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Pattern formation for NO+NH3 on Pt(100): two-dimensional numerical results.

Hannes Uecker1

  • 1Mathematisches Institut I, Universität Karlsruhe, D-76128 Karlsruhe, Germany. hannes.uecker@math.uni-karlsruhe.de

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 9, 2005
PubMed
Summary

Surface diffusion couples oscillators in the NO+NH3 reaction model, creating phase clusters and standing waves. This numerical study explores pattern formation on a Pt(100) surface, differing from gas-phase coupling in related models.

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Area of Science:

  • Chemical Kinetics
  • Surface Science
  • Computational Chemistry

Background:

  • The Lombardo-Fink-Imbihl model describes the NO+NH3 reaction on a Pt(100) surface using seven coupled ordinary differential equations (ODEs).
  • This model exhibits stable relaxation oscillations and sharp transitions within the relevant temperature range.

Purpose of the Study:

  • To numerically investigate the impact of surface diffusion coupling on the ODEs of the NO+NH3 reaction model in two dimensions.
  • To explore the formation of spatio-temporal patterns, such as phase clusters and standing waves, arising from this coupling.

Main Methods:

  • Numerical simulations of the two-dimensional reaction-diffusion system based on the Lombardo-Fink-Imbihl model.
  • Investigating the effect of coupling via surface diffusion for kinetically slaved variables, replacing global gas-phase coupling.

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Main Results:

  • Observed formation of diverse patterns, including phase clusters and standing waves, due to surface diffusion coupling.
  • Demonstrated that relatively fast diffusion of two kinetically slaved variables can induce clustered solutions, previously only seen with global gas-phase coupling.

Conclusions:

  • Surface diffusion provides an alternative mechanism for pattern formation in surface reactions, leading to complex spatio-temporal dynamics.
  • The study highlights the importance of considering diffusion effects in heterogeneous catalysis and compares simulation findings with experimental data, noting model limitations.