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

## TL;DR

This study investigates how applying bias voltage influences the statistical and microstructural properties of rough surfaces, using atomic force microscopy and stochastic analysis to connect microscopic changes with macroscopic surface characteristics.

## Contribution

It introduces a method to analyze the impact of bias voltage on surface roughness through stochastic parameters and examines the tip convolution effect on these parameters.

## Key findings

- Bias voltage alters surface roughness parameters.
- Stochastic parameters correlate with macroscopic surface properties.
- Tip convolution affects the measurement of stochastic parameters.

## 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.