Computational Analysis on the Composition-Dependent Solute Clustering Behavior During Early-Stage Natural Aging in Al–Si–Mg–(Cu) Alloys

This paper presents a comprehensive computational analysis of solute clusters formed during the natural aging (NA) of Al–Si–Mg–(Cu) alloys. The behavior of solute–solute and solute–vacancy pairs are predicted using density functional theory calculations, based on the solute binding energy and obtained the two-body interaction parameters for kinetic Monte Carlo (KMC) simulations. The KMC results reveal that clusters in Al–Si–Mg alloys grow to ~ 30 atoms within 1440 min of NA, with their Mg and Si compositions mirroring those of the alloy. In Cu-added alloys, the clusters grow more rapidly, and their composition distributions lean toward Mg-rich clusters. We evaluated cluster stability by calculating the cluster energy for all configurations with up to 19 atoms. Stable clusters consistently exhibited β-Mg₂Si stoichiometry, and their stability increased with cluster growth, indicating an underlying solute cluster growth mechanism. Vacancy trapping was more pronounced in the Si-rich clusters, leading to increased stability, which impedes the formation of precipitates during artificial aging. Quantitative analysis of the local strain distribution around the solute dimers enabled the calculation of its strengthening contribution, revealing that clusters with Mg/(Mg + Si) = 0.5 exhibited the most significant strengthening effect.