Enhancement of strength and toughness of multicomponent Al-alloy via nano twining and nano precipitate through heat treatment

• Different processing parameters have been optimized using Marc Mentat simulation software. • The optimal heat treatment process was solution treatment at 530℃ for 3 hours followed by aging at 175℃ for 8 hours. • The twin formation during the heat treatment process enables excellent strength and toughness trade-off • A dislocation-based model is proposed to validate the mechanical properties of the alloy. This study proposes an integrated optimization strategy to enhance the synergistic improvement of strength and toughness in Al 6082 alloys for high-speed rail applications - a critical requirement given the growing demands on rail material performance. Through a systematic combination of experimental characterization and numerical simulation, we establish an optimized thermomechanical processing protocol for this alloy system. The Marc Mentat finite element analysis platform simulated and refined three crucial processing parameters: solution treatment temperature/duration, quenching conditions, and artificial aging parameters. Subsequent experimental validation revealed that solution treatment at 530℃ for 3 hours followed by aging at 175℃ for 8 hours produced a dual-phase microstructure containing both semi-coherent and non-coherent precipitates. High-resolution transmission electron microscopy analysis demonstrated that these precipitates, particularly those at nanotwin boundaries, create effective barriers for dislocation motion while maintaining reasonable ductility. The optimized material exhibited superior mechanical properties with a tensile strength of 454 MPa, yield strength of 397 MPa, and elongation of 11.8%, representing a 22% improvement in strength-ductility balance compared to conventional processing routes. LIMO simulation results also showed excellent agreement with experimental tensile data, confirming the reliability of our multi-scale modeling approach. This work provides two key advancements: 1) A quantitative correlation between precipitate morphology (size/shape distribution) and mechanical performance metrics; 2) A validated simulation-experiment framework that enables predictive optimization of aluminum alloy processing parameters. These findings offer new perspectives for developing high-performance aluminum alloys through controlled microstructural engineering.