Interface Properties of the Partially Oxidized Pt(111) Surface Using Hybrid DFT–Solvation Models

Abstract

This article reports a theoretical–computational effort to model the interface between an oxidized platinum surface and aqueous electrolyte. It strives to account for the impact of the electrode potential, formation of surface-bound oxygen species, orientational ordering of near-surface solvent molecules, and metal surface charging on the potential profile along the normal direction. The computational scheme is based on the DFT/ESM-RISM method to simulate the charged Pt(111) surface with varying number of oxygen adatoms in acidic solution. This hybrid solvation method is known to qualitatively reproduce bulk metal properties like the work function. However, the presented calculations reveal that vital interface properties such as the electrostatic potential at the outer Helmholtz plane are highly sensitive to the position of the metal surface slab relative to the DFT-RISM boundary region. Shifting the relative position of the slab also affects the free energy of the system. It follows that there is an optimal distance for the first solvent layer within the ESM-RISM framework, which could be found by optimizing the position of the frozen Pt(111) slab. As it stands, manual sampling of the position of the slab is impractical and betrays the self-consistency of the method. Based on this understanding, we propose the implementation of a free energy optimization scheme of the relative position of the slab in the DFT-RISM boundary region. This optimization scheme could considerably increase the applicability of the hybrid method.

Grand-Canonical Model of Electrochemical Double Layers from a Hybrid Density–Potential Functional

“…In general, the “closest” approach of anions shifts further away from the metal surface as ϕ M decreases, while the opposite applies for cations; see the insets of Figure a,b. It has been shown that the width of the metal–solution gap is crucial to the surface charging relation and the double-layer capacitance of the EDL. ,,, Some previous works assumed a constant value for the vacuum-gap width, − while other works tried to determine the vacuum-gap width by minimizing the grand potential ,, or by using a force balance equation . Compared to these previous treatments, our approach is simpler because it removes the need for calculating the model at a series of the gap width or an additional controlling equation of the force balance.…”

Essays on Conceptual Electrochemistry: I. Bridging Open-Circuit Voltage of Electrochemical Cells and Charge Distribution at Electrode–Electrolyte Interfaces

“…Theory and experiment revealed that the pushback effect of adsorbed hydrogen decreases the work function of Pt(111) ( Li et al, 2021 ), whereas the pullout effect of adsorbed oxygen increases it ( Malek and Eikerling, 2018 ). As regards the EDL at Pt(111) contacted with an acidic aqueous solution, a mean-field model has shown that chemisorption of partially charged hydroxyl and oxygen contributes an additional surface dipole moment, leading to a second pzc and an overall nonmonotonic surface charging behavior ( Huang et al, 2016 ; Huang et al, 2018 ), which are confirmed in atomistic simulations ( Fernandez-Alvarez and Eikerling, 2019 ; Tesch et al, 2021 ; Braunwarth et al, 2022 ).…”

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

“…where q s = −eN s is the excess charge at the electrode surface, and we used Eqs. ( 20), (15), and ( 16). Note that the surface excess electron number N s cannot be directly specified as an input parameter of HBM-DFT calculations.…”

“…Therefore, different methods have been developed for an implicit treatment of both the solvent and the ionic charge of the electrolyte. The implicit solvent is typically described at the level of polarizable continuum models (PCM) [9][10][11][12] , but also advanced methods are used such as the reference interaction site model (RISM) [13][14][15][16] . For the ionic charge of the electrolyte, various implicit models have been developed, including the homogeneous compensating background 17 , Gaussian distributions 18 , and screening layers described by Poisson-Boltzmann-type equations [19][20][21][22][23][24][25][26] .…”