DOI: 10.1039/c7sc01052d. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

10.1039/c7sc01052d

Crossref journal-article

Royal Society of Chemistry (RSC)

Chemical Science (292)

Abstract

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD).

Bibliography

Yang, Q., Sing-Long, C. A., & Reed, E. J. (2017). Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics. Chemical Science, 8(8), 5781â5796.

Authors 3

Qian Yang (first)
Carlos A. Sing-Long (additional)
Evan J. Reed (additional)

References 33 Referenced 19

10.1063/1.3686505 / AIP Conf. Proc. by Rice (2012)
A. F. Voter , Radiation Effects in Solids, 2007, ch. 1, pp. 1–23 / Radiation Effects in Solids by Voter (2007)
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{'key': 'C7SC01052D-(cit16)/*[position()=1]', 'first-page': '795', 'volume': '14', 'author': 'Turanyi', 'year': '1990', 'journal-title': 'New J. Chem.'} / New J. Chem. by Turanyi (1990)
10.1016/j.combustflame.2008.11.001 / Combust. Flame by Nagy (2009)
M. Allen and D.Tildesley, Computer Simulation of Liquids, Oxford University Press, New York, 1991 / Computer Simulation of Liquids by Allen (1991)
10.1137/060666457 / SIAM Rev. by Higham (2008)
10.1016/0021-9991(76)90041-3 / J. Comput. Phys. by Gillespie (1976)
10.1006/jcph.1995.1039 / J. Comput. Phys. by Plimpton (1995)
http://lammps.sandia.gov
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10.1021/jp901353a / J. Phys. Chem. A by Zhang (2009)
10.1021/jp308068c / J. Phys. Chem. A by Qi (2012)
10.1063/1.2220036 / J. Chem. Phys. by Goldman (2006)
10.1063/1.1378322 / J. Chem. Phys. by Gillespie (2001)
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Dates

Type	When
Created	8 years, 2 months ago (June 19, 2017, 11:33 a.m.)
Deposited	1 year, 1 month ago (June 24, 2024, 5:11 p.m.)
Indexed	2 weeks, 1 day ago (Aug. 6, 2025, 8:13 a.m.)
Issued	8 years, 7 months ago (Jan. 1, 2017)
Published	8 years, 7 months ago (Jan. 1, 2017)
Published Online	8 years, 7 months ago (Jan. 1, 2017)

Funders 2

National Nuclear Security Administration 10.13039/100006168
Region: Americas
gov (National government)
Labels8
1. U.S. National Nuclear Security Administration
2. Department of Energy's National Nuclear Security Administration
3. Department of Energy/National Nuclear Security Administration
4. National Nuclear Security Administration (NNSA), DOE
5. NNSA
6. DOE NNSA
7. DOE - NNSA
8. DOE/NNSA
Awards1
1. DE-NA0002007
Division of Materials Research 10.13039/100000078
Region: Americas
gov (National government)
Labels4
1. NSF Division of Materials Research
2. Materials Research
3. DMR
4. MPS/DMR
Awards1
1. DMR-1455050

BibTeX

@article{Yang_2017, title={Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics}, volume={8}, ISSN={2041-6539}, url={http://dx.doi.org/10.1039/c7sc01052d}, DOI={10.1039/c7sc01052d}, number={8}, journal={Chemical Science}, publisher={Royal Society of Chemistry (RSC)}, author={Yang, Qian and Sing-Long, Carlos A. and Reed, Evan J.}, year={2017}, pages={5781–5796} }

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