Venkat Kapil
(University of Cambridge)
Abstract:
Understanding water behavior in nanocavities is relevant to technologies in water treatment and energy. I will present computational studies of a water monolayer confined in a graphene-like channel using a predictive approach combining electronic structure theory, machine learning, and statistical sampling [1]. We find monolayer water exhibits rich phase behavior sensitive to van der Waals pressure. Besides ice phases that defy ice rules [2], we predict a superionic phase at milder conditions than bulk, with high electrical conductivity exceeding that of battery materials. Finally, quantum nuclear motion lowers the onset of superionic water dramatically. Our work shows that nanoconfinement could be a route to exploiting superionic water at ambient conditions.
[1] Kapil, Schran, Zen, Chen, Pickard, & Michaelides (2022) Nature. https://doi.org/10.1038/s41586-022-05036-x
[2] Ravindra, Advincula, Schran, Michaelides, & Kapil (2024) Nature Comms. https://doi.org/10.1038/