Statistical and Fractal Description of Defects on Topography Surfaces

Fredrick Mwema*, Tien-Chien Jen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

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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.
Original languageEnglish
Article number01001
Number of pages8
JournalMATEC Web of Conferences
Early online date5 Jan 2023
Publication statusPublished - 2023
Externally publishedYes
EventInternational Conference on Applied Research and Engineering (ICARAE2022) - Cape Peninsula University of Technology, Cape Town, South Africa
Duration: 18 Nov 202220 Nov 2022

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