Sorption and catalysis at nanosurfaces
Many materials in nature are amorphous; furthermore, such materials can also be produced from thermal treatment of waste and therefore their reuse can have an important impact in the development of a circular economy. For example, amorphous materials can be efficiently used as adsorption and catalytic substrates. Their disordered structures generate physicochemical heterogeneities which can be exploited for enhancing the adsorption and conversion of fluids.
At our lab, we focus on the multi-scale in-silico characterization of amorphous substrates for adsorption and catalytic applications. We apply atomistic modelling, such as Molecular Dynamics (MD) simulations and Quantum Chemical (QC) calculations (also combined with enhanced sampling techniques) to study adsorption and reactions at the nanoscale. Machine Learning (ML) algorithms are used to characterize the complex physicochemical heterogeneity of amorphous substrates and to develop kinetic models based on the properties predicted at the nanoscale.
We currently focus on applying MD simulations to study the adsorption of CO2 at the amorphous silica surfaces. We show how the physicochemical heterogeneity of the amorphous surface (i.e., surface roughness and presence of coordination defects), enhances the gas adsorption (Figure 1a). We use ML to segment (Figure 1b) and characterize the adsorption landscape of CO2 at the silica surface.
