CALPHAD-Informed Phase-Field Modeling of Microstructure Evolution in Chemically Complex Mg Alloys and CoCrNi-Based Medium-Entropy Alloys
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Chemically complex alloys, including Mg–Zn–RE lightweight alloys and CoCrNi-based medium-entropy alloys, exhibit strong solute partitioning, multi-phase competition, and non-equilibrium microstructural evolution during solidification and subsequent heat treatment. In this work, we employ a CALPHAD-informed multiphase-field framework implemented in MICRESS, using thermodynamically and kinetically consistent inputs from Thermo-Calc thermodynamic and mobility databases, to investigate microstructure selection and segregation behavior across these two alloy families within a unified modeling strategy. For Mg–Zn–RE alloys, the multiphase-field approach is particularly advantageous because realistic microstructures are governed by the concurrent formation and competitive growth of multiple second phases (e.g., W-type intermetallics and other Zn/RE-rich compounds), coupled with substantial solute redistribution in the Mg-rich matrix; the simulations therefore target phase competition, segregation pathways, and morphology evolution that single-phase descriptions cannot capture. This Mg-alloy modeling route builds on established phase-field practices for Mg alloys and is formulated to support process-relevant interpretation of microstructure sensitivity during solidification and post-solidification thermal exposure. For CoCrNi-based medium-entropy alloys with Si additions, the same framework is used to simulate dendritic solidification microsegregation and subsequent homogenization behavior, allowing for the quantitative tracking of segregation decay, composition-dependent persistence, and processing constraints, such as incipient melting. By emphasizing MICRESS-based phase-field modeling tightly coupled with CALPHAD thermodynamics and mobilities, this study demonstrates the transferability of a single mesoscale framework across rare-earth Mg alloys and compositionally complex CoCrNi-based systems, and provides mechanistic, computation-ready insights for linking composition/process windows to microstructure control in lightweight structural and functional materials.
