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  Complex Reaction Network Thermodynamic and Kinetic Autoconstruction Based on Ab Initio Statistical Mechanics: A Case Study of O2 Activation on Ag4 Clusters

Wang, W., Liu, X., & Pérez-Ríos, J. (2021). Complex Reaction Network Thermodynamic and Kinetic Autoconstruction Based on Ab Initio Statistical Mechanics: A Case Study of O2 Activation on Ag4 Clusters. The Journal of Physical Chemistry A, 125(25), 5670-5680. doi:10.1021/acs.jpca.1c03454.

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 Urheber:
Wang, Weiqi1, Autor           
Liu, Xiangyue1, Autor           
Pérez-Ríos, Jesús1, Autor           
Affiliations:
1Molecular Physics, Fritz Haber Institute, Max Planck Society, ou_634545              

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 Zusammenfassung: An approach based on ab initio statistical mechanics is demonstrated for autoconstructing complex reaction networks. Ab initio molecular dynamics combined with Markov state models are employed to study relevant transitions and corresponding thermodynamic and kinetic properties of a reaction. To explore the capability and flexibility of this approach, we present a study of oxygen activation on Ag4 as a model reaction. Specifically, with the same sampled trajectories, it is possible to study the structural effects and the reaction rate of the cited reaction. The results show that this approach is suitable for automatized construction of reaction networks, especially for non-well-studied reactions, which can benefit from this ab initio molecular dynamics based approach to construct comprehensive reaction networks with Markov state models without prior knowledge about the potential energy landscape.

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Sprache(n): eng - English
 Datum: 2021-06-092021-04-172021-06-162021-07-01
 Publikationsstatus: Erschienen
 Seiten: 11
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1021/acs.jpca.1c03454
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Titel: The Journal of Physical Chemistry A
  Andere : J. Phys. Chem. A
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Columbus, OH : American Chemical Society
Seiten: 11 Band / Heft: 125 (25) Artikelnummer: - Start- / Endseite: 5670 - 5680 Identifikator: ISSN: 1089-5639
CoNE: https://pure.mpg.de/cone/journals/resource/954926947766_4