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在交叉偶联催化中对膦配体状态和反应性进行单变量分类。

Univariate classification of phosphine ligation state and reactivity in cross-coupling catalysis.

机构信息

Department of Chemistry, Princeton University, Princeton, NJ 08544, USA.

Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA.

出版信息

Science. 2021 Oct 15;374(6565):301-308. doi: 10.1126/science.abj4213. Epub 2021 Oct 14.

Abstract

Chemists often use statistical analysis of reaction data with molecular descriptors to identify structure-reactivity relationships, which can enable prediction and mechanistic understanding. In this study, we developed a broadly applicable and quantitative classification workflow that identifies reactivity cliffs in 11 Ni- and Pd-catalyzed cross-coupling datasets using monodentate phosphine ligands. A distinctive ligand steric descriptor, minimum percent buried volume [% (min)], is found to divide these datasets into active and inactive regions at a similar threshold value. Organometallic studies demonstrate that this threshold corresponds to the binary outcome of bisligated versus monoligated metal and that % (min) is a physically meaningful and predictive representation of ligand structure in catalysis.

摘要

化学家经常使用统计分析反应数据与分子描述符来识别结构反应关系,这可以实现预测和机理理解。在这项研究中,我们开发了一种广泛适用的定量分类工作流程,该流程使用单齿膦配体识别 11 个 Ni 和 Pd 催化交叉偶联数据集中的反应性峭壁。发现一个独特的配体空间位阻描述符,最小百分比埋藏体积 [%(min)],可以将这些数据集划分为活性和非活性区域,其阈值相似。金属有机研究表明,该阈值对应于双配位与单配位金属的二进制结果,并且 %(min)是催化中配体结构的物理意义和可预测表示。

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