The dissociation of water is an important step in many chemical processes at solid surfaces. In particular, water often spontaneously dissociates near metal oxide surfaces, resulting in a mixture of HO, H, and OH at the interface. Ubiquitous proton-transfer (PT) reactions cause these species to dynamically interconvert, but the underlying mechanisms are poorly understood. Here, we develop and use a reactive high-dimensional neural-network potential based on density functional theory data to elucidate the structural and dynamical properties of the interfacial species at the liquid-water-metal-oxide interface, using the nonpolar ZnO(101̅0) surface as a prototypical case. Molecular dynamics simulations reveal that water dissociation and recombination proceed via two types of PT reactions: (i) to and from surface oxide and hydroxide anions ("surface-PT") and (ii) to and from neighboring adsorbed hydroxide ions and water molecules ("adlayer-PT"). We find that the adlayer-PT rate is significantly higher than the surface-PT rate. Water dissociation is, for both types of PT, governed by a predominant presolvation mechanism, i.e., thermal fluctuations that cause the adsorbed water molecules to occasionally accept a hydrogen bond, resulting in a decreased PT barrier and an increased dissociation rate as compared to when no hydrogen bond is present. Consequently, we are able to show that hydrogen bond fluctuations govern PT events at the water-metal-oxide interface in a way similar to that in acidic and basic aqueous bulk solutions.
Neural network molecular dynamics simulations unravel the long-range proton transport properties of ZnO–water interfaces.
Interfaces between water and metal oxides exhibit many interesting phenomena like dissociation and recombination of water molecules and water exchange between the interface and the bulk liquid. Moreover, a variety of structural motifs can be found, differing in hydrogenbonding patterns and molecular orientations. Here, we report the structure and dynamics of liquid water interacting with the two most stable ZnO surfaces, (101̅ 0) and (112̅ 0), by means of reactive molecular dynamics simulations based on a machine learning high-dimensional neural network potential. For both surfaces, three distinct hydration layers can be observed within 10 Å from the surface with the first hydration layer (nearest to the surface) representing the most interesting region to investigate. There, water molecules dynamically dissociate and recombine, leading to a variety of chemical species at the interface. We characterized these species and their molecular environments by analyzing the properties of the hydrogen bonds and local geometries. At ZnO(112̅ 0), some of the adsorbed hydroxide ions bridge two surface Zn ions, which is not observed at ZnO(101̅ 0). For both surfaces, adsorbed water molecules always bind to a single Zn ion, and those located in proximity of the substrate are mostly "H-down" oriented for ZnO(101̅ 0) and "flat-lying", i.e., parallel to the surface, for ZnO(112̅ 0). The time scales for proton-transfer (PT) reactions are quite similar at the two surfaces, with the average lifetime of adsorbed hydroxide ions being around 41 ± 3 ps until recombination. However, water exchange events, in which adsorbed water molecules leave the surface and enter the bulk liquid, happen more frequently at ZnO(112̅ 0) than at ZnO(101̅ 0).
Unraveling the atomistic details of solid/liquid interfaces, e.g., by means of vibrational spectroscopy, is of vital importance in numerous applications, from electrochemistry to heterogeneous catalysis. Water-oxide interfaces represent a formidable challenge because a large variety of molecular and dissociated water species are present at the surface. Here, we present a comprehensive theoretical analysis of the anharmonic OH stretching vibrations at the water/ZnO(101¯0) interface as a prototypical case. Molecular dynamics simulations employing a reactive high-dimensional neural network potential based on density functional theory calculations have been used to sample the interfacial structures. In the second step, one-dimensional potential energy curves have been generated for a large number of configurations to solve the nuclear Schrödinger equation. We find that (i) the ZnO surface gives rise to OH frequency shifts up to a distance of about 4 Å from the surface; (ii) the spectrum contains a number of overlapping signals arising from different chemical species, with the frequencies decreasing in the order ν(adsorbed hydroxide) > ν(non-adsorbed water) > ν(surface hydroxide) > ν(adsorbed water); (iii) stretching frequencies are strongly influenced by the hydrogen bond pattern of these interfacial species. Finally, we have been able to identify substantial correlations between the stretching frequencies and hydrogen bond lengths for all species.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.