ChemDyME: Kinetically Steered, Automated Mechanism Generation through Combined Molecular Dynamics and Master Equation Calculations

被引:23
作者
Shannon, Robin J. [4 ]
Martinez-Nunez, Emilio [1 ]
Shalashilin, Dmitrii, V [2 ]
Glowacki, David R. [3 ]
机构
[1] Univ Santiago Compostela, Dept Phys Chem, Santiago De Compostela 15705, Spain
[2] Univ Leeds, Sch Chem, Leeds LS2 9JT, W Yorkshire, England
[3] ArtSci Int Fdn, Bristol BS1 4QD, Avon, England
[4] Univ Bristol, Sch Chem, Bristol BS8 1TS, Avon, England
基金
英国工程与自然科学研究理事会;
关键词
MULTIPLE-WELL; CHEMICAL-REACTIONS; TRANSITION-STATES; OH; DISTRIBUTIONS; SIMULATIONS; EXPLORATION; SEARCHES; MODELS; IMPACT;
D O I
10.1021/acs.jctc.1c00335
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
In many scientific fields, there is an interest in understanding the way in which chemical networks evolve. The chemical networks which researchers focus upon have become increasingly complex, and this has motivated the development of automated methods for exploring chemical reactivity or conformational change in a "black-box" manner, harnessing modern computing resources to automate mechanism discovery. In this work, we present a new approach to automated mechanism generation which couples molecular dynamics and statistical rate theory to automatically find kinetically important reactions and then solve the time evolution of the species in the evolving network. The key to this chemical network mapping through combined dynamics and ME simulation approach is the concept of "kinetic convergence", whereby the search for new reactions is constrained to those species which are kinetically favorable at the conditions of interest. We demonstrate the capability of the new approach for two systems, a well-studied combustion system and a multiple oxygen addition system relevant to atmospheric aerosol formation.
引用
收藏
页码:4901 / 4912
页数:12
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