Analysis of AFM images of self-structured surface textures by directional fractal signature method

A new method, called augmented blanket with rotating grid (ABRG), has been proposed in our recent work on characterizing roughness and directionality of self-structured surface textures. This is the first method that calculates fractal dimensions (FDs) at individual scales and directions for the ent...

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Main Authors: Wolski, Marcin, Podsiadlo, Pawel, Stachowiak, Gwidon
Format: Journal Article
Published: Springer 2013
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/12192
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author Wolski, Marcin
Podsiadlo, Pawel
Stachowiak, Gwidon
author_facet Wolski, Marcin
Podsiadlo, Pawel
Stachowiak, Gwidon
author_sort Wolski, Marcin
building Curtin Institutional Repository
collection Online Access
description A new method, called augmented blanket with rotating grid (ABRG), has been proposed in our recent work on characterizing roughness and directionality of self-structured surface textures. This is the first method that calculates fractal dimensions (FDs) at individual scales and directions for the entire surface image data and does not require the data to be Brownian fractal. However, before the ABRG method can be used in real applications, effects of atomic force microscope (AFM) imaging conditions on FDs need to be evaluated first. In this paper, computer-generated AFM images with three different resolutions, 48 combinations of tip radii and cone angles, and 15 noise levels were used in the tests. The images represent isotropic self-structured surface textures with small, medium and large motif sizes, and anisotropic surfaces exhibiting two dominating directions. For isotropic surfaces, the ABRG method is not significantly affected (i.e. FDs changes <5 %) by image resolution, tip size (for surfaces with large motifs) and noise (except the level above 8 %). For anisotropic surfaces, the method exhibits large changes in FDs (up to −34 %). The results obtained show that the ABRG method can be effective in analysing the AFM images of self-structured surface textures. However, some precautions should be taken with anisotropic and isotropic surfaces with small motifs.
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spelling curtin-20.500.11937-121922017-09-13T14:56:51Z Analysis of AFM images of self-structured surface textures by directional fractal signature method Wolski, Marcin Podsiadlo, Pawel Stachowiak, Gwidon Atomic force microscope Self-structured surfaces Surface characterization Texture A new method, called augmented blanket with rotating grid (ABRG), has been proposed in our recent work on characterizing roughness and directionality of self-structured surface textures. This is the first method that calculates fractal dimensions (FDs) at individual scales and directions for the entire surface image data and does not require the data to be Brownian fractal. However, before the ABRG method can be used in real applications, effects of atomic force microscope (AFM) imaging conditions on FDs need to be evaluated first. In this paper, computer-generated AFM images with three different resolutions, 48 combinations of tip radii and cone angles, and 15 noise levels were used in the tests. The images represent isotropic self-structured surface textures with small, medium and large motif sizes, and anisotropic surfaces exhibiting two dominating directions. For isotropic surfaces, the ABRG method is not significantly affected (i.e. FDs changes <5 %) by image resolution, tip size (for surfaces with large motifs) and noise (except the level above 8 %). For anisotropic surfaces, the method exhibits large changes in FDs (up to −34 %). The results obtained show that the ABRG method can be effective in analysing the AFM images of self-structured surface textures. However, some precautions should be taken with anisotropic and isotropic surfaces with small motifs. 2013 Journal Article http://hdl.handle.net/20.500.11937/12192 10.1007/s11249-012-0088-4 Springer restricted
spellingShingle Atomic force microscope
Self-structured surfaces
Surface characterization
Texture
Wolski, Marcin
Podsiadlo, Pawel
Stachowiak, Gwidon
Analysis of AFM images of self-structured surface textures by directional fractal signature method
title Analysis of AFM images of self-structured surface textures by directional fractal signature method
title_full Analysis of AFM images of self-structured surface textures by directional fractal signature method
title_fullStr Analysis of AFM images of self-structured surface textures by directional fractal signature method
title_full_unstemmed Analysis of AFM images of self-structured surface textures by directional fractal signature method
title_short Analysis of AFM images of self-structured surface textures by directional fractal signature method
title_sort analysis of afm images of self-structured surface textures by directional fractal signature method
topic Atomic force microscope
Self-structured surfaces
Surface characterization
Texture
url http://hdl.handle.net/20.500.11937/12192