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PyCDFT: A Python package for constrained density functional theory.
Ma, He; Wang, Wennie; Kim, Siyoung; Cheng, Man-Hin; Govoni, Marco; Galli, Giulia.
Afiliação
  • Ma H; Department of Chemistry, University of Chicago, Chicago, Illinois, USA.
  • Wang W; Materials Science Division and Center for Molecular Engineering, Argonne National Laboratory, Lemont, Illinois, USA.
  • Kim S; Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, USA.
  • Cheng MH; Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, USA.
  • Govoni M; Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, USA.
  • Galli G; Materials Science Division and Center for Molecular Engineering, Argonne National Laboratory, Lemont, Illinois, USA.
J Comput Chem ; 41(20): 1859-1867, 2020 Jul 30.
Article em En | MEDLINE | ID: mdl-32497321
ABSTRACT
We present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object-oriented, customizable implementation of CDFT, and allows for both single-point self-consistent-field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn-Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first-principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available at https//dx.doi.org/10.5281/zenodo.3821097.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article