Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities.

Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities.
复制标题

DOI:
10.1021/acs.jpca.2c06408
复制
发表时间:
2022-10-13
影响因子:
2.9
通讯作者:
Habershon, Scott
Habershon, Scott
中科院分区:
化学3区
文献类型:
--
作者:
Ismail, Idil;Majerus, Raphael Chantreau;Habershon, Scott

文献摘要

参考文献

被引文献

相似文献

基于图的描述符,例如键序矩阵和邻接矩阵,提供了一种简单而紧凑的对分子结构进行分类的方法;此外,这种描述符可以容易地用于对化学反应进行分类(即,键合和断裂)。因此,已经开发了许多基于图的方法,其目标是使生成化学反应网络模型的过程自动化,该化学反应网络模型描述给定的一组反应物物种中的可能的机械化学。在这里,我们概述了这些基于图形的反应发现计划的演变,特别强调最近的方法,将基于图形的方法与半经验和从头计算的电子结构计算,最小能量路径的改进,和过渡态搜索。使用代表性的例子,从均相催化和星际化学,我们强调这些计划如何越来越多地充当“虚拟反应容器”的询问机制的问题。最后,我们强调了仍然存在的挑战,包括化学精度和计算速度的问题,以及处理可访问的化学反应空间的巨大规模的固有挑战。
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 ab initio 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.
用于大规模反应网络的化学一致的图形结构应用于固体溶解度相间的形成。
DOI: 10.1039/d0sc05647b
发表时间: 2021-02-24
期刊: Chemical science
影响因子: 8.4
作者:
Blau SM;Patel HD;Spotte-Smith EWC;Xie X;Dwaraknath S;Persson KA
通讯作者: Persson KA
DOI: 10.1002/qua.10709
发表时间: 2003-09-20
影响因子: 2.2
作者:
Bofill, JM
通讯作者: Bofill, JM
DOI: 10.1021/jp070186p
发表时间: 2007-07-05
影响因子: 2.9
作者:
Aradi, B.;Hourahine, B.;Frauenheim, Th.
通讯作者: Frauenheim, Th.
DOI: 10.1021/acs.jpcc.7b02133
发表时间: 2017-05-11
影响因子: 3.7
作者:
Goldsmith, C. Franklin;West, Richard H.
通讯作者: West, Richard H.
DOI: 10.1021/acs.jpca.0c09168
发表时间: 2021-02-11
影响因子: 2.9
作者:
Ford, Jason;Seritan, Stefan;Martinez, Todd J.
通讯作者: Martinez, Todd J.