AIM AND TASK: This project will make use of classical and ab-initio molecular dynamics simulations to probe the wettability of solid surfaces. TiO2, CeO2 and graphene interfaces with varying protonation state or coatings will be used. CONTEXT: Water-metal-oxide interfaces play decisive roles in a range of vital applications such as photoelectrochemical energy conversion, nanotoxicology, biosensing and energy storage (e.g. Li-ion batteries and solar cells). To understand and tailor the structure and functionality of such interfaces is therefore of prime interest. One key aspect is the structure of water molecules in the proximity of nanosurfaces (say, within 1 nm) that mediate the interaction with the surrounding environment. Probing minute amounts of adsorbed surface water species in the presence of significant excess of a bulk water phase represents a serious challenge for experimental approaches, due to the dispersion of the interfacial signal with respect to the bulk liquid phase. Relatively few attempts to probe metal-oxide surfaces directly in aqueous environments have been reported so far (e.g. using sum frequency generation). Although these studies indicate the existence of a layer of constrained water molecules exhibiting limited mobility at the nanoparticle perimeter, no further information on structure and speciation within that layer could be elucidated. This is a very challenging field in strong development. PREVIOUS ACHIEVEMENTS: In our recent publications, thank to previously allocated NAISS (see report for details), we demonstrated that: 1) proton NMR can solve water structure and reactivity at the metal-oxide interfaces (https://doi.org/10.1021/jacs.5c18863), 2) complex proton surface patterns trigger different wetting (https://doi.org/10.1021/acscatal.5c09228), 3) interfacial diffusion is quantitative measurement of wetting (https://doi.org/10.1038/s41524-026-02079-w). FUTURE DEVELOPMENT: We will extend the study of diffusion regimes for water in close contact with TiO2 and CeO2 metal-oxide surfaces in order to grasp their wetting properties under different pH environments. Machine learning models able to extend the time and system size length scales for improved statistics will be build. The diffusion-wetting dualism will be tested for such interfaces offering the possibility to create a new universal probe for studying water interfacial affinity. A further extension will be assessed on graphene coated with biological molecules, in order to study the use of these interfaces for water depuration. Specifically the adhesion of phthalocyanines will be tested, as these are supposed to create stable monolayers for further selective adsorption of water pollutants. This project is now funded by FORMAS-Water4all European joint call granted by me for the period 2025-2028.