Confinement Effects on Proton Transfer in TiO₂ Nanopores from Machine Learning Potential Molecular Dynamics Simulations

Improved understanding of proton transfer in nanopores is critical for a wide range of emerging applications, yet experimentally probing mechanisms and energetics of this process remains a significant challenge. To help reveal details of this process, we developed and applied a machine learning potential derived from first-principles calculations to examine water reactivity and proton transfer in TiO₂ slit-pores. We find that confinement of water within pores smaller than 0.5 nm imposes strong and complex effects on water reactivity and proton transfer. Although the proton transfer mechanism is similar to that at a TiO₂ interface with bulk water, confinement reduces the activation energy of this process, leading to more frequent proton transfer events. This enhanced proton transfer stems from the contraction of oxygen-oxygen distances dictated by the interplay between confinement and hydrophilic interactions. Our simulations also highlight the importance of the surface topology, where faster proton transport is found in the direction where a unique arrangement of surface oxygens enables the formation of an ordered water chain. In a broader context, our study demonstrates that proton transfer in hydrophilic nanopores can be enhanced by controlling pore size, surface chemistry, and topology.