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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. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. Radar for Accelerated Breaching of Concrete Structures (RABCS)

    SBC: PHYSICAL SCIENCES INC.            Topic: A21CT012

    The US Army and other DOD forces occasionally need to breach reinforced concrete structures. There are several existing methods to assess the structural properties and predict reinforcement but each of these methods has specific deficiencies (e.g. to loud, too large, too inconsistent). Ground penetrating radar is a promising technology for non-destructive concrete substructure characterization but ...

    STTR Phase II 2023 Department of DefenseArmy
  7. Measurement of the Plasma Environment in a Rb DPAL

    SBC: PHYSICAL SCIENCES INC.            Topic: MDA22T008

    Diode-pumped alkali lasers (DPAL) offer the potential for scaling to high output powers required for directed energy weapons systems. As power-scaling studies have progressed, increasing concern has emerged about uncertainty in the roles of higher-lying states and the degree of ionization, and their effects on device performance. Ionization by multi-photon absorption and collisional energy pooling ...

    STTR Phase I 2023 Department of DefenseMissile Defense Agency
  8. 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
  9. Scalable production of sequence-defined biopolymers containing multiple distinct non-canonical amino acids in recoded cell and cell-free systems

    SBC: PEARL BIO, INC.            Topic: OSD22B001

    Engineered biological systems can enable the template-directed synthesis of biopolymers such as proteins and peptides with desirable material properties and functions. The cellular engine of this process, the ribosome and associated translation apparatus, drives the polymerization of hundreds to thousands of amino acid monomers into sequence-defined biopolymers with speed, efficiency, and accuracy ...

    STTR Phase I 2023 Department of DefenseOffice of the Secretary of Defense
  10. AI-Driven Cyber Operations

    SBC: AUTONOMOUS CYBER, INC.            Topic: AFX23DTCSO1

    Autonomous Cyber ("AC") is building an artificial intelligence product, "the AC model," that autonomously conducts hacking operations. The AC model accepts english language instruction from a human operator as input, e.g. "scan this target," and translate

    STTR Phase I 2023 Department of DefenseAir Force
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