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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Interlaminar Mode I and Mode II Fracture Toughnesses in Ceramic Matrix Composites (CMCs)

    SBC: ALPHASTAR TECHNOLOGY SOLUTIONS LLC            Topic: N13AT008

    The Alpha STAR Corporation and the University of Akron STTR Phase II proposal will establish ASTM standards test methods to determine relevant ceramics matrix composites (CMC) delamination crack growth resistance (CGR) material properties (Mode I & Mode II)under service load temperature conditions. Phase Ii will expand on Phase I results, conclusions & recommendations. Emphasis will be on testing ...

    STTR Phase II 2015 Department of DefenseNavy
  2. LCS Radar Modeling for Training (LRMT)

    SBC: Intelligent Automation, Inc.            Topic: N14AT012

    We propose the design and development of LCS radar modeling for training a radar modeling engine that capture the effects of environment, weather, jamming/interference and operator actions on radar display. The purpose of this engine is to reduce or eliminate the need for live training by faithfully capturing the scenarios encountered by a radar operator. The primary target radars for the propose ...

    STTR Phase II 2016 Department of DefenseNavy
  3. LEARNING-BASED APPROACH FOR RELEVANT DATA EXTRACTION (LARDE)

    SBC: ROBOTIC RESEARCH OPCO LLC            Topic: N13AT016

    Robotic Research, LLC (RR) and Southwest Research Institute (SwRI) are creating a prototype Learning-based Approach for Relevant Data Extraction (LARDE). The LARDE framework is a data extraction and handling framework that can intelligently reduce the volume of raw data from on-board sensors, and organize and persistently store the reduced relevant dataset.

    STTR Phase II 2015 Department of DefenseNavy
  4. Marburg Virus Prophylactic Medical Countermeasure

    SBC: Flow Pharma, Inc.            Topic: CBD18A002

    Through this STTR contract, we propose to evaluate the efficacy of our vaccine, FlowVax Marburg, in nonhuman primates (NHPs). This will be achieved through four Tasks. In Task 1, we will manufacture the vaccine in a quantity sufficient for the animal studies. In Task 2, we will perform MHC genotyping on a representative population of NHPs and, based on results, select a set of MHC-matched NHPs for ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  5. Marburg Virus Prophylactic Medical Countermeasure

    SBC: MAPP BIOPHARMACEUTICAL, INC.            Topic: CBD18A002

    There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...

    STTR Phase II 2020 Department of DefenseOffice for Chemical and Biological Defense
  6. Nondestructive Evaluator for Polymer Ablatives (NEPAL)

    SBC: Intelligent Automation, Inc.            Topic: N18AT011

    Materials for thermal protection are required to protect structural components of missile launching systems, space vehicles during the re-entry stage, 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 II 2020 Department of DefenseNavy
  7. Nonlinear-DSP-Enabled RF-Photonic Link

    SBC: RAM PHOTONICS LLC            Topic: N14AT023

    Digital equalizers have been the major enablers in RF communications in terms of managing component imperfections and channel impairments. Specifically, the ever increasing processing power of the dedicating computing processors has availed a steady increase in the ability of complex communication systems to deal with impairments as well as allowing higher capacities in the information transfer.On ...

    STTR Phase II 2016 Department of DefenseNavy
  8. Object Cueing Using Biomimetic Approaches to Visual Information Processing

    SBC: MAYACHITRA, INC.            Topic: N14AT008

    Thousands of years of evolution have produced the human vision system that computers cannot replicate well. Humans are still unsurpassed in their ability to search for objects in visual scenes. To successfully detect objects in cluttered scenes, the human brain is thought to rely on multiple factors: prior probabilities of object occurrence, global scene statistics and object co-occurrence. Machin ...

    STTR Phase II 2015 Department of DefenseNavy
  9. Optimization of Fatigue Test Signal Compression Using The Wavelet Transform

    SBC: ATA ENGINEERING, INC.            Topic: N18BT029

    ATA Engineering has developed a wavelet-based damage squeezing methodology for generating optimally compressed fatigue test signals that produce an equivalent amount of fatigue damage in a predictably reduced amount of time compared to the baseline (uncompressed) signals. Fatigue-critical signal characteristics (e.g., magnitude, phase, frequency, and sequencing relationships) are identified in the ...

    STTR Phase II 2020 Department of DefenseNavy
  10. Proactive Contextual Decision Support for Decision Making Under Uncertainty

    SBC: PACIFIC SCIENCE & ENGINEERING GROUP, INC.            Topic: N13AT020

    Current decision tools often omit important situational context. Unfortunately, this can lead to dangerous and costly errors, as context drives decision making. For example, in operational navigation planning tasks, decisions must be made that rely on multiple information sources of different fidelities and uncertainties. Furthermore, after obtaining additional information the necessity for replan ...

    STTR Phase II 2015 Department of DefenseNavy
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