直觉
计算机科学
机制(生物学)
反应机理
软件
反应中间体
量子
基本反应
化学
生化工程
纳米技术
计算化学
催化作用
物理
材料科学
工程类
认知科学
量子力学
心理学
生物化学
动力学
程序设计语言
作者
Amanda Dewyer,Alonso J. Argüelles,Paul M. Zimmerman
摘要
The area of reaction mechanism discovery simulation has taken considerable strides in recent years. Novel methods that make hypotheses for elementary steps and complementary means for reaction path and transition state (TS) optimization are lowering the amount of chemical intuition and user effort required to explore reaction networks. The resulting networks lead from reactants to reactive intermediates and products, and are becoming closer representations of physical mechanisms involved in experiments. This review describes several of these approaches, which are categorized based on their overarching TS finding strategies. Future advances are discussed that may revolutionize the ability of simulation to fully predict not just the reaction mechanism but reaction outcomes. WIREs Comput Mol Sci 2018, 8:e1354. doi: 10.1002/wcms.1354 This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Software > Quantum Chemistry Software > Simulation Methods
科研通智能强力驱动
Strongly Powered by AbleSci AI