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Inverse Design of Materials with Lab Automation and AI-driven Experimentation
Document ID
20240011982
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Josh Stuckner
(Glenn Research Center Cleveland, United States)
Diana Santiago-deJesus
(Glenn Research Center Cleveland, United States)
Peter Toma
(University of California, Berkeley Berkeley, United States)
Roberto Obregon
(University of Akron Akron, Ohio, United States)
Jacob Goodin
(University of Akron Akron, Ohio, United States)
Brandon Hearley
(Glenn Research Center Cleveland, United States)
Stephen Xie
(KBR (United States) Houston, Texas, United States)
Date Acquired
September 18, 2024
Subject Category
Chemistry and Materials (General)
Mathematical and Computer Sciences (General)
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: International Materials Application & Technologies Conference and Exposition (IMAT)
Location: Cleveland, OH
Country: US
Start Date: September 30, 2024
End Date: October 3, 2024
Sponsors: ASM International
Funding Number(s)
WBS: 109492.02.03.05.02
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Single Expert
Keywords
automated lab
machine learning
materials science
inverse design
Bayesian optimization
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