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240823s2024 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.27482
|2 doi
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|a eng
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|a Moradi, Siyavash
|e verfasserin
|4 aut
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|a Spin parameter optimization for spin-polarized extended tight-binding methods
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|c 2024
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 08.11.2024
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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 Author(s). Journal of Computational Chemistry published by Wiley Periodicals LLC.
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|a We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine. Sensitivity analysis using Sobol indices guides the identification of the most influential parameters for a given reference dataset, allowing for a nuanced understanding of their impact on diverse molecular properties. In the case of the W4-11 dataset, substantial error reduction was achieved, demonstrating the potential of the optimization. Transferability of the optimized spin-polarization constants over different properties, however, is limited, as we demonstrate by applying the optimized parameters on a set of singlet-triplet gaps in carbenes. Further studies on ionization potentials and electron affinities highlight some inherent limitations of current extended tight-binding methods that can not be resolved by simple parameter optimization. We conclude that the significantly improved accuracy strongly encourages the present re-optimization of the spin-polarization constants, whereas the limited transferability motivates a property-specific optimization strategy
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|a Journal Article
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|a benchmark
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|a density functional tight‐binding
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|a parameter optimization
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|a semi‐empirical methods
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|a sensitivity analysis
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|a spin‐polarization
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|a Tomann, Rebecca
|e verfasserin
|4 aut
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| 700 |
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|a Hendrix, Josie
|e verfasserin
|4 aut
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|a Head-Gordon, Martin
|e verfasserin
|4 aut
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| 700 |
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|a Stein, Christopher J
|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), 32 vom: 15. Nov., Seite 2786-2792
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
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|g volume:45
|g year:2024
|g number:32
|g day:15
|g month:11
|g pages:2786-2792
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|u http://dx.doi.org/10.1002/jcc.27482
|3 Volltext
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