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Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural Network Potential: CHD(3) + Cu(111)
[Image: see text] An accurate description of reactive scattering of molecules on metal surfaces often requires the modeling of energy transfer between the molecule and the surface phonons. Although ab initio molecular dynamics (AIMD) can describe this energy transfer, AIMD is at present untractable...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477808/ https://www.ncbi.nlm.nih.gov/pubmed/30922058 http://dx.doi.org/10.1021/acs.jpclett.9b00560 |
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author | Gerrits, N. Shakouri, Khosrow Behler, Jörg Kroes, Geert-Jan |
author_facet | Gerrits, N. Shakouri, Khosrow Behler, Jörg Kroes, Geert-Jan |
author_sort | Gerrits, N. |
collection | PubMed |
description | [Image: see text] An accurate description of reactive scattering of molecules on metal surfaces often requires the modeling of energy transfer between the molecule and the surface phonons. Although ab initio molecular dynamics (AIMD) can describe this energy transfer, AIMD is at present untractable for reactions with reaction probabilities smaller than 1%. Here, we show that it is possible to use a neural network potential to describe a polyatomic molecule reacting on a mobile metal surface with considerably reduced computational effort compared to AIMD. The highly activated reaction of CHD(3) on Cu(111) is used as a test case for this method. It is observed that the reaction probability is influenced considerably by dynamical effects such as the bobsled effect and surface recoil. A special dynamical effect for CHD(3) + Cu(111) is that a higher vibrational efficacy is obtained for two quanta in the CH stretch mode than for a single quantum. |
format | Online Article Text |
id | pubmed-6477808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-64778082019-04-24 Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural Network Potential: CHD(3) + Cu(111) Gerrits, N. Shakouri, Khosrow Behler, Jörg Kroes, Geert-Jan J Phys Chem Lett [Image: see text] An accurate description of reactive scattering of molecules on metal surfaces often requires the modeling of energy transfer between the molecule and the surface phonons. Although ab initio molecular dynamics (AIMD) can describe this energy transfer, AIMD is at present untractable for reactions with reaction probabilities smaller than 1%. Here, we show that it is possible to use a neural network potential to describe a polyatomic molecule reacting on a mobile metal surface with considerably reduced computational effort compared to AIMD. The highly activated reaction of CHD(3) on Cu(111) is used as a test case for this method. It is observed that the reaction probability is influenced considerably by dynamical effects such as the bobsled effect and surface recoil. A special dynamical effect for CHD(3) + Cu(111) is that a higher vibrational efficacy is obtained for two quanta in the CH stretch mode than for a single quantum. American Chemical Society 2019-03-28 2019-04-18 /pmc/articles/PMC6477808/ /pubmed/30922058 http://dx.doi.org/10.1021/acs.jpclett.9b00560 Text en Copyright © 2019 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes. |
spellingShingle | Gerrits, N. Shakouri, Khosrow Behler, Jörg Kroes, Geert-Jan Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural Network Potential: CHD(3) + Cu(111) |
title | Accurate Probabilities for Highly Activated Reaction
of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural
Network Potential: CHD(3) + Cu(111) |
title_full | Accurate Probabilities for Highly Activated Reaction
of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural
Network Potential: CHD(3) + Cu(111) |
title_fullStr | Accurate Probabilities for Highly Activated Reaction
of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural
Network Potential: CHD(3) + Cu(111) |
title_full_unstemmed | Accurate Probabilities for Highly Activated Reaction
of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural
Network Potential: CHD(3) + Cu(111) |
title_short | Accurate Probabilities for Highly Activated Reaction
of Polyatomic Molecules on Surfaces Using a High-Dimensional Neural
Network Potential: CHD(3) + Cu(111) |
title_sort | accurate probabilities for highly activated reaction
of polyatomic molecules on surfaces using a high-dimensional neural
network potential: chd(3) + cu(111) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477808/ https://www.ncbi.nlm.nih.gov/pubmed/30922058 http://dx.doi.org/10.1021/acs.jpclett.9b00560 |
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