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Laser-Enhanced Wettability Control: Superhydrophilic and Superhydrophobic Surfaces
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Laser-Enhanced Wettability Control: Superhydrophilic and Superhydrophobic Surfaces

A special issue of Coatings (ISSN 2079-6412). This special issue belongs to the section "Laser Coatings".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 855

Special Issue Editors

Dr. Jingnan Zhao

E-Mail Website
Guest Editor
College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin 300453, China
Interests: laser surface modification; surface modification technology of metal materials
Special Issues, Collections and Topics in MDPI journals
Dr. Yan Wang

E-Mail Website
Guest Editor
College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin 300453, China
Interests: ultrasonic special machining; research and development of special equipment for aerospace
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advancements in laser surface modification have demonstrated significant potential in controlling superhydrophilic and superhydrophobic properties on material surfaces. This technique allows precise control over the micro- and nanoscale structures of surfaces, endowing metallic materials with unique characteristics such as antifouling, anti-icing, corrosion resistance, and antibacterial properties. These advancements can be broadly applied across various fields, including aerospace, medical devices, the automotive industry, and architecture. The combination of laser surface modification with strategic material selection and surface morphology design provides new possibilities for achieving high levels of performance under specific environmental conditions.

This Special Issue aims to explore the latest research progress, mechanistic studies, and practical applications of superhydrophilic and superhydrophobic laser surface modification technologies. We welcome researchers in the field to submit high-quality original research papers, reviews, and technical reports that showcase the development trends of laser-modified surfaces with superhydrophilic and superhydrophobic properties for various applications.

Topics of interest include, but are not limited to, the following:

  • Preparation and mechanistic studies of superhydrophilic and superhydrophobic surfaces using laser modification techniques.
  • Durability, antifouling, and corrosion resistance of laser-modified surfaces.
  • Applications of laser surface modification in anti-icing, antifouling, and antibacterial fields.
  • Design and optimization of multi-scale structural control in laser surface modification.
  • Performance testing and evaluation methods for superhydrophilic and superhydrophobic surfaces under different environments.
  • Computer modeling and simulation to predict the lifetime and reliability of laser-modified surfaces.

Dr. Yan Wang
Dr. Jingnan Zhao
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 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

  • superhydrophilic
  • superhydrophobic
  • laser surface modification
  • surface structure control
  • durability
  • antifouling

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Published Papers (2 papers)

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Research

17 pages, 3377 KiB  
Article
The Development and Experimental Validation of a Surface Roughness Prediction Model for the Vertical Vibratory Finishing of Blisks
by Yan Zhang, Yashuang Zhang, Liaoyuan Zhang, Wenhui Li, Xiuhong Li and Kun Shan
Coatings 2025, 15(6), 634; https://doi.org/10.3390/coatings15060634 - 25 May 2025
Viewed by 87
Abstract
The surface roughness of blisks during vibratory finishing is a critical evaluation index for their processing effect. Establishing a surface roughness prediction model helps reveal the processing mechanism and guide the optimization of process parameters. Therefore, based on wear theory and the least [...] Read more.
The surface roughness of blisks during vibratory finishing is a critical evaluation index for their processing effect. Establishing a surface roughness prediction model helps reveal the processing mechanism and guide the optimization of process parameters. Therefore, based on wear theory and the least squares centerline system, a relationship between the surface roughness and material removal depth was established, and a scratch influence factor was introduced to correct the impact of surface scratches on the theoretical model. Interaction parameters between the blisk and granular media were obtained through discrete element simulations and used as input parameters for the model. Machining experiments were conducted to solve the model coefficients and verify the model’s effectiveness. The results show that the average error between the surface roughness model predictions and experimental results is 11.8%. As the machining time increases, the surface roughness exhibits three successive stages: accelerated decrease, decelerated decrease, and stability. The surface roughness decreases most rapidly at 48 min of machining and reaches the machining limit at 198 min. The surface roughness prediction model established in this study effectively reveals the coupling mechanism between the scratch accumulation and material removal during vibratory finishing, providing a basis and methodology for determining the process parameters in blisk vibratory finishing. Full article
(This article belongs to the Special Issue Laser-Enhanced Wettability Control: Superhydrophilic and Superhydrophobic Surfaces)
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Graphical abstract

15 pages, 3336 KiB  
Article
Prediction Model for Material Removal Rate of TC4 Titanium Alloy Processed by Vertical Vibratory Finishing
by Kun Shan, Liaoyuan Zhang, Bo Tan, Yashuang Zhang, Wenhui Li, Xiuhong Li and Xuejie Wen
Coatings 2025, 15(3), 286; https://doi.org/10.3390/coatings15030286 - 1 Mar 2025
Viewed by 586
Abstract
To establish a high-precision prediction model for the material removal rate (MRR) of TC4 titanium alloy material in vertical vibratory finishing equipment, an orthogonal experiment was conducted using TC4 titanium alloy plate as the experimental specimen. We performed variance analysis of [...] Read more.
To establish a high-precision prediction model for the material removal rate (MRR) of TC4 titanium alloy material in vertical vibratory finishing equipment, an orthogonal experiment was conducted using TC4 titanium alloy plate as the experimental specimen. We performed variance analysis of the impact of vibration frequency, the phase difference, the mass of upper eccentric block, and the mass of lower eccentric block on the MRR. We then drew the main effect diagram and analyzed the influence of various process parameters on the MRR. Mathematical regression and a neural network were used to construct predictive models for the MRR with respect to process parameters, and a genetic algorithm (GA) was coupled to optimize the neural network to improve the predictive performance of the model. By calculating the R2, validating the set sample prediction error, and averaging the absolute percentage error (MAPE) of each model, it was found that the neural network model had better prediction performance than the mathematical regression model, with an accuracy of 82.2%. After coupling with the GA, the prediction accuracy reached 95.5%. The research results indicated that, compared with mathematical regression and the original neural networks, the neural network coupled with the GA had better predictive performance, providing an effective method for predicting the MRR in vertical vibratory finishing. Full article
(This article belongs to the Special Issue Laser-Enhanced Wettability Control: Superhydrophilic and Superhydrophobic Surfaces)
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