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Phase separation is a relevant mode of transformation for microstructure development in multicomponent alloys. Its occurrence can drastically alter the composition landscape and lead to patterns, either beneficial or undesired to the alloy design. This phenomenon is reported commonly in the BCC phase region of AlCoCrFeNi high-entropy alloys and their cost-effective Co-free alternatives based on AlCrFeNi due to chemical ordering. To better understand this transformation, we employ a phase-field model with materials parameters obtained from the CALPHAD methodology. Microstructure simulations of phase separation are conducted for the BCC-B2 phase on the    $$\mathrm {Al_{n}CrFe_{2}Ni_{2}}$$  Al n CrFe 2 Ni 2 alloy (   $$\mathrm {n}$$  n is the stoichiometric coefficient). The free energy density is obtained from a CALPHAD sublattice model, in which the disordered BCC and ordered B2 phases are formulated as a single Gibbs free energy expression. The relation between the site fraction variables in the CALPHAD sublattice model and the mole fractions in the phase-field equations is provided via neural networks. The acquisition of training data on the equilibrium value of the site fractions is presented along with the training and validation procedure. The trained neural networks are combined with a finite-element framework and Cahn–Hilliard model to simulate the BCC-B2 phase separation at different compositions. Graphical Abstract

Phase-field approach to simulate BCC-B2 phase separation in the AlnCrFe2Ni2 medium-entropy alloy