The influence of cluster composition and the addition of vacancies on the decomposition behavior of clusters during artificial aging in Al–Si–Mg alloys were analyzed according to the kinetic Montel Carlo model. Clusters with a balanced composition (Mg/(Mg + Si) = 0.5) were the most difficult to decompose. In addition, the cluster decomposition was slower when more vacancies were added to the cluster. Among Si, Mg, and vacancies, vacancies most significantly affect decomposition. The clusters with Mg/(Mg + Si) ≤ 0.4 strongly trap vacancies, which can be classified as hardly decomposable vacancy-rich clusters. The clustering behavior during natural aging and the effect of pre-aging were analyzed using the Kinetic Monte Carlo model. Pre-aging slows down cluster formation due to the lowered vacancy concentration. In addition, the overall composition of the clusters changes to easily decomposable clusters after pre-aging. Thus, not only is the number of clusters reduced but also the clusters are more easily decomposable when pre-aging is performed.
The effects of the shapes (needle and round) and volume fractions (low and high) of microscale particles in Al-Si-Mg-Cu-based alloys on recrystallization behavior, texture evolution, mechanical properties, and formability are investigated. The recrystallized grain size decreases as the size and volume fraction of the particles decrease and increase, respectively, regardless of the particle shape. The investigated alloys with a relatively low volume fraction of 0.7 to 2.4 vol.% exhibit higher efficiency particle-stimulated nucleation (PSN) than alloys with a high volume fraction of 6.0 to 21.0 vol.%. This is because the interaction between the particles and dislocations cannot be greatly promoted when the volume fraction of the particles is large enough to form agglomerates. The sheets with round-shaped particles exhibit higher yield strength (YS) and elongation (EL) than sheets with needle-shaped particles. The improvement in YS is due to the combined effects of grain refinement and particle strengthening, and the EL is improved by reducing the probability of cracking at the tips of round-shaped particles. The sheets with round-shaped particles exhibit relatively higher average plastic strain ratio (r¯) and planar anisotropy (∆r) than the sheets with needle-shaped particles, owing to the development of Goss {110}<001> or rotated-Goss {110}<110> orientations.
The crack propagation behavior of Al containing Mg–Si clusters is investigated using molecular dynamics (MD) simulations to demonstrate the relationship between the natural aging time in Al–Si–Mg alloys and ductility. Experimental results show that the elongation at failure decreases with natural aging. There are few studies on the relationship between natural aging and ductility because of the difficult observation of Mg–Si clusters. To solve the difficulty, cracked Al containing Mg–Si clusters of varying sizes are assumed for the MD simulations. A larger Mg–Si cluster in Al results in earlier crack opening and dislocation emission. Moreover, as the Mg–Si cluster size increases, the stress near the crack tip becomes more concentrated. This causes rapid crack propagation, a similar effect to that of crack tip sharpening. As a result of long-term natural aging, the cracks expand rapidly. The influence of geometry is also investigated. Crack lengthening and thickness reduction negatively impact the fracture toughness, with the former having a larger impact than the latter. Although there are several discrepancies in the practical deformation conditions, the simulation results can help to more thoroughly understand natural aging in Al–Si–Mg alloys.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.