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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.

Displaying 1 - 10 of 5415 results
  1. Toolkit to Produce Common Adaptive Mesh for Virtual Reality-based Multidisciplinary Interactive Design of Naval Aircraft

    SBC: Global Engineering and Materials, Inc.            Topic: N23AT001

    Global Engineering and Materials, Inc. (GEM), along with its team member Professor Ming-Chen Hsu’s research group at Iowa State University (ISU), proposes the development of an innovative and effective octree-based adaptive meshing tool for efficient multi-physics simulations for aircraft design and analysis. The proposed tool is capable of autonomously generating a common mesh from Computer-Aid ...

    STTR Phase I 2023 Department of DefenseNavy
  2. Digital Engineering-Digital Twin-based Machine Control for Adaptive Additive Manufacturing Processing of Metallic Aerospace Components

    SBC: Global Engineering and Materials, Inc.            Topic: N23AT004

    Due to the physical complexity and intrinsic randomness in metal additive manufacturing (AM), the process control is intractable, the part quality is not repeatable, and the existing models fail to give consistent results to guide process design. To address this challenge, Global Engineering and Materials, Inc. (GEM) and its team members propose to develop a digital twin (DT) for AM process to ena ...

    STTR Phase I 2023 Department of DefenseNavy
  3. 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
  4. Microwave Curing Process Modeling for Continuous Carbon Fiber Reinforced Thermoset Composites

    SBC: Global Engineering and Materials, Inc.            Topic: N23AT006

    The NAVY seeks microwave curing process modeling and technology demonstration for the cost-effective fabrication of continuous carbon fiber reinforced thermoset composites with reduced cure time and energy consumption. Despite the relatively extensive research work done for the microwave curing of polymer composites, the technology extension for the fabrication of continuous carbon fiber-reinforce ...

    STTR Phase I 2023 Department of DefenseNavy
  5. Composite Microwave Curing Hybrid Simulation Model

    SBC: TDA RESEARCH, INC.            Topic: N23AT006

    TDA proposes to develop a multi-physics-based model to simulate and optimize the microwave curing process of thick fiber reinforced composites. The primary objective is to improve the manufacturing speed and cost of high-quality carbon fiber reinforced composites by quickly identifying the right processing parameters for a given part during microwave processing. The model will account for the inte ...

    STTR Phase I 2023 Department of DefenseNavy
  6. 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
  7. Discrete Axial Symmetry Accelerated Inverse Design for LWIR Large-diameter Metalenses

    SBC: SNOCHIP INC            Topic: N23AT008

    Designing and simulating large-diameter metalenses in the long-wave infrared (LWIR) range poses significant challenges due to the cost of computation resources involved. To address this challenge, we propose a scalable 3D FDTD inverse design approach that utilizes axial symmetry to enable the development of integrated meta-optics for LWIR. Our approach incorporates discrete axial symmetry and radi ...

    STTR Phase I 2023 Department of DefenseNavy
  8. 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
  9. 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
  10. 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
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