Studies of the micromorphology of sputtered TiN thin films by autocorrelation techniques

Smagoń, Kamil; Stach, Sebastian; Ţălu, Ștefan; Arman, Ali; Achour, Amine; Luna, Carlos; Ghobadi, Nader; Mardani, Mohsen; Hafezi, Fatemeh; Ahmadpourian, Azin; Ganji, Mohsen; Korpi, Alireza Grayeli

doi:10.1140/epjp/i2017-11801-5

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…ST noise errors can be counted into scattering noise, 25 background errors, 26 measurement or instrument noise, 27 spikes-like errors, 28 static noise 29 and other noise-like errors. 30 Characterization of ST with frequency-representative Fourier transform was proposed with wavelet decomposition, 31 full frequency denoising technique based on wavelet decomposition, 32 autocorrelation approaches (e.g., autocorrelation function [AF]) 33 or Fourier reduction or random phase exclusion methods. 34 Many papers are referred to the cylinder liners and piston skirts assemblies 35,36 and assessments 37,38 Amplitude of NS (also referred to the measurement noise amplitude or shortly noise amplitude) can be directly specified by calculation of discrepancy from two measured details-results of two type of measuring with the same method.…”

Section: Introductionmentioning

confidence: 99%

“…ST noise errors can be counted into scattering noise, 25 background errors, 26 measurement or instrument noise, 27 spikes‐like errors, 28 static noise 29 and other noise‐like errors 30 . Characterization of ST with frequency‐representative Fourier transform was proposed with wavelet decomposition, 31 full frequency denoising technique based on wavelet decomposition, 32 autocorrelation approaches (e.g., autocorrelation function [AF]) 33 or Fourier reduction or random phase exclusion methods 34 …”

Section: Introductionmentioning

confidence: 99%

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Proposal of frequency‐based decomposition approach for minimization of errors in surface texture parameter calculation

Podulka

2020

Surface & Interface Analysis

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In this paper, the frequency‐based decomposition approach (FBDA) for preprocessing of surface texture parameters calculation/assessment was proposed. Two types of textures were analysed: turned or grinded details. They were measured with interferometric method. For detection/minimization of high‐frequency measuring errors (HFME) the wavelets, Haar, Daubechies, Coiflet, biorthogonal or reverse‐biorthogonal approaches were proposed. Moreover, in some cases, the power spectrum density and/or autocorrelation function analysis provided an additional and/or valuable information about surface texture/features as well. It was assumed that application of various extraction methods (such as FBDA) can provide reasonable results for noise extraction in accordance to the commonly used algorithms, such as median filter, moving average (arithmetic mean) filter or other denoising procedures (e.g., Gaussian denoising filter) proposed in commercial software. The influence of proposed procedure on calculation (error minimization) of surface topography parameters (from ISO 25178 standard) was also presented. Some errors (especially those caused by false estimation of noise‐removal procedure) in surface topography parameter calculation were comprehensively studied with profile analysis; for areal HFME decomposition, the noise surface was defined. For some turned details, the HFME was observed in profiles analysis mostly. The biggest high frequencies from removed noise surface (created by noise extraction with FBDA) contained, the better results (of proposed approach) were obtained. It was also assumed that FBDA for preprocessing of both grinded and turned surfaces with various decomposition filters (in some cases the RBW) gave more ‘direct results’ that commonly used denoising approaches.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Proposal of frequency‐based decomposition approach for minimization of errors in surface texture parameter calculation

Podulka

2020

Surface & Interface Analysis

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“…Atomic force microscopy (AFM) is an effective very‐high‐resolution tool in the investigation of surface structure (Méndez, Reyes, Trejo, Stępień, & Ţălu, ; Naseri et al, ; Sobola, Ţălu, Solaymani, & Grmela, ; Stach et al, ; Ţălu et al, ). Analysis of high resolution AFM images by image processing technique can reveal the specific distribution pattern and complexity of the 3‐D surface structures (Smagoń et al, ; Solaymani et al, ; Ţălu et al, ; Zavarian et al, ).…”

Section: Introductionmentioning

confidence: 99%

The effects of deposition time on the nanoscale patterns of Ag/DLC nanocomposite synthesized by RF‐PECVD

Ţălu

Stach

Abdolghaderi

2019

Microscopy Res & Technique

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Introduction: In this study, a stereometric analysis of the three dimensional (3‐D) surfaces of the Ag/DLC nanocomposite synthesized by RF‐PECVD was performed. Materials and methods: Atomic force microscopy in noncontact mode was used to study surface morphology in correlation with multi‐parametric statistical analysis. The associated parameters of segmented motifs in conformity with ISO 25178‐2:, 2012 have been extracted using MountainsMap® Premium software. The mathematical algorithm computes detached watersheds of hill or dale motifs and determines the maximum and minimum points of motifs. Results and discussion: The stereometric analyses with MountainsMap® Premium software provided detailed information on the 3‐D surface topography of samples. Fractal analyses revealed the fractal nature of the performed samples is in correlation with the deposition time of samples. Detailed information of manufactured Ag/diamond‐like carbon (DLC) nanocomposite is given based on the information about the surface structure, properties, and performance characteristics. The performed analysis allows the high‐resolution modeling of Ag/DLC nanocomposite surface microtexture with motif analysis (intrinsic characteristics disclosure and characterization of surfaces fractal), in order to be included in computer interactive simulation algorithms. Conclusion: It was found the fractal dimension decreases with the increase of the deposition times on samples.

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“…However, the suitable selection of the analysis method of the AFM data is crucial to extract the relevant information to characterize the morphology properties of surfaces. For this reason, a variety of approaches based on the use of functional characterizations and fractal analysis have been implemented during the last few years in the study of thin films [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Improving the Corrosion Resistance of Ni/SS Thin Films by Nitrogen Ion Implantation

et al. 2019

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N + ions were incorporated into nickel-coated 316 stainless steel (SS) at room temperature using different energies (10, 20, and 50 keV) and a fluence of 5 × 10 17 N + cm −2. The microstructure, surface morphology, and corrosion inhibition of the obtained materials were investigated and compared with the properties of the untreated steel using several analytical techniques. The X-ray diffraction patterns indicated the formation of nickel nitride with the ion implantation process. The surface morphology of the samples was studied by atomic force microscopy and statistical and multifractal analytical methods. Moreover, the potentiodynamic polarization test in 3.5% NaCl solution was carried out to evaluate the corrosion properties of the samples. These studies revealed that the generalized fractal dimension, Dq, is dependent on the ion implantation energy and the symmetry of the multifractal singularity spectra, f (α), which is related to the uniformity of the sample. In this manner, the lowest value was obtained for the sample prepared with the maximum ion implantation energy. Also, the increment of the implantation energy yields to increase the corrosion resistance. The simultaneous decrease of the corrosion current density (Icorr) and the increase of the corrosion potential observed with the N + ion-implantation indicate that treated samples are more resistant to corrosion than the untreated steel, and the highest corrosion protection was observed for the maximum implantation energy (50 keV). The correlation between corrosion resistance, structural and surface morphology induced by implantation is discussed.

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Studies of the micromorphology of sputtered TiN thin films by autocorrelation techniques

Cited by 10 publications

References 29 publications

Proposal of frequency‐based decomposition approach for minimization of errors in surface texture parameter calculation

Proposal of frequency‐based decomposition approach for minimization of errors in surface texture parameter calculation

The effects of deposition time on the nanoscale patterns of Ag/DLC nanocomposite synthesized by RF‐PECVD

Improving the Corrosion Resistance of Ni/SS Thin Films by Nitrogen Ion Implantation

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