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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. SHAPE-BASED GENERALIZATION BOUNDS FOR DEEP LEARNING

    SBC: GEOMETRIC DATA ANALYTICS INC.            Topic: NGA20A001

    We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. Bounding generalization risk for Deep Neural Networks

    SBC: EULER SCIENTIFIC            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. Enabling Technology- Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors

    SBC: Cambridge Crops, Inc.            Topic: G

    Food production, and in particular animal-derived meat products, are a major source of green-house gases, compounded by the remarkable inefficiency in biomass conversion (grain to dense muscle tissue in meat), along with growing challenges with food safety, quality and nutrition. To address this growing problem, we propose to exploit the emerging field of cellular agriculture (tissue engineering o ...

    STTR Phase II 2020 Department of EnergyARPA-E
  4. Low-Cost Hybrid Plasmonic and Photonic "Campanile" Near-Field Probes by Nanoimprint Lithography

    SBC: HIGHRI OPTICS, INC.            Topic: 07a

    Near-field scanning optical microscopy (NSOM) is a powerful and unique approach to characterize the chemical, physical and potentially biochemical properties of materials with the nanometer scale resolution in real-time. A key element for NSOM systems that combine optical spectroscopy with scanning probe microscopy, is the actual probe itself. While many commercial vendors offer off-the-shelf meta ...

    STTR Phase II 2020 Department of Energy
  5. Photonic Memory Controller Module (P-MCM)

    SBC: FREEDOM PHOTONICS LLC            Topic: 04a

    As computational density for high-performance computing and big-data services continues to scale, performance scalability of next generation computing systems is becoming increasingly constrained by limitations in memory access, power dissipation and chip packaging. The processor-memory communication bottleneck, a major challenge in current multicore processors due to limited pin-out and power bud ...

    STTR Phase II 2020 Department of Energy
  6. Energy-Efficient Reconfigurable Universal Accelerator Interconnect

    SBC: FREEDOM PHOTONICS LLC            Topic: 05a

    Recent advances in computing systems fundamentally changed and shaped almost every aspect of today’s society; from healthcare to finances and scientific discoveries, our everyday lives will depend more and more on computing and communication infrastructures and their capability to process and deliver critical information in real time. However, as high-performance-computing systems and datacenter ...

    STTR Phase II 2020 Department of Energy
  7. Novel Membranes for Electrochemical Compressors

    SBC: Giner ELX, Inc.            Topic: 19c

    Hydrogen compression represents a key technical challenge for the widespread use of Fuel Cell Electric Vehicles (FCEV). To dispense hydrogen to a FCEV tank, hydrogen must be compressed to a minimum of 875 bar. Conventional compressors account for over half of the refueling station’s cost, have poor reliability, and insufficient flow rates. To enable the widespread use of FCEVs, an additional maj ...

    STTR Phase II 2020 Department of Energy
  8. NOVEL POLYMER-ELECTROLYTE MEMBRANE DEVELOPMENT FOR CARBON DIOXIDE CONVERSION TO SOLAR FUEL

    SBC: TWELVE BENEFIT CORPORATION            Topic: 19b

    Solar fuels production is necessary for the future of the global economy. To produce solar fuels from CO2, a highly conductive and stable polymer-electrolyte is needed for this demanding application. A promising class of polymer-electrolytes for electrochemical energy applications has been developed, and this project’s goal is to scale-up production, add quality controls, and reduce waste. The n ...

    STTR Phase II 2020 Department of Energy
  9. Diaphanous diamond x-ray beam imaging system

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: 13a

    The goal of the research is to provide pixelated diamond x-ray detectors with the required readout electronics for transmission imaging of hard and soft x-ray beams to facilitate the use of dynamic focusing at advanced light source facilities. This program investigates the use of diamond detectors and the associated readout electronics for x-ray imaging. The present technology, developed by Stony ...

    STTR Phase II 2020 Department of Energy
  10. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA18A001

    The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

    STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
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