Kinetic Monte Carlo (KMC) is a widely employed technique for studying various phenomena such as transport, material properties, and chemical reactions, bridging the gap between the microscopic and macroscopic worlds. It serves as a crucial tool in understanding atomistic diffusion and catalysis. However, existing multiscale surface kinetic Monte Carlo simulation methods have limitations, leading to inconsistencies between theoretical and experimental findings. In our research, we aim to enhance these multiscale models by:
1) Developing frameworks that enable macroscopic computations over large space-time scales using microscopic simulations initialized at smaller scales
2) Distinguishing between “slow” and “fast” processes, treating the former stochastically at the KMC level and the latter deterministically
3) Introducing the concept of a super basin, representing a set of lattice configurations accessible through quasi-equilibrated processes.
Through these improvements, we seek to advance the accuracy and applicability of multiscale surface kinetic Monte Carlo simulations, fostering better agreement with experimental observations and theoretical investigations.