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231226s2023 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26890
|2 doi
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|a pubmed24n1139.xml
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|a eng
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|a Maley, Steven M
|e verfasserin
|4 aut
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|a Density functional theory and CCSD(T) evaluation of ionization potentials, redox potentials, and bond energies related to zirconocene polymerization catalysts
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|c 2023
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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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|a Date Completed 06.01.2023
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|a Date Revised 11.01.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2022 Wiley Periodicals LLC.
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|a Quantum-mechanical-based computational design of molecular catalysts requires accurate and fast electronic structure calculations to determine and predict properties of transition-metal complexes. For Zr-based molecular complexes related to polyethylene catalysis, previous evaluation of density functional theory (DFT) and wavefunction methods only examined oxides and halides or select reaction barrier heights. In this work, we evaluate the performance of DFT against experimental redox potentials and bond dissociation enthalpies (BDEs) for zirconocene complexes directly relevant to ethylene polymerization catalysis. We also examined the ability of DFT to compute the fourth atomic ionization potential of zirconium and the effect the basis set selection has on the ionization potential computed with CCSD(T). Generally, the atomic ionization potential and redox potentials are very well reproduced by DFT, but we discovered relatively large deviations of DFT-calculated BDEs compared to experiment. However, evaluation of BDEs with CCSD(T) suggests that experimental values should be revisited, and our CCSD(T) values should be taken as most accurate
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|a Journal Article
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|a DFT
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|a ab initio
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|a benchmarking
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|a bond dissociation enthalpies
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|a redox potentials
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|a zirconocenes
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|a Lief, Graham R
|e verfasserin
|4 aut
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|a Buck, Richard M
|e verfasserin
|4 aut
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|a Sydora, Orson L
|e verfasserin
|4 aut
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|a Yang, Qing
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Bischof, Steven M
|e verfasserin
|4 aut
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| 700 |
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|a Ess, Daniel H
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 44(2023), 4 vom: 05. Feb., Seite 506-515
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
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|g volume:44
|g year:2023
|g number:4
|g day:05
|g month:02
|g pages:506-515
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|u http://dx.doi.org/10.1002/jcc.26890
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