Nanomaterials, with their intrinsic high surface/volume ratio and abundance of chemically active sites, are excellent for applications such as water sanitation. Our general objective is to understand the mechanisms and prerequisites of the degradation process at the atomic level for promising candidates of contaminated water treatment and wastewater before they enter the environment. For highly miscible liquids with water, such as methanol, we can use the methodologies we have developed for water near nanointerfaces of graphene. More generally, we want to define strategies, based on supervised machine learning, for free energy calculations in soft condensed matter systems. In collaboration with the UPC and the Elettra Synchrotron, we will calculate free energies from first principles and experimental data.
