journal article·2026-05Open access

Interfacial microstructure and mechanical properties of diffusion-bonded Mg-4Y-3RE magnesium alloy

Dexi Xu, Huiping Wu, Dayong An, Qi Hu, Xifeng Li, Jun Chen

Abstract

• Shear strength of 179.9 ± 3.9 MPa and bonding ratio of 94.14 % is achieved. • Superior joint results from recrystallization, precipitates and elemental diffusion. • Strength further increases to highest value of 229.5 ± 5.2 MPa by T6 treatment. The Mg-4Y-3RE (WE43) magnesium alloy possesses high specific strength, excellent shock absorption, strong electromagnetic shielding, and recyclability. However, the oxidation and defects often happen during conventional welding. Solid-state diffusion bonding in a near-vacuum environment enables high-reliability joints by minimizing these issues. It is difficult to obtain high bonding joint strength due to the limitation of various factors. This work systematically investigates the effects of temperature, time, pressure, and surface roughness on the diffusion-bonded joint quality of WE43 magnesium alloy through a phased optimization strategy. The optimal parameter combination is optimized. The results demonstrate that the joint interface achieves a shear strength of 179.9 ± 3.9 MPa and a bonding ratio of 94.14 % when the minimal plastic deformation is ensured. Microstructural characterization reveals that recrystallization, precipitates evolution and elemental diffusion effects collectively promote metallurgical bonding at the interface. Subsequent solution treatment at 525 °C for 8 h and aging at 250 °C for 16 h, the shear strength significantly increases to 229.5 ± 5.2 MPa, which represents the highest value in comparable reported studies. This research provides theoretical foundations and technical references for solid-state bonding processes of high-strength magnesium alloys.
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Research context

OpenAlex topics: Magnesium Alloys: Properties and Applications · Advanced Welding Techniques Analysis · Aluminum Alloys Composites Properties

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

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