Composition design of 7XXX aluminum alloys optimizing stress corrosion cracking resistance using machine learning

In this paper, three different strategies based on machine learning methods were applied to Al-Zn-Mg-Cu series alloy composition design with the targeted property of stress corrosion cracking (SCC) resistance. By comparing the results of the strategies, it was discovered that the performance of the...

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Bibliographic Details
Published in:Materials research express 2020-04, Vol.7 (4), p.46506
Main Authors: Xinyu, Cao, Yingbo, Zhang, Jiaheng, Li, Hui, Chen
Format: Article
Language:English
Subjects:
Aging (metallurgy)
Al-Zn-Mg-Cu alloy
Alloys
Aluminum base alloys
Composition
composition design
Copper
Corrosion
Corrosion rate
Corrosion resistance
Corrosion resistant alloys
Design optimization
efficient global optimization
Global optimization
Intergranular fracture
Machine learning
machine learning method
Magnesium
Quadrilaterals
Rare earth elements
Response surface methodology
Slow strain rate
Stress corrosion cracking
Yttrium
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Summary:In this paper, three different strategies based on machine learning methods were applied to Al-Zn-Mg-Cu series alloy composition design with the targeted property of stress corrosion cracking (SCC) resistance. By comparing the results of the strategies, it was discovered that the performance of the efficient global optimization (EGO) method was better than that of response surface optimization method, and much better than that of Random method, among which the Al-6.05Zn-1.46Mg-1.32Cu-0.13Zr-0.02Ti-0.50Y-0.23Ce (named EGO alloy) alloy had the best stress corrosion cracking resistance. The slow strain rate test (SSRT) technique was carried out to compare the EGO alloy with the traditional 7N01 alloy. It indicated that the ISCC of the new EGO alloy was lower than that of traditional 7N01 alloy for both single and double aging treatment. With the XRD, SEM and EDS analysis, it was found the rare earth elements formed Al8Cu4(Y, Ce) and quadrilateral phase Al20Ti2(Y, Ce) in the EGO alloy.
ISSN:2053-1591
2053-1591
DOI:10.1088/2053-1591/ab8492