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Revealing chemical reactions of coal pyrolysis with GPU-enabled ReaxFF molecular dynamics and cheminformatics analysis
Alternative TitleMol. Simul.
Li, Xiaoxia1; Mo, Zheng1,2; Liu, Jian1,2; Guo, Li1
2015-02-11
Source PublicationMOLECULAR SIMULATION
ISSN0892-7022
Volume41Issue:1-3Pages:13-27
Abstract

The complex chemistry of coal pyrolysis is difficult to be captured by experimental techniques or simulated with the quantum mechanics computational methods. The emerging of both the large-scale coal models and the promising capability of reactive molecular dynamics (ReaxFF MD) motivated us to develop a new methodology by combining graphics processing unit (GPU)-enabled high performance computing with cheminformatics analysis in order to explore the coal pyrolysis mechanisms using ReaxFF MD. The methodology is rooted in two new software tools, GMD-Reax, the first GPU-enabled ReaxFF MD codes that make it practical to simulate large-scale models (similar to 10,000 atoms) on desktop workstations, and visualisation and analysis of reactive molecular dynamics (VARMD), the first software dedicated to analysis of detailed chemical reactions from the trajectories of ReaxFF MD simulation. With this methodology, reasonable product profiles and gas generation sequences of pyrolysis for bituminous coal models ranging from similar to 1000 to similar to 10,000 atoms (including the system with 28,351 atoms, one of the largest systems used in ReaxFF MD) have been obtained. The complex and detailed chemical reactions directly revealed by VARMD can provide further information on radical behaviours and their connection with pyrolysates. The methodology presented here offers a new and promising approach to systematically understand the complex chemical reactions in thermolysis of very complicated molecular systems.

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The complex chemistry of coal pyrolysis is difficult to be captured by experimental techniques or simulated with the quantum mechanics computational methods. The emerging of both the large-scale coal models and the promising capability of reactive molecular dynamics (ReaxFF MD) motivated us to develop a new methodology by combining graphics processing unit (GPU)-enabled high performance computing with cheminformatics analysis in order to explore the coal pyrolysis mechanisms using ReaxFF MD. The methodology is rooted in two new software tools, GMD-Reax, the first GPU-enabled ReaxFF MD codes that make it practical to simulate large-scale models (similar to 10,000 atoms) on desktop workstations, and visualisation and analysis of reactive molecular dynamics (VARMD), the first software dedicated to analysis of detailed chemical reactions from the trajectories of ReaxFF MD simulation. With this methodology, reasonable product profiles and gas generation sequences of pyrolysis for bituminous coal models ranging from similar to 1000 to similar to 10,000 atoms (including the system with 28,351 atoms, one of the largest systems used in ReaxFF MD) have been obtained. The complex and detailed chemical reactions directly revealed by VARMD can provide further information on radical behaviours and their connection with pyrolysates. The methodology presented here offers a new and promising approach to systematically understand the complex chemical reactions in thermolysis of very complicated molecular systems.

KeywordReaction Mechanism Reaxff Molecular Dynamics Gmd-reax Coal Pyrolysis Simulation Varmd
SubtypeArticle
WOS HeadingsScience & Technology ; Physical Sciences
DOI10.1080/08927022.2014.913789
URL查看原文
Indexed BySCI
Language英语
WOS KeywordFORCE-FIELD ; BLUE-OBELISK ; SIMULATIONS ; MODEL ; COMBUSTION ; CHEMISTRY ; OXIDATION ; REPRESENTATION ; HYDROCARBONS ; MECHANISMS
WOS Research AreaChemistry ; Physics
WOS SubjectChemistry, Physical ; Physics, Atomic, Molecular & Chemical
WOS IDWOS:000350693800003
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/11779
Collection研究所(批量导入)
Affiliation1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Li, Xiaoxia,Mo, Zheng,Liu, Jian,et al. Revealing chemical reactions of coal pyrolysis with GPU-enabled ReaxFF molecular dynamics and cheminformatics analysis[J]. MOLECULAR SIMULATION,2015,41(1-3):13-27.
APA Li, Xiaoxia,Mo, Zheng,Liu, Jian,&Guo, Li.(2015).Revealing chemical reactions of coal pyrolysis with GPU-enabled ReaxFF molecular dynamics and cheminformatics analysis.MOLECULAR SIMULATION,41(1-3),13-27.
MLA Li, Xiaoxia,et al."Revealing chemical reactions of coal pyrolysis with GPU-enabled ReaxFF molecular dynamics and cheminformatics analysis".MOLECULAR SIMULATION 41.1-3(2015):13-27.
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