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231226s2022 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26952
|2 doi
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|a eng
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|a Omodemi, Oluwaseun
|e verfasserin
|4 aut
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|a Permutationally invariant polynomial representation of polarizability tensor surfaces for linear regression analysis
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|c 2022
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|a Text
|b txt
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 18.07.2022
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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 A linearly parameterized functional form for a Cartesian representation of molecular dipole polarizability tensor surfaces (PTS) is described. The proposed expression for the PTS is a linearization of the recently reported power series ansatz of the original Applequist model, which by construction is non-linear in parameter space. This new approach possesses (i) a unique solution to the least-squares fitting problem; (ii) a low level of the computational complexity of the resulting linear regression procedure, comparable to those of the potential energy and dipole moment surfaces; and (iii) a competitive level of accuracy compared to the non-linear PTS model. Calculations of CH4 PTS, with polarizabilities fitted to 9000 training set points with the energies up to 14,000 cm-1 show an impressive level of accuracy of the linear PTS model obtained with ~1600 parameters: ~1% versus 0.3% RMSE for the non-linear vs. linear model on a test set of 1000 configurations
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|a Journal Article
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|a Applequist model
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|a ab initio molecular dynamics
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|a linear regression
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|a permutationally invariant polynomials
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|a polarizability tensor
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|a Kaledin, Martina
|e verfasserin
|4 aut
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|a Kaledin, Alexey L
|e verfasserin
|4 aut
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 43(2022), 22 vom: 15. Aug., Seite 1495-1503
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnas
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|g volume:43
|g year:2022
|g number:22
|g day:15
|g month:08
|g pages:1495-1503
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|u http://dx.doi.org/10.1002/jcc.26952
|3 Volltext
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