Effects of Cu content and Sintering temperature on microstructure and mechanical properties of SiCp/Al-Cu-Mg composites through experimental study, CALPHAD-type simulation and machine learning

被引:0
作者
Yang, Wei [1 ,2 ]
Wang, Yiwei [3 ]
Huang, Xiaozhong [1 ,2 ]
Liu, Shuhong [2 ]
Wang, Peisheng [1 ,2 ]
Du, Yong [2 ]
机构
[1] Cent South Univ, Hunan Key Lab Adv Fibers & Composites, Changsha 410083, Peoples R China
[2] Cent South Univ, State Key Lab Powder Met, Changsha, Hunan, Peoples R China
[3] Hunan Boxiang New Mat Ltd, Changsha, Hunan, Peoples R China
来源
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T | 2024年 / 33卷
关键词
SiCp/Al; Composite materials; Machine learning; Alloy design; CALPHAD; PARAMETERS;
D O I
10.1016/j.jmrt.2024.09.202
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
SiCp/Al composite materials are widely used due to their lightweight and high strength. There is no systematic study on the effect of variation of Cu content on the mechanical properties of composites. In order to study the effect of Cu content on the properties of composites, SiCp/Al composites with Cu content of 0.35-4 wt% were designed and prepared with the assistance of the CALPHAD method. The samples were sintered between 570 and 620 degrees C. The microstructures and mechanical properties of the composites were systematically studied. The results show that the sample with a Cu content of 2.45 wt% and a sintering temperature of 590 degrees C achieved a maximum tensile strength of 314 MPa, which is different from the Cu composition widely used in the literature. For practical use, the relationship between the optimum sintering temperature and the Cu content, liquidus temperature and solidus temperature was studied. In order to explore ingredients with better performance, machine learning was applied. The database containing information including material compositions, preparation process, and mechanical properties was constructed, and then four machine learning models were applied to establish the quantitative relationship of "component-process-performance" in SiCp/Al composite materials. The RFReg model was selected as the best model and used to design the composition and process parameters of the composite alloy. A new composite was designed by the machine learning models. The sintered tensile strength was 349 MPa, and the strength reached 561 MPa after hot pressing and heat treatment.
引用
收藏
页码:2216 / 2225
页数:10
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