  We present a new network modeling approach for various thin film growth
techniques that incorporates re-emitted particles due to the non-unity sticking
coefficients. We model re-emission of a particle from one surface site to
another one as a network link, and generate a network model corresponding to
the thin film growth. Monte Carlo simulations are used to grow films and
dynamically track the trajectories of re-emitted particles. We performed
simulations for normal incidence, oblique angle, and chemical vapor deposition
(CVD) techniques. Each deposition method leads to a different dynamic evolution
of surface morphology due to different sticking coefficients involved and
different strength of shadowing effect originating from the obliquely incident
particles. Traditional dynamic scaling analysis on surface morphology cannot
point to any universal behavior. On the other hand, our detailed network
analysis reveals that there exist universal behaviors in degree distributions,
weighted average degree versus degree, and distance distributions independent
of the sticking coefficient used and sometimes even independent of the growth
technique. We also observe that network traffic during high sticking
coefficient CVD and oblique angle deposition occurs mainly among edges of the
columnar structures formed, while it is more uniform and short-range among
hills and valleys of small sticking coefficient CVD and normal angle
depositions that produce smoother surfaces.
