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Award Data
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.
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Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia
SBC: HVMN Inc. Topic: SOCOM17C001In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Human Performance Optimization
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Marburg Virus Prophylactic Medical Countermeasure
SBC: Flow Pharma, Inc. Topic: CBD18A002Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...
STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense -
STability and Resilience Analysis Technology for Urban Systems analysis (STRATUS)
SBC: Systems & Technology Research LLC Topic: ST17C003The unique scale, population density, complexity, and connectedness of megacities requires new tools for detecting and assessing risks related to civil unrest, rule of law, terrorism, and other sources of instability, and for understanding the underlying dynamics. In addition, gray zone operations pose a new and strategically important class of threats to the stability of nation states and cities ...
STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency -
Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.
SBC: X-Wave Innovations, Inc. Topic: DLA18A001Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...
STTR Phase I 2018 Department of DefenseDefense Logistics Agency -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Rapid Discovery of Evasive Satellite Behaviors
SBC: APPLIED DEFENSE SOLUTIONS, INC. Topic: AF17CT02This is a prototype system that will take raw observation data, detect and characterize maneuvers, and use reinforcement learning to understand and react to evasive RSO behaviors in near real time. This will provide a framework to evaluate autonomous behavior strategies, such a safety, effectiveness, and robustness to manipulation. This work will enable surveillance operators to distinguish betwee ...
STTR Phase I 2018 Department of DefenseAir Force -
Adaptive Markov Inference Game Optimization (AMIGO) for Rapid Discovery of Evasive Satellite Behaviors
SBC: INTELLIGENT FUSION TECHNOLOGY, INC. Topic: AF17CT02Space superiority requires space protection and space situational awareness (SSA), which rely on rapid and accurate space object behavioral and operational intent discovery. The focus of this project is to develop a stochastic approach for rapid discovery of evasive satellite behaviors. Designing the innovative decision support tool has numerous challenges: (i) partial observable actions; (ii) eva ...
STTR Phase I 2018 Department of DefenseAir Force -
Verification and Validation of Algorithms for Resilient Complex Software Controlled Systems
SBC: APPLIED DEFENSE SOLUTIONS, INC. Topic: AF17CT05In response to the challenges described in AF173-CT05, Applied Defense Solutions (ADS) and the University of New Mexico (UNM) (equivalently, the ADS Team) propose to research and develop innovative validation and verification (V&V) algorithms for spacecraft GN&C. The ADS Team is unique in that it brings operational flight GN&C software experience (ADS) with cutting edge research on algorithm V&V ( ...
STTR Phase I 2018 Department of DefenseAir Force -
Novel Structure-Preserving Algorithms for Accurate Rocket Trajectory Propagation
SBC: OPTIMAL SYNTHESIS INC. Topic: MDA17T002The Department of Defense uses large-scale high-resolution federated simulations to propagate rocket vehicle trajectories. Runge-Kutta methods have served as a de-facto standard while conducting such simulations. However, there are several challenges while using Runge-Kutta methods for this task. Firstly, there should be exact time-step matching between federates, otherwise the states have to be i ...
STTR Phase I 2018 Department of DefenseMissile Defense Agency