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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.

Displaying 1 - 10 of 5134 results
  1. Data-Driven Hypersonic Turbulence Modeling Toolset

    SBC: ATA ENGINEERING, INC.            Topic: N22AT016

    Development of hypersonic aircraft and weapon systems has become a critical focus for the Department of Defense to maintain global strike and projection of force capabilities. Despite decades of research, traditional computational fluid dynamics (CFD) methods are either incapable of adequately predicting complex features in hypersonic flows or too expensive to be of practical use for vehicle desig ...

    STTR Phase II 2024 Department of DefenseNavy
  2. Time Resolved Multiparameter Flow Diagnostic for Engine Exhaust Plumes

    SBC: METROLASER, INCORPORATED            Topic: N23AT005

    High temperature jet plumes emanating from aircraft engines and missiles produce effects that are of interest for threat detection, environmental noise, and engine development purposes. Optical and infrared emissions from plumes are sources of light and heat signatures, respectively, that can potentially be used for tracking or targeting vehicles in flight.  Acoustic noise from jet plumes can pot ...

    STTR Phase I 2023 Department of DefenseNavy
  3. Flat Lens Ultra-Compact Lightweight MWIR Zoom lens for small pixel

    SBC: ATTOLLO ENGINEERING, LLC            Topic: N23AT007

    Attollo Engineering will develop a zoom capable ultra-compact lightweight MWIR camera based off its commercial MWIR Griffin-HD8 camera with a zoom capable Metalens optic. The imager format is 1280 x 720 on an 8 micron pitch, among the smallest size in industry weighing just 240 grams without the optical lens, and was designed for small battery-operated Group 1 unmanned aerial vehicles (UAVs). The ...

    STTR Phase I 2023 Department of DefenseNavy
  4. UUV Sensor Transformation

    SBC: Arete Associates            Topic: N23AT013

    Areté and its teaming partner the University of Arizona (UofA) will develop a software tool that transforms sensor and metadata from a given sensor system into realistic synthetic data as if it were collected by a different sensor system. The exponential rise in available data from a multitude of sensor systems has driven commercial and academic entities to achieve significant innovations in arti ...

    STTR Phase I 2023 Department of DefenseNavy
  5. AI-Based Learning Environment (ABLE) for Undersea Warfare (USW) Training

    SBC: PACIFIC SCIENCE & ENGINEERING GROUP, INC.            Topic: N23AT014

    To compete on the world stage of undersea warfare (USW), the US Navy’s USW systems are frequently updated with advanced capabilities. As a result, modernization trainers need to perform the challenging tasks of updating training material to reflect the new (and obsolete) capabilities. This process requires comparing legacy to updated documentation, identifying changes to system capabilities, and ...

    STTR Phase I 2023 Department of DefenseNavy
  6. Non-thermal Plasma for Deployable JP-10 Fuel Synthesis

    SBC: MALACHITE TECHNOLOGIES INC            Topic: N23AT015

    Our Phase I project will synthesize JP-10 jet fuel from CO2 feedstock using a multi-step process.  CO2 will be converted to syngas (CO and H­2) in a plasma reactor. The syngas will be used as the feedstock for a catalytic Fischer-Tropsch synthesis of JP-10. This carbon-neutral system will be easily deployable to synthesize jet fuel in remote locations, fit in a standard shipping container, and i ...

    STTR Phase I 2023 Department of DefenseNavy
  7. Lightweight Turbogenerator for eVTOL Systems in Marine Environments

    SBC: SCALED POWER INC            Topic: N23AT016

    The proposed R&D project is to develop a lightweight integrated turbogenerator in a compact package intended for embedded integration into a Vertical Take-off and Landing Unmanned Aerial System (VTOL UAS). The turbogenerator will support short duration, high-power flight conditions, such as those encountered during takeoff and landing. The project will take an existing, innovative compact turbogen ...

    STTR Phase I 2023 Department of DefenseNavy
  8. Distributed Consensus for Coherent Spectrum Sensing

    SBC: TIAMI LLC            Topic: N23AT017

    In this Phase I effort, Tiami, LLC, aims to develop and demonstrate a hardware proof of concept for a completely distributed spectrum sensing scheme that leverages consensus learning amongst radio frequency (RF) sensors. The algorithm is based on low-bandwidth message exchange between one-hop neighbors, spans multiple RF bands, is agnostic to the sensing modality, and is resilient to link disrupti ...

    STTR Phase I 2023 Department of DefenseNavy
  9. Synthetic Graphite from Biomass as Anode Material for 6T Batteries

    SBC: FARAD POWER INC            Topic: N23AT020

    Farad Power Inc. proposes to develop and commercialize a Li-ion battery (LIB)- grade graphite from an agricultural waste extract for use in 6T batteries for the US Navy.  Specifically, furan chemicals (furfural C5H4O2 and furfuryl alcohol C5H6O2) are extracted from the hemicellulose component of plant-based biomass.  These chemicals are pure, cheap, and abundant. We have developed a patented pro ...

    STTR Phase I 2023 Department of DefenseNavy
  10. Multisensor Insitu Data with Machine Learning

    SBC: QUARTUS ENGINEERING INCORPORATED            Topic: N222117

    The Multisensor Insitu Data with Machine Learning (MIDML) program will develop a convolutional neural network (CNN) to leverage data generated from multiple AM inprocess sensors. This can provide more accurate and reliable assessments and predictions of final part quality during layer-by-layer fabrication, in real time. The CNN will be developed for maximum prediction accuracy from multiple senso ...

    SBIR Phase I 2023 Department of DefenseNavy
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