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ReacNetGenerator: an Automatic Reaction Network Generator for Reactive Molecular Dynamic Simulations

Abstract

Reactive molecular dynamics (MD) simulation makes it possible to study the reaction mechanisms of complex reaction systems at the atomic level. However, the analysis of the MD trajectories which contain thousands of species and reaction pathways has become a major obstacle to the application of reactive MD simulation in large-scale systems. Here, we report the development and application of the Reaction Network Generator (ReacNetGenerator) method. It can automatically extract the reaction network from the reaction trajectory without any predefined reaction coordinates and elementary reaction steps. Molecular species can be automatically identified from the cartesian coordinates of atoms and the hidden Markov model is used to filter the trajectory noises which makes the analysis process easier and more accurate. The ReacNetGenerator has been successfully used to analyze the reactive MD trajectories of the combustion of methane and 4-component surrogate fuel for rocket propellant 3 (RP-3), and it has great advantages in efficiency and accuracy compared to traditional manual analysis.

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Supplementary files

Publication details

The article was received on 15 Sep 2019, accepted on 25 Nov 2019 and first published on 26 Nov 2019


Article type: Paper
DOI: 10.1039/C9CP05091D
Phys. Chem. Chem. Phys., 2019, Accepted Manuscript

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    ReacNetGenerator: an Automatic Reaction Network Generator for Reactive Molecular Dynamic Simulations

    J. Zeng, L. Cao, C. Chin, H. Ren, J. Z.H. Zhang and T. Zhu, Phys. Chem. Chem. Phys., 2019, Accepted Manuscript , DOI: 10.1039/C9CP05091D

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