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Title: Computational Methods Enable the Prediction of Improved Catalysts for Nickel-Catalyzed Cross-Electrophile Coupling
Cross-electrophile coupling has emerged as an attractive and efficient method for the synthesis of C(sp2)–C(sp3) bonds. These reactions are most often catalyzed by nickel complexes of nitrogenous ligands, especially 2,2’-bipyridines. Precise prediction, selection, and design of optimal ligands remains challenging, despite significant increases in reaction scope and mechanistic understanding. Molecular parame-terization and statistical modeling provide a path to the development of improved bipyridine ligands that will enhance the selectivity of existing reactions and broaden the scope of electrophiles that can be coupled. Herein, we describe the generation of a computational lig-and library, correlation of observed reaction outcomes with features of the ligands, and in silico design of improved bipyridine ligands for Ni-catalyzed cross-electrophile coupling. The new nitrogen-substituted ligands display a fivefold increase in selectivity for product formation versus homodimerization when compared to the current state of the art. This increase in selectivity and yield was general for several cross-electrophile couplings, including the challenging coupling of an aryl chloride with an N-alkylpyridinium salt.  more » « less
Award ID(s):
1900366 2154502
PAR ID:
10489752
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
American Chemical Society
Date Published:
Journal Name:
Journal of the American Chemical Society
Volume:
146
Issue:
5
ISSN:
0002-7863
Page Range / eLocation ID:
3043 to 3051
Subject(s) / Keyword(s):
organic chemistry catalysis modeling
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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