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. Our results show that the desorption of the surface K+ ions in pure ion-free water has a significant free energy barrier irrespective of their local surface arrangement. In contrast, facile K+ diffusion between mica's ditrigonal cavities characterized by different Al/Si orderings is observed. This behavior suggests that the K+ ions may favor a dynamic disordered surface arrangement rather than complete desorption when exposed to deionized water.

Acid-Base Chemistry of a Model IrO2 Catalytic Interface.

Iridium oxide (IrO2) 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 IrO2(110)-water interface are investigated using ab initio 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. A large fraction (≈80%) of adsorbed water dissociation is observed, together with a short lifetime (≈0.5 ns) of the resulting terminal hydroxy groups, due to rapid proton exchanges between adsorbed H2O and adjacent OH species. This rapid surface proton transfer supports the suggestion that the rate-determining step in the OER may not involve proton transfer across the double layer into solution, as indicated by recent experiments.

Modeling the Solvation and Acidity of Carboxylic Acids Using an Ab Initio 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 ab initio molecular dynamics simulations. In this study, we present a deep neural network potential trained using accurate ab initio 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. In particular, we show that our model captures proton dissociation and provides a good estimate of the pKa, as well as the dimerization of formic and acetic acid. This provides a suitable starting point for applications in different research areas where computational efficiency coupled with the accuracy of ab initio methods is required.

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 SrIrO3, SrRuO3 and SrTiO3, 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 (ABO3) 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 LaFeO3 (LSF), LaMnO3 (LSM), and LaCoO3 (LSCo). Density functional theory calculations were performed to determine the stability of different active sites on a collection of surfaces. With LSF and LSM, rates for the ORR are significantly higher on the A-site terminated surface, while surface termination is less important for LSCo. Our findings highlight the importance of tailoring the surface termination of the perovskite to obtain its ultimate ORR performance.

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. We found that the Widom lines derived from these response functions all coincide near the critical point until about 25 bars and 15-20 K, beyond which the isothermal compressibility line begins to deviate. We also obtained the crossover from liquid-like to vapor-like behavior of the translational diffusion coefficient, shear viscosity, and rotational relaxation time of supercritical oxygen. While the crossover of the translational diffusion coefficient and shear viscosity coincided with the Widom lines, the rotational relaxation time showed a crossover that was largely independent of the Widom line. Further, we characterized the clustering behavior and percolation transition of supercritical oxygen molecules, identified the percolation threshold based on the fractal dimension of the largest cluster and the probability of finding a cluster that spans the system in all three dimensions, and found that the locus of the percolation threshold also coincided with the isothermal compressibility Widom line. It is therefore clear that supercritical oxygen is far more complex than originally perceived and that the Widom line, dynamical crossovers, and percolation transitions serve as useful routes to better our understanding of the supercritical state.