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Accelerated experimental materials discovery through integration with theory and artificial intelligence

Gregoire, John (2018) Accelerated experimental materials discovery through integration with theory and artificial intelligence. In: 255th American Chemical Society National Meeting & Exposition, March 18-22, 2018, New Orleans, LA. http://resolver.caltech.edu/CaltechAUTHORS:20180412-075704210

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Abstract

Solar photochem. is a promising energy technol. limited by the performance and compatibility of its component materials. A variety of approaches for discovering solar fuels materials have been and continue to be deployed, with photoactive components proving to be particularly difficult to identify due to their need to simultaneously exhibit a broad range of chem. and phys. properties. The development of high throughput screening techniques in the Joint Center for Artificial Photosynthesis has opened new avenues for materials discovery with unique challenges and opportunities. Most notably, rapid synthesis and screening enables evaluation of candidate materials proposed by high throughput computational screening, and some expts. produce datasets that are too large and complex to be interpreted by std. techniques or even expert materials scientists, motivating the development of artificial intelligence algorithms. Integration of the resp. computational techniques with expts. accelerates both materials discovery and understanding of known materials, creating new paradigms for conducting materials research and developing multi-functional materials.


Item Type:Conference or Workshop Item (Paper)
Related URLs:
URLURL TypeDescription
https://global.acs.org/events/255th-acs-national-meeting-exposition/OrganizationConference Website
ORCID:
AuthorORCID
Gregoire, John0000-0002-2863-5265
Additional Information:© 2018 American Chemical Society.
Group:JCAP
Record Number:CaltechAUTHORS:20180412-075704210
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180412-075704210
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85773
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:12 Apr 2018 15:02
Last Modified:12 Apr 2018 15:02

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