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Coatings
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Advanced Surface Topography and Engineering in Machine and Tool Applications
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Advanced Surface Topography and Engineering in Machine and Tool Applications

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

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2083

Special Issue Editors

Prof. Dr. Chithirai Pon Selvan

E-Mail Website
Guest Editor
Science and Engineering, Curtin University Dubai, Dubai, United Arab Emirates
Interests: manufacturing practices; optimization techniques; materials engineering; tribology
Special Issues, Collections and Topics in MDPI journals
Dr. Avinash Lakshmikanthan

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology (NMIT), Nitte (Deemed to be University), Bengaluru 560064, India
Interests: additive manufacturing; machine design; materials engineering; tribology
Prof. Dr. Wahidul K. Biswas

E-Mail Website
Guest Editor
School of Civil and Mechanical Engineering, Curtin University, Bentley, Perth, WA 6102, Australia
Interests: sustainable engineering; sustainable materials; life cycle assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Surface topography is an important part of modern machine and tool engineering, enabling the development of new ideas and applications. It affects almost every part of how a component works, including wear, friction, energy efficiency, and how long the product lasts. As production is increasingly requiring more rigorous and demanding applications, better topography characterisation and control are more critical than ever. With micro- and nano-scale features being built into surfaces, it is now possible to improve lubrication, extend tool life, and improve tribological behaviour. This changes how materials and machine parts work together in real life. This Special Issue highlights the latest research, methods, and case studies on how to measure, simulate, and create engineered surfaces for tools and machines. The latest developments in metrology, like atomic force microscopy and optical interferometry, are discussed, along with new ways to model, develop, and test surface features aimed at solving problems in various industries. This Special Issue seeks to improve knowledge of how advanced surface engineering enhances performance, durability, and sustainability in essential machinery through fundamental research and application-oriented examples. This collection promotes the development of new manufacturing technologies by encouraging investigation of the scientific basis and real-world applications arising from advances in surface topography and engineering.

We look forward to receiving your contributions.

Prof. Dr. Chithirai Pon Selvan
Dr. Avinash Lakshmikanthan
Prof. Dr. Wahidul K. Biswas
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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 topography
  • sustainable surface engineering
  • tribology
  • tool life enhancement
  • micro- and nano-scale features

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

22 pages, 4084 KB  
Article
Multi-Objective Optimization of Surface Roughness and Material Removal Rate in Ultrasonic Vibration-Assisted CBN Grinding of External Cylindrical Surfaces
by Toan-Thang Ha, Anh-Tung Luu and Ngoc-Pi Vu
Coatings 2026, 16(3), 333; https://doi.org/10.3390/coatings16030333 - 8 Mar 2026
Cited by 1 | Viewed by 530
Abstract
Ultrasonic vibration-assisted grinding using cubic boron nitride (CBN) wheels has emerged as an effective approach for improving surface integrity and machining efficiency in hard-to-machine materials. However, achieving a desirable balance between surface roughness and material removal rate remains a critical challenge due to [...] Read more.
Ultrasonic vibration-assisted grinding using cubic boron nitride (CBN) wheels has emerged as an effective approach for improving surface integrity and machining efficiency in hard-to-machine materials. However, achieving a desirable balance between surface roughness and material removal rate remains a critical challenge due to their inherently conflicting nature. In this study, a multi-objective optimization framework is proposed to simultaneously minimize surface roughness (Ra) and maximize material removal rate (MRR) in external cylindrical CBN grinding performed on a computer numerical control (CNC) milling machine under ultrasonic vibration assistance. Gaussian process regression models were first developed to accurately represent the nonlinear relationships between machining parameters and the target responses. These surrogate models were subsequently integrated with the non-dominated sorting genetic algorithm II (NSGA-II) to generate a set of Pareto-optimal solutions. The convergence behavior of the optimization process was evaluated using the hypervolume indicator, confirming fast and stable convergence. The resulting Pareto front clearly illustrates the trade-off between Ra and MRR, and a knee point solution was identified as a practical compromise for industrial application. The optimized results demonstrate that ultrasonic vibration-assisted CBN grinding can significantly enhance machining performance while maintaining acceptable surface quality. The proposed methodology provides an effective decision-support tool for multi-objective process optimization in advanced grinding applications. Full article
(This article belongs to the Special Issue Advanced Surface Topography and Engineering in Machine and Tool Applications)
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13 pages, 10330 KB  
Article
Enhancing Surface Integrity and Fatigue Performance of 42CrMo Rolled Threads Through Localized Root Rolling Strengthening
by Ziliang Huang, Shiqi Chen, Zhilong Xu, Fasheng Zhong, Zejie Li, Weiwen Chen, Qingshan Jiang and Bicheng Guo
Coatings 2026, 16(1), 90; https://doi.org/10.3390/coatings16010090 - 11 Jan 2026
Viewed by 539
Abstract
To improve the fatigue life of high-strength bolts, this study builds upon conventional thread rolling by introducing a localized rolling reinforcement process specifically at the thread root. Experimental specimens were prepared from 42CrMo high-strength bolts using a combined manufacturing technique that integrates thread [...] Read more.
To improve the fatigue life of high-strength bolts, this study builds upon conventional thread rolling by introducing a localized rolling reinforcement process specifically at the thread root. Experimental specimens were prepared from 42CrMo high-strength bolts using a combined manufacturing technique that integrates thread forming and root rolling. A comparative analysis was conducted to evaluate the fatigue performance of bolts with and without the root rolling reinforcement. The experimental results demonstrated that the thread root rolling treatment further refines the surface grains beyond the effects of standard thread rolling. At a rolling force of 2.5 kN, the surface microhardness increased from the original 500 HV0.2 to 540 HV0.2. The process also improved surface finish, reduced grain size, and increased dislocation density. The optimal enhancement was achieved at a rolling force of 3.5 kN, resulting in an approximately 11-fold improvement in fatigue life. Fractographic analysis via Scanning Electron Microscopy (SEM) indicated a reduced number of crack initiation sites. This study confirms the effectiveness of the proposed rolling reinforcement process, offering a viable technical pathway for optimizing the anti-fatigue manufacturing of high-strength bolts. Full article
(This article belongs to the Special Issue Advanced Surface Topography and Engineering in Machine and Tool Applications)
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13 pages, 2715 KB  
Article
Ensemble Machine Learning for Predicting Machining Responses of LB-PBF AlSi10Mg Across Distinct Cutting Environments with CVD Cutter
by Zekun Zhang, Zhenhua Dou, Kai Guo, Jie Sun and Xiaoming Huang
Coatings 2026, 16(1), 22; https://doi.org/10.3390/coatings16010022 - 24 Dec 2025
Viewed by 631
Abstract
The efficiencies of additive manufacturing (AM) over conventional processes have enabled the rapid production of aluminum (Al) alloys with AM. Because laser beam powder bed fusion (LB-PBF) parts do not offer the surface quality and geometrical accuracy for direct use, the functional surfaces [...] Read more.
The efficiencies of additive manufacturing (AM) over conventional processes have enabled the rapid production of aluminum (Al) alloys with AM. Because laser beam powder bed fusion (LB-PBF) parts do not offer the surface quality and geometrical accuracy for direct use, the functional surfaces of LB-PBF parts are usually machined by subtractive machining. The machinability of LB-PBF AlSi10Mg was studied in dry, MQL (used corn oil), and cryo-LN2 cutting environments across distinct speed–feed combinations using CVD-AlTiN-coated carbide inserts, and surface integrity and tool life were quantified in terms of surface roughness (Ra) and flank wear (Vb), respectively. The lowest Ra (0.98–1.107 μm) was obtained with cryo-LN2, followed by MQL and dry cutting environments, because the trends observed were consistent with the surface mechanisms observed in 3D topography and bearing curves. Similarly, the tool wear results mirrored the Ra results, lowest with LN2 (0.087–0.110 mm), due to improved thermal management, reduced adhesion and abrasion, and shorter contact length. Cryo-LN2 provided the best surface finish and tool life among all tested environments. To enable data-driven prediction, the limited dataset was augmented using SMOTE, and machine learning (ML) models were trained to predict Ra and Vb. CatBoost was found to yield the best Ra predictions (R2 = 0.9090), while Random Forest and XGBoost yielded the best Vb predictions (R2 ≈ 0.878). Full article
(This article belongs to the Special Issue Advanced Surface Topography and Engineering in Machine and Tool Applications)
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