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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. Applying Machine Learning Techniques for Sensitive Spectral Identification and Detection of Hazardous Target Molecules

    SBC: Caelum Research Corporation            Topic: DHS221005

    Our team has conducted a Phase 1 feasibility analysis of developing an Artificial Intelligence (AI) platform to augment and integrate into currently available biological aerosolized detectors in support of DHS and its BioWatchProgram.The BioWatch program was stood up in the Department of Homeland Security (DHS) in 2003.The program currently operates in more than 30 metropolitan jurisdictions and p ...

    SBIR Phase II 2023 Department of Homeland Security
  5. Artificial Intelligence Enabled Screening for Limited Mobility Passengers using Advanced Imaging Technologies

    SBC: Analytical AI, LLC            Topic: DHS221006

    The Transportation Security Administration (TSA) operates security screening for all air passengers of outgoing aircraft. The Air Carrier Access Act of 1986 (ACAA) ensured access to air travel for passengers with disabilities, including mandating equal or similar treatment in the screening process. This ACAA requirement comports with the Americans with Disabilities Act (ADA) which prohibits discri ...

    SBIR Phase II 2023 Department of Homeland Security
  6. A Real-time Hardware-assisted Endpoint Threat Detection Framework

    SBC: TRUSTED SCIENCE AND TECHNOLOGY, INC.            Topic: DHS231001

    IoT devices expose greater security risks due to their limited resources, lack of security functions and maintenance. There is a fast-growing trend for cyber-attacks exploiting IoT system vulnerabilities. software based IoT security solutions cannot meet the stringent requirements of real-time detection high accuracy, and low performance overhead. Our goal is to a multi-level hardware-assisted thr ...

    SBIR Phase I 2023 Department of Homeland Security
  7. Advanced Machine Learning for Explosives Detection

    SBC: STREAMLINE AUTOMATION LLC            Topic: DHS231004

    Transportation Safety Officers (TSOs) currently use a multi-step decision tree to screen and resolve an alarm of a suspicious object in crowded and high-throughput environments, such as aviation and security checkpoints. In high-throughput environments, this can lead to information overload and mental fatigue. Homeland Security desires a more capable integrated Alarm Resolution (AR) sensor suite, ...

    SBIR Phase I 2023 Department of Homeland Security
  8. Simulation-based Transfer-learning for Explosive Alarm Resolution Sensors (STARS)

    SBC: ASSURED INFORMATION SECURITY, INC.            Topic: DHS231004

    Security at transportation checkpoints is a key strategic aspect of the DHS mission of preventing future attacks against the U.S. and its allies. The ability to freely move assets within, into, and out of the nation is paramount to national security. While DHS currently employs highly-effective explosive alarm resolution sensors (AR), these sensors require special training to operate and produce a ...

    SBIR Phase I 2023 Department of Homeland Security
  9. ACIS: A Machine Learning Platform for Chemical Signature and Toxicity Prediction

    SBC: CFD RESEARCH CORPORATION            Topic: DHS231007

    The rapid detection of highly toxic compounds, such as chemical warfare agents, toxic industrial compounds, pharmaceutical-based agents, and non-traditional agents, is paramount to industrial and national security. While multiple chemical detection platforms exist, the ability to detect toxic compounds is fundamentally limited by the available reference database of known chemical signatures. Recen ...

    SBIR Phase I 2023 Department of Homeland SecurityCountering Weapons of Mass Destruction
  10. Active Material Technology to Improve Solar Sail Performance for Space Weather Monitoring

    SBC: NEXOLVE HOLDING CO LLC            Topic: 96

    Development of a reflection control and direction device (RCDD) is proposed. This innovative device will progress the state of the art for propulsion of solar sails used to fly space weather monitoring sensors to sub-LaGrange point orbits for earlier warning times of impending destructive space weather events. A reflection control device (RCD) utilizes polymer dispersed liquid crystal (PDLC) mater ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
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