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Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings

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A special issue of Coatings (ISSN 2079-6412). This special issue belongs to the section "Surface Characterization, Deposition and Modification".

Deadline for manuscript submissions: closed (15 October 2024) | Viewed by 25252

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Dr. Przemysław Podulka

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Department of Manufacturing Process and Production Engineering, The Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, Powstancow Warszawy 8 Street, 35-959 Rzeszow, Poland
Interests: surface topography; roughness; measurement noise; additive manufacturing; machining; modern manufacturing
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Special Issue Information

Dear Colleagues,

Surface topography (ST) has a significant influence on the characterisation of plenty of ‘engineering-defined’ surfaces that, generally, studies, including measurement and data analysis, of the geometric features of machined elements are crucial when defining the functional performance of surfaces. This issue has also special importance in the process of control when manufacturing is provided. The analysis of ST parameters plays, consequently, many other important roles in mechanical engineering.

Recent advantages in ST analysis contain many different issues that can be affected by various errors. Most of the current papers consider studies of measurement uncertainty, noise, measurement errors in general. Many research areas are considered around the surface quality with various coatings performance. However, analysis of the errors when data are processed were not comprehensively considered when measured results were obtained.

With this in mind please welcome a Special Issue titled ‘Advances in measurement and data analysis of surfaces with functionalized coatings’. This special issue aims to collect the current high-quality results considering errors in measurement and data analysis of surface topography and review the articles that focus on the functional properties of machined elements. Contribution involving modelling, simulation and, generally, experimental methods are particularly welcome.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

Theoretical and experimental research, knowledge and new ideas in surface texture measurement uncertainty analysis.
Recent developments in measurement noise characterisation.
Characterisation of different surface coatings with a specification of surface topography parameters.
Experimental and processing high-performance coatings with their tribological properties.
Understanding of the surface coatings characterisation with minimisation of errors in surface roughness parameters calculation process.

We look forward to receiving your contributions.

Dr. Przemysław Podulka
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Coatings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

surface metrology
surface topography analysis
surface texture characterisation
functionalized coatings
measurement noise
measurement uncertainty
data analysis
surface topography creation in machining
manufacturing metrology
surface engineering

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Published Papers (11 papers)

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Editorial

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5 pages, 216 KiB

Open AccessEditorial

Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings

by Przemysław Podulka

Coatings 2022, 12(9), 1331; https://doi.org/10.3390/coatings12091331 - 13 Sep 2022

Cited by 2 | Viewed by 1693

Abstract

Coatings, taking comprehensive studies into account, cannot be considered without their functional performance [...] Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

Research

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19 pages, 4428 KiB

Open AccessArticle

Machine Learning-Driven Optimization of Micro-Textured Surfaces for Enhanced Tribological Performance: A Comparative Analysis of Predictive Models

by Zhenghui Ge, Qifan Hu, Rui Wang, Haolin Fei, Yongwei Zhu and Ziwei Wang

Coatings 2024, 14(12), 1539; https://doi.org/10.3390/coatings14121539 - 8 Dec 2024

Cited by 1 | Viewed by 969

Abstract

Micro-textured surfaces show promise in improving tribological properties, but predicting their performance remains challenging due to complex relationships between surface features and frictional behavior. This study evaluates five algorithms—linear regression, decision tree, gradient boosting, support vector machine, and neural network—for their ability to predict load-carrying capacity and friction force based on texture parameters including depth, side length, surface ratio, and shape. The neural network model demonstrated superior performance, achieving the lowest MAE (24.01) and highest R-squared value (0.99) for friction force prediction. The results highlight the potential of machine learning techniques to enhance the understanding and prediction of friction-reducing micro-textures, contributing to the development of more efficient and durable tribological systems in industrial applications. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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16 pages, 4776 KiB

Open AccessArticle

Terahertz Non-Destructive Testing of Porosity in Multi-Layer Thermal Barrier Coatings Based on Small-Sample Data

by Dongdong Ye, Zhou Xu, Houli Liu, Zhijun Zhang, Peiyong Wang, Yiwen Wu and Changdong Yin

Coatings 2024, 14(11), 1357; https://doi.org/10.3390/coatings14111357 - 25 Oct 2024

Cited by 1 | Viewed by 5554

Abstract

Accurately characterizing the internal porosity rate of thermal barrier coatings (TBCs) was essential for prolonging their service life. This work concentrated on atmospheric plasma spray (APS)-prepared TBCs and proposed the utilization of terahertz non-destructive detection technology to evaluate their internal porosity rate. The internal porosity rates were ascertained through a metallographic analysis and scanning electron microscopy (SEM), followed by the reconstruction of the TBC model using a four-parameter method. Terahertz time-domain simulation data corresponding to various porosity rates were generated employing the time-domain finite difference method. In simulating actual test signals, white noise with a signal-to-noise ratio of 10 dB was introduced, and various wavelet transforms were utilized for denoising purposes. The effectiveness of different signal processing techniques in mitigating noise was compared to extract key features associated with porosity. To address dimensionality challenges and further enhance model performance, kernel principal component analysis (kPCA) was employed for data processing. To tackle issues related to limited sample sizes, this work proposed to use the Siamese neural network (SNN) and generative adversarial network (GAN) algorithms to solve this challenge in order to improve the generalization ability and detection accuracy of the model. The efficacy of the constructed model was assessed using multiple evaluation metrics; the results indicate that the novel hybrid WT-kPCA-GAN model achieves a prediction accuracy exceeding 0.9 while demonstrating lower error rates and superior predictive performance overall. Ultimately, this work presented an innovative, convenient, non-destructive online approach that was safe and highly precise for measuring the porosity rate of TBCs, particularly in scenarios involving small sample sizes facilitating assessments regarding their service life. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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15 pages, 4890 KiB

Open AccessArticle

Surface Tribological Properties Enhancement Using Multivariate Linear Regression Optimization of Surface Micro-Texture

by Zhenghui Ge, Qifan Hu, Haitao Zhu and Yongwei Zhu

Coatings 2024, 14(10), 1258; https://doi.org/10.3390/coatings14101258 - 1 Oct 2024

Cited by 3 | Viewed by 1006

Abstract

This work aims to provide a comprehensive understanding of the structural impact of micro-texture on the properties of bearing capacity and friction coefficient through numerical simulation and theoretical calculation. Compared to the traditional optimization method of single-factor analysis (SFA) and orthogonal experiment, the multivariate linear regression (MLA) algorithm can optimize the structure parameters of the micro-texture within a wider range and analyze the coupling effect of the parameters. Therefore, in this work, micro-textures with varying texture size, area ratio, depth, and geometry were designed, and their impact on the bearing capacity and friction coefficient was investigated using SFA and MLA algorithms. Both methods obtained the optimal structures, and their properties were compared. It was found that the MLA algorithm can further improve the friction coefficient based on the SFA results. The optimal friction coefficient of 0.070409 can be obtained using the SFA method with a size of 500 µm, an area ratio of 40%, a depth of 5 µm, and a geometry of the slit, having a 10.7% reduction compared with the texture-free surface. In comparison, the friction coefficient can be further reduced to 0.067844 by the MLA algorithm under the parameters of size of 600 µm, area ratio of 50%, depth of 9 µm, and geometry of the slit. The final optimal micro-texture surface shows a 15.6% reduction in the friction coefficient compared to the texture-free surfaces and a 4.9% reduction compared to the optimal surfaces obtained by SFA. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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15 pages, 4628 KiB

Open AccessArticle

Improvement of Methods and Devices for Multi-Parameter High-Voltage Testing of Dielectric Coatings

by Vladimir Syasko, Alexey Musikhin and Igor Gnivush

Coatings 2024, 14(4), 427; https://doi.org/10.3390/coatings14040427 - 1 Apr 2024

Cited by 3 | Viewed by 1337

Abstract

Currently, the high voltage testing method is widely used to detect pinholes and porosity defects in dielectric coatings. However, most modern coatings also have requirements for the minimum allowable coating thickness. Conducting tolerance tests on the thickness of dielectric coatings concurrently along with monitoring integrity within a single technological process appears promising. Additionally, mitigating the impact of various interfering parameters is crucial. This paper conducts a theoretical and experimental examination of spark formation processes in both gas and dielectrics. This analysis takes place during the identification of both through and non-through defects in dielectric coatings on conductive substrates. The principles of selecting the test voltage for the investigated dielectric coatings, considering the need to detect both through defects and inadmissible thinning, are theoretically and experimentally justified. It is suggested to utilize a probabilistic approach for evaluating the detectability of the mentioned defects. It is demonstrated that, when the dielectric strength of the coating is known, it is feasible to identify both through and non-through defects in coatings with a calculated probability under a specified test voltage. The conditions of occurrence of partial discharges in the process of testing are investigated, and measures to suppress their influence on the inspection results are proposed. The influence of the substrate surface roughness on the magnitude of the breakdown voltage during testing is considered. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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22 pages, 10506 KiB

Open AccessArticle

A New Approach for Determining Rubber Enveloping on Pavement and Its Implications for Friction Estimation

by Di Yun, Cheng Tang, Ulf Sandberg, Maoping Ran, Xinglin Zhou, Jie Gao and Liqun Hu

Coatings 2024, 14(3), 301; https://doi.org/10.3390/coatings14030301 - 29 Feb 2024

Viewed by 1436

Abstract

The depth to which the pavement texture is enveloped by the tire tread rubber (d) is an important parameter related to contact performance. This study presents a new method (S-BAC), which relies on the ratio between the real contact area and the nominal tire-pavement contact area (S) and the bearing area curve (BAC), to measure the depth on pavements. The tire-pavement contact was simulated by contact between a non-patterned rubber block and pavement specimens. After analyzing the affecting factors, the new method was compared with previous methods by the d values and the application on the relationship between pavement texture parameters and friction. The results reveal that though there is a linear regression between the d obtained with the S-BAC and previous methods, the d values obtained with different methods differ. Applying the S-BAC method can strengthen the relationship between texture parameters and friction more than other methods. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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21 pages, 14430 KiB

Open AccessArticle

Analysis of Surface Topography Changes during Friction Testing in Cold Metal Forming of DC03 Steel Samples

by Tomasz Trzepieciński, Krzysztof Szwajka and Marek Szewczyk

Coatings 2023, 13(10), 1738; https://doi.org/10.3390/coatings13101738 - 7 Oct 2023

Cited by 1 | Viewed by 1342

Abstract

Predicting changes in the surface roughness caused by friction allows the quality of the product and the suitability of the surface for final treatments of varnishing or painting to be assessed. The results of changes in the surface roughness of DC03 steel sheets after friction testing are presented in this paper. Strip drawing tests with a flat die and forced oil pressure lubrication were carried out. The experiments were conducted under various contact pressures and lubricant pressures, and lubrication was carried out using various oils intended for deep-drawing operations. Multilayer perceptrons (MLPs) were used to find relationships between friction process parameters and other parameters (Sa, Ssk and Sku). The following statistical measures of contact force were used as inputs in MLPs: the average value of contact force, standard deviation, kurtosis and skewness. Many analyses were carried out in order to find the best network. It was found that the lubricant pressure and lubricant viscosity most significantly affected the value of the roughness parameter, Sa, of the sheet metal after the friction process. Increasing the lubricant pressure reduced the average roughness parameter (Sa). In contrast, skewness (Ssk) increased with increasing lubrication pressure. The kurtosis (Sku) of the sheet surface after the friction process was the most affected by the value of contact force and lubricant pressure. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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19 pages, 39012 KiB

Open AccessArticle

Resolving Selected Problems in Surface Topography Analysis by Application of the Autocorrelation Function

by Przemysław Podulka

Coatings 2023, 13(1), 74; https://doi.org/10.3390/coatings13010074 - 31 Dec 2022

Cited by 11 | Viewed by 2998

Abstract

In this paper, the validity of the application of an autocorrelation function for resolving some surface topography measurement problems was presented. Various types of surfaces were considered: plateau-honed, honed with burnished dimples, ground, turned, milled, laser-textured, or isotropic. They were measured with stylus and non-contact (optical) methods. Extraction of selected features, such as form and waviness (defined as an L-surface) and high-frequency measurement noise (S-surface) from raw measured data, was supported with an autocorrelation function. It was proposed to select the analysis procedures with an application of the autocorrelation function for both profile (2D) and areal (3D) analysis. Moreover, applications of various types of regular (available in the commercial software) analysis methods, such as least-square-fitted polynomial planes, selected Gaussian (regression and robust) functions, median filter, spline approach, and fast Fourier transform scheme, were proposed for the evaluation of surface topography parameters from ISO 25178 standards. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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15 pages, 4937 KiB

Open AccessArticle

Prediction Model of Aluminized Coating Thicknesses Based on Monte Carlo Simulation by X-ray Fluorescence

by Zhuoyue Li, Cheng Wang, Haijuan Ju, Xiangrong Li, Yi Qu and Jiabo Yu

Coatings 2022, 12(6), 764; https://doi.org/10.3390/coatings12060764 - 2 Jun 2022

Cited by 3 | Viewed by 2015

Abstract

An aluminized coating can improve the high-temperature oxidation resistance of turbine blades, but the inter-diffusion of elements renders the coating’s thickness difficult to achieve in non-destructive testing. As a typical method for coating thickness inspection, X-ray fluorescence mainly includes the fundamental parameter method and the empirical coefficient method. The fundamental parameter method has low accuracy for such complex coatings, while it is difficult to provide sufficient reference samples for the empirical coefficient method. To achieve accurate non-destructive testing of aluminized coating thickness, we analyzed the coating system of aluminized blades, simulated the spectra of reference samples using the open-source software XMI-MSIM, established the mapping between elemental spectral intensity and coating thickness based on partial least squares and back-propagation neural networks, and validated the model with actual samples. The experimental results show that the model’s prediction error based on the back-propagation neural network is 4.45% for the Al-rich layer and 16.89% for the Al-poor layer. Therefore, the model is more suitable for predicting aluminized coating thickness. Furthermore, the Monte Carlo simulation method can provide a new way of thinking for materials that have difficulty in fabricating reference samples. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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21 pages, 24217 KiB

Open AccessArticle

Proposals of Frequency-Based and Direction Methods to Reduce the Influence of Surface Topography Measurement Errors

by Przemysław Podulka

Coatings 2022, 12(6), 726; https://doi.org/10.3390/coatings12060726 - 25 May 2022

Cited by 13 | Viewed by 2238

Abstract

Various methods, based on both surface frequency and direction, can be alternatively proposed to reduce the influence of high-frequency measurement and data analysis errors. Various types of details were studied, e.g., cylinder liners after the plateau-honing process, plateau-honed cylinder liners with additionally burnished oil pockets (dimples), turned, ground, milled or laser-textured. They were measured with stylus or non-contact (optic) techniques. It was suggested to support various frequency-based methods, e.g., Frequency Spectrum, Power Spectral Densities or Autocorrelation Function, with direction techniques to provide reduction of errors in both detection and extraction of high-frequency measurement errors. Results can be especially valuable for regular studies when frequency-based measurement errors are difficult to be identified. Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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Review

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35 pages, 9324 KiB

Open AccessFeature PaperReview

Functionalized and Biomimicked Carbon-Based Materials and Their Impact for Improving Surface Coatings for Protection and Functionality: Insights and Technological Trends

by Aniket Kumar, Bapun Barik, Piotr G. Jablonski, Sanjiv Sonkaria and Varsha Khare

Coatings 2022, 12(11), 1674; https://doi.org/10.3390/coatings12111674 - 4 Nov 2022

Cited by 4 | Viewed by 3197

Abstract

Interest in carbon materials has soared immensely, not only as a fundamental building block of life, but because its importance has been critical to the advancement of many diverse fields, from medicine to electrochemistry, which has provided much deeper appreciation of carbon functionality in forming unprecedented structures. Since functional group chemistry is intrinsic to the molecular properties, understanding the underlying chemistry of carbon is crucial to broadening its applicability. An area of economic importance associated with carbon materials has been directed towards engineering protective surface coatings that have utility as anticorrosive materials that insulate and provide defense against chemical attack and microbial colonization of surfaces. The chemical organization of nanoscale properties can be tuned to provide reliance of materials in carbon-based coating formulations with tunable features to enhance structural and physical properties. The transition of carbon orbitals across different levels of hybridization characterized by sp¹, sp², and sp³ orientations lead to key properties embodied by high chemical resistance to microbes, gas impermeability, enhanced mechanical properties, and hydrophobicity, among other chemical and physical attributes. The surface chemistry of epoxy, hydroxyl, and carboxyl group functionalities can form networks that aid the dispersibility of coatings, which serves as an important factor to its protective nature. A review of the current state of carbon-based materials as protective coating materials are presented in the face of the main challenges affecting its potential as a future protective coating material. The review aims to explore and discuss the developmental importance to numerous areas that connects their chemical functionality to the broader range of applications Full article

(This article belongs to the Special Issue Advances in Measurement and Data Analysis of Surfaces with Functionalized Coatings)

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