Numerical characterization of AFM images of self-structured surface textures

Results obtained showed that, for the isotropic surfaces, the ABRG method is not considerably affected (i.e. <5%) by image resolution, tip size (for surfaces with large motifs) and noise levels lower than 9%. On the other hand, for anisotropic surfaces, the effects were much stronger (i.e. -34%)....

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Main Authors: Wolski, M., Podsiadlo, P., Stachowiak, Gwidon
Format: Conference Paper
Published: Politecnico di Torino (DIMEAS) 2014
Online Access:http://hdl.handle.net/20.500.11937/8013
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author Wolski, M.
Podsiadlo, P.
Stachowiak, Gwidon
author_facet Wolski, M.
Podsiadlo, P.
Stachowiak, Gwidon
author_sort Wolski, M.
building Curtin Institutional Repository
collection Online Access
description Results obtained showed that, for the isotropic surfaces, the ABRG method is not considerably affected (i.e. <5%) by image resolution, tip size (for surfaces with large motifs) and noise levels lower than 9%. On the other hand, for anisotropic surfaces, the effects were much stronger (i.e. -34%). This indicates that ABRG method can be effective in the analysis of AFM images of self-structured surface textures. However, precautions should be taken when analyzing AFM images of surface textures with small motifs and/or anisotropy. The results also showed that the ABRG method is able to quantify changes in surface roughness occurring during the formation of photoinduced textures. Thus, the method has a potential to become a valuable tool in analyzing formation process of self-structured surfaces.
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format Conference Paper
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institution Curtin University Malaysia
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publishDate 2014
publisher Politecnico di Torino (DIMEAS)
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spelling curtin-20.500.11937-80132017-01-30T11:03:59Z Numerical characterization of AFM images of self-structured surface textures Wolski, M. Podsiadlo, P. Stachowiak, Gwidon Results obtained showed that, for the isotropic surfaces, the ABRG method is not considerably affected (i.e. <5%) by image resolution, tip size (for surfaces with large motifs) and noise levels lower than 9%. On the other hand, for anisotropic surfaces, the effects were much stronger (i.e. -34%). This indicates that ABRG method can be effective in the analysis of AFM images of self-structured surface textures. However, precautions should be taken when analyzing AFM images of surface textures with small motifs and/or anisotropy. The results also showed that the ABRG method is able to quantify changes in surface roughness occurring during the formation of photoinduced textures. Thus, the method has a potential to become a valuable tool in analyzing formation process of self-structured surfaces. 2014 Conference Paper http://hdl.handle.net/20.500.11937/8013 Politecnico di Torino (DIMEAS) restricted
spellingShingle Wolski, M.
Podsiadlo, P.
Stachowiak, Gwidon
Numerical characterization of AFM images of self-structured surface textures
title Numerical characterization of AFM images of self-structured surface textures
title_full Numerical characterization of AFM images of self-structured surface textures
title_fullStr Numerical characterization of AFM images of self-structured surface textures
title_full_unstemmed Numerical characterization of AFM images of self-structured surface textures
title_short Numerical characterization of AFM images of self-structured surface textures
title_sort numerical characterization of afm images of self-structured surface textures
url http://hdl.handle.net/20.500.11937/8013