Multiscale defect structure design and strength-ductility synergistic optimization of 6082 aluminum alloy based on machine learning and non-equilibrium processing

6082 aluminum alloys are widely applied in lightweight structural fields, but their strength levels are relatively limited, and the difficulty in synergistically enhancing strength and ductility remains a key issue restricting the expansion of their high-end applications. To address this issue, this paper proposes an integrated research strategy combining machine learning (ML)-assisted composition design with high-energy ball milling-pulse forging (HEBM-PF) non-equilibrium processing. Under the premise of satisfying national standard composition constraints, target compositions with excellent strength-ductility matching potential were screened out through an automated composition discovery framework, and further experimentally prepared using the HEBM-PF process. The results show that the ML-assisted composition design can effectively pinpoint the target composition of 6082 aluminum alloy with both high strength and good ductility potential in a multi-component space; on this basis, HEBM induced significant mechanical alloying (MA), grain refinement, and high-density defect introduction; while PF further achieved alloy densification, precipitation regulation, and non-equilibrium microstructure retention. The PF-processed alloy eventually formed a multi-scale defect non-equilibrium composite microstructure composed of an ultrafine-grained α -Al matrix, high-density dislocation tangles, stacking faults (SFs), multiple stacking faults (MSFs), nanotwins (NTs), and β -Mg₂Si and α -Al(Fe, Mn)Si nano-precipitates. Benefiting from this microstructure, the PF-processed 6082 aluminum alloy obtained a yield strength (YS) of 493 MPa, an ultimate tensile strength (UTS) of 586 MPa, and an elongation (EL) of 7.92%. Strengthening mechanism analysis indicates that dislocation strengthening, grain boundary strengthening, second-phase strengthening, and nanoscale planar defect strengthening collectively contributed to the high strength of the alloy, among which nanoscale planar defect strengthening and second-phase strengthening are particularly critical. This study provides a new pathway for the efficient design and preparation of high-performance 6082 aluminum alloys, and simultaneously provides theoretical support for the synergistic optimization of data-driven alloy design and advanced metal processing technologies.

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Journal
Applied Materials Today
Published
2026-09-29
DOI
https://doi.org/10.1016/j.apmt.2026.103436
Primary Topic
Metallurgy and Material Forming
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article
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Multiscale defect structure design and strength-ductility synergistic optimization of 6082 aluminum alloy based on machine learning and non-equilibrium processing

Zhuhui Qiao, Wenjie Zhong, Liyuan Wang, Xinlong Li et al.
Applied Materials Today
Metallurgy and Material Forming
article

Multiscale defect structure design and strength-ductility synergistic optimization of 6082 aluminum alloy based on machine learning and non-equilibrium processing

Zhuhui Qiao, Wenjie Zhong, Liyuan Wang, Xinlong Li, Gang Xu, Wengang Sheng, Huaguo Tang
article en

Abstract

6082 aluminum alloys are widely applied in lightweight structural fields, but their strength levels are relatively limited, and the difficulty in synergistically enhancing strength and ductility remains a key issue restricting the expansion of their high-end applications. To address this issue, this paper proposes an integrated research strategy combining machine learning (ML)-assisted composition design with high-energy ball milling-pulse forging (HEBM-PF) non-equilibrium processing. Under the premise of satisfying national standard composition constraints, target compositions with excellent strength-ductility matching potential were screened out through an automated composition discovery framework, and further experimentally prepared using the HEBM-PF process. The results show that the ML-assisted composition design can effectively pinpoint the target composition of 6082 aluminum alloy with both high strength and good ductility potential in a multi-component space; on this basis, HEBM induced significant mechanical alloying (MA), grain refinement, and high-density defect introduction; while PF further achieved alloy densification, precipitation regulation, and non-equilibrium microstructure retention. The PF-processed alloy eventually formed a multi-scale defect non-equilibrium composite microstructure composed of an ultrafine-grained α -Al matrix, high-density dislocation tangles, stacking faults (SFs), multiple stacking faults (MSFs), nanotwins (NTs), and β -Mg₂Si and α -Al(Fe, Mn)Si nano-precipitates. Benefiting from this microstructure, the PF-processed 6082 aluminum alloy obtained a yield strength (YS) of 493 MPa, an ultimate tensile strength (UTS) of 586 MPa, and an elongation (EL) of 7.92%. Strengthening mechanism analysis indicates that dislocation strengthening, grain boundary strengthening, second-phase strengthening, and nanoscale planar defect strengthening collectively contributed to the high strength of the alloy, among which nanoscale planar defect strengthening and second-phase strengthening are particularly critical. This study provides a new pathway for the efficient design and preparation of high-performance 6082 aluminum alloys, and simultaneously provides theoretical support for the synergistic optimization of data-driven alloy design and advanced metal processing technologies.

Applied Materials TodayVol. 53
Harbin University (CN), University of Electronic Science and Technology of China (CN), Harbin Engineering University (CN), Ludong University (CN), Chinese Academy of Sciences (CN), Lanzhou Institute of Chemical Physics (CN), State Key Laboratory of Solid Lubrication
Openalex Percentile: Top 20%
Metallurgy and Material Forming
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