Stuyver Thijs, Shaik Sason
Institute of Chemistry, The Hebrew University, Jerusalem 91904, Israel.
J Am Chem Soc. 2021 Mar 24;143(11):4367-4378. doi: 10.1021/jacs.1c00307. Epub 2021 Mar 9.
To develop an approach to pre-emptively predict the existence of major reaction modes associated with a chemical system, based on exclusive consideration of reactant properties, we build herein on the valence bond perspective of chemical reactivity. In this perspective, elementary chemical reactions are conceptualized as crossovers between individual diabatic/semilocalized states. As demonstrated, the spacings between the main diabatic states in the reactant geometries-the so-called promotion energies-contain predictive information about which types of crossings are likely to occur on a potential energy surface, facilitating the identification of potential transition states and products. As an added bonus, promotion energy analysis provides direct insight into the impact of environmental effects, e.g., the presence of (polar) solvents and/or (local) electric fields, on a mechanistic landscape. We illustrate the usefulness of our approach by focusing on model nucleophilic and electrophilic aromatic substitution reactions. Overall, we envision our analysis to be useful not only as a tool for conceptualizing individual mechanistic landscapes but also as a facilitator of systematic reaction-network exploration efforts. Because the emerging VB descriptors are computationally inexpensive (and can alternatively be inferred through machine learning), they could be evaluated on-the-fly as part of an exploration algorithm. The so-predicted reaction modes could subsequently be examined in detail through computationally more-demanding methods.
为了开发一种基于仅考虑反应物性质来预先预测与化学体系相关的主要反应模式存在的方法，我们在此基于化学反应性的价键观点进行构建。从这个观点来看，基本化学反应被概念化为各个非绝热/半局域化状态之间的交叉。如所证明的，反应物几何构型中主要非绝热状态之间的间距——即所谓的激发能——包含了关于在势能面上可能发生哪种类型交叉的预测信息，有助于识别潜在的过渡态和产物。另外，激发能分析能直接洞察环境效应（例如（极性）溶剂和/或（局部）电场的存在）对反应机理图景的影响。我们通过聚焦于模型亲核和亲电芳香取代反应来说明我们方法的实用性。总体而言，我们设想我们的分析不仅作为一种概念化单个反应机理图景的工具有用，而且作为系统反应网络探索努力的促进因素也有用。由于新出现的价键描述符计算成本低（并且可以通过机器学习推断），它们可以作为探索算法的一部分即时评估。随后可以通过计算要求更高的方法详细检查如此预测的反应模式。
