journal article·2026-05Open access

Microstructural evolution and property of Al–Mg–Si–Fe–Cu flat wires prepared by continuous rheological extrusion and cold deformation

Zhantao He, Changfeng Wang, Minqiang Gao, Jiuyang Pei, Renguo Guan

Abstract

There is an urgent demand for high strength and high conductivity aluminum alloy conductors in the fields of wind energy electromagnetic wires and motor wires. However, achieving a balance between a challenge due to the trade-off between them. In this work, continuous rheological extrusion (CRE) Al–Mg–Si–Fe–Cu alloy flat wires were first prepared, and then deformed by cold drawing after heat treatment. Results showed that cold drawing induced significant grain refinement and promoted a gradual transition from equiaxed grains to a pronounced fibrous structure along the drawing direction, accompanied by a marked increase in dislocation density. After T6 heat treatment, some nanoscale β′′ and Cu-containing Q′ precipitates were formed, which provided effective precipitation strengthening while limiting conductivity degradation. With increasing cross-sectional reduction, the alloy exhibited a continuous increase in strength and a typical decrease–recovery behavior in electrical conductivity. At a maximum reduction of 79.8%, an optimal combination of properties was achieved, with an ultimate tensile strength of 308 MPa, a yield strength of 295 MPa, and an electrical conductivity of 53.8% IACS. Strengthening analysis revealed that grain boundary strengthening, dislocation strengthening, and precipitation strengthening act synergistically to enhance the mechanical performance. This work demonstrates that the CRE–heat treatment–cold drawing route is an efficient strategy for producing high-performance Al–Mg–Si–Fe–Cu alloy flat wires for advanced electrical conductor applications.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Microstructure and mechanical properties · Aluminum Alloy Microstructure Properties · Metal Forming Simulation Techniques

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

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