Prediction of reversion kinetics in medium Mn steel by linking real experimental data with diffusion simulation

Reversion kinetics during austenite reversion treatment (ART) significantly influence the microstructure and mechanical properties of medium Mn steels. Unfortunately, commercial diffusion simulation software typically utilizes ferrite phase databases, limiting the precision of reversion kinetics predictions due to the differing dislocation densities between ferrite and martensite phases. This study developed a model to predict reversion kinetics at various temperatures for Fe-6 Mn wt.% steel, incorporating a dislocation pipe diffusion mechanism and temperature-dependent changes in the diffusivity of Mn in martensite. By introducing the diffusivity enhancement parameter (DEP) associated with the high dislocation density of martensite, the model overcomes the limitations of previous DICTRA-based predictions. Predictions incorporating DEP accurately reproduce reversion kinetics at temperatures above 600 ℃, where austenite nucleation minimally influences transformation, demonstrating strong agreement with measured dilatometer data. This model reduces experimental effort, time, and cost, offering practical guidelines for optimizing the reversion process in medium Mn steel.