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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. Massively Parallel Micromachining with Ultrafast Lasers

    SBC: Kapteyn-Murnane Laboratories, Inc.            Topic: AF08T029

    We are proposing to develop a highly parallel, rapid prototyping system for the manufacture of microfluidic devices. In this phase II proposal we will build a complete system for making such devices for continued research on fieldable microfluidic systems for use in the military, and in hospitals. The project will also allow manufacturing in widely different materials, and structures, without an ...

    STTR Phase II 2010 Department of DefenseAir Force
  2. Low Level Signal Detection for Passive Electro-Optical Space-based Surveillance

    SBC: TOYON RESEARCH CORPORATION            Topic: AF12BT02

    ABSTRACT: Toyon Research Corporation and the University of California, Santa Barbara (UCSB) are proposing development and feasibility demonstration of advanced algorithms for the detection of vibration signatures in scattered light. The algorithms are being developed for applications including space-based electro-optical (EO)/infrared (IR) sensing at high frame rates and extremely low signal-to-n ...

    STTR Phase I 2013 Department of DefenseAir Force
  3. Learner Engagement and Motivation to Learn Assessment and Monitoring System

    SBC: Design Interactive, Inc.            Topic: AF17AT009

    Training can now be delivered on a large scale through emerging platforms, but training must be engaging to be effectively utilized. Key to providing training that makes a difference in the field is an understanding of how to induce high levels of engagement during learning and the ability to objectively assess engagement in real-time so that interventions can be tailored during training to optimi ...

    STTR Phase II 2019 Department of DefenseAir Force
  4. Lasers Based on Gas or Liquid Filled Hollow-Core Photonic Crystal Fibers

    SBC: SA PHOTONICS, LLC            Topic: AF18BT015

    We propose a compact, monolithic, power scalable, hollow core fiber-gas laser emitting in the atmospheric transmission region in the mid-IR. The proposed optically pumped fiber-gas laser system is efficient, has a small footprint as well has a broad spectral coverage in the mid-IR. Due to the unique approach employed, the proposed technology allows generation of mid-IR output with varying pulse re ...

    STTR Phase I 2019 Department of DefenseAir Force
  5. Intra-Subaperture Adaptive Optical (ISAO) System

    SBC: NUTRONICS, INC.            Topic: AF12BT13

    ABSTRACT: Current and projected limitations on the maximum power from a high power single mode fiber laser amplifier impose architectural limitations on a high power phased array laser weapon system. Prior studies strongly indicate that when faced with this limitation the optimal approach is (to borrow the term for Paul McManamon) a Phased Array of Phased Arrays (PAPA) geometry wherein large(r) ...

    STTR Phase I 2013 Department of DefenseAir Force
  6. Intelligent In-Situ Feature Detection, Extraction, Tracking and Visualization For Turbulent Flow Simulations

    SBC: JMSI, INC            Topic: AF08T017

    The Phase II STTR project proposed herein presents a new methodology that Detect, Ex-tract, Track and Display features in a CFD solution. BENEFIT: It is projected that his work will impact the Air Force’s procurement methods through improved analysis capabilities in: 1. Aerostructures analysis 2. Weapons bay and structural acoustics analysis 4. Active flow control analysis 5. High lift syste ...

    STTR Phase II 2010 Department of DefenseAir Force
  7. Integrated Quantum Systems Design and Fabrication Technology

    SBC: Guided Particle Systems Inc.            Topic: AF19BT001

    Our proposal is focused on determining the need and feasibility for integrated quantum systems design and fabrication technologies to enable rapid research and development prototyping, and subsequent production, and an industrial base for integrated quantum machines and systems. We focus on the problem of field-able quantum systems for communication networks to support the Air Force as a use case ...

    STTR Phase I 2019 Department of DefenseAir Force
  8. Innovative Combat Simulation to Craft Tomorrow’s UAV Operational Doctrine

    SBC: HPS Simulations            Topic: AF09BT31

    Existing computer combat wargames offer a sophisticated and high fidelity base platform for accurately modeling standard combat scenarios. However, the rapid development of UAV capabilities in terms of sizes, weapons, sensors, communications and flight ability is presenting a new challenge for these simulations. At the same time, the general state of world affairs is changing such that the likeli ...

    STTR Phase I 2010 Department of DefenseAir Force
  9. Innovative CFD Algorithm, Libraries & Python Frameworks for Hybrid-GPU Computing Architectures

    SBC: JMSI, INC            Topic: AF09BT18

    The need for faster highly resolved solutions coupled with the advent of General Purpose Graphics Processing Unit (GPGPU) architectures and the development of GPGPU algorithms at the University of California, Davis present an opportunity that JMSI Inc. proposes to leverage by developing algorithmic and software solutions for GPGPUs in “Innovative CFD Algorithms, Libraries & Python Frameworks for ...

    STTR Phase I 2010 Department of DefenseAir Force
  10. Innovations in Physical Modeling and Statistical Exploitation of Electromagnetic Target Signatures

    SBC: Five Focal LLC            Topic: AF12BT06

    ABSTRACT: Feature extraction and target recognition suffer from a lack of a reliable model for both exploitable target features and the electromagnetic signature they possess. Signature data are often hard to interpret and invert to recover the target robustly. Bayesian learning approaches to statistical pattern recognition are based on the use of training sets of inputs and outputs, a data mode ...

    STTR Phase I 2013 Department of DefenseAir Force
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