Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces.

The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. Herein, we use ab initio-based machine learning potential simulations incorporating long-range electrostatics to unravel the molecular-scale picture of the EDL at the prototypical anatase TiO-electrolyte interface under various pH conditions.

Insights into the structure and dynamics of K+ ions at the muscovite-water interface from machine learning potential simulations.

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. In this work, we make a first step in this direction by investigating the behavior of the native K+ ions at the interface between neat water and the muscovite mica (001) surface with ab-initio-based machine learning molecular dynamics and enhanced sampling simulations.

Acid-Base Chemistry of a Model IrO Catalytic Interface.

Iridium oxide (IrO) is one of the most efficient catalytic materials for the oxygen evolution reaction (OER), yet the atomic scale structure of its aqueous interface is largely unknown. Herein, the hydration structure, proton transfer mechanisms, and acid-base properties of the rutile IrO(110)-water interface are investigated using based deep neural-network potentials and enhanced sampling simulations. The proton affinities of the different surface sites are characterized by calculating their acid dissociation constants, which yield a point of zero charge in agreement with experiments.

Modeling the Solvation and Acidity of Carboxylic Acids Using an Deep Neural Network Potential.

Formic and acetic acid constitute the simplest of carboxylic acids, yet they exhibit fascinating chemistry in the condensed phase such as proton transfer and dimerization. The go-to method of choice for modeling these rare events have been accurate but expensive molecular dynamics simulations. In this study, we present a deep neural network potential trained using accurate data that can be used in tandem with enhanced-sampling methods to perform an efficient exploration of the free-energy surface of aqueous solutions of weak carboxylic acids.

Surface stability of perovskite oxides under OER operating conditions: a first principles approach.

The activity-stability conundrum has long been the Achilles' heel in the design of catalysts, in particular, for electrochemical reactions such as water splitting. Here, we use ab initio thermodynamics to delineate the surface stoichiometry of a group of perovskite oxides with different activities towards the oxygen evolution reaction (OER), in order to get a measure of their stability under OER operating conditions. In particular, we compare the surface stability of SrIrO, SrRuO and SrTiO, establishing atomistic insights into the stability and dissolution of these oxide surfaces.

Enhancing Oxygen Exchange Activity by Tailoring Perovskite Surfaces.

A detailed understanding of the effects of surface chemical and geometric composition is essential for understanding the electrochemical performance of the perovskite (ABO) oxides commonly used as electrocatalysts in the cathodes of ceramic fuel cells. Herein, we report how the addition of submonolayer quantities of A- and B-site cations affects the rate of the oxygen reduction reaction (ORR) of Sr-doped LaFeO (LSF), LaMnO (LSM), and LaCoO (LSCo). Density functional theory calculations were performed to determine the stability of different active sites on a collection of surfaces.

Widom line, dynamical crossover, and percolation transition of supercritical oxygen via molecular dynamics simulations.

Supercritical oxygen, a cryogenic fluid, is widely used as an oxidizer in jet propulsion systems and is therefore of paramount importance in gaining physical insights into processes such as transcritical and supercritical vaporization. It is well established in the scientific literature that the supercritical state is not homogeneous but, in fact, can be demarcated into regions with liquid-like and vapor-like properties, separated by the "Widom line." In this study, we identified the Widom line for oxygen, constituted by the loci of the extrema of thermodynamic response functions (heat capacity, volumetric thermal expansion coefficient, and isothermal compressibility) in the supercritical region, via atomistic molecular dynamics simulations.