Kinetic Monte Carlo simulations of Au clusters on Si(111)-7 × 7 surface

Self-assembled growth of Au nanoclusters on the Si(111)-7 × 7 surface has been studied using kinetic Monte Carlo simulations. A model considering various atomic processes of deposition, adsorption, diffusion, nucleation, and aggregation is introduced, and the main energetic parameters are optimized based on the experimental results. The evolution of surface morphology during Au growth is simulated in real time, from which the atomic behaviors of Au could be really captured. Most of Au atoms diffuse on the substrate in the very early stage of growth, and Au clusters nucleate and grow with the increasing coverage. The competition among various atomic processes results in the distinct distribution of Au clusters under different coverages. The growth conditions are further optimized, showing that the higher uniformity of Au clusters would be obtained at a low deposition rate and an optimal substrate temperature of about 380 K.