  The growth of a crystal is usually determined by its surface. Many factors
influence the growth dynamics. Energy barriers associated with the presence of
steps most often decide about the emerging pattern. The height and type of
Ehrlich-Schwoebel step barriers lead to the growth of nanocolumns, nanowires,
pyramids, and bunches or meanders in the same system. Surface diffusion is
another factor that determines the nature of growth. We used the (2+1)D
cellular automaton model to investigate the additional effect of diffusion
along with step barriers. We show that when we only change the diffusion rate,
the length of the meanders or the height of the bunches increase, while the
cracked structure of the nanopillars changes into very long, tall nanowires. We
show that the length of the step-step correlation is a good characterization of
the resulting patterns.
