Electrochemical corrosion and tribocorrosion behavior of CrN and CrAlN coatings in artificial seawater.
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| Title: | Electrochemical corrosion and tribocorrosion behavior of CrN and CrAlN coatings in artificial seawater. |
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| Authors: | Bai, Xiao1 (AUTHOR), Li, Yang1,2 (AUTHOR), Guo, Chunting1 (AUTHOR), Man, Jia3 (AUTHOR), Zhang, Dejian1 (AUTHOR), Wan, Yong1,4 (AUTHOR) wanyong@qlu.edu.cn, Sun, Huilai1 (AUTHOR) sunhl@qlu.edu.cn |
| Source: | International Journal of Applied Ceramic Technology. Sep2024, Vol. 21 Issue 5, p3569-3582. 14p. |
| Subjects: | DC sputtering, Electrolytic corrosion, Magnetron sputtering, Wear resistance, Corrosion resistance, Tribo-corrosion, Artificial seawater |
| Abstract: | This study investigated the corrosion and tribocorrosion behavior of CrN and CrAlN coatings deposited on steel through direct current magnetron sputtering. Additionally, the effects of Al addition on the microstructure, corrosion inhibition, and tribocorrosion behavior of CrN coatings were evaluated. Compared with the CrN coating, the CrAlN coating exhibited a denser columnar crystal structure and a higher hardness of 23.8 GPa. The CrAlN coating reacted with water to form Al2O3 and Cr2O3 films, which enhanced its corrosion resistance. Moreover, the addition of Al enhanced the wear resistance of the CrN coating and reduced the material loss due to corrosion, wear, and their synergistic effects. The CrAlN coating exhibited a low corrosion current density of 1.14 × 10−8 A/cm2, indicating a 92% reduction compared with the CrN coating. Furthermore, under either open circuit potential or anodic accelerated tribocorrosion conditions, the CrAlN coating featured significantly lower total material loss and synergistic material loss than the CrN coating, demonstrating higher corrosion and tribocorrosion protection. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Applied Ceramic Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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