Double hybrids and time-dependent density functional theory: An implementation and benchmark on charge transfer excited states.

DFT TD-DFT charge transfer excitations double hybrids

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 May 2020
Historique:
received: 25 11 2019
revised: 29 01 2020
accepted: 30 01 2020
pubmed: 20 2 2020
medline: 20 2 2020
entrez: 20 2 2020
Statut: ppublish

Résumé

In this paper we present the implementation and benchmarking of a Time Dependent Density Functional Theory approach in conjunction with Double Hybrid (DH) functionals. We focused on the analysis of their performance for through space charge-transfer (CT) excitations which are well known to be very problematic for commonly used functionals, such as global hybrids.Two different families of functionals were compared, each of them containing pure, hybrid and double-hybrid functionals.The results obtained show that, beside the robustness of the implementation, these functionals provide results with an accuracy comparable to that of adjusted range-separated functionals, with the relevant difference that for DHs no parameter is tuned on specific compounds thus making them more appealing for a general use. Furthermore, the algorithm described and implemented is characterized by the same computational cost scaling as that of the ground state algorithm employed for MP2 and double hybrids.

Identifiants

pubmed: 32073175
doi: 10.1002/jcc.26170
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1242-1251

Subventions

Organisme : Agence Nationale de la Recherche
ID : ANR-14-CE05-0002
Organisme : H2020 European Research Council
ID : 648558

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2020 Wiley Periodicals, Inc.

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Auteurs

Alistar Ottochian (A)

Chimie ParisTech, PSL Research University, CNRS, Institute of Chemistry for Life and Health Sciences, Paris, France.

Carmela Morgillo (C)

Chimie ParisTech, PSL Research University, CNRS, Institute of Chemistry for Life and Health Sciences, Paris, France.

Ilaria Ciofini (I)

Chimie ParisTech, PSL Research University, CNRS, Institute of Chemistry for Life and Health Sciences, Paris, France.

Michael J Frisch (MJ)

Gaussian, Inc., Wallingford, Connecticut.

Giovanni Scalmani (G)

Gaussian, Inc., Wallingford, Connecticut.

Carlo Adamo (C)

Chimie ParisTech, PSL Research University, CNRS, Institute of Chemistry for Life and Health Sciences, Paris, France.
Institut Universitaire de France, Paris, France.

Classifications MeSH