journal article·2026-01-02

Surface tension determination of liquid ternary and sub-binary alloys in Mg–Al–RE (RE = La, Ce, Nd, Gd, Y) system

Jun Luan, Yu Li, Xindi Wang, Zhigang Yu, Lei Shi, Wenxin Hu, Yunying Fan, Kuochih Chou

Philosophical Magazine· Volume 106· Issue 1
Publisher page

Abstract

The surface tension of rare earth-magnesium alloys significantly influences its castability and mould-filling behaviour, whereas experimental measurements of such thermophysical properties remain challenging. In this study, the surface tension of liquid ternary and Sub-binary alloys in Mg–Al–RE (La, Ce, Nd, Gd, Y) system was determined by Butler equation combined with the thermodynamic parameters calculated by General Solution Model (GSM). The influence of temperature and composition on surface tension was studied systematically. The surface tension of magnesium alloy melts exhibits a strong negative temperature dependence, decreasing significantly with increasing temperature. For the Mg-RE binary systems, the surface tension increased with the addition of RE elements, while for the Al-RE binary systems, the surface tension exhibited maximum values in the composition range of mole Fraction of RE = 0.6–0.8. For various Mg-xAl (mole fraction of Al = 0.02, 0.06, 0.1)-RE ternary systems, the surface tension increased linearly with addition of RE content (mole fraction of RE = 0–0.5). The ternary surface tension contours in the whole composition range were also predicted by the present model, which can guide the design of novel Mg–Al–RE casting alloys.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Magnesium Alloys: Properties and Applications · Thermodynamic and Structural Properties of Metals and Alloys · Metallurgical and Alloy Processes

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Shanghai University

Baotou Research Institute of Rare Earths

Kunming University of Science and Technology

Funding

National Natural Science Foundation of China · Aeronautical Science Foundation of China · National Key Research and Development Program of China · Kunming University of Science and Technology · Ningbo Yongjiang Talent-Introduction Programme · Zhejiang Phenomenological Materials Technology Co., Ltd., China

References (38)

Show source-provided references
1. 10.1007/s10853-015-8883-610.1007/s10853-015-8883-6 ↗
2. 10.1007/s10853-024-09909-610.1007/s10853-024-09909-6 ↗
3. 10.1016/j.cis.2010.06.00910.1016/j.cis.2010.06.009 ↗
4. 10.1080/14786435.2024.241531110.1080/14786435.2024.2415311 ↗
5. 10.1080/14786435.2024.242566710.1080/14786435.2024.2425667 ↗
6. 10.1080/14786435.2020.177590710.1080/14786435.2020.1775907 ↗
7. 10.1016/j.physb.2024.41616010.1016/j.physb.2024.416160 ↗
8. 10.1080/14786435.2019.157693710.1080/14786435.2019.1576937 ↗
9. 10.1080/14786435.2024.244351110.1080/14786435.2024.2443511 ↗
10. 10.1080/14786435.2018.144812410.1080/14786435.2018.1448124 ↗
11. 10.1080/14786435.2016.121736110.1080/14786435.2016.1217361 ↗
12. S.P. Sun, D.Q. Yi, and B. Zang, Calculation of surface tension of Al-Mg-Er ternary alloy based on Butler's equation. Chin. J. Nonferr. Met. 20 (2010), pp. 930–936.
13. 10.1080/14786435.2019.170409010.1080/14786435.2019.1704090 ↗
14. S. Bofeng, Z. Yumei, and F. Daqing, Estimating the performance of a material in its service space via Bayesian active learning: A case study of the damping capacity of Mg alloys. J. Mater. Inf. 2(8) (2022), pp. 1–13.
15. J. Chen, Y. Zhang, and J. Luan, Prediction of thermal conductivity in multi-component magnesium alloys based on machine learning and multiscale computation. J. Mater. Inf. 5(22) (2025), pp. 1–18.
16. 10.1098/rspa.1932.004010.1098/rspa.1932.0040 ↗
17. 10.1016/j.jnoncrysol.2022.12144410.1016/j.jnoncrysol.2022.121444 ↗
18. 10.1016/j.apsusc.2012.10.09810.1016/j.apsusc.2012.10.098 ↗
19. 10.1016/j.matdes.2020.10877810.1016/j.matdes.2020.108778 ↗
20. 10.1016/0364-5916(95)00029-E10.1016/0364-5916(95)00029-E ↗
21. 10.1016/j.surfin.2025.10632010.1016/j.surfin.2025.106320 ↗
22. 10.1007/s12613-022-2411-x10.1007/s12613-022-2411-x ↗
23. 10.1080/14786435.2025.244967210.1080/14786435.2025.2449672 ↗
24. 10.1016/j.jmst.2023.11.00210.1016/j.jmst.2023.11.002 ↗
25. 10.1021/ie50458a03510.1021/ie50458a035 ↗
26. Z.F. Yuan, J.J. Ke, and J. Li, Surface tension of metals and alloys, Science Press, 2006. (in Chinese)
27. S.S. Liu, B. Wang, and A.L. Zhou, Estimation of surface tension for Al-Mg-Li ternary alloys. Chin. J. Process Eng. 20 (2020), pp. 59–66.
28. 10.1016/j.jallcom.2010.03.06210.1016/j.jallcom.2010.03.062 ↗
29. 10.3139/146.11038010.3139/146.110380 ↗
30. 10.1016/j.jallcom.2010.07.05610.1016/j.jallcom.2010.07.056 ↗
31. 10.1007/s10853-011-5905-x10.1007/s10853-011-5905-x ↗
32. 10.1361/154770306X10978210.1361/154770306X109782 ↗
33. 10.1016/j.actamat.2005.10.01310.1016/j.actamat.2005.10.013 ↗
34. 10.1016/j.calphad.2003.07.00110.1016/j.calphad.2003.07.001 ↗
35. 10.1016/S0966-9795(03)00151-110.1016/S0966-9795(03)00151-1 ↗
36. 10.1007/PL0002024710.1007/PL00020247 ↗
37. 10.1007/BF0044598010.1007/BF00445980 ↗
38. 10.1016/j.calphad.2015.04.00810.1016/j.calphad.2015.04.008 ↗