Ismail Idil, Chantreau Majerus Raphael, Habershon Scott
Department of Chemistry, University of Warwick, CoventryCV4 7AL, United Kingdom.
J Phys Chem A. 2022 Oct 13;126(40):7051-7069. doi: 10.1021/acs.jpca.2c06408. Epub 2022 Oct 3.
Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as "virtual reaction vessels" for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space.
基于图的描述符，如键序矩阵和邻接矩阵，提供了一种简单而紧凑的分子结构分类方法；此外，此类描述符可轻松用于编排化学反应（即键的形成和断裂）。因此，已经开发了许多基于图的方法，目标是实现生成化学反应网络模型过程的自动化，该模型描述了给定反应物物种集合中可能的机理化学。在此，我们概述这些基于图的反应发现方案的演变，特别强调将基于图的方法与半经验和电子结构计算、最小能量路径优化以及过渡态搜索相结合的最新方法。通过均相催化和星际化学中的代表性例子，我们强调这些方案如何越来越多地充当用于探究机理问题的“虚拟反应容器”。最后，我们强调仍然存在的挑战，包括化学准确性和计算速度问题，以及处理可及化学反应空间巨大规模的固有挑战。
