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pro vyhledávání: '"Tseo, Yitong"'
Atom-by-atom design of metal oxide catalysts for the oxygen evolution reaction with machine learning
Autor:
Lunger, Jaclyn R., Karaguesian, Jessica, Chun, Hoje, Peng, Jiayu, Tseo, Yitong, Shan, Chung Hsuan, Han, Byungchan, Shao-Horn, Yang, Gomez-Bombarelli, Rafael
Green hydrogen production is crucial for a sustainable future, but current catalysts for the oxygen evolution reaction (OER) suffer from slow kinetics, despite many efforts to produce optimal designs, particularly through the calculation of descripto
Externí odkaz:
http://arxiv.org/abs/2305.19930
Clinical trials predicate subject eligibility on a diversity of criteria ranging from patient demographics to food allergies. Trials post their requirements as semantically complex, unstructured free-text. Formalizing trial criteria to a computer-int
Externí odkaz:
http://arxiv.org/abs/2006.07296
Akademický článek
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Autor:
Zhang X; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, U.S.A.; Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, U.S.A., Tseo Y; Computational and Systems Biology Program, Massachusetts Institute of Technology, U.S.A., Bai Y; Broad Institute of MIT and Harvard, U.S.A., Chen F; Broad Institute of MIT and Harvard, U.S.A.; Department of Stem Cell and Regenerative Biology, Harvard University, U.S.A., Uhler C; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, U.S.A.; Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, U.S.A.
Publikováno v:
BioRxiv : the preprint server for biology [bioRxiv] 2024 Jul 25. Date of Electronic Publication: 2024 Jul 25.
