  The reliability of kinetic Monte Carlo (KMC) simulations depends on accurate
transition rates. The self-learning KMC method (Trushin et al 2005 Phys. Rev. B
72 115401) combines the accuracy of rates calculated from a realistic potential
with the efficiency of a rate catalog, using a pattern recognition scheme. This
work expands the original two-dimensional method to three dimensions. The
concomitant huge increase in the number of rate calculations on the fly needed
can be avoided by setting up an initial database, containing exact activation
energies calculated for processes gathered from a simpler KMC model. To provide
two representative examples, the model is applied to the diffusion of Ag
monolayer islands on Ag(111), and the homoepitaxial growth of Ag on Ag(111) at
low temperatures.
