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构建和解释火山图和活性图,以探索均相催化剂领域。

Constructing and interpreting volcano plots and activity maps to navigate homogeneous catalyst landscapes.

机构信息

Laboratory for Computational Molecular Design (LCMD), Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

National Center for Competence in Research-Catalysis (NCCR-Catalysis), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

出版信息

Nat Protoc. 2022 Nov;17(11):2550-2569. doi: 10.1038/s41596-022-00726-2. Epub 2022 Aug 17.

Abstract

Volcano plots and activity maps are powerful tools for studying homogeneous catalysis. Once constructed, they can be used to estimate and predict the performance of a catalyst from one or more descriptor variables. The relevance and utility of these tools has been demonstrated in several areas of catalysis, with recent applications to homogeneous catalysts having been pioneered by our research group. Both volcano plots and activity maps are built from linear free energy scaling relationships that connect the value of a descriptor variable(s) with the relative energies of other catalytic cycle intermediates/transition states. These relationships must be both constructed and postprocessed appropriately to obtain the resulting plots/maps; this process requires careful execution to obtain meaningful results. In this protocol, we provide a step-by-step guide to building volcano plots and activity maps using curated reaction profile data. The reaction profile data are obtained using density functional theory computations to model the catalytic cycle. In addition, we provide volcanic, a Python code that automates the steps of the process following data acquisition. Unlike the computation of individual reaction energy profiles, our tools lead to a holistic view of homogeneous catalyst performance that can be broadly applied for both explanatory and screening purposes.

摘要

火山图和活性图是研究均相催化的有力工具。一旦构建完成,它们可以用于从一个或多个描述符变量来估计和预测催化剂的性能。这些工具的相关性和实用性已在催化的几个领域得到证明,最近我们的研究小组率先将其应用于均相催化剂。火山图和活性图都是从线性自由能标度关系构建的,这些关系将描述符变量的值与其他催化循环中间体/过渡态的相对能量联系起来。为了获得最终的图/图,必须适当地构建和后处理这些关系;这个过程需要仔细执行才能获得有意义的结果。在本方案中,我们提供了使用经过策展的反应剖面数据构建火山图和活性图的分步指南。反应剖面数据是使用密度泛函理论计算获得的,用于模拟催化循环。此外,我们还提供了 Python 代码 volcanic,它可以自动执行数据采集后的步骤。与单个反应能量剖面的计算不同,我们的工具可以对均相催化剂性能进行整体观察,可广泛用于解释和筛选目的。

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