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231225s2017 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.24866
|2 doi
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|a pubmed24n0913.xml
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|a (DE-627)NLM274117517
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|a (NLM)28736893
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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 |
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|a Gruden, Maja
|e verfasserin
|4 aut
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|a Benchmarking density functional tight binding models for barrier heights and reaction energetics of organic molecules
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|c 2017
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Revised 06.03.2020
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2017 Wiley Periodicals, Inc.
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|a Density Functional Tight Binding (DFTB) models are two to three orders of magnitude faster than ab initio and Density Functional Theory (DFT) methods and therefore are particularly attractive in applications to large molecules and condensed phase systems. To establish the applicability of DFTB models to general chemical reactions, we conduct benchmark calculations for barrier heights and reaction energetics of organic molecules using existing databases and several new ones compiled in this study. Structures for the transition states and stable species have been fully optimized at the DFTB level, making it possible to characterize the reliability of DFTB models in a more thorough fashion compared to conducting single point energy calculations as done in previous benchmark studies. The encouraging results for the diverse sets of reactions studied here suggest that DFTB models, especially the most recent third-order version (DFTB3/3OB augmented with dispersion correction), in most cases provide satisfactory description of organic chemical reactions with accuracy almost comparable to popular DFT methods with large basis sets, although larger errors are also seen for certain cases. Therefore, DFTB models can be effective for mechanistic analysis (e.g., transition state search) of large (bio)molecules, especially when coupled with single point energy calculations at higher levels of theory. © 2017 Wiley Periodicals, Inc
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|a Journal Article
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|a Research Support, N.I.H., Extramural
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a DFTB
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|a barrier heights
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| 650 |
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|a reaction energies
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| 650 |
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|a transition state optimization
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|a Andjeklović, Ljubica
|e verfasserin
|4 aut
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| 700 |
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|a Jissy, Akkarapattiakal Kuriappan
|e verfasserin
|4 aut
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| 700 |
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|a Stepanović, Stepan
|e verfasserin
|4 aut
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| 700 |
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|a Zlatar, Matija
|e verfasserin
|4 aut
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| 700 |
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|a Cui, Qiang
|e verfasserin
|4 aut
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| 700 |
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|a Elstner, Marcus
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 38(2017), 25 vom: 30. Sept., Seite 2171-2185
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
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|g volume:38
|g year:2017
|g number:25
|g day:30
|g month:09
|g pages:2171-2185
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|u http://dx.doi.org/10.1002/jcc.24866
|3 Volltext
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