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Kinetic processes play a crucial role in the formation and evolution of molecular layers. In this perspective we argue that adaptive kinetic Monte Carlo is a powerful simulation technique for determining key kinetic processes in molecular solids. The applicability of the method is demonstrated by simulating the diffusion of a CO admolecule on a water ice surface, which is an important process for the formation of organic compounds on interstellar dust grains. CO diffusion is found to follow Arrhenius behavior and the corresponding effective activation energy for diffusion is determined to be 50 ± 1 meV. A coarse graining algorithm is applied which greatly enhances the efficiency of the simulations at low temperatures, down to 10 K, without altering the underlying physical processes. Eventually, we argue that a combination of both on- and off-lattice kinetic Monte Carlo techniques is a good way for simulating large-scale processes in molecular solids over long time spans.
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Physical Chemistry Chemical Physics
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