Statistical and Fractal Description of Defects on Topography Surfaces

University of Johannesburg, Department of Mechanical Engineering Sciences, Auckland Park Kingsway Campus, 2006, Johannesburg, South Africa

^* Corresponding author: fredrick.mwema@dkut.ac.ke

Abstract

In this article, simulated/artificial surfaces consisting of perfectly ordered and mounded (perfect) structures and defective surfaces are characterised through statistical and fractal methods. The image sizes are designed to mimic atomic force microscopy (AFM) of scan area 1 μm2 and maximum height features of 500 nm. The simulated images are then characterised using statistical tools such as root mean square and average roughness, skewness, kurtosis, and maximum pit and peaks. Fractal analyses are also undertaken using fractal dimensions, autocorrelation, height-height correlation and power spectral density functions. The results reveal significant differences between defective and perfectly ordered and mounded surfaces. The defective surfaces exhibit higher roughness values and lower fractal dimensions values as compared to the perfect surfaces. The results in this article can help researchers to better explain their results on topography and surface evolution of thin films.