Controlling surface statistical properties using bias voltage: Atomic force microscopy and stochastic analysis

Abstract

The effect of bias voltages on the statistical properties of rough surfaces has been studied using atomic force microscopy technique and its stochastic analysis. We have characterized the complexity of the height fluctuation of a rough surface by the stochastic parameters such as roughness exponent, level crossing, and drift and diffusion coefficients as a function of the applied bias voltage. It is shown that these statistical as well as microstructural parameters can also explain the macroscopic property of a surface. Furthermore, the tip convolution effect on the stochastic parameters has been examined.

arXiv comment8 pages, 11 figures;

References in corpus (8)

• Stochastic Growth Equations and Reparametrization Invariance
• Stochastic Analysis and Regeneration of Rough Surfaces
• Spatial Persistence of Fluctuating Interfaces
• Stochastic analysis of different rough surfaces
• Theoretical Model for the Kramers-Moyal Description of Turbulence Cascades
• Level Crossing Analysis of Growing surfaces
• Statistical Theory for the Kardar-Parisi-Zhang Equation in 1+1 Dimension
• Height Fluctuations and Intermittency of $V_2{O}_5$ Films by Atomic Force Microscopy

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• Analytic height correlation function of rough surfaces derived from light scattering
• Path derivation for a wave scattered model to estimate height correlation function of rough surfaces
• Markov Properties of Electrical Discharge Current Fluctuations in Plasma
• The level crossing and inverse statistic analysis of German stock market index (DAX) and daily oil price time series