Proton-Driven Dynamic Behavior of Nanoconfined Water in Hydrophilic MXene Sheets

Liquid water under nanoscale confinement has attracted intensive attention due to its pivotal role in understanding various phenomena across many scientific fields. MXenes serve an ideal paradigm for investigating the dynamic behaviors of nanoconfined water in a hydrophilic environment. Combining deep neural networks and an active learning scheme, here we elucidate the proton-driven dynamics of water molecules confined between V2CTx sheets using molecular dynamics simulation. Firstly, we have found that the Eigen and Zundel cations can inhibit water-induced oxidation by adjusting the orientation of water molecules, thus proposing a general antioxidant strategy. Besides, we also identified a hexagonal ice phase with abnormal bonding rules at room temperature, rather than only at ultralow temperatures as other studies reported, and further captured the proton-induced water phase transition. This highlighted the importance of protons in the maintaining stable crystal phase and phase transition of water. Furthermore, we discussed the conversions of different water structures and water diffusivity with changing proton concentrations in detail. The results provide useful guidance in practical applications of MXenes including developing antioxidant strategies, identifying novel 2D water phases and optimizing energy storage and conversion. We reported the detailed proton-driven dynamic behaviors of nanoconfined water between hydrophilic MXene sheets using molecular dynamics simulation based on the active learning potential trained by deep neural network algorithms. These findings have illuminated several novel phenomena including the MXene oxidation rate regulated by protons, the formation of a hexagonal ice phase exhibiting unconventional bonding patterns at room temperature, and a significant reduction in water diffusivity. image