激进的
化学
单重态
动能
化学物理
分子动力学
完整活动空间
反应机理
碰撞
光化学
计算化学
原子物理学
密度泛函理论
物理
激发态
经典力学
生物化学
计算机安全
有机化学
基准集
计算机科学
催化作用
作者
Christopher D. Daub,Itai Zakai,Rashid R. Valiev,Vili-Taneli Salo,R. Benny Gerber,Theo Kurtén
摘要
In this paper we study collisions between polyatomic radicals - an important process in fields ranging from biology to combustion. Energy transfer, formation of intermediate complexes and recombination reactions are treated, with applications to peroxy radicals in atmospheric chemistry. Multi-reference perturbation theory, supplemented by coupled-cluster calculations, describes the potential energy surfaces with high accuracy, including the interaction of singlet and triplet spin states during radical recombination. Our multi-reference molecular dynamics (MD) trajectories on methyl peroxy radicals confirm the reaction mechanism postulated in earlier studies. Specifically, they show that if suitable pre-reactive complexes are formed, they will rapidly lead to the formation and subsequent decomposition of tetroxide intermediates. However, generating multi-reference MD trajectories is exceedingly computationally demanding, and we cannot adequately sample the whole conformational space. To answer this challenge, we promote the use of a novel simplified semi-empirical MD methodology. It assumes the collision is governed by two states, a singlet (S0) and a triplet (T1) state. The method predicts differences between collisions on S0 and T1 surfaces, and qualitatively includes not only pre-reactive complex formation, but also recombination processes such as tetroxide formation. Finally, classical MD simulations using force-fields for non-reactive collisions are employed to generate thousands of collision trajectories, to verify that the semi-empirical method is sampling collisions adequately, and to carry out preliminary investigations of larger systems. For systems with low activation energies, the experimental rate coefficient is surprisingly well reproduced by simply multiplying the gas-kinetic collision rate by the simulated probability for long-lived complex formation.
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