2016
DOI: 10.1021/acs.jpcc.6b06635
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Surface Roughness Measurements Using Power Spectrum Density Analysis with Enhanced Spatial Correlation Length

Abstract: Roughness of a surface as characterized by an atomic force microscope (AFM) is typically expressed using conventional statistical measurements including root-mean-square, peak-to-valley ratio, and average roughness. However, in these measurements only the vertical distribution of roughness (z-axis) is considered. Additionally, roughness of a surface as determined by AFM is a function of the scanning scale, sampling interval and/ or scanning methods; therefore, the consideration and quantification of the latera… Show more

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Cited by 111 publications
(54 citation statements)
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“…Fractal analyses have been undertaken by height-toheight (H(r)), power spectral density (PSDF) functions and two-dimensional Minkowski measurements. The H(r) computation was based on the equations presented by Yadav et al [13], [14] whereas the PSDFs have been determined using the method presented by [11,18] in MATLAB®. The H(r) formula for an image area of m × m can be written as…”
Section: Experiments and Methodsmentioning
confidence: 99%
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“…Fractal analyses have been undertaken by height-toheight (H(r)), power spectral density (PSDF) functions and two-dimensional Minkowski measurements. The H(r) computation was based on the equations presented by Yadav et al [13], [14] whereas the PSDFs have been determined using the method presented by [11,18] in MATLAB®. The H(r) formula for an image area of m × m can be written as…”
Section: Experiments and Methodsmentioning
confidence: 99%
“…Surface roughness has also been shown to influence other properties such as tribology [7], wettability, transparency and hydrophobicity [8,9] and so many other physical and chemical characteristics of thin films as presented in literature [10,11]. As such, detailed characterisation of surface roughness is critical for quality control and optimisation of functionality of the thin films.…”
Section: Introduction mentioning
confidence: 99%
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“…However, the study did not provide universal testimony for the significance of these advantages for the accuracy of measurements . Extensive research is carried out on non‐contact‐type assessment of surface roughness parameters using machine vision system and artificial intelligence technology, which include methods such as laser speckle, light scattering, and optical interference . Pontes et al proposed the technique called multilayer perceptron (MLP) network architecture, which considerably reduces errors in predicting surface roughness parameters of machined components compared with currently used techniques.…”
Section: Introductionmentioning
confidence: 99%
“…14 Extensive research is carried out on non-contact-type assessment of surface roughness parameters using machine vision system and artificial intelligence technology, which include methods such as laser speckle, light scattering, and optical interference. [15][16][17][18][19] Pontes et al 20 proposed the technique called multilayer perceptron (MLP) network architecture, which considerably reduces errors in predicting surface roughness parameters of machined components compared with currently used techniques. Huaian et al presented a new methodology to assess surface roughness that uses uniform texture direction without any primary necessities, which defeats the present issues such as limited range, complex calculations, and so on.…”
mentioning
confidence: 99%