New perspectives on oxide-water interfaces

The current project proposal deals with water on metal oxide surfaces.

Water adsorption on an oxide surface is known to play a decisive role regarding its character and functionality, such as its stability, lattice terminations, and its interaction characteristics with other molecules through molecular adsorption and chemical reactions.

The "molecular wettability" of a material, i.e. its hydrophilic or hydrophobic character, is also crucial in a wide range of technical applications, from hydrophobic coatings to make mechanical parts thermally and mechanically resistant in industry to hydrophilic surfaces for self-cleaning purposes.

This methodology in this proposal can be described as ´physics-based and data-driven´.

The focus is on the scientific problems but I take aid from machine learning in several cases, still it is for the purpose of getting insight about the chemical/materials systems. The problems in forcus are structure-oriented.

It is extremely challenging to extract information about a solid-liqui interface region from experiment so here computational efforts have an important role to play.

The subtopics of my proposal are:o   Interface structures from MD simulation (´When does water adhesion lead to water repelling?´)ando    Interface structures from spectral information. (´Spectroscopy-structure models from ML to physics-based ´ and ´How near-sighted are different spectroscopy methods?´)