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<p>This study investigates the evolution of precipitate phases in Al–Si–Mg–<i>x</i>Cu alloys during various aging treatments and their influence on mechanical properties. The results show that increasing Cu content leads to significant changes in the types and amounts of precipitates: the β″ phase gradually diminishes, while precipitation of the <i>Q</i>′ and <i>θ</i>′ phases becomes more pronounced, resulting in a substantial improvement in strength. However, the formation of the <i>θ</i>′ phase is associated with a marked decrease in elongation after fracture. Alloys with Cu content ≥ 1.2 wt% exhibit a “double peak” hardness behavior during aging, which is primarily attributed to the transformation of dominant precipitates from the <i>Q</i>′ to the <i>θ</i>′ phase. Fractographic analysis reveals a transition in fracture mode from ductile to quasi-cleavage. Furthermore, the strengthening and toughening mechanisms are analyzed by integrating first-principles calculations.</p>

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The influence of Cu content on the aging precipitation behavior of Al–Si–Mg–Cu alloys

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • Pengfei Zhou,
  • Nengjun Ben,
  • Weidong Hui

摘要

This study investigates the evolution of precipitate phases in Al–Si–Mg–xCu alloys during various aging treatments and their influence on mechanical properties. The results show that increasing Cu content leads to significant changes in the types and amounts of precipitates: the β″ phase gradually diminishes, while precipitation of the Q′ and θ′ phases becomes more pronounced, resulting in a substantial improvement in strength. However, the formation of the θ′ phase is associated with a marked decrease in elongation after fracture. Alloys with Cu content ≥ 1.2 wt% exhibit a “double peak” hardness behavior during aging, which is primarily attributed to the transformation of dominant precipitates from the Q′ to the θ′ phase. Fractographic analysis reveals a transition in fracture mode from ductile to quasi-cleavage. Furthermore, the strengthening and toughening mechanisms are analyzed by integrating first-principles calculations.