Creep Mechanism Mapping of Lamellar Ti–Al Alloys With Crystal‐Plasticity Phase‐Field and Interpretable Machine Learning Framework

Ti–Al alloys are key lightweight contenders for engines, while the long‐term creep resistance is undermined by progressive lamellar coarsening. A crystal‐plasticity phase‐field is integrated with stacked ensemble machine learning to simulate and predict the creep–microstructure relationships in Ti‐45 at.% Al alloys under tensile stresses 50–350 MPa at 1373 K. Phase‐field simulations reveal that increasing stress can elevate the proportion of γ phase, accelerates spheronization and interfacial migration. The diffusion creep mechanism is dominant at low stress level, and dislocation creep mechanism is enhanced under high stress. Lamellar thinning raises the Orowan threshold shear stress and the creep resistance, while the multi‐lamellar γ phase can reduce stress concentration. The simulation captures lamellar coarsening and spheroidization under creep stress. Quantitative features are extracted from the phase‐field outputs and analyzed by using an explainable machine learning model. The contributions of elastic strain energy, interfacial energy, and lamella thickness to creep strain and creep resistance are identified. The integrated phase‐field–machine learning approach supplies the physical insight for the creep characteristics of lamellar alloy.