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User-Defined Electrostatic Potentials in DFT Supercell Calculations: Implementation and Application to Electrified

Samuel Mattoso1, Jing Yang1, Florian Deißenbeck1

  • 1Max Planck Institute for Sustainable Materials, Max-Planck-Straße 1, 40237 Düsseldorf, Germany.

Journal of Chemical Theory and Computation
|February 25, 2026
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Summary
This summary is machine-generated.

We developed a new method to apply electric fields in density functional theory (DFT) calculations. This approach simplifies studying materials under bias and electrochemical interfaces using the VASP software.

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Area of Science:

  • Computational materials science
  • Quantum chemistry
  • Surface science

Background:

  • Applying electric fields in density functional theory (DFT) is crucial for simulating electrochemical and interfacial phenomena.
  • Current methods often require complex modifications to DFT codes.
  • A flexible and accessible implementation is needed for broader application.

Purpose of the Study:

  • To present a novel implementation for supercell DFT calculations under arbitrary electric fields.
  • To provide necessary corrections for energies and forces in electric field calculations.
  • To enable user-defined electric fields within the standard VASP software via a Python interface.

Main Methods:

  • Implementation of electric field calculations within a supercell framework.
  • Utilizing the VASP-Python interface for seamless integration with VASP.
  • Derivation and application of energy and force correction schemes.

Main Results:

  • Successful implementation of arbitrary electric field application in DFT.
  • Demonstration of the method's utility through diverse case studies.
  • Validation of energy and force corrections for accurate simulations.

Conclusions:

  • The presented VASP-Python based method offers a flexible and user-friendly approach to DFT calculations with electric fields.
  • This facilitates research in electrified surfaces, field ion microscopy, and electrochemical interfaces.
  • The implementation simplifies the study of materials under applied bias and in electrochemical environments.