Investigation of the Laser Parameters that Should Be Used to Optimize the Root Mean Square Height Value, One of the Roughness Parameters Required to Obtain a More Hydrophobic Surface

Yıl 2025, Cilt: 8 Sayı: 2, 1 - 12, 31.12.2025

Timur Canel , Çağla Pilavcı , Şeref Tosunoğlu

https://doi.org/10.38061/idunas.1727587

Öz

This study investigates the effects of fiber laser surface texturing on ST52 steel plates to enhance hydrophobicity by optimizing surface roughness (Sq). Three key parameters—geometric pattern type (square, diamond, hexagon, circle), laser power (40–100 W), and theoretical laser-scanned area factor (20–80%)—were examined using the Taguchi L16 orthogonal array to minimize experimental runs while ensuring statistical validity. The goal was to maximize the Root Mean Square Height (Sq) for improved hydrophobic performance.
Results revealed that the hexagonal pattern, 100 W laser power, and 80% scanning area produced the highest Sq value (338.39 µm), with a corresponding signal-to-noise (S/N) ratio of 50.59. ANOVA identified the scanning area factor (39.94%) as the most influential parameter, followed by laser power (34.29%) and pattern type (25.77%). Non-linear trends were observed: Sq peaked at 60 W and 100 W but dipped at 80 W, while the 80% scanning area yielded the roughest surface, and 40% the smoothest.
For hydrophobic applications, the optimal combination was circular/diamond patterns, 80% scanning area, and 60 W or 100 W laser power. Conversely, low-friction surfaces required square/hexagonal patterns, 40% scanning area, and 40 W or 80 W power. The study demonstrates the efficacy of fiber laser texturing for tailoring ST52 steel surfaces and underscores the Taguchi method’s utility in parameter optimization.

Anahtar Kelimeler

Fiber laser texturing , ST52 steel , surface roughness (Sq) , Taguchi method , hydrophobicity , laser power , geometric patterning.

Daha Hidrofobik Bir Yüzey Elde Etmek İçin Gerekli Pürüzlülük Parametrelerinden Biri Olan Kök Ortalama Kare Yükseklik Değerinin Optimize Edilmesinde Kullanılması Gereken Lazer Parametrelerinin Araştırılması

Öz

Bu çalışma, yüzey pürüzlülüğünü (Sq) optimize ederek hidrofobikliği artırmak için ST52 çelik levhalar üzerinde fiber lazer yüzey dokulandırmanın etkilerini araştırmaktadır. Geometrik desen türü (kare, elmas, altıgen, daire), lazer gücü (40–100 W) ve teorik lazer tarama alanı faktörü (20–80%) olmak üzere üç temel parametre, deneysel çalışmalardan en az sayıda yararlanırken istatistiksel geçerliliği sağlamak için Taguchi L16 ortogonal dizisi kullanılarak incelenmiştir. Amaç, hidrofobik performansı iyileştirmek için Kare Ortalama Yükseklik (Sq) değerini en üst düzeye çıkarmaktı.
Sonuçlar, altıgen desen, 100 W lazer gücü ve %80 tarama alanının en yüksek Sq değerini (338,39 µm) ürettiğini ve buna karşılık gelen sinyal-gürültü (S/N) oranının 50,59 olduğunu ortaya koydu. ANOVA, tarama alanı faktörünü (%39,94) en etkili parametre olarak belirledi, bunu lazer gücü (%34,29) ve desen türü (%25,77) izledi. Doğrusal olmayan eğilimler gözlemlendi: Sq, 60 W ve 100 W'da zirveye ulaşırken 80 W'da düştü, %80 tarama alanı en pürüzlü yüzeyi, %40 ise en pürüzsüz yüzeyi verdi.
Hidrofobik uygulamalar için en uygun kombinasyon dairesel/elmas desenler, %80 tarama alanı ve 60 W veya 100 W lazer gücüydü. Tersine, düşük sürtünmeli yüzeyler için kare/altıgen desenler, %40 tarama alanı ve 40 W veya 80 W güç gerekliydi. Çalışma, ST52 çelik yüzeylerin uyarlanmasında fiber lazer tekstüreleme yönteminin etkinliğini göstermekte ve parametre optimizasyonunda Taguchi yönteminin yararını vurgulamaktadır.

Anahtar Kelimeler

Fiber lazer dokulandırma , ST52 çeliği , yüzey pürüzlülüğü (Sq) , Taguchi yöntemi , hidrofobisite , lazer gücü , geometrik desenlendirme.

Kaynakça

• 1. Nassiri, N., Abbasi, A., Ardestani, M., & Farnia, A. (2023). Effect of welding mode and filler metal on microstructure and mechanical properties of dissimilar joints of S900MC thermomechanical steel to St52 carbon steel welded by gas tungsten arc welding. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 237(3), 771-781.
• 2. Radu, S. M., Vîlceanu, F., Toderas, M., Lihoacă, A., & Dinescu, S. (2024). Determining the Level of Structural and Mechanical Degradation of Steel in the Supporting Structure of Mining Excavation Machinery. Processes, 12(1), 153.
• 3. Sengupta, P., & Manna, I. (2022). Advanced high-temperature structural materials in petrochemical, metallurgical, power, and aerospace sectors—An overview. Future landscape of structural materials in India, 79-131.
• 4. Wypych, G. (2023). Handbook of Surface Improvement and Modification. Elsevier.
• 5. Lausmaa, J. (2001). Mechanical, thermal, chemical and electrochemical surface treatment of titanium. Titanium in medicine: material science, surface science, engineering, biological responses and medical applications, 231-266.
• 6. Adeoye, A. E., Adeaga, O. A., & Ukoba, K. (2024). Chemical Vapour Deposition (CVD) and Physical Vapour Deposition (PVD) techniques: Advances in thin film solar cells. Nigerian Journal of Technology, 43(3), 479-489.
• 7. Kanchana, R., Ponnuchamy, M., Kapoor, A., & Sethupathi, P. B. (2024). Coatings in the Automobile Application. Functional Coatings for Biomedical, Energy, and Environmental Applications, 343-361.
• 8. Grilli, M. L., Valerini, D., Slobozeanu, A. E., Postolnyi, B. O., Balos, S., Rizzo, A., & Piticescu, R. R. (2021). Critical raw materials saving by protective coatings under extreme conditions: A review of last trends in alloys and coatings for aerospace engine applications. Materials, 14(7), 1656.
• 9. Sultana, N., Nishina, Y., & Nizami, M. Z. I. (2024). Surface modifications of medical grade stainless steel. Coatings, 14(3), 248.
• 10. Yeomans, S. R. (2018). Galvanized steel reinforcement: Recent developments and new opportunities. Proceedings of the 5th International Federation for Structural Concrete, 7-11.
• 11. Seshan, K. (Ed.). (2012). Handbook of thin film deposition. William Andrew.
• 12. Saran, R., Ginjupalli, K., George, S. D., Chidangil, S., & VK, U. (2023). LASER as a tool for surface modification of dental biomaterials: A review. Heliyon, 9(6).
• 13. Wang, H., Deng, D., Zhai, Z., & Yao, Y. (2024). Laser-processed functional surface structures for multi-functional applications-a review. Journal of Manufacturing Processes, 116, 247-283.
• 14. Arulvel, S., Jain, A., Kandasamy, J., & Singhal, M. (2023). Laser processing techniques for surface property enhancement: Focus on material advancement. Surfaces and Interfaces, 42, 103293.
• 15. Van Dam, J. P. B., Abrahami, S. T., Yilmaz, A., Gonzalez-Garcia, Y., Terryn, H., & Mol, J. M. C. (2020). Effect of surface roughness and chemistry on the adhesion and durability of a steel-epoxy adhesive interface. International Journal of Adhesion and Adhesives, 96, 102450.
• 16. Murari, G., Nahak, B., & Pratap, T. (2025). Hybrid surface modification for improved tribological performance of IC engine components–a review. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 239(3), 1103-1115.
• 17. Arabian, J. (2020). Computer integrated electronics manufacturing and testing. CRC Press. 18. Shetty, R. (2022). DIFFICULT TO MACHINE MATERIALS. Industrial Engineering.
• 19. Machado, A. R., da Silva, L. R. R., Pimenov, D. Y., de Souza, F. C. R., Kuntoğlu, M., & de Paiva, R. L. (2024). Comprehensive review of advanced methods for improving the parameters of machining steels. Journal of Manufacturing Processes, 125, 111-142.
• 20. Bharathidasan, T., Kumar, S. V., Bobji, M. S., Chakradhar, R. P. S., & Basu, B. J. (2014). Effect of wettability and surface roughness on ice-adhesion strength of hydrophilic, hydrophobic and superhydrophobic surfaces. Applied surface science, 314, 241-250.
• 21. Pan, R., Cai, M., Liu, W., Luo, X., Chen, C., Zhang, H., & Zhong, M. (2019). Extremely high Cassie–Baxter state stability of superhydrophobic surfaces via precisely tunable dual-scale and triple-scale micro–nano structures. Journal of Materials Chemistry A, 7(30), 18050-18062.
• 22. Du, R., Gao, X., Feng, Q., Zhao, Q., Li, P., Deng, S., ... & Zhang, J. (2016). Microscopic dimensions engineering: stepwise manipulation of the surface wettability on 3D substrates for oil/water separation. Advanced Materials, 28(5), 936-942.
• 23. Sushil, K., Ramkumar, J., & Chandraprakash, C. (2025). Surface roughness analysis: A comprehensive review of measurement techniques, methodologies, and modeling. Journal of Micromanufacturing, 25165984241305225.
• 24. Bhushan, B. (2000). Surface roughness analysis and measurement techniques. In Modern tribology handbook, two volume set (pp. 79-150). CRC press.
• 25. Razavifar, M., Abdi, A., Nikooee, E., Aghili, O., & Riazi, M. (2025). Quantifying the impact of surface roughness on contact angle dynamics under varying conditions. Scientific Reports, 15(1), 1-18.
• 26. Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. (2011). Optimization methods applied to renewable and sustainable energy: A review. Renewable and sustainable energy reviews, 15(4), 1753-1766.
• 27. Tsui, K. L. (1992). An overview of Taguchi method and newly developed statistical methods for robust design. Iie Transactions, 24(5), 44-57.