Coarse-Grained Kinetic Monte Carlo Models: Complex Lattices, Multicomponent Systems, and Homogenization at the Stochastic Level

Stuart D. Collins, Chemical Engineering, University of Delaware, Newark, DE 19716, Abhijit Chatterjee, Theoretical Division, Los Alamos National Laboratory, T-12 MS B268, Los Alamos, NM 87545, and Dion Vlachos, Director of Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE 19716.

On-lattice kinetic Monte Carlo (KMC) simulations have extensively been applied to numerous systems. However, their applicability is severely limited to relatively short time and length scales. Recently, the Coarse-Grained MC (CGMC) method was introduced to greatly expand the reach of the lattice KMC technique. Herein, we extend the previous spatial CGMC methods to multicomponent species and/or site types. The underlying theory is derived and numerical examples are presented to demonstrate the method. Furthermore, we introduce the concept of homogenization at the stochastic level over all site types of a spatially coarse grained cell. Homogenization provides a novel coarsening of the number of processes, an important aspect for complex problems plagued by numerous microscopic processes (combinatorial complexity). As expected, the homogenized CGMC method outperforms the traditional KMC method on computational cost while retaining good accuracy.