Machine learning surrogates for CALPHAD inputs in mean-field precipitation modelling of IN738LC

This study presents a novel application of a machine learning-based surrogate modelling approach to replace CALPHAD-based inputs in the mean-field simulation of precipitation in the nickel-based superalloy IN738LC. A multi-component mean-field precipitation model is employed to describe the nucleation, growth and coarsening of precipitates. This model requires composition and temperature-dependent inputs, including chemical driving force and grouped mobility, which are calculated using CALPHAD t