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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. Design and Analysis of Multi-core Software

    SBC: SECURBORATION, INC.            Topic: OSD11T03

    Modern processor design is trending increasingly toward multicore architectures. This is problematic for programmers because writing a correct parallel program is known to be difficult compared to writing the equivalent sequential program. Additionally, a wide body of sequential code has already been developed that cannot exploit the power offered by these new cores because it was written in a s ...

    STTR Phase II 2013 Department of DefenseAir Force
  2. A Trusted Computing Framework for Embedded Systems

    SBC: Intelligent Automation, Inc.            Topic: AF11BT15

    ABSTRACT: The damage and loss caused by attacks and security breaches have drawn attentions to develop secure and reliable systems for embedded systems. Compared to their desktop counterparts, embedded devices are facing more security challenges, such as the more possible physical access to a target device and more constrained computing environment (e.g., limited RAM and CPU power). Together, the ...

    STTR Phase II 2013 Department of DefenseAir Force
  3. Nublu: Assured Information Sharing in Clouds

    SBC: Modus Operandi, Inc.            Topic: AF11BT30

    ABSTRACT: We propose to develop an assured information sharing framework for cloud-based systems that leverages our ongoing work in the areas of policy-based usage management and semantic interoperability. The development of this framework will involve the creation of a novel approach to information sharing that treats security as a commodity that can be dynamically provisioned within the cloud, ...

    STTR Phase II 2013 Department of DefenseAir Force
  4. Electron emitting graphene based composite coating for spacecraft charging mitigation

    SBC: Faraday Technology, Inc.            Topic: AF18AT011

    Faraday and Utah State University propose to demonstrate the feasibility of utilizing electrophoretic deposition to develop graphene features with controlled functional properties in order to address the DoD need for a spacecraft charging mitigation. Implementation of such materials in DoD mission areas is anticipated to lower costs, improve sustainability, and increase readiness. The proposed Pha ...

    STTR Phase I 2019 Department of DefenseAir Force
  5. High Temperature Materials for Hypersonic Radomes and Antennas

    SBC: AMERICAN TECHNICAL COATINGS, INC.            Topic: AF18AT013

    Successful completion of this Phase II proposal will fully characterize and evaluate a material for use in RF windows on hypersonic flight vehicles. Phase II will specifically examine the materials suitability through RF testing in X, Ku, and Ka bands and at elevated temperatures to 2000°F. The desired outcome will be a material with predictable, repeatable dielectric properties over frequency ...

    STTR Phase II 2019 Department of DefenseAir Force
  6. Resilient Directional Mesh Enhanced Tactical Airborne Networks

    SBC: FIRST RF CORPORATION            Topic: AF17BT003

    FIRST RF will lead the Phase II effort and will leverage the system architecture of the MAINLINE system and integrate multifunctional SiGe integrated circuits (ICs) developed by The University of California San Diego under the supervision of Prof. Gabriel Rebeiz. The SiGe devices developed during the Phase II effort will significantly reduce the power requirements of the MAINLINE system allowing f ...

    STTR Phase II 2019 Department of DefenseAir Force
  7. Shear Stabilization Based Framework for the Failure Testing and Analysis of HSCs

    SBC: Roccor, LLC            Topic: AF17AT019

    Over the past 2 years, Roccor has successfully qualified and delivered High Strain Composite (HSC) products for space-flight customers including, 1) RF-Furlable boom, 2) a furlable-antenna system; and is currently qualifying HSC products for space-flight customers including 3) an FCC certified deorbit device, and 4) a solar array deployment system. Three of these missions will be launched in 2018. ...

    STTR Phase II 2019 Department of DefenseAir Force
  8. SLACA: Self-Learned Agents for Collective Aerial Video Analysis

    SBC: Intelligent Automation, Inc.            Topic: AF18BT002

    For this STTR Intelligent Automation, Inc. teams with researchers from University of Maryland, College Park to develop SLA, a self-learned agent system for collective human activities and events in aerial videos. Aerial video analytics often faces challenges such as low resolution, shadows, varied spatio-temporal dynamics, etc. The traditional methods depending on the object detection and tracking ...

    STTR Phase I 2019 Department of DefenseAir Force
  9. Carbon Nanotube FET Modeling and RF Circuit Simulation

    SBC: Electronics of the future, Inc..            Topic: AF18BT006

    The project will develop and validate a geometry scalable CNTFET compact model for HF circuit design and extract the model parameters from the measured characteristics of the fabricated devices. The ballistic and quasi-ballistic transport, quantum and parasitic effects will be accounted for the predicted performance will be compared to 130 nm RF Si-CMOS to determine the conditions for breaking eve ...

    STTR Phase I 2019 Department of DefenseAir Force
  10. High Speed High Accuracy Artificial Neural Networks for UAV based Target Identification

    SBC: UHV TECHNOLOGIES, INC.            Topic: AF18BT007

    The machine learning and artificial intelligence community has recently garnered much attention for ground breaking performance of novel neural network architectures for self-driving cars. One of the machine learning methods used in self-driving cars is semantic segmentation. In this fashion each pixel in an image is label with a class, allowing for contour-based image segmentation which is differ ...

    STTR Phase I 2019 Department of DefenseAir Force
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