Adaptive multiscale modeling in heterogeneous catalysis

The intermittent nature of sustainable energy sources creates a pressing need for catalysts that enable energy storage in chemical bonds. Fundamental understanding of governing processes provides a way to facilitate catalyst development. Heterogeneous catalysts are commonly realized as nanoparticles supported on porous oxide supports.

One outstanding challenge when linking catalyst performance with elementary reaction steps is the dynamic character of the catalyst system during operating conditions.

As the shape and composition of the catalyst change with adsorbate coverages and temperature, it is notoriously difficult to establish unambiguous structure-function relations.

A related issue is the fact that several reactions depend on the structurally complex interface between the nanoparticle and the oxide.

The project will address these challenges by development of computational methods where the shape and composition of supported catalysts adopt to the reaction conditions.

The methods will be based on first principles electronic structure calculations coupled to Monte Carlo simulations for reaction kinetics via layers of advanced parametrization and thermodynamic analysis.

The developed approach will be applied to selective hydrogenation for production of biofuels and CO2 hydrogenation to methane and methanol.

These are examples of suitable model reactions for which there is a strong need for catalysts with enhanced performance.