Dendritic growth of the Pt–Cu islands on Cu(111) surface: Self-learning kinetic Monte Carlo simulations

Growth of the Pt–Cu islands on the Cu(111) surface at different deposition fluxes, relative amounts of Pt atoms and surface temperatures is investigated on the atomic scale by performing the self-learning kinetic Monte-Carlo simulations. The shape transition of the islands from sixfold symmetry to threefold symmetry with increasing of the relative amount of Pt atoms n Pt / n Cu in clusters at room temperature was found and explained by the corner diffusion anisotropy. Nonmonotonic dependence of the fractal dimension of the dendritic islands on the ratio n Pt / n Cu is observed. It is shown that this effect can be interpreted in the framework of the generalized diffusion limited aggregation model if we assume that the dependence of the effective diffusion barrier on the ratio n Pt / n Cu has the third-degree polynomial function form. This dependence is in qualitative agreement with the analysis of the edge diffusion barriers. The dendritic cluster obtained with the simulations at room temperature looks very similar to the experimentally observed one (Soy et al. (2015) [33]).