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使用扩散映射分析氢气燃烧基准数据集的反应动力学

Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset.

作者信息

Ko Taehee, Heindel Joseph P, Guan Xingyi, Head-Gordon Teresa, Williams-Young David B, Yang Chao

机构信息

Department of Mathematics, Penn State University, University Park, Pennsylvania 16802, United States.

Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, California 94720, United States.

出版信息

J Chem Theory Comput. 2023 Sep 12;19(17):5872-5885. doi: 10.1021/acs.jctc.3c00426. Epub 2023 Aug 16.

Abstract

We use local diffusion maps to assess the quality of two types of collective variables (CVs) for a recently published hydrogen combustion benchmark dataset that contains ab initio molecular dynamics (MD) trajectories and normal modes along minimum energy paths. This approach was recently advocated in for assessing CVs and analyzing reactions modeled by classical MD simulations. We report the effectiveness of this approach to molecular systems modeled by quantum ab initio MD. In addition to assessing the quality of CVs, we also use global diffusion maps to perform committor analysis as proposed in. We show that the committor function obtained from the global diffusion map allows us to identify transition regions of interest in several hydrogen combustion reaction channels.

摘要

我们使用局部扩散映射来评估最近发布的氢燃烧基准数据集的两种集体变量(CV)的质量,该数据集包含从头算分子动力学(MD)轨迹和沿最小能量路径的简正模式。这种方法最近被提倡用于评估CV和分析由经典MD模拟建模的反应。我们报告了这种方法对由量子从头算MD建模的分子系统的有效性。除了评估CV的质量,我们还使用全局扩散映射来进行文献中提出的反应概率分析。我们表明,从全局扩散映射获得的反应概率函数使我们能够识别几个氢燃烧反应通道中感兴趣的过渡区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca19/10500976/65ce774d4d78/ct3c00426_0002.jpg

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