Computational design of high-performance ligand for enantioselective Markovnikov hydroboration of aliphatic terminal alkenes
Trial-and-error methods to identify suitable ligands for transition metal catalysis are time-consuming and costly. Here, the authors developed a combined experimental and computational approach to design chiral ligands for the enantioselective Markovnikov hydroboration of aliphatic terminal alkenes.
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2018-06-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-018-04693-9 |
Summary: | Trial-and-error methods to identify suitable ligands for transition metal catalysis are time-consuming and costly. Here, the authors developed a combined experimental and computational approach to design chiral ligands for the enantioselective Markovnikov hydroboration of aliphatic terminal alkenes. |
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ISSN: | 2041-1723 |