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Open AccessArticle

Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions

1
Institute of Physics—Centre for Science and Education, Silesian University of Technology, 44-100 Gliwice, Poland
2
Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, 44-100 Gliwice, Poland
3
Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
4
Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences, 33619 Bielefeld, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Ştefan Ţǎlu
Appl. Sci. 2021, 11(5), 2436; https://doi.org/10.3390/app11052436
Received: 24 February 2021 / Revised: 3 March 2021 / Accepted: 3 March 2021 / Published: 9 March 2021
(This article belongs to the Special Issue Characterizations of Three-Dimensional Surfaces at Micro/Nanoscale)
Two-dimensional structures, either periodic or random, can be classified by diverse mathematical methods. Quantitative descriptions of such surfaces, however, are scarce since bijective definitions must be found to measure unique dependency between described structures and the chosen quantitative parameters. To solve this problem, we use statistical analysis of periodic fibrous structures by Hurst exponent distributions. Although such a Hurst exponent approach was suggested some years ago, the quantitative analysis of atomic force microscopy (AFM) images of nanofiber mats in such a way was described only recently. In this paper, we discuss the influence of typical AFM image post-processing steps on the gray-scale-resolved Hurst exponent distribution. Examples of these steps are polynomial background subtraction, aligning rows, deleting horizontal errors and sharpening. Our results show that while characteristic features of these false-color images may be shifted in terms of gray-channel and Hurst exponent, they can still be used to identify AFM images and, in the next step, to quantitatively describe AFM images of nanofibrous surfaces. Such a gray-channel approach can be regarded as a simple way to include some information about the 3D structure of the image. View Full-Text
Keywords: Hurst exponent distribution; random walk; atomic force microscopy (AFM); electrospinning; poly(acrylonitrile) (PAN) Hurst exponent distribution; random walk; atomic force microscopy (AFM); electrospinning; poly(acrylonitrile) (PAN)
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MDPI and ACS Style

Blachowicz, T.; Domino, K.; Koruszowic, M.; Grzybowski, J.; Böhm, T.; Ehrmann, A. Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions. Appl. Sci. 2021, 11, 2436. https://doi.org/10.3390/app11052436

AMA Style

Blachowicz T, Domino K, Koruszowic M, Grzybowski J, Böhm T, Ehrmann A. Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions. Applied Sciences. 2021; 11(5):2436. https://doi.org/10.3390/app11052436

Chicago/Turabian Style

Blachowicz, Tomasz; Domino, Krzysztof; Koruszowic, Michał; Grzybowski, Jacek; Böhm, Tobias; Ehrmann, Andrea. 2021. "Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions" Appl. Sci. 11, no. 5: 2436. https://doi.org/10.3390/app11052436

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