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Related Experiment Videos

Pattern formation on nonuniform surfaces by correlated random sequential absorptions.

Zhi-Jie Tan1, Xian-Wu Zou, Wei Zhang

  • 1Department of Physics, Wuhan University, Wuhan 430072, People's Republic of China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|June 13, 2002
PubMed
Summary

Computer simulations reveal how particle absorption on nonuniform surfaces forms patterns. Surface properties and particle interactions dictate pattern evolution, transitioning from dispersed to correlated percolation structures.

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Area of Science:

  • Physics
  • Materials Science
  • Computational Modeling

Background:

  • Nonuniform surfaces present complex challenges for modeling pattern formation.
  • Correlated-Random Sequential Absorption (CRSA) is a key process for understanding surface interactions.
  • Percolation theory provides a framework for analyzing cluster formation on such surfaces.

Purpose of the Study:

  • To investigate pattern formation on nonuniform surfaces using the CRSA process.
  • To analyze the influence of surface nonuniformity and particle interactions on pattern development.
  • To explore the transition between different percolation regimes based on surface properties.

Main Methods:

  • Computer simulations were employed to model the CRSA process.
  • Nonuniform surfaces were represented by percolation clusters with varying probabilities p(s).

Related Experiment Videos

  • A sticking coefficient 's' was introduced to account for particle-defect interactions.

    • Main Results:

    • At low sticking coefficients (s-->0), patterns evolved from dispersed site percolation to correlated and then to lattice percolation clusters with increasing correlation.
    • At high sticking coefficients (s-->1) and near percolation threshold (p(s)-->p(c)), patterns were randomly dispersed despite correlations.
    • A transition in control from defect absorption to surface absorption and particle correlation was observed with decreasing 's' and increasing p(s).

    Conclusions:

    • The study elucidates the complex interplay between surface characteristics and particle interactions in dictating pattern formation.
    • The transition correlation exponent alpha(c) was found to equal the fractal dimension of the percolation surfaces (d(s)) for the s-->0 system.
    • Findings contribute to understanding self-organization processes on complex substrates.