Influence of scanning rate on quality of AFM image: Study of surface statistical metrics

TLDR

The study discusses how fractal and statistical surface parameters can characterize data distortion caused by inappropriate AFM scanning rates. The study investigates how AFM data reliability depends on scanning rate. The authors examined 3D surface topographies of micro‑motif samples, performed cube‑counting fractal analysis and statistical metric evaluation, and plotted combined quantitative parameters to assess artifacts from scanning rate. Results show that sensitivity to scanning rate increases with sample fractal dimension, enabling image distortion description and potential application to other measurement parameters.

Abstract

Abstract The purpose of this work is to study the dependence of AFM‐data reliability on scanning rate. The three‐dimensional (3D) surface topography of the samples with different micro‐motifs is investigated. The analysis of surface metrics for estimation of artifacts from inappropriate scanning rate is presented. Fractal analysis was done by cube counting method and evaluation of statistical metrics was carrying out on the basis of AFM‐data. Combination of quantitate parameters is also presented in graphs for every measurement. The results indicate that the sensitivity to scanning rate growths with fractal dimension of the sample. This approach allows describing the distortion of the images against scanning rate and could be applied for dependences on the other measurement parameters. The article explains the relevance and comparison of fractal and statistical surface parameters for characterization of data distortion caused by inappropriate choice of scanning rate.