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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. Additive Manufacturing of Advanced Metallics

    SBC: TRITON SYSTEMS, INC.            Topic: MDA22T010

    The Missile Defense Agency is seeking innovative material and manufacturing processes for advanced metallic components for hypersonic flight systems. Triton Systems and their academic partner are proposing to develop the manufacturing and qualification evaluation techniques for reliable production of hypersonic environment appropriate metallic components at reduced cost and timelines compared to t ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  2. Measurement of the Plasma Environment in a Rb DPAL

    SBC: PHYSICAL SCIENCES INC.            Topic: MDA22T008

    Diode-pumped alkali lasers (DPAL) offer the potential for scaling to high output powers required for directed energy weapons systems. As power-scaling studies have progressed, increasing concern has emerged about uncertainty in the roles of higher-lying states and the degree of ionization, and their effects on device performance. Ionization by multi-photon absorption and collisional energy pooling ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  3. Improved Hypersonic Jet Interaction Modeling with Propulsion Exhaust Chemistry

    SBC: BLAZETECH CORPORATION            Topic: MDA22T005

    BlazeTech is collaborating with University of Colorado using their hypersonic CFD code LeMANS as a platform on which to integrate a novel combustion code that iteratively adapts its chemical model based on the local flow structure. In this way, the chemistry and fluid mechanics are closely coupled, and simplified models may be leveraged for their low computational cost when more detailed models ar ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  4. Additively Manufactured Ceramic Syntactic Foams

    SBC: PHYSICAL SCIENCES INC.            Topic: MDA22T012

    The Advanced Composite Structures group at Physical Sciences Inc. has partnered with the University of Virginia to develop a high temperature, ceramic syntactic foam that can be fabricated using additive manufacturing (AM) techniques. The AM ceramic insulator is compatible for co-processing with other CMC components such as aeroshells, fins, and additional hypersonic flight vehicle control surface ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  5. DR WATSON: Document Recommender With Adaptively Tailored Sensing of Needs

    SBC: APTIMA INC            Topic: MDA22T002

    Reusing prior work is an adaptive strategy that allows an organization to learn from missteps and extend its most promising insights and capabilities. Reuse grows as a challenge as the artifacts of effort accumulate. For example, stove-piped or hidden data streams make keeping abreast of internal reports and reviews difficult for engineers. The challenges are not merely in the variety and volume o ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  6. A Framework for Efficient Paratemporal Simulation

    SBC: TRITON SYSTEMS, INC.            Topic: MDA22T001

    Running and testing highly complex models and simulations has historically been a very computationally intensive and extremely inefficient process, since full simulations are run from start to finish for each realization of a set of stochastic variables until a full distribution of simulation outcomes has been established. Recently, the concept of cloning has been used to speed up stochastic simul ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  7. sUAS Munition Teaming for Advanced Precision Strike

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: SOCOM21C001

    Precision-guided munitions have demonstrated dramatic effects with minimal collateral damage. New technology developed specifically to deny them accurate guidance information is now feasible, even for non-traditional adversaries. Further, digital communications are flooding the air with signals that interfere with communications many guidance methods rely on. Swarms of small, covert small Uncrewed ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  8. Methodologies to Develop Radiation Testing Environments for Survivable Microelectronics

    SBC: INNOSYS, INC.            Topic: MDA21T001

    We will investigate the radiation effects on microelectronics due to gamma-rays and beta-rays and compare the effects on electrical and material properties between the two radiation types to formulate a quantitative mapping of radiation types (gamma and beta) and effects. The purpose is to: 1) Develop an overall physics-based strategy; 2) Define the experimental design, guided by analytical calcul ...

    STTR Phase I 2022 Department of DefenseMissile Defense Agency
  9. Enhancement of Cross Validation using Hybrid Visual and Analytical Means with Shannon Function

    SBC: LONGSHORTWAY INC.            Topic: MDA21T003

    LongShortWay Inc. and CWU propose new algorithms for Enhancement of Cross Validation using Hybrid Visual and Analytical Means with Shannon Function (Hybrid CV). Approved for Public Release | 21-MDA-11013 (19 Nov 21)

    STTR Phase I 2022 Department of DefenseMissile Defense Agency
  10. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
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