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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. PREFAB MODULAR LIQUID-COOLED MICRO DATA CENTER

    SBC: Flexnode Inc            Topic: 1

    "To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

    STTR Phase I 2024 Department of EnergyARPA-E
  2. PREFAB MODULAR LIQUID-COOLED MICRO DATA CENTER

    SBC: Flexnode Inc            Topic: 1

    "To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

    STTR Phase II 2024 Department of EnergyARPA-E
  3. PREFAB MODULAR LIQUID-COOLED MICRO DATA CENTER

    SBC: Flexnode Inc            Topic: 1

    "To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

    STTR Phase II 2024 Department of EnergyARPA-E
  4. Machine Intelligence for Space Weather (MINTS)

    SBC: NEXTGEN FEDERAL SYSTEMS LLC            Topic: 95

    NextGen Federal Systems (NextGen), a Small Business Concern (SBC), is excited to propose a powerful software package, coupled database, and a machine-learning (ML) workflow to support streamlined evaluation and research-to-operations (R2O) of space weather ML models and techniques. In response to the NOAA Effect of Space Weather subtopic (NOAA SBIR 9.5), we propose the Machine Intelligence for Spa ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  5. Low Cost All Temperature Zinc-pulp Battery for Stationary Storage

    SBC: WH-POWER INC            Topic: C

    WH-Power (WattHour-Power, or WHP) and University of Maryland (Profs. Chunsheng Wang and Laingbing Hu) propose to produce a high entropy electrolyte (HEE) and pulp based low-cost zinc battery with –80 ˚C to 80 ˚C operation temperature range for stationary storage (grid and residential energy storage). The zinc-pulp battery is inherently safe, the cost to produce and use the battery is low, and ...

    SBIR Phase I 2023 Department of EnergyARPA-E
  6. Low Cost All Temperature Zinc-pulp Battery for Stationary Storage

    SBC: WH-POWER INC            Topic: C

    WH-Power (WattHour-Power, or WHP) and University of Maryland (Profs. Chunsheng Wang and Laingbing Hu) propose to produce a high entropy electrolyte (HEE) and pulp based low-cost zinc battery with –80 ˚C to 80 ˚C operation temperature range for stationary storage (grid and residential energy storage). The zinc-pulp battery is inherently safe, the cost to produce and use the battery is low, and ...

    SBIR Phase II 2023 Department of EnergyARPA-E
  7. Developing a proof-of-concept Neutral Density Monitoring and Alert Service for satellite operators.

    SBC: ENSEMBLE GOVERNMENT SERVICES, LLC            Topic: 95

    Ensemble intends to develop a proof-of concept Neutral Density Monitoring and Alert Service. To establish an innovative and accurate space weather analytics service, Ensemble has partnered with CU Boulder's SWx-TREC, who offer leading space weather research-to-operations support. Ensemble will create the foundational architecture for Neutral Density Alerts and Notifications for commercial satellit ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  8. An Ultrawideband RFI-Mitigating Software Defined Radiometer

    SBC: DeepSpace Technologies, Inc            Topic: 94

    Anthropogenic Radio-Frequency Interference (RFI), or interference from human-generated sources, continues to plague spaceborne microwave radiometer and sounder instruments. Unmitigated RFI adversely affects the quality and reliability of Earth remote sensing data used for determining water availability, quality, and risk. Proliferation of wireless technologies, Earth-orbiting commercial satellite ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  9. Artificial Intelligence-based Recommender for Model-Based Systems Engineering (ARMS)

    SBC: NEXCEPTA INC            Topic: MDA22T002

    There is a critical need for innovative recommendation technology for digital data engineering artifacts and tools. To address this need, we propose design and implement the Artificial Intelligence-based Recommender System for Model-Based Systems Engineering (ARMS) software as a user-personalized context-aware content recommender system solution for Model Based Systems Engineering (MBSE) applicati ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  10. Deep Reinforcement Learning Enabled Warfighter Assistant (DICE)

    SBC: NEXCEPTA INC            Topic: MDA22T004

    Deep reinforcement learning (DRL) provides strong capabilities to make decisions under uncertain and complicated scenarios. However, there is a lack of explainability of DRL when applied to assist warfighters in training and operational scenarios. To address this critical need, we propose to develop Deep Reinforcement Learning Enabled Warfighter Assistant (DICE). The key innovation of DICE is util ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
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