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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. Autonomic Performance Assurance for Multi-Processor Supervisory Control

    SBC: COLORADO ENGINEERING INC.            Topic: OSD11T01

    Multi-processor computing systems are growing in capacity and usage. They encompass multiple, distributed implementations as well as heterogeneous, embedded computing architectures. The processing density enabled by such approaches holds promise for unmanned combat air vehicles (UCAVs) with their plethora of mission sensors and command and control processing requirements. However, the software ...

    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. Lasers Based on Gas Filled Hollow-Core Photonic Crystal Fibers

    SBC: IRFLEX CORP            Topic: AF18BT015

    Current continuous wave (CW) and pulse mid-wave infrared (MWIR) lasers have design and performance limitations that constrain their usability in some critical Air Force applications. There is an important need to create a new class of MWIR laser sources with less drawbacks and higher pulse energies and CW powers. The proposed work will demonstrate the technical feasibility of an innovative MWIR la ...

    STTR Phase I 2019 Department of DefenseAir Force
  5. Low-Energy Adiabatic Circuits for Space Applications

    SBC: SIGNAL SOLUTIONS LLC            Topic: AF18BT013

    Adiabatic logic-based energy-conserving circuits have potential to significantly improve energy efficiency. Adiabatic circuits recycle charge stored in load capacitance resulting in lower power dissipation as compared to conventional CMOS. However, these circuits have only targeted low-frequency operations. Research is needed to develop adiabatic logic circuits for high performance applications wi ...

    STTR Phase I 2019 Department of DefenseAir Force
  6. PRIME: PRimary Integration and Maturation of EGS

    SBC: KBR Wyle Services, LLC            Topic: AF18BT012

    Legacy satellite command and control capabilities and their related telemetry operate in a largely stove piped framework. Satellites are still commanded, controlled, and communicated with their ground station in a specific constellation structure. Each ground station is unique to a given constellation and the communications and telemetry are aligned to the specific constellation, underscoring an o ...

    STTR Phase I 2019 Department of DefenseAir Force
  7. Electronically Dimmable Eye Protection Devices (EDEPD)

    SBC: NANOSONIC INC.            Topic: AF18BT003

    Through the proposed Phase I Air Force STTR program, NanoSonic and Virginia Tech will demonstrate metal organic framework materials and electrospray fabrication methods for the manufacture of eye protection devices that are capable of controlling the amount of light transmitted through the device. The objective of this program is to 1) increase the dynamic range and speed of electronically switche ...

    STTR Phase I 2019 Department of DefenseAir Force
  8. 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
  9. 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
  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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