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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. Provably Unclonable Functions on Re-configurable Devices

    SBC: IERUS TECHNOLOGIES, INC            Topic: A18BT001

    The ability to authenticate electronic devices is an important step towards modernizing the hardware/software of our Nations communication systems. Protecting these targeted networks and devices from malicious cyber-based attacks is becoming increasingly important as the technological and cyber capabilities of our adversaries continue to advance. In addition to network security, device authenticat ...

    STTR Phase I 2018 Department of DefenseArmy
  2. Anisotropic Property Manipulation of Selective Laser Melted GRCop-84

    SBC: Special Aerospace Services            Topic: AF18AT009

    In partnership with the Colorado School of Mines Alliance for the Development of Additive Processing Technologies and with support from the Johns Hopkins University Energetic Research Group, Special Aerospace Services will provide the Air Force with characterization of fully dense Selective Laser Melted GRCop-84 subjected to a variety of manipulations that affect key performance metrics for regene ...

    STTR Phase I 2018 Department of DefenseAir Force
  3. Marburg Virus Prophylactic Medical Countermeasure

    SBC: MAPP BIOPHARMACEUTICAL, INC.            Topic: CBD18A002

    There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terriblemorbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditionalvaccines have proven to be a huge contribution to public health, they do have some limitations especially in the cont ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  4. 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
  5. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  6. Novel Circulating RNA-based Markers as Diagnostic Biomarkers of Infectious Diseases

    SBC: CFD Research Corporation            Topic: CBD18A001

    In resource limited settings, rapid and accurate diagnosis of infections is critical for managing potential exposures to highly virulent pathogens,whether occurring from an act of bioterrorism or a natural event. This is especially important for hard to detect intracellular bacterial andalphavirus infections, that overlap symptomatically and often treated empirically due to a lack of reliable and ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  7. Complex Object Reflectance Characterization System (CORCS)

    SBC: NUTRONICS, INC.            Topic: AF18AT007

    Nutronics, Inc. and Montana State University propose to develop a method for characterization of the full Mueller matrix for reflective scattering from a test object. The Complex Object Reflectance Characterization System (CORCS) will initially be designed for laboratory use and characterization of test objects by active imaging to measure both the Mueller Matrix and the target depth associated wi ...

    STTR Phase I 2018 Department of DefenseAir Force
  8. Multi-Physics Models for Parachute Deployment and Braking for Coupling with DoD CREATE-AV Kestrel

    SBC: Kord Technologies, Inc.            Topic: AF18AT004

    Design analysis of parachute recovery systems has relied on a combination of core design principles, historical empirical data, and extensive testing for decades. Parachute motion involves complex phenomena involving porous bluff-body aerodynamics and highly deformable cloth. The proposed project is a plugin for the DoD CREATE-AV Kestrel simulation suite that will enable high-fidelity simulations ...

    STTR Phase I 2018 Department of DefenseAir Force
  9. Multi-Physics Models for Parachute Deployment and Braking

    SBC: Cmsoft, Inc.            Topic: AF18AT004

    The main objective of this STTR Phase I effort is two-fold. First, to develop a robust approach for coupling the flow solver Kestrel with the multidisciplinary software tool AERO Suite in order to enable the physics-based modeling and simulation of the dynamics of Aerodynamics Decelerator Systems (ADS) such as parachutes from deployment to terminal velocity or terminal descent and touchdown, and t ...

    STTR Phase I 2018 Department of DefenseAir Force
  10. 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
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