journal article·2024-05Open access

Effect of cluster chemistry on the strengthening of Al alloys

Yixin Wang, Xinren Chen, Huan Zhao, Wenwen Sun, Qi Zhang, Baptiste Gault, Christopher Hutchinson

Acta Materialia· Volume 269

Abstract

When a supersaturated Al solid solution is held at room temperature, natural ageing occurs through the formation of clusters/zones providing a strengthening of the material. Recently, it was shown that this process can be greatly amplified by applying a cyclic plastic strain to a supersatured Al alloy. The cyclic strengthening also leads to a microstructure dominated by clusters/zones but the strengths are much higher than those obtained by natural aging, and can even exceed the peak aged strength. This work uses a combination of atom probe tomography and small angle x-ray scattering to provide a quantitative comparison of the cluster states in commercial Al alloys AA2024 and AA7075, after both natural aging and cyclic strengthening. We show that the chemistry of the clusters formed by these processes is different, and the clusters formed by cyclic strengthening tend to have chemistries closer to the composition of the relevant local equilibrium precipitate. The average force required to shear an individual cluster/zone is back-calculated from the strengthening observed experimentally and a strong correlation is found between the shearing force and the solute content of the cluster (i.e. 1-XAl, where XAl is the Al content of the cluster). This correlation applies not only for AA2024 and AA7075, but also AA6111 and AA7050 data taken from the literature, as well as some precipitates formed at elevated temperatures. This work shows that the first order effect controlling cluster strengthening is simply the cluster chemistry and its proportional effect on the force required to shear a cluster.
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Research context

OpenAlex topics: Aluminum Alloy Microstructure Properties · Aluminum Alloys Composites Properties · Microstructure and mechanical properties

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

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