Fabrication of high-performance quasicrystal-reinforced aluminum composites via holding-ultrasonic assisted controlled diffusion solidification
Source abstract
Abstract
Traditional methods for fabricating quasicrystal-reinforced aluminum matrix composites (QC-AMCs) often involve complex processes and face challenges such as low quasicrystal content, inhomogeneous distribution, and coarse particles, which limit their strengthening potential. In this study, a novel approach combining holding-ultrasonic melt treatment with controlled diffusion solidification (CDS) is proposed to address these issues. The process begins with holding and ultrasonic treatment of an Al-Cu-Mn precursor alloy to promote quasicrystal nucleation. The resulting semi-solid melt, enriched with quasicrystals, is then mixed with liquid A356 alloy at different ratios (1:6, 1:8, 1:10) using CDS to produce QC-AMCs. The results show that the combined melt treatments significantly increase the volume fraction of the quasicrystal I-phase (Al 65 Cu 20 Mn 15 ) to 36%, with a uniform dispersion of refined near-spherical and petal-like particles. The CDS process induces strong forced convection and undercooling, which refine the α-Al grains and eutectic Si while retaining the stable I-phase. Interfacial enrichment and interdiffusion of solute atoms (Cu, Si, Fe) facilitate the formation of a multi-phase structure consisting of quaternary I-phase, eutectic Si, and eutectic Al 2 Cu. With decreasing mixing ratio, the tensile strength of the composites first increases and then decreases, while elongation consistently improves. At the optimal mixing ratio of 1:8, the composite exhibits a tensile strength of 238.3 MPa and an elongation of 6.5%, representing improvements of 44.2% and 27.9%, respectively, over the base A356 alloy.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Quasicrystal Structures and Properties · Cellular and Composite Structures · Microstructure and mechanical properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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