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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)
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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.
An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive ManufacturingSBC: Citrine Informatics, Inc. Topic: N18AT013
In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...STTR Phase I 2018 Department of DefenseNavy
Analysis and Application of Treatments to Mitigate Exfoliation Corrosion (Delamination) of 5XXX Series AluminumSBC: OCEANIT LABORATORIES INC Topic: N18AT016
Oceanit proposes to research and develop chemical or non-chemical methods and processes to impart surface morphology modifications to aluminum-magnesium (Al-Mg) alloys to mitigate and increase the exfoliation corrosion resistance.STTR Phase I 2018 Department of DefenseNavy
SBC: ATA ENGINEERING, INC. Topic: N18BT029
Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...STTR Phase I 2018 Department of DefenseNavy
SBC: COMBUSTION SCIENCE & ENGINEERING, INC. Topic: N17AT003
The ability to predict the ignitibility potential of a combustor at various operating conditions is not practical at this time due to the complexity of this process. Ignition within a gas turbine combustor is dependent on various parameters; including spark (or plasma) energy, flow conditions, fuel/air ratio, and fuel spray density. All these parameters must be properly predicted in order to effec ...STTR Phase II 2018 Department of DefenseNavy