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Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation

Combustion is a complex chemical system which involves thousands of chemical reactions and generates hundreds of molecular species and radicals during the process. In this work, a neural network-based molecular dynamics (MD) simulation is carried out to simulate the benchmark combustion of methane....

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Autores principales: Zeng, Jinzhe, Cao, Liqun, Xu, Mingyuan, Zhu, Tong, Zhang, John Z. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658983/
https://www.ncbi.nlm.nih.gov/pubmed/33177517
http://dx.doi.org/10.1038/s41467-020-19497-z
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author Zeng, Jinzhe
Cao, Liqun
Xu, Mingyuan
Zhu, Tong
Zhang, John Z. H.
author_facet Zeng, Jinzhe
Cao, Liqun
Xu, Mingyuan
Zhu, Tong
Zhang, John Z. H.
author_sort Zeng, Jinzhe
collection PubMed
description Combustion is a complex chemical system which involves thousands of chemical reactions and generates hundreds of molecular species and radicals during the process. In this work, a neural network-based molecular dynamics (MD) simulation is carried out to simulate the benchmark combustion of methane. During MD simulation, detailed reaction processes leading to the creation of specific molecular species including various intermediate radicals and the products are intimately revealed and characterized. Overall, a total of 798 different chemical reactions were recorded and some new chemical reaction pathways were discovered. We believe that the present work heralds the dawn of a new era in which neural network-based reactive MD simulation can be practically applied to simulating important complex reaction systems at ab initio level, which provides atomic-level understanding of chemical reaction processes as well as discovery of new reaction pathways at an unprecedented level of detail beyond what laboratory experiments could accomplish.
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spelling pubmed-76589832020-11-17 Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation Zeng, Jinzhe Cao, Liqun Xu, Mingyuan Zhu, Tong Zhang, John Z. H. Nat Commun Article Combustion is a complex chemical system which involves thousands of chemical reactions and generates hundreds of molecular species and radicals during the process. In this work, a neural network-based molecular dynamics (MD) simulation is carried out to simulate the benchmark combustion of methane. During MD simulation, detailed reaction processes leading to the creation of specific molecular species including various intermediate radicals and the products are intimately revealed and characterized. Overall, a total of 798 different chemical reactions were recorded and some new chemical reaction pathways were discovered. We believe that the present work heralds the dawn of a new era in which neural network-based reactive MD simulation can be practically applied to simulating important complex reaction systems at ab initio level, which provides atomic-level understanding of chemical reaction processes as well as discovery of new reaction pathways at an unprecedented level of detail beyond what laboratory experiments could accomplish. Nature Publishing Group UK 2020-11-11 /pmc/articles/PMC7658983/ /pubmed/33177517 http://dx.doi.org/10.1038/s41467-020-19497-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zeng, Jinzhe
Cao, Liqun
Xu, Mingyuan
Zhu, Tong
Zhang, John Z. H.
Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title_full Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title_fullStr Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title_full_unstemmed Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title_short Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
title_sort complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658983/
https://www.ncbi.nlm.nih.gov/pubmed/33177517
http://dx.doi.org/10.1038/s41467-020-19497-z
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