A first-principles modeling of heterogeneous catalysis that quantitatively describes the activity over a wide range of realistic environmental situations of varying temperatures and pressures is a daunting task. Since one is dealing with an open system, even steady-state conditions, where the conversion of the chemicals at the solid surface proceeds at a stable (constant) rate, are entirely determined by kinetics. A quantitative computation of the steady-state rate requires therefore to explicitly follow the time evolution of a large enough surface area, fully treating the interplay of all relevant underlying atomic-scale processes.
We tackle this challenge by a first-principles statistical mechanics setup [1], where we first use density-functional theory (DFT) together with transition state theory (TST) to accurately obtain the energetics of all relevant processes. Subsequently the statistical mechanics problem is solved by kinetic Monte Carlo (kMC) simulations. This two-step approach enables us to gain microscopic insight into the system, following its full dynamics from picoseconds up to seconds and explicitly considering the detailed statistical interplay of all elementary processes, i.e. by fully accounting for the correlations, fluctuations and spatial distributions of the chemicals at the catalyst surface.
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