Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality

Catalyst optimization for enantioselective transformations has traditionally relied on empirical evaluation of catalyst properties. Although this approach has been successful in the past it is intrinsically limited and inefficient. To address this problem, our laboratory has developed a fully inform...

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Bibliographic Details
Main Authors: N. Ian Rinehart, Andrew F. Zart, Scott E. Denmark
Format: Article
Language:deu
Published: Swiss Chemical Society 2021-08-01
Series:CHIMIA
Subjects:
Online Access:https://www.ingentaconnect.com/contentone/scs/chimia/2021/00000075/f0020007/art00002