Neural Network-Based Sum-Frequency Generation Spectra of Pure and Acidified Water Interfaces with Air.

Abstract

The affinity of hydronium ions (H3O+) for the air-water interface is a crucial question in environmental chemistry. While sum-frequency generation (SFG) spectroscopy has been instrumental in indicating the preference of H3O+ for the interface, key questions persist regarding the molecular origin of the SFG spectral changes in acidified water. Here we combine nanosecond long neural network (NN) reactive simulations of pure and acidified water slabs with NN predictions of molecular dipoles and polarizabilities to calculate SFG spectra of long reactive trajectories including proton transfer events. Our simulations show that H3O+ ions cause two distinct changes in phase-resolved SFG spectra: first, a low-frequency tail due to the vibrations of H3O+ and its first hydration shell, analogous to the bulk proton continuum, and second, an enhanced hydrogen-bonded band due to the ion-induced static field polarizing molecules in deeper layers. Our calculations confirm that changes in the SFG spectra of acidic solutions are caused by hydronium ions preferentially residing at the interface.