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arXiv 2102.02682physics.chem-phastro-ph.GA
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用于 H2CO + OH 反应低温环聚合物分子动力学的神经网络势能面

Neural Network Potential Energy Surface for the low temperature Ring Polymer Molecular Dynamics of the H2CO + OH reaction

Pablo del Mazo-Sevillano, Alfredo Aguado, Octavio Roncero

AI总结:

本文构建 H2CO + OH 反应的新型神经网络势能面,通过透热矩阵加多体 NN 项消除虚假长程作用,并利用准经典轨迹与 RPMD 计算速率常数、解释低温捕获共振。

摘要:

本文针对 H2CO + OH 反应生成 HCO + H2O 和 HCOOH + H 的反应过程,提出了一种新的势能面(PES)并开展了动力学研究。在这项工作中,识别出对称适配神经网络(NN)方案中虚假长程相互作用的一个来源,这会阻碍其直接应用于低温动力学研究。为此,本文将 PES 划分为一个透热矩阵加上一个 NN 多体项,并采用一种新型人工神经网络方案进行拟合,以避免虚假渐近相互作用。在该 PES 上开展了准经典轨迹和环聚合物分子动力学(RPMD)研究,以评估不同反应过程的速率常数对温度的依赖关系,结果显示其与现有实验数据吻合良好。特别值得关注的是,对 RPMD 研究中此前已识别的捕获机制所做的分析;该机制可归因于与环聚合物简正模激发相关的虚假共振。

英文摘要:

A new potential energy surface (PES) and dynamical study are presented of the reactive process between H2CO + OH towards the formation of HCO + H2O and HCOOH + H. In this work a source of spurious long range interactions in symmetry adapted neural network (NN) schemes is identified, what prevents their direct application for low temperature dynamical studies. For this reason, a partition of the PES into a diabatic matrix plus a NN many body term has been used fitted with a novel artificial neural networks scheme that prevents spurious asymptotic interactions. Quasi-classical trajectory and ring polymer molecular dynamics (RPMD) studies have been carried on this PES to evaluate the rate constant temperature dependence for the different reactive processes, showing a good agreement with the available experimental data. Of special interest is the analysis of the previously identified trapping mechanism in the RPMD study, which can be attributed to spurious resonances associated to excitations of the normal modes of the ring polymer.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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