β'' needle-shape precipitate formation in Al-Mg-Si alloy: Phase field simulation and experimental verification
Type
ArticleAuthors
Mao, HongKong, Yi

Cai, Dan
Yang, Mingjun
Peng, Yingbiao
Zeng, Yinping
Zhang, Geng
Shuai, Xiong
Huang, Qi
Li, Kai
Zapolsky, Helena
Du, Yong

KAUST Department
Physical Science and Engineering (PSE) DivisionDate
2020-06-20Online Publication Date
2020-06-20Print Publication Date
2020-11Embargo End Date
2022-06-20Submitted Date
2020-02-23Permanent link to this record
http://hdl.handle.net/10754/663849
Metadata
Show full item recordAbstract
β'' needle-shape precipitate structures significantly affect the mechanical properties of 6xxx aluminum alloys. In this study, a modified multi-phase field (MPF) method combined with the thermodynamic and kinetic databases provided with the CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) method has been employed to investigate the morphological evolution of the monoclinic β'' precipitates in Al-Mg-Si alloy. Emphasis has been placed on understanding the influences of interfacial energy anisotropy and elastic interaction on the shape of β'' precipitates. It is shown that the high anisotropic strain alone cannot explain the needle shape of β'' precipitates. In the case of considering the contributions from both anisotropic interfacial energy and elastic interaction simultaneously, the simulations lead to the formation of unique micro-needle-like structures in age strengthening 6xxx Al alloy. The simulation results are compared with plate-shaped θ'(Al2Cu) precipitate in Al-Cu system, and verified with high-resolution transmission electron microscopy (HRTEM) images of needle-like β'' precipitates in Al-Mg-Si system.Citation
Mao, H., Kong, Y., Cai, D., Yang, M., Peng, Y., Zeng, Y., … Du, Y. (2020). β’’ needle-shape precipitate formation in Al-Mg-Si alloy: Phase field simulation and experimental verification. Computational Materials Science, 184, 109878. doi:10.1016/j.commatsci.2020.109878Sponsors
This study was funded by the National Natural Science Foundation of China (Grant Numbers: 51531009, 51771234) and National Key R&D Program of China (2018YFB0704003). Thanks to Guangxi Natural Science Foundation under Grant No.AD19245052&AD19110008. Hong Mao also thanks the project of the CSU Special Scholarship for Study Abroad to attend the exchange program. The data that support the findings of this study are available from the authors upon reasonable request.Publisher
Elsevier BVJournal
Computational Materials ScienceAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S0927025620303694ae974a485f413a2113503eed53cd6c53
10.1016/j.commatsci.2020.109878