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240229s2024 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.27332
|2 doi
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|a pubmed24n1392.xml
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|a (DE-627)NLM369041992
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|a (NLM)38414274
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Ghysbrecht, Simon
|e verfasserin
|4 aut
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|a Thermal isomerization rates in retinal analogues using Ab-Initio molecular dynamics
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|c 2024
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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 Revised 29.04.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2024 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
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|a For a detailed understanding of chemical processes in nature and industry, we need accurate models of chemical reactions in complex environments. While Eyring transition state theory is commonly used for modeling chemical reactions, it is most accurate for small molecules in the gas phase. A wide range of alternative rate theories exist that can better capture reactions involving complex molecules and environmental effects. However, they require that the chemical reaction is sampled by molecular dynamics simulations. This is a formidable challenge since the accessible simulation timescales are many orders of magnitude smaller than typical timescales of chemical reactions. To overcome these limitations, rare event methods involving enhanced molecular dynamics sampling are employed. In this work, thermal isomerization of retinal is studied using tight-binding density functional theory. Results from transition state theory are compared to those obtained from enhanced sampling. Rates obtained from dynamical reweighting using infrequent metadynamics simulations were in close agreement with those from transition state theory. Meanwhile, rates obtained from application of Kramers' rate equation to a sampled free energy profile along a torsional dihedral reaction coordinate were found to be up to three orders of magnitude higher. This discrepancy raises concerns about applying rate methods to one-dimensional reaction coordinates in chemical reactions
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|a Journal Article
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|a DFT
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|a DFTB
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4 |
|a Kramers
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| 650 |
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4 |
|a metadynamics
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| 650 |
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|a rate theory
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| 650 |
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4 |
|a retinal
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| 650 |
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|a square‐root approximation
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| 650 |
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4 |
|a umbrella sampling
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| 700 |
1 |
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|a Keller, Bettina G
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 45(2024), 16 vom: 15. Apr., Seite 1390-1403
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:45
|g year:2024
|g number:16
|g day:15
|g month:04
|g pages:1390-1403
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.27332
|3 Volltext
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