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  5. Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation

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Preprint
English
2025

Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation

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0 Files

English
2025
arXiv (Cornell University)
DOI: 10.48550/arxiv.2501.02435

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Kresse Georg
Kresse Georg

University of Vienna

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Sudarshan Vijay
Martin Schlipf
Henrique Miranda
+4 more

Abstract

Density functional theory (DFT) calculations of charged molecules and surfaces are critical to applications in electro-catalysis, energy materials and related fields of materials science. DFT implementations such as the Vienna ab-initio Simulation Package (VASP) compute the electrostatic potential under 3D periodic boundary conditions, necessitating charge neutrality. In this work, we implement 0D and 2D periodic boundary conditions to facilitate DFT calculations of charged molecules and surfaces respectively. We implement these boundary conditions using the Coulomb kernel truncation method. Our implementation computes the potential under 0D and 2D boundary conditions by selectively subtracting unwanted long-range interactions in the potential computed under 3D boundary conditions. By combining the Coulomb kernel truncation method with a computationally efficient padding approach, we remove nonphysical potentials from vacuum in 0D and 2D systems. To illustrate the computational efficiency of our method, we perform large supercell calculations of the formation energy of a charged chlorine defect on a sodium chloride (001) surface and perform long time-scale molecular dynamics simulations on a stepped gold (211) | water electrode-electrolyte interface.

How to cite this publication

Sudarshan Vijay, Martin Schlipf, Henrique Miranda, Ferenc Karsai, Merzuk Kaltak, Martijn Marsman, Kresse Georg (2025). Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation. arXiv (Cornell University), DOI: 10.48550/arxiv.2501.02435.

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Publication Details

Type

Preprint

Year

2025

Authors

7

Datasets

0

Total Files

0

Language

English

Journal

arXiv (Cornell University)

DOI

10.48550/arxiv.2501.02435

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