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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. Conformal Passivation of High Aspect Ratio HgCdTe Surfaces by ALD Using a Novel Cd-Precursor

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: A13AT013

    The goal of the proposed program is to identify an effective passivation material and develop a capable passivation methodology to protect highly reticulated HgCdTe surfaces. The proposed passivation material and technique using highly conformal atomic layer deposition (ALD) will allow the DOD to develop high-performance infrared focal plane array detectors that can operate under wider operating c ...

    STTR Phase I 2013 Department of DefenseArmy
  2. Contamination-free, Ultra-rapid Reactive Chemical Mechanical Polishing (RCMP) of GaN substrates

    SBC: Sinmat Inc            Topic: MDA09T001

    Gallium Nitride (GaN) substrates are ideal materials for fabrication of high-power and high-frequency devices based on III-V materials. The current state-of-the-art Chemical Mechanical Polishing (CMP) methods are plagued by several challenges, including, surface charge affects due to surface contamination, and sub-surface damages, which can limit the quality of III-V devices. Furthermore, there is ...

    STTR Phase I 2010 Department of DefenseMissile Defense Agency
  3. Coupled Cluster Methods for Multi-Reference Applications

    SBC: ACES QC, LC            Topic: AF09BT40

    The objective of Phase I is to identify the strengths and weaknesses of the various multi-reference coupled-cluster (MRCC) methods that have been proposed for the description of molecular states depending upon near degeneracies and non-dynamic electron correlation. Such effects are encountered in bond breaking, at transition states, for complex open shell systems like transition metal atoms, and f ...

    STTR Phase I 2010 Department of DefenseAir Force
  4. CRANE: Cervical Readiness Using Analytics and Non-Invasive Evaluation

    SBC: APTIMA INC            Topic: DHA18B001

    Current cervical spine assessment methodologies are focused on subjective measures (i.e. pain reports) and range-of-motion (ROM) measures that only measure maximum head excursion and reach, but not dynamic motion. Due to report bias and existing incentive

    STTR Phase I 2019 Department of DefenseDefense Health Agency
  5. Cryodeposit Mitigation and Removal Techniques for Radiometric Calibration Chambers

    SBC: OPTICAL SCIENCES CORPORATION            Topic: AF12BT10

    ABSTRACT: Optical Sciences Corporation (OSC) and the University of Alabama in Huntsville"s Center for Applied Optics (UAH/CAO) will demonstrate the feasibility and present a plan for developing optical instrumentation for the monitoring, mitigation, and removal of cryodeposits accumulated on optical and mechanical surfaces in cryogenic-vacuum radiometric calibration chambers. OSC will investigat ...

    STTR Phase I 2013 Department of DefenseAir Force
  6. CUPID: Cognitive-service Utilized for Proactive Intelligent Decision-support

    SBC: APTIMA INC            Topic: N13AT020

    The Navy"s mission success increasingly relies on complex decision support systems and automation. Navy command and control systems must provide the users with the right information, at the right time, depending on the context in which they are operating, and must do it in a proactive manner. Today, massive quantities of data are passed blindly between nodes, with no ability to adapt the delivery ...

    STTR Phase I 2013 Department of DefenseNavy
  7. Cyber Adversary Discovery Engine (CADE)

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: N19AT021

    We propose to design and build the Cyber Adversary Discovery Engine (CADE) for forensic cyber analysis. CADE combines expressive behavioral modeling technology with machine learning to automatically recognize adversary behaviors, goals and tactics, techniques and procedures (TTPs). CADE can further automatically recognize changes in adversary TTPs that occur in forensic data. A key technical capab ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Data Analytics and Machine Learning Toolkit to Accelerate Materials Design and Processing Development

    SBC: CFD RESEARCH CORPORATION            Topic: N19AT020

    Navy has identified refractory high entropy alloy (RHEA) and metal additive manufacturing as two potential areas of interest. This includes designing new RHEA and optimizing metal additive manufacturing with specific material property requirements. Developing materials and processes via applying traditional experimentation and process optimization techniques is painfully slow due to the large numb ...

    STTR Phase I 2019 Department of DefenseNavy
  9. Decision Support for Operators of Fully Autonomous Systems using RESTORE: Robust Execution System for Trusted Operation in Relevant Environments

    SBC: SCIENTIFIC SYSTEMS CO INC            Topic: N18BT032

    SSCI and MIT (Prof. Julie Shah) propose to develop and test a system that provides real-time assurance and trust in decisions made by autonomous collaborating vehicles. The proposed system is referred to as the RESTORE and represents a decision support tool which facilitates decision making by the operator in cases when decisions by the Collaborative Autonomy (CA) system results in deviations from ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Deep Agent with Self-learning for Human Events Recognition (DASHER)

    SBC: BOSTON FUSION CORP            Topic: AF18BT002

    Automated analysis of human activities and events on the ground from aerial videos is key to extracting critical situational awareness and gathering actionable intelligence. It poses multiple challenges, including dynamic backgrounds that can be confused with foreground, multiple simultaneous activities in the field of view, occurrence of unknown activities, and large data volume and velocity. The ...

    STTR Phase I 2019 Department of DefenseAir Force
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