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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. Damage Morphology for Advanced Concretes

    SBC: DYNAMIC SYSTEMS & RESEARCH CORP            Topic: AF18AT012

    The development and implementation of new damage morphology models for concrete materials is critical to understanding their dynamic behavior during severe shock loading environments. Current constitutive models of conventional strength concretes do not accurately represent the behavioral characteristics of new ultra-high strength concretes because of differences in damage mechanisms during failur ...

    STTR Phase II 2019 Department of DefenseAir Force
  2. Biological Microdosimetry System

    SBC: QUINC.TECH INC.            Topic: AF18AT001

    The Biomagnetics Micro Dosimetry System (BMDS) program will design, model, and simulate a microdosimetry system that can measure and create a three dimensional map of weak radiofrequency signals in biological organisms. The heart of the BMDS project is the front end that delivers very sensitive, broad band measurements with high spatial resolution. The front end is a valuable tool in the investiga ...

    STTR Phase II 2019 Department of DefenseAir Force
  3. Radio Frequency (RF) Filter Tuning Element

    SBC: MAXENTRIC TECHNOLOGIES LLC            Topic: AF18AT015

    To meet the requirements of the AF18A-T015 solicitation, MaXentric and University of California San Diego are proposing the development of a low loss, high linearity capacitor. The tunable capacitor target is a compact integrated design, capable of a tuning range up to 4:1, with a minimum Q of 80 at 4 GHz, and handling up to 20W CW. During phase I, UCSD studied a novel varactor structure to improv ...

    STTR Phase II 2019 Department of DefenseAir Force
  4. Environmentally-Compliant Inorganic Material(s) for Corrosion and/or Wear Protection of Structural Metals on Military Aircraft and Weapon Systems

    SBC: INNOVATIVE TECHNOLOGY INC            Topic: AF15AT31

    The proposed project will focus on qualifying amorphous-iron Particle Reinforced Metal Matrix Composite (PRMMC) coatings as replacements for Electrolytic Hard Chrome (EHC) and HVOF WC- Co wear and corrosion resistant coatings on high-strength steel components. These legacy coatings have been identified on the OSD Emerging Contaminants Watch or Action Lists, and future manufacture and maintenance o ...

    STTR Phase II 2019 Department of DefenseAir Force
  5. Volume Digital Holographic Wavefront Sensor Phase 2

    SBC: NUTRONICS, INC.            Topic: AF18AT006

    Through the execution of our Phase 1 effort, Nutronics, Inc. and Montana State University developed an improved means to optimize the Pellizzarri cost functional for coherent imaging using digital holography. Our algorithm developed during the Phase 1 effort accelerates convergence times by a factor of 20-40 for the majority of scenarios evaluated. Our proposed Phase 2 effort has a two-fold focus: ...

    STTR Phase II 2019 Department of DefenseAir Force
  6. Carbon Nanotube FET Modeling and RF circuits

    SBC: CARBON TECHNOLOGY INC            Topic: AF18BT006

    Carbon nanotubes (CNTs) have great potential for high performance RF applications. Theoretical study has shown that the electrical current in a CNT field effect transistor (CFET) is intrinsically linear. Today, linearity is the underlying limitation in increasing the data transport densities of wireless networks. The complex modulation protocols used to achieve higher data rates requires linear am ...

    STTR Phase II 2019 Department of DefenseAir Force
  7. 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
  8. CIM-MIAS (Cyber Information Management and Mission Impact Analysis System)

    SBC: MODUS OPERANDI, INC.            Topic: AF18CT002

    The DoD lacks an multi-level security (MLS) cyber information management (CIM) system capable of collecting, sharing and disseminating cyber information containing threats, system vulnerabilities and mission impacts and risks for systems operating at multiple security levels. A system that can securely collect and persist this information from various systems operating at various security levels i ...

    STTR Phase I 2019 Department of DefenseAir Force
  9. 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
  10. Virtual Reality for Multi-INT Deep Learning (VR-MDL)

    SBC: INFORMATION SYSTEMS LABORATORIES INC            Topic: AF19AT010

    Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...

    STTR Phase I 2019 Department of DefenseAir Force
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