Back to Search Start Over

PyCDFT: A Python package for constrained density functional theory

Authors :
Ma, He
Wang, Wennie
Kim, Siyoung
Cheng, Man-Hin
Govoni, Marco
Galli, Giulia
Source :
Journal of Computational Chemistry, 41, 1859 (2020)
Publication Year :
2020

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://github.com/hema-ted/pycdft/.<br />Comment: main text: 27 pages, 6 figures supplementary: 7 pages, 2 figures

Details

Database :
arXiv
Journal :
Journal of Computational Chemistry, 41, 1859 (2020)
Publication Type :
Report
Accession number :
edsarx.2005.08021
Document Type :
Working Paper
Full Text :
https://doi.org/10.1002/jcc.26354