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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. Rapid Identification of Effects of Defects within Metal Additive Manufacturing (RIED-AM)

    SBC: Intelligent Automation, Inc.            Topic: N18AT013

    Additive manufacturing (AM) systems, especially metal AM, bring revolutionary capabilities, but suffer from a lack of understanding of the defects that exist within the components. In this research, based on selective experimental study and numerical simulations, we will develop an empirical database of defects and their effects on mechanical properties using Laser Powder Bed Fusion (LPBF) technol ...

    STTR Phase I 2018 Department of DefenseNavy
  2. Advanced Ship-handling Simulators

    SBC: D'Angelo Technologies, LLC            Topic: N18AT014

    There is a need to create an automated, adaptive, real time coaching module that can integrate the Conning Officer Virtual Environment (COVE) along with the associated Intelligent Tutor System (COVE-ITS) and the Conning-Officer Ship Handling Assessment (COSA) together. By automating the evaluation process, Surface Warfare Officers (SWOs) will have the opportunity to use the COVE simulations more f ...

    STTR Phase I 2018 Department of DefenseNavy
  3. Nondestructive Evaluator for Polymer Ablatives (NEPAL)

    SBC: Intelligent Automation, Inc.            Topic: N18AT011

    Materials for thermal protection are required to protect structural components of space vehicles during the re-entry stage, missile launching systems, and solid rocket motors (SRMs). Polymer resins that have high char retention (e.g., phenolic resins) are the most common matrices in the composite materials for rigid thermal protection systems (TPSs) due to their tunable density, lower cost, and hi ...

    STTR Phase I 2018 Department of DefenseNavy
  4. Power and Propulsion System Optimization

    SBC: CORNERSTONE RESEARCH GROUP INC            Topic: N18AT012

    Unmanned underwater vehicles (UUVs) are currently limited in the type of missions they can perform. Limited available power limits which sensors can be run or for how long, and also limits the duration and range of the mission. More efficient propulsion systems would increase the power available to the UUV payload. Improved power distribution systems and control systems would also increase the ava ...

    STTR Phase I 2018 Department of DefenseNavy
  5. Situational Awareness for Mission Critical Ship Systems

    SBC: IERUS TECHNOLOGIES INC            Topic: N18AT009

    The US Navy operates a vast fleet of combat and support vessels with complex power control systems under the control and decision authority of human operators. Several current resources such as SPY-1D radar and Vertical Launch System (VLS) and future resources such as railgun, AMDR, and high energy laser (HEL) are energy hungry, exceeding current and planned power generation capability when deploy ...

    STTR Phase I 2018 Department of DefenseNavy
  6. Information-based Norms on Flow, Operations, and Traffic Over Networks (INFOTON)

    SBC: ISEA TEK, LLC            Topic: N18AT027

    The Internet of Things (IoT) connects people, data, and "things" (e.g., software, sensors, platforms), facilitating the translation of information into actions. Although naval platforms’ networks and communication suites have evolved significantly in the past few years to support such required connectivity, one of the greatest technical challenges still facing the military community is the proce ...

    STTR Phase I 2018 Department of DefenseNavy
  7. High Throughput Static and Dynamic Testing of AM Materials for Uncertainty Quantification and Qualification

    SBC: MRL MATERIALS RESOURCES LLC            Topic: N18AT028

    Qualification of additively manufactured parts is hampered by the inherent uncetainty in properties due to heterogeneity in processing, microstructure, and defects. The proposed effort combines high-throughput testing of static and dynamic properties using tailored sample geometry, fixture design, and load application method with microstructure quantification and analysis. This system will drastic ...

    STTR Phase I 2018 Department of DefenseNavy
  8. Hot Filament CVD technology for disruptive, high-throughput SiC epitaxial growth reactors

    SBC: TRUENANO, INC.            Topic: N18AT004

    TrueNano, Inc. will in collaboration with the University of Colorado and industry partners, develop a novel single-wafer, high-throughput hot filament CDV reactor for the growth of high quality silicon carbide (SiC) epitaxial layers, suitable for the next generation of power electronic devices and systems. This includes the design and simulation of the reactor, the development of a throughput mode ...

    STTR Phase I 2018 Department of DefenseNavy
  9. Twiner

    SBC: SOAR TECHNOLOGY INC            Topic: N18AT019

    We currently lack the ability to holistically and autonomously look across all three layers of cyberspace (persona, logical and physical) and identify interesting patterns, which would give us an edge in understanding complex activities in and through cyberspace. To address this challenge, Soar Technology (SoarTech) and the GeorgiaTech Research Institute (GTRI) propose Twiner, an intelligent syste ...

    STTR Phase I 2018 Department of DefenseNavy
  10. New Integrated Total Design of Unmanned Underwater Vehicles (UUVs) Propulsion System Architecture for Higher Efficiency and Low Noise

    SBC: CONTINUOUS SOLUTIONS LLC            Topic: N18AT012

    In this proposal, a meta model-based scaling law will be used to represent each system component. A components meta model-based scaling law describes the tradeoffs between performance metrics for that component or subsystem as a function of its ratings in relation to the system. This greatly reduces the number of degrees of freedom for each component, and at the same time, retains the information ...

    STTR Phase I 2018 Department of DefenseNavy
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