Computing Surface Acidity Constants of Proton Hopping Groups from Density Functional Theory-Based Molecular Dynamics: Application to the SnO2(110)/H2O Interface

Accelerating Computation of Acidity Constants and Redox Potentials for Aqueous Organic Redox Flow Batteries by Machine Learning Potential-Based Molecular Dynamics

Due to the increased concern about energy and environmental issues, significant attention has been paid to the development of large-scale energy storage devices to facilitate the utilization of clean energy sources. The redox flow battery (RFB) is one of the most promising systems. Recently, the high cost of transition-metal complex-based RFB has promoted the development of aqueous RFBs with redox-active organic molecules. To expand the working voltage, computational chemistry has been applied to search for organic molecules with lower or higher redox potentials. However, redox potential computation based on implicit solvation models would be challenging due to difficulty in parametrization when considering the complex solvation of supporting electrolytes. Besides, although ab initio molecular dynamics (AIMD) describes the supporting electrolytes with the same level of electronic structure theory as the redox couple, the application is impeded by the high computation costs. Recently, machine learning molecular dynamics (MLMD) has been illustrated to accelerate AIMD by several orders of magnitude without sacrificing the accuracy. It has been established that redox potentials can be computed by MLMD with two separated machine learning potentials (MLPs) for reactant and product states, which is redundant and inefficient. In this work, an automated workflow is developed to construct a universal MLP for both states, which can compute the redox potentials or acidity constants of redox-active organic molecules more efficiently. Furthermore, the predicted redox potentials can be evaluated at the hybrid functional level with much lower costs, which would facilitate the design of aqueous organic RFBs.

Water effect on the band edges of anatase TiO2 surfaces: A theoretical study on charge migration across surface heterojunctions and facet-dependent photoactivity

The charge migration mechanism across the surface heterojunction constructed on an anatase TiO2 nanocrystal is still under debate. To solve this longstanding question, we present a systematic study of the band edges (vs. standard hydrogen electrode, SHE) of aqueous TiO2 interfaces with anatase (101), (100) and (001) surfaces, using a combination of density functional theory-based molecular dynamics (DFTMD) and efficient computational SHE (cSHE) methods. Our calculations show that the conduction band minimum (CBM) of the (101) surface is lower than that of (001) and (100) surfaces, which is thermodynamically favorable for electrons migrating to the (101) surface through the surface heterojunction, while the hole preferentially accumulates on the (100) surface due to its highest valence band minimum (VBM). In addition, we qualitatively explore the facet-dependent photocatalytic activity of anatase TiO2. Due to the possession of both the beneficial atomic structure (with 100% undercoordinated Ti5c atoms at the surface) and electronic structure (more strongly oxidizing holes in the VBM and efficient electron-hole spatial separation separation), the (001) surface exhibits the most efficient photocatalytic performance for water oxidation. Furthermore, it is confirmed that the use of simplified theoretical models neglecting the detailed atomic structures of water at the aqueous interface is inadequate to predict the band alignment of semiconductors relative to water redox potentials, so that it may result in substantial errors in evaluating the photocatalytic performance of materials to be used for water splitting.

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.

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.

Origin of Asymmetric Electric Double Layers at Electrified Oxide/Electrolyte Interfaces

The structure of electric double layers (EDLs) dictates the chemistry and the physics of electrified interfaces, and the differential capacitance is the key property for characterizing EDLs. Here we develop a theoretical model for computing the differential Helmholtz capacitance C_H of oxide-electrolyte interfaces using density functional theory-based finite-field molecular dynamics simulations. It is found that the dipole of interfacial adsorbed groups (i.e., water molecule, hydroxyl ion, and proton) at the electrified SnO₂(110)/NaCl interfaces significantly modulates the double layer potential which leads to the asymmetric distribution of C_H. We also find that the dissociative water adsorption prefers the inner sphere binding of counterions, which in turn leads to a higher Helmholtz capacitance, compared with that of the nondissociative case at the interface. This work provides a molecular interpretation of asymmetric EDLs seen experimentally in a range of metal oxides/hydroxides.