One-dimensional model of interacting-step fluctuations on vicinal surfaces: analytical formulas and kinetic Monte Carlo simulations.

Phys Rev E Stat Nonlin Soft Matter Phys

Department of Physics, University of Maryland, College Park, Maryland 20742, USA.

Published: December 2010

AI Article Synopsis

  • The study examines a one-dimensional model of fluctuating line defects on a vicinal crystal, aiming to develop analytical methods for solving coupled nonlinear stochastic differential equations related to surface motion.
  • It builds on the Burton-Cabrera-Frank (BCF) model, incorporating factors like atom diffusion, step energy, and introducing Gaussian white noise to analyze system behavior.
  • The researchers utilize perturbation theory and mean-field approximations to derive formulas for the time-dependent distribution of terrace widths, with results aligning well with Monte Carlo simulations.

Article Abstract

We study analytically and numerically a one-dimensional model of interacting line defects (steps) fluctuating on a vicinal crystal. Our goal is to formulate and validate analytical techniques for approximately solving systems of coupled nonlinear stochastic differential equations (SDEs) governing fluctuations in surface motion. In our analytical approach, the starting point is the Burton-Cabrera-Frank (BCF) model by which step motion is driven by diffusion of adsorbed atoms on terraces and atom attachment-detachment at steps. The step energy accounts for entropic and nearest-neighbor elastic-dipole interactions. By including Gaussian white noise to the equations of motion for terrace widths, we formulate large systems of SDEs under different choices of diffusion coefficients for the noise. We simplify this description via (i) perturbation theory and linearization of the step interactions and, alternatively, (ii) a mean-field (MF) approximation whereby widths of adjacent terraces are replaced by a self-consistent field but nonlinearities in step interactions are retained. We derive simplified formulas for the time-dependent terrace-width distribution (TWD) and its steady-state limit. Our MF analytical predictions for the TWD compare favorably with kinetic Monte Carlo simulations under the addition of a suitably conservative white noise in the BCF equations.

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Source
http://dx.doi.org/10.1103/PhysRevE.82.061601DOI Listing

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