Natural Aging and Vacancy Trapping in Al-6xxx

Abstract

Undesirable natural aging (NA) in Al-6xxx delays subsequent artificial aging (AA) but the size, composition, and evolution of clustering are challenging to measure. Here, atomistic details of early-stage clustering in Al-1\%Mg-0.6\%Si during NA are studied computationally using a chemically-accurate neural-network potential. Feasible growth paths for the preferred $\beta''$ precipitates identify: dominant clusters differing from $\beta''$ motifs; spontaneous vacancy-interstitial formation creating 14-18 solute atom $\beta''$-like motifs; and lower-energy clusters requiring chemical re-arrangement to form $\beta''$ nuclei. Quasi-on-lattice kinetic Monte Carlo simulations reveal that 8-14 solute atom clusters form within 1000 s but that growth slows considerably due to vacancy trapping inside clusters, with trapping energies of 0.3-0.5 eV. These findings rationalize why cluster growth and alloy hardness saturate during NA, confirm the concept of ''vacancy prisons", and suggest why clusters must be dissolved during AA before formation of $\beta''$. This atomistic understanding of NA may enable design of strategies to mitigate negative effects of NA