photonics. We will exploit the expertise of the team m ...

    STTR Phase I 2018 National Aeronautics and Space Administration
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