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Reversible random sequential adsorption of mixtures on a triangular lattice.

I Loncarević1, Lj Budinski-Petković, S B Vrhovac

  • 1Faculty of Engineering, Trg D. Obradovića 6, Novi Sad 21000, Serbia.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
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Summary

This study numerically investigates how object shape symmetry affects reversible adsorption in binary mixtures on a 2D lattice. Findings reveal collective events and mixture composition significantly influence adsorption kinetics and steady-state coverage.

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Area of Science:

  • Statistical Physics
  • Surface Science
  • Computational Chemistry

Background:

  • Reversible random sequential adsorption (RSA) is crucial for understanding surface processes.
  • Binary mixtures introduce complexity due to interactions and differing particle properties.
  • Lattice models provide a simplified yet powerful framework for studying adsorption phenomena.

Purpose of the Study:

  • To numerically investigate the influence of shape symmetry on adsorption-desorption kinetics in binary mixtures.
  • To analyze the role of collective events and mixture composition in two-component RSA.
  • To develop a predictive model for steady-state coverage in binary mixtures of equal-sized objects.

Main Methods:

  • Monte Carlo simulations were employed to model reversible random sequential adsorption.
  • The study focused on binary mixtures of extended objects on a two-dimensional triangular lattice.
  • Self-avoiding lattice steps were used to define the depositing objects' shapes.

Main Results:

  • Shape symmetry significantly impacts the kinetics of adsorption-desorption processes.
  • Collective events play a key role in governing the time-coverage behavior of components.
  • Mixture composition influences the overall deposition process and final coverage.

Conclusions:

  • Object symmetry is a critical factor in RSA of binary mixtures.
  • A simple formula can predict mixture steady-state coverage from pure component data for equal-sized objects.
  • Understanding these factors is essential for designing surface processes and materials.