Water-Mediated Proton\nHopping Mechanisms at the SnO<sub>2</sub>(110)/H<sub>2</sub>O Interface\nfrom Ab Initio Deep Potential\nMolecular Dynamics

The interfacial proton transfer (PT) reaction on the\nmetal oxide\nsurface is an important step in many chemical processes including\nphotoelectrocatalytic water splitting, dehydrogenation, and hydrogen\nstorage. The investigation of the PT process, in terms of thermodynamics\nand kinetics, has received considerable attention, but the individual\nfree energy barriers and solvent effects for different PT pathways\non rutile oxide are still lacking. Here, by applying a combination\nof ab initio and deep potential molecular dynamics methods, we have\nstudied interfacial PT mechanisms by selecting the rutile SnO<sub>2</sub>(110)/H<sub>2</sub>O interface as an example of an oxide with\nthe characteristic of frequently interfacial PT processes. Three types\nof PT pathways among the interfacial groups are found, i.e., proton\ntransfer from terminal adsorbed water to bridge oxygen directly (surface-PT)\nor via a solvent water (mediated-PT), and proton hopping between two\nterminal groups (adlayer PT). Our simulations reveal that the terminal\nwater in mediated-PT prefers to point toward the solution and forms\na shorter H-bond with the assisted solvent water, leading to the lowest\nenergy barrier and the fastest relative PT rate. In particular, it\nis found that the full solvation environment plays a crucial role\nin water-mediated proton conduction, while having little effect on\ndirect PT reactions. The PT mechanisms on aqueous rutile oxide interfaces\nare also discussed by comparing an oxide series composed of SnO<sub>2</sub>, TiO<sub>2</sub>, and IrO<sub>2</sub>. Consequently, this\nwork provides valuable insights into the ability of a deep neural\nnetwork to reproduce the ab initio potential energy surface, as well\nas the PT mechanisms at such oxide/liquid interfaces, which can help\nunderstand the important chemical processes in electrochemistry, photoelectrocatalysis,\ncolloid science, and geochemistry.

Publication Details

Journal
Figshare
Published
2024-12-23
DOI
https://doi.org/10.1021/prechem.4c00056.s001
Primary Topic
Mycorrhizal Fungi and Plant Interactions
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article
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article

Water-Mediated Proton\nHopping Mechanisms at the SnO2(110)/H2O Interface\nfrom Ab Initio Deep Potential\nMolecular Dynamics

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Mycorrhizal Fungi and Plant Interactions
article

Water-Mediated Proton\nHopping Mechanisms at the SnO2(110)/H2O Interface\nfrom Ab Initio Deep Potential\nMolecular Dynamics

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Abstract

The interfacial proton transfer (PT) reaction on the\nmetal oxide\nsurface is an important step in many chemical processes including\nphotoelectrocatalytic water splitting, dehydrogenation, and hydrogen\nstorage. The investigation of the PT process, in terms of thermodynamics\nand kinetics, has received considerable attention, but the individual\nfree energy barriers and solvent effects for different PT pathways\non rutile oxide are still lacking. Here, by applying a combination\nof ab initio and deep potential molecular dynamics methods, we have\nstudied interfacial PT mechanisms by selecting the rutile SnO<sub>2</sub>(110)/H<sub>2</sub>O interface as an example of an oxide with\nthe characteristic of frequently interfacial PT processes. Three types\nof PT pathways among the interfacial groups are found, i.e., proton\ntransfer from terminal adsorbed water to bridge oxygen directly (surface-PT)\nor via a solvent water (mediated-PT), and proton hopping between two\nterminal groups (adlayer PT). Our simulations reveal that the terminal\nwater in mediated-PT prefers to point toward the solution and forms\na shorter H-bond with the assisted solvent water, leading to the lowest\nenergy barrier and the fastest relative PT rate. In particular, it\nis found that the full solvation environment plays a crucial role\nin water-mediated proton conduction, while having little effect on\ndirect PT reactions. The PT mechanisms on aqueous rutile oxide interfaces\nare also discussed by comparing an oxide series composed of SnO<sub>2</sub>, TiO<sub>2</sub>, and IrO<sub>2</sub>. Consequently, this\nwork provides valuable insights into the ability of a deep neural\nnetwork to reproduce the ab initio potential energy surface, as well\nas the PT mechanisms at such oxide/liquid interfaces, which can help\nunderstand the important chemical processes in electrochemistry, photoelectrocatalysis,\ncolloid science, and geochemistry.

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