Advancement of the Homogeneous Background Method for the Computational Simulation of Electrochemical Interfaces

TL;DR

This paper introduces an improved homogeneous background method for DFT simulations of electrochemical interfaces, eliminating the need for energy corrections and active electron fraction specification, thus broadening its applicability.

Contribution

The authors develop an advanced HBM that simplifies charged interface simulations by removing the need for boundary location and energy corrections, especially in complex systems with adsorbates or explicit solvents.

Findings

Excellent agreement with Poisson-Boltzmann model in interfacial charging

Applicable to various metal electrodes in high-dielectric solvents

Facilitates simulations without specifying active electron fraction

Abstract

Computational studies of electrochemical interfaces based on density-functional theory (DFT) play an increasingly important role in present research on electrochemical processes for energy conversion and storage. The homogeneous background method (HBM) offers a straightforward approach to charge the electrochemical system within DFT simulations, but it typically requires the specification of the "active" fraction of excess electrons based on a certain choice of the electrode-electrolyte boundary location, which can be difficult in presence of electrode-surface adsorbates or explicit solvent molecules. In this work, we present a methodological advancement of the HBM, both facilitating and extending its applicability. The advanced version neither requires energy corrections nor the specification of the "active" fraction of excess electrons, providing a versatile and readily available method for the simulation of charged interfaces also when adsorbates or explicit solvent molecules are present. Our computational DFT results for Pt(111), Au(111) and Li(100) metal electrodes in high-dielectric-constant solvents demonstrate an excellent agreement in the interfacial charging characteristics obtained from simulations with the advanced HBM in comparison with the (linearized) Poisson-Boltzmann model (PBM).