Unsleber Jan P, Reiher Markus
Laboratory for Physical Chemistry, ETH Zurich, 8093 Zurich, Switzerland; email:
Annu Rev Phys Chem. 2020 Apr 20;71:121-142. doi: 10.1146/annurev-physchem-071119-040123. Epub 2020 Feb 19.
Modern computational chemistry has reached a stage at which massive exploration into chemical reaction space with unprecedented resolution with respect to the number of potentially relevant molecular structures has become possible. Various algorithmic advances have shown that such structural screenings must and can be automated and routinely carried out. This will replace the standard approach of manually studying a selected and restricted number of molecular structures for a chemical mechanism. The complexity of the task has led to many different approaches. However, all of them address the same general target, namely to produce a complete atomistic picture of the kinetics of a chemical process. It is the purpose of this overview to categorize the problems that should be targeted and to identify the principal components and challenges of automated exploration machines so that the various existing approaches and future developments can be compared based on well-defined conceptual principles.
现代计算化学已经发展到一个阶段，即能够以前所未有的分辨率对化学反应空间进行大规模探索，涉及潜在相关分子结构的数量。各种算法的进步表明，这种结构筛选必须且能够自动化并常规进行。这将取代手动研究化学机理中选定且数量有限的分子结构的标准方法。任务的复杂性导致了许多不同的方法。然而，它们都针对同一个总体目标，即生成化学过程动力学的完整原子图像。本综述的目的是对应针对的问题进行分类，并确定自动探索机器的主要组成部分和挑战，以便能够基于明确的概念原则对各种现有方法和未来发展进行比较。
