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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. Enhanced Sensor Resource Management Utilizing Bayesian Inference

    SBC: GCAS, Inc.            Topic: N19AT002

    This proposal describes the use of machine learning, data mining and Bayesian inference algorithms for incorporation into a surveillance aircraft cognitive radar system. The need for incorporation of higher-order uncertainty distributions will also be assessed. This will result in enhanced sensor resource management capability for surveillance aircraft radar.

    STTR Phase I 2019 Department of DefenseNavy
  2. Human Performance Optimization

    SBC: HVMN Inc.            Topic: SOCOM17C001

    During altitude-induced hypoxia, operator cognitive and physical capacity degrades, compromising individual and team performance. Cognitive degradation is linked to falling brain energy levels, increased reliance on anaerobic energy production and lactate accumulation. Ketones are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies demonstrated that ...

    STTR Phase II 2019 Department of DefenseSpecial Operations Command
  3. Carbon Nanotube FET Modeling and RF circuits

    SBC: CARBON TECHNOLOGY INC            Topic: AF18BT006

    Carbon nanotubes (CNTs) have great potential for high performance RF applications. Theoretical study has shown that the electrical current in a CNT field effect transistor (CFET) is intrinsically linear. Today, linearity is the underlying limitation in increasing the data transport densities of wireless networks. The complex modulation protocols used to achieve higher data rates requires linear am ...

    STTR Phase II 2019 Department of DefenseAir Force
  4. Clearance of Aircraft Stores Carriage under Uncertainty

    SBC: CMSOFT, INC.            Topic: AF18BT008

    The main objective of this STTR effort is three-fold. First, to develop and demonstrate in Phase I a Bayesian methodology exploiting flight test data in order to identify critical store carriage tests and clear non-critical store carriage configurations by updated analysis. Second, to extend in Phase II the scope of this methodology to viscous flows with analysis enriched using analytical sensitiv ...

    STTR Phase I 2019 Department of DefenseAir Force
  5. Predictive Graph Convolutional Networks

    SBC: Arete Associates            Topic: N19AT017

    The US Navy’s mission to maintain, train and equip combat-ready Naval forces requires that decision makers have situational awareness of the capabilities, limitations, vulnerabilities/opportunities for adversarial and allied forces. An incomplete or inaccurate understanding of the current landscape and associated trends could lead to suboptimal mission readiness and outcomes. Analysts need tools ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Seamless Wireless Charging of Micro and Small Unmanned Aerial System Through Local Power Transmission Infrastructure

    SBC: EH GROUP INC            Topic: N19AT019

    Wireless charging of unmanned aerial system (UAS) platforms from the environment has the potential to greatly increase flight and mission times. A promising option is to use electromagnetic fields from the power transmission infrastructure as an energy source. EH Group and the University of Alabama propose a design for UAS wireless charging in the near-field environment of the commercial power tra ...

    STTR Phase I 2019 Department of DefenseNavy
  7. Data Analytics and Machine Learning Toolkit to Accelerate Materials Design and Processing Development

    SBC: CFD RESEARCH CORPORATION            Topic: N19AT020

    Navy has identified refractory high entropy alloy (RHEA) and metal additive manufacturing as two potential areas of interest. This includes designing new RHEA and optimizing metal additive manufacturing with specific material property requirements. Developing materials and processes via applying traditional experimentation and process optimization techniques is painfully slow due to the large numb ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Integrated photonic Raman sensor on a chip

    SBC: PARTOW TECHNOLOGIES LLC            Topic: N19AT023

    A photonic integrated spectrometer based on high-index contrast thin film platform is proposed for Raman signal processing. Raman signal generation on the chip via waveguide collection integrated with a spectrometer is proposed to increase the efficiency and signal to noise ratio and significantly reduce cost and the size of Raman sensor systems. All components of the proposed Raman detection syst ...

    STTR Phase I 2019 Department of DefenseNavy
  9. Compact and Low-cost High Performance Spectrometer Sensor based on Integrated Photonics Technology

    SBC: ULTRA-LOW LOSS TECHNOLOGIES LLC            Topic: N19AT023

    Ultra-Low Loss Technologies (ULL Technologies) is proposing in collaboration with Prof. Arka Majumdar from University of Washington (UW), to develop a compact, low-cost spectrometer module to be used for chemical sensing applications and to be fabricated using the process design kit (PDK) available through AIM Photonics multi-project wafer run (MPW). The team will combine ULL Technologies expertis ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Multi-lingual Social-media Crowd Manipulation Detector (MSCMD)

    SBC: BCL Technologies            Topic: N19AT024

    In this SBIR, BCL proposes developing a Multi-lingual Social-media Crowd Manipulation Detector (MSCMD). The MSCMD will use natural language processing techniques to detect terms that arouse emotion using information out of context to trigger reaction from the audience and move them to act.The MSCMD will operate in Asian languages using a Natural Language Processor for each language. The MSCMD will ...

    STTR Phase I 2019 Department of DefenseNavy
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