Interpretation and Automatic Generation of Fermi-Orbital Descriptors.
FLO-SIC
Linnett double-quartet theory
chemical bonding
density functional theory
Journal
Journal of computational chemistry
ISSN: 1096-987X
Titre abrégé: J Comput Chem
Pays: United States
ID NLM: 9878362
Informations de publication
Date de publication:
15 Dec 2019
15 Dec 2019
Historique:
received:
19
02
2019
revised:
13
08
2019
accepted:
14
08
2019
pubmed:
11
9
2019
medline:
11
9
2019
entrez:
11
9
2019
Statut:
ppublish
Résumé
We present an interpretation of Fermi-orbital descriptors (FODs) and argue that these descriptors carry chemical bonding information. We show that a bond order derived from these FODs agrees well with reference values, and highlight that optimized FOD positions used within the Fermi-Löwdin orbital self-interaction correction (FLO-SIC) method correspond to expectations from Linnett's double-quartet theory, which is an extension of Lewis theory. This observation is independent of the underlying exchange-correlation functional, which is shown using the local spin density approximation, the Perdew-Burke-Ernzerhof generalized gradient approximation (GGA), and the strongly constrained and appropriately normed meta-GGA. To make FOD positions generally accessible, we propose and discuss four independent methods for the generation of Fermi-orbital descriptors, their implementation as well as their advantages and drawbacks. In particular, we introduce a re-implementation of the electron force field, an approach based on the centers of mass of orbital densities, a Monte Carlo-based algorithm, and a method based on Lewis-like bonding information. All results are summarized with respect to future developments of FLO-SIC and related methods. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2843-2857Subventions
Organisme : U. S. Department of Energy
Organisme : Office of Science
Organisme : Office of Basic Energy Sciences
ID : #DE-SC0018331
Organisme : Deutsche Forschungsgemeinschaft
ID : KO 1924/9-1
Informations de copyright
© 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
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