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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. Microwave Radiator for Curing Polymer Composites (MRCPC)

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT006

    The Navy requires a low-cost, industrial microwave system for curing aerospace composite materials. In this Phase I STTR proposal, Physical Sciences Inc outlines the development of a microwave applicator that uses low-cost RF sources and can be installed in heritage autoclaves for curing large aerospace composite parts. This technology has the potential to improve cured mechanical properties, and ...

    STTR Phase I 2023 Department of DefenseNavy
  2. Large-scale Meta-optic Optimization

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT008

    Physical Sciences Inc. (PSI), in collaboration with Stanford University, will develop an electromagnetic simulation package used for the development and optimization of large-scale meta-optics, and demonstrate the functionality of the package in the long-wave infrared (LWIR). Our team will combine recent progress in physics-augmented deep learning neural networks with rigorous far-field diffractio ...

    STTR Phase I 2023 Department of DefenseNavy
  3. Gradient index for reduced integration costs (GRIN-RICH)

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT011

    Physical Sciences Inc. partnered with Alfred University will develop an F/1, 90 degree full field of view MWIR/SWIR gradient index (GRIN) compound lens for reduced size and lens integration cost. The element-by-element achromatization and athermalization of GRIN provide useful performance improvements to GRIN systems. Element count is reduced (= 2), diversity of optical material needed is fixed, a ...

    STTR Phase I 2023 Department of DefenseNavy
  4. Sensor Modality Translation through Contrastive Deep Learning

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT013

    Physical Sciences Inc. (PSI), in collaboration with the University of Rhode Island, proposes to develop an advanced algorithm suite for data translation across sensing modalities to support the development of automated target recognition and classification algorithms for Unmanned Underwater Vehicles. The proposed Deep Diffusion Sensor Translation (DDST) leverages recent advancements in generative ...

    STTR Phase I 2023 Department of DefenseNavy
  5. HTPB Predictive Model Development for Rocket Motors

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT018

    Physical Sciences Inc. and Purdue University propose to develop a chemical model that accurately predicts the performance of hydroxyl terminated polybutadiene (HTPB) polymer commonly used as a propellant binder in rocket motors. The model will utilize chemical and physical data from HTPB feedstock to predict propellant cure kinetics, mechanical properties, and aging performance. The model will inc ...

    STTR Phase I 2023 Department of DefenseNavy
  6. Autonomous, Long Duration, Directional Ambient Sound Sensor

    SBC: TRITON SYSTEMS, INC.            Topic: N23AT021

    Triton Systems is developing an autonomous, long-duration, directional ambient sound sensing system capable of being integrated into a variety of platforms including floats, gliders, and ocean observation buoys. It will include onboard processing to provide sound intensity levels as a function of frequency and direction (both horizontal and vertical) to establish the background soundscape in the e ...

    STTR Phase I 2023 Department of DefenseNavy
  7. Velocimetric Flash LiDAR for Underwater Autonomous Vehicles

    SBC: PHYSICAL SCIENCES INC.            Topic: N23AT023

    Physical Sciences Inc (PSI), in cooperation with the University of Rhode Island (URI), will develop a Velocimetric Flash LiDAR (VFL) for Underwater Autonomous Vehicles (UAV).  The VFL will combine (and extend) two capabilities previously developed and demonstrated at PSI: an underwater flash lidar (UWFL) and an expendable seawater optical attenuation meter (K-meter).  K-meter mode is a high spee ...

    STTR Phase I 2023 Department of DefenseNavy
  8. TacDS- A Wearable Haptic-Based Alerting and SA System for Submarine Watchstander Augmentation

    SBC: HUMAN SYSTEMS INTEGRATION INC            Topic: N23AT027

    Human Systems Integration (HSI), a leading developer and provider of garment-integrated, wearable electronic solutions, will design, develop and field a comfortable, affordable and robust Tactical Digital Sidekick (TacDS) garment platform that integrates any desired number of tactile/haptic actuators of the same or different technologies that dramatically enhances situation awareness (SA) for Subm ...

    STTR Phase I 2023 Department of DefenseNavy
  9. Sidekick Mobile-DSSWA

    SBC: APTIMA INC            Topic: N23AT027

    The Navy has rapidly increased submarine capabilities in recent decades, with watchstanders now monitoring more systems and data sources than ever before. In addition to increasing the attentional and cognitive demands on watchstanders, this dynamic creates a balancing act between physical payload and the crew size necessary to handle the systems and meet mission requirements. Cognitive assistance ...

    STTR Phase I 2023 Department of DefenseNavy
  10. Learning Architecture for Short-Term Forecasts of Cloud Characteristics Using Satellites (LAST FOCUS)

    SBC: NEXTGEN FEDERAL SYSTEMS LLC            Topic: N23AT025

    The Learning Architecture for Short-Term Forecasts of Cloud Characteristics Using Satellites (LAST FOCUS) introduces a novel approach and state-of-the-art ML methodologies to forecast cloud properties including, but not limited to, ceiling, optical depth, phases, and reflectance.  Using a suite of cloud-observing geostationary and Low-Earth Orbiting (LEO) satellites, atmospheric profiles, and an ...

    STTR Phase I 2023 Department of DefenseNavy
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