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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26757
|2 doi
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|a pubmed24n1105.xml
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|a (DE-627)NLM331772884
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|a (NLM)34636424
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Schmitz, Gunnar
|e verfasserin
|4 aut
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|a An automatized workflow from molecular dynamic simulation to quantum chemical methods to identify elementary reactions and compute reaction constants
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|c 2021
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 30.12.2021
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|a Date Revised 30.12.2021
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2021 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
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|a We present an automatized workflow which, starting from molecular dynamics simulations, identifies reaction events, filters them, and prepares them for accurate quantum chemical calculations using, for example, Density Functional Theory (DFT) or Coupled Cluster methods. The capabilities of the automatized workflow are demonstrated by the example of simulations for the combustion of some polycyclic aromatic hydrocarbons (PAHs). It is shown how key elementary reaction candidates are filtered out of a much larger set of redundant reactions and refined further. The molecular species in question are optimized using DFT and reaction energies, barrier heights, and reaction rates are calculated. The setup is general enough to include at this stage configurational sampling, which can be exploited in the future. Using the introduced machinery, we investigate how the observed reaction types depend on the gas atmosphere used in the molecular dynamics simulation. For the re-optimization on the DFT level, we show how the additional information needed to switch from reactive force-field to electronic structure calculations can be filled in and study how well ReaxFF and DFT agree with each other and shine light on the perspective of using more accurate semi-empirical methods in the MD simulation
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a DFT
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|a MD simulations
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|a ReaxFF
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| 650 |
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|a automatized workflow
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| 650 |
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|a reaction finder
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| 700 |
1 |
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|a Yönder, Özlem
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Schnieder, Bastian
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Schmid, Rochus
|e verfasserin
|4 aut
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| 700 |
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|a Hättig, Christof
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 42(2021), 32 vom: 15. Dez., Seite 2264-2282
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:42
|g year:2021
|g number:32
|g day:15
|g month:12
|g pages:2264-2282
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|u http://dx.doi.org/10.1002/jcc.26757
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