Prediction of multilayer Cr/GLC coatings degradation in deep-sea environments based on integrated mechanistic and machine learning models

doi:10.1016/j.corsci.2023.111513

IMR OpenIR

	Prediction of multilayer Cr/GLC coatings degradation in deep-sea environments based on integrated mechanistic and machine learning models
	Ma, Hongyu 1; Qin, Pengfei 1; Cui, Yu 2; Liu, Rui 1; Ke, Peiling 3; Wang, Fuhui 1; Liu, Li 1
通讯作者	Cui, Yu(ycui@imr.ac.cn) ; Liu, Rui(liurui@mail.neu.edu.cn) ; Liu, Li(liuli@mail.neu.edu.cn)
	2023-11-01
发表期刊	CORROSION SCIENCE
ISSN	0010-938X
卷号	224 页码:14
摘要	Improving the accuracy of coating lifetime prediction on small sample data has been an urgent issue to be addressed. In this paper, based on in-situ electrochemical impedance spectroscopy data of multilayer Cr/GLC coatings, a lifetime prediction formula related to the coating failure mechanism is developed, which provides a quantitative basis for estimating the coating lifetime. Furthermore, the combination of the mechanistic prediction model and the ANN + RF integrated machine learning model can further increase the model's prediction accuracy, reach 97.9%, and provide a new method for predicting coating performance and lifetime in deep-sea environments.
关键词	Multilayer Cr/GLC coatings EIS Mechanistic empirical model Machine learning models Lifetime prediction
资助者	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Chinese Academy of Sciences ; CAS Interdisciplinary Innovation Team
DOI	10.1016/j.corsci.2023.111513
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[U20B2026] ; National Key Research and Development Program of China[2022YFB3808800] ; Chinese Academy of Sciences[XDA22010303] ; CAS Interdisciplinary Innovation Team[292020000008]
WOS研究方向	Materials Science ; Metallurgy & Metallurgical Engineering
WOS类目	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:001074784300001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/179359
专题	中国科学院金属研究所
通讯作者	Cui, Yu; Liu, Rui; Liu, Li
作者单位	1.Northeastern Univ, Shenyang Natl Lab Mat Sci, Shenyang 110819, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Shi Changxu Innovat Ctr Adv Mat, Wencui Rd 62, Shenyang 110016, Peoples R China 3.Chinese Acad Sci, Ningbo Inst Mat Technol & Engn, Key Lab Marine Mat & Related Technol, Zhejiang Key Lab Marine Mat & Protect Technol, Ningbo 315201, Peoples R China
推荐引用方式 GB/T 7714	Ma, Hongyu,Qin, Pengfei,Cui, Yu,et al. Prediction of multilayer Cr/GLC coatings degradation in deep-sea environments based on integrated mechanistic and machine learning models[J]. CORROSION SCIENCE,2023,224:14.
APA	Ma, Hongyu.,Qin, Pengfei.,Cui, Yu.,Liu, Rui.,Ke, Peiling.,...&Liu, Li.(2023).Prediction of multilayer Cr/GLC coatings degradation in deep-sea environments based on integrated mechanistic and machine learning models.CORROSION SCIENCE,224,14.
MLA	Ma, Hongyu,et al."Prediction of multilayer Cr/GLC coatings degradation in deep-sea environments based on integrated mechanistic and machine learning models".CORROSION SCIENCE 224(2023):14.