Effect of seawater intrusion in water-glycol hydraulic fluid on the electrochemical corrosion behavior of carbon steel and stainless steel
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Runzhou Xu
Abstract
Water-glycol hydraulic fluid (HFC) has been applied in deep-sea hydraulic systems owing to its flame retardant and environmental performance. However, the corrosion characteristics of metals in HFC have not been widely investigated. The electrochemical corrosion behavior of 45# steel and 17-4PH stainless steel in HFC containing four concentrations of seawater (0 %, 3 %, 11 %, 19 %) were evaluated by potentiodynamic polarizations (−800 mV∼1,500 mV vs. Hg/HgO), electrochemical impedance spectroscopy (EIS), potentiostatic polarizations (0.5 VHg/HgO) and immersion test (240 h). The research results indicate that a corrosion-resistant carbon film is formed on the surface of 17-4PH stainless steel and 45# steel in HFC. The infrared spectroscopy results suggest that the formation of the carbon film is due to the adsorption of the benzene ring of tolyltriazole (TTA) in HFC by the metal C. 45# steel exhibited stronger corrosion resistance than 17-4PH stainless steel due to the formation of a denser carbon film through high carbon content adsorption. The infiltration of seawater into HFC enhanced its corrosiveness by enhancing its conductivity and Cl− pitting on the C film. This research is significant as it sheds light on the corrosion behavior of metals in HFC, a crucial aspect in the design and maintenance of deep-sea hydraulic systems.
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: No. 52235001, 52075192
Acknowledgments
The authors would like to thank the technical support from the Experiment Center for Advanced Manufacturing and Technology in the School of Mechanical Science & Engineering of HUST. They also acknowledged the technical support from the Technology Analytical & Testing Center of HUST.
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Research ethics: Not applicable.
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. Yipan Deng: Conceptualization. Runzhou Xu: Formal analysis, Writing - Original draft, Writing - Review & Editing. Yinshui Liu: Supervision, Funding acquisition. Xianchun Jiang: Investigation.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: This study is funded by the National Natural Science Foundation of China (nos. 52235001, 52075192).
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Data availability: The raw data can be obtained on request from the corresponding author.
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