Water dissociation at the water-rutile TiO 2 (110) interface from ab initio-based deep neural network simulations.

The interaction of water with TiO ₂ surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO ₂ -water interface has a critical role in the surface chemistry of TiO ₂ , but is difficult to determine both experimentally and computationally. Among TiO ₂ surfaces, rutile TiO ₂ (110) is of special interest as the most abundant surface of TiO ₂ 's stable rutile phase. While surface-science studies have provided detailed information on the interaction of rutile TiO ₂ (110) with gas-phase water, much less is known about the TiO ₂ (110)-water interface, which is more relevant to many applications. In this work, we characterize the structure of the aqueous TiO ₂ (110) interface using nanosecond timescale molecular dynamics simulations with ab initio-based deep neural network potentials that accurately describe water/TiO ₂ (110) interactions over a wide range of water coverages. Simulations on TiO ₂ (110) slab models of increasing thickness provide insight into the dynamic equilibrium between molecular and dissociated adsorbed water at the interface and allow us to obtain a reliable estimate of the equilibrium fraction of water dissociation. We find a dissociation fraction of 22 ± 6% with an associated average hydroxyl lifetime of 7.6 ± 1.8 ns . These quantities are both much larger than corresponding estimates for the aqueous anatase TiO ₂ (101) interface, consistent with the higher water photooxidation activity that is observed for rutile relative to anatase.