Monte Carlo simulations of particle 2D attachment on and detachment from plane and rough substrates were presented. The model involved 2D diffusion of particles from the solution (attachment) and from the solid front outwards (detachment), and in both the 1D surface diffusion of particles as main ingredients. The attachment and detachment probabilities Ps and Pd, respectively, the concentration of particles (cp), and the geometric parameters of the square-wave surface profile were varied. Dense deposits were obtained for large values of the diffusion length on the surface (lD), small attachment probability (Ps), and large concentration of particles (cp). The increase in the surface area of the deposit produces a departure from constant area pure diffusion behavior. For the attachment of particles on rough surfaces two types of processes were observed, i.e., one which was similar to that found for the plane and another which was characteristic of the presence of holes. The efficiency of hole filling depended on lD, Ps, cp, and geometric parameters of the substrates. At low Monte Carlo time (tMC) bulk diffusion dominates the hole filling process, whereas for large tm surface diffusion on hole walls became rate determining. Clogging effects also play a key role in particle attachment and detachment from hole walls. Monte Carlo simulations of detachment proceeds under a low detachment probability of particles in direct contact with the substrate and under a tenfold larger one for overlayer particles. The detachment process was highly dependent on the initial geometry of the substrate throughout the surface area and on the degree of branching of the deposit that determines the magnitude of clogging. Comparison of Monte Carlo simulations and experimental data was envisaged for the leveling of silver electrodeposits and stripping processes.

Monte Carlo Simulations of Solid 2D Phase Growth on 1D Solid Substrates with Square-Wave Surface Profiles. Influence of Hole Design and Depositing Particle Surface Diffusion. F.J.Rodríguez Nieto, M.A.Pasquale, M.E.Martins, F.A.Bareilles, A.J.Arvia: Monte Carlo Methods and Applications, 2006, 12[3], 271-89