Phase field dislocation dynamics prediction of stacking fault widths in Cu-Al Alloys using generalised stacking fault energy from DFT and interatomic potentials

Overview & Synopsis

The equilibrium width of intrinsic stacking faults is an important material parameter affecting key deformation phenomena. Here, we perform a comparative assessment of $γ$-surfaces generated using MD -- with a classical embedded-atom potential (ZW) and a machine-learned Gaussian Approximation Potential (GAP) -- and density functional theory (DFT), for Cu-Al alloys of varying Al content, and incorporate them as an energy term in PFDD simulations to obtain the equilibrium SFW. All three methods reproduce the lattice parameter and elastic moduli of Cu and Cu-Al alloys in reasonable agreement with each other and with experimental measurements from literature, but the MD-derived $γ$-surfaces, for both ZW and GAP, deviate substantially from DFT at the seven characteristic points, with the largest discrepancies at $T$ and $T_1$. When incorporated into PFDD, the DFT-derived $γ$-surfaces successfully predict an equilibrium SFW that increases with Al content and agrees well with standalone MD measurements and experimental values for pure Cu, whereas the MD-derived $γ$-surfaces do not yield an accurate SFW within PFDD, as the altered generalized stacking fault energy landscape causes the dissociating partials to become pinned soon after separation. These results show that DFT-derived $γ$-surfaces remain the more reliable route to alloy SFW prediction, and interatomic potentials must capture the shear path accurately to enable robust, efficient MD-PFDD modelling of stacking faults in alloys.