Prediction of grain boundary chemistry in multicomponent alloys

Abstract

Hillert’s grain-boundary-phase (GBP) model is employed for predicting grain boundary (GB) chemistry in multicomponent alloys. The GB is approximated as a thin layer of a homogeneous phase with a constant thickness and its own Gibbs energy. The GB composition is computed to minimize the Gibbs energy of the mixture of a grain phase and the GBP; the Gibbs energy of liquid phase is assigned to that of the GBP. The calculation of phase diagram (CALPHAD) databases are employed to calculate the Gibbs energy of a phase of interest as a function of composition and temperature. To verify the calculation results’ validity, the predicted GB chemistry was compared with experimental data from previous research for nickel-based superalloys, an austenitic stainless steel, and a high-entropy alloy. It is demonstrated that the method combining Hillert’s GBP model and CALPHAD databases is effective for predicting the equilibrium solute segregation to stationary random high-angle GBs in multicomponent alloys, enabling the advanced compositional design of materials for GB segregation engineering.

Keywords

• grain boundary segregation
• grain-boundary-phase model
• calphad databases
• random high-angle grain boundaries
• multicomponent alloys