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The authors present a network modeling approach for various thin film growth techniques that incorporates reemitted particles due to the nonunity sticking coefficients. They 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. They 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.
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