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. Graphical abstract Energy and RMS vacancy displacement vs simulation time for three different kMC simulations of Al matrix containing Mg (green) and Si atoms(orange), and 1 vacancy (pink). Geometries extracted from the third trajectory at four different times show solute clustering and vacancy trapping.