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Interfacial microstructure evolution and mechanical properties of Al/Sn joints by ultrasonic-assisted soldering 被引量:3
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作者 Wei-bing GUO Tian-min LUAN +2 位作者 xue-song leng Jing-shan HE Jiu-chun YAN 《Transactions of Nonferrous Metals Society of China》 SCIE EI CAS CSCD 2017年第4期962-970,共9页
Soldering aluminum alloys at low temperature have great potential to avoid softening of base metals.Pure Al was solderedwith pure tin assisted by ultrasound.The influence of primaryα(Al)on the microstructure of Al/Sn... Soldering aluminum alloys at low temperature have great potential to avoid softening of base metals.Pure Al was solderedwith pure tin assisted by ultrasound.The influence of primaryα(Al)on the microstructure of Al/Sn interface and its bonding strengthwas studied.It is found that the primaryα(Al)in liquid tin tends to be octahedron enclosed by Al{111}facet with the lowest surfacefree energy and growth rate.The ultrasonic action could increase the nucleation rate and refine the particles of primaryα(Al).For thelonger ultrasonic and holding time,a large amount of the octahedral primaryα(Al)particles crystallize at the Al/Sn interface.Thebonding interface exhibits the profile of rough dentation,resulting in an increment of bonding interface area and the effect ofmechanical occlusion.The bonding strength at interface could reach63MPa with ultrasonic time of40s and holding time of10min. 展开更多
关键词 aluminum alloy tin ultrasonic soldering interfacial microstructure mechanical properties
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Gaussian process regressions on hot deformation behaviors of FGH98 nickel-based powder superalloy 被引量:2
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作者 Jie Xiong Jian-Chao He +1 位作者 xue-song leng Tong-Yi Zhang 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2023年第15期177-185,共9页
The hot deformation behaviors of FGH98 nickel-based powder superalloy were experimentally investigated and theoretically analyzed by Arrhenius models and machine learning(ML).Hot compression tests were conducted with ... The hot deformation behaviors of FGH98 nickel-based powder superalloy were experimentally investigated and theoretically analyzed by Arrhenius models and machine learning(ML).Hot compression tests were conducted with a Gleeble-3800 thermo-mechanical simulation machine on the FGH98 superalloy at strain rates of 0.001–1 s–1 and temperatures of 1025–1175℃.The peak stresses under different deformation conditions were analyzed via the Sellars model and an ML-inspired Gaussian process regression(GPR)model.The prediction of the GPR model outperformed that from the Sellars model.In addition,the stress-strain responses were predicted by the GPR model and tested by experimentally measured stress-strain curves.The results indicate that the developed GPR model has great power with wide generalization capability in the prediction of hot deformation behaviors of FGH98 superalloy,as evidenced by the R2 value higher than 0.99 on the test dataset. 展开更多
关键词 Hot compressive deformation Nickel-based powder superalloy Activation energy Gaussian process regression
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