Random Sequential Adsorption, Series Expansion and Monte Carlo Simulation

نویسنده

  • Jian-Sheng Wang
چکیده

Random sequential adsorption is an irreversible surface deposition of extended objects. In systems with continuous degrees of freedom coverage follows a power law, θ(t) ≈ θJ−c t , where the exponent α depends on the geometric shape (symmetry) of the objects. Lattice models give typically exponential saturation to jamming coverage. We discuss how such function θ(t) can be computed by series expansions and analyzed with Padé approximations. We consider the applications of efficient Monte Carlo computer simulation method (event-driven method) to random sequential adsorptions with high precision and at very long-time scale.

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تاریخ انتشار 1997