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

Jinzhe Zeng, Liqun Cao, Mingyuan Xu, Tong Zhu, John Z.H. Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number5713
JournalNature communications
Volume11
Issue number1
DOIs
StatePublished - Dec 2020

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Fingerprint Dive into the research topics of 'Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation'. Together they form a unique fingerprint.

Cite this