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Water dissociation at the water–rutile TiO~2~(110) interface from ab initio-based deep neural network simulations by Bo Wen; Marcos F. Calegari Andrade; Li-Min Liu; Annabella Selloni is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Significance The character—molecular vs. dissociated—of adsorbed water on TiO~2~surfaces plays a critical role in many applications, e.g., photocatalysis and surface functionalization, and has been studied for decades. However, there is still limited information on water dissociation at theTiO~2~–liquid water interface, the system most relevant to applications. Ab initio simulations have provided valuable insights, but their time scales are insufficient to characterize the amount of dissociation at aqueous interfaces. We here overcome this limitation using deep neural network potentials that accurately reproduce the ab initio results for water interacting with the prototypical TiO~2~(110) surface. The average dissociation fraction,22 ± 6%, predicted by these simulations is a key information for understanding TiO~2~’s photocatalytic activity.

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Author

Bo Wen; Marcos F. Calegari Andrade; Li-Min Liu; Annabella Selloni

Publisher

Proceedings of the National Academy of Sciences

Published

2023

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)