Abstract

Amorphous titanium dioxide (a-TiO2) is widely used as a coating material in applications such as electrochemistry and self-cleaning surfaces where its interface with water has a central role. However, little is known about the structures of the a-TiO2 surface and aqueous interface, particularly at the microscopic level. In this work, we construct a model of the a-TiO2 surface via a cut-melt-and-quench procedure based on molecular dynamics simulations with deep neural network potentials (DPs) trained on density functional theory data. After interfacing the a-TiO2 surface with water, we investigate the structure and dynamics of the resulting system using a combination of DP-based molecular dynamics (DPMD) and abinitio molecular dynamics (AIMD) simulations. Both AIMD and DPMD simulations reveal that the distribution of water on the a-TiO2 surface lacks distinct layers normally found at the aqueous interface of crystalline TiO2, leading to an ∼10 times faster diffusion of water at the interface. Bridging hydroxyls (Ti2-ObH) resulting from water dissociation decay several times more slowly than terminal hydroxyls (Ti-OwH) due to fast Ti-OwH2 → Ti-OwH proton exchange events. These results provide a basis for a detailed understanding of the properties of a-TiO2 in electrochemical environments. Moreover, the procedure of generating the a-TiO2-interface employed here is generally applicable to studying the aqueous interfaces of amorphous metal oxides.

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