Propensity of water self-ions at air(oil)-water interfaces revealed by deep potential molecular dynamics with enhanced sampling
The preference of water self-ions (hydronium and hydroxide) towards air/oil-water interfaces is one of the hottest topics in water research due to its importance for understanding properties, phenomena, and reactions of interfaces. In this work, we performed enhanced-sampling molecular dynamics simulations based on state-of-the-art neural network potentials with approximate M06-2X accuracy to investigate the propensity of hydronium and hydroxide ions at air/oil(decane)-water interfaces, which can simultaneously describe well the water autoionization process forming these ions, recombination of ions, and ionic distribution along the normal distance to the interface by employing a set of appropriate Voronoi collective variables. A stable ionic double-layer distribution is observed near the air-water interface, while the distribution is different at oil-water interfaces, where hydronium tends to be repelled from the interface into the bulk water, whereas hydroxide, with an interfacial stabilization free energy of -0.6 kcal/mol, is enriched in the interfacial layer. Through simulations of oil droplets in water, we further reveal that the interfacial propensity of hydroxide ions is caused by the positive charge distribution of the oil-water interface contributed by hydrogens of the dangling OH bonds of interfacial water layer and the outmost layer decane molecules laying flat on the droplet. The present results may aid in understanding the acid-base nature of water interfaces with wide applications.