Softening Behavior and Hardness Prediction of H13 Hot-Work Die Steel during Isothermal Tempering

In this study, the microstructural evolution of H13 hot-work die steel during isothermal tempering at 500 approximate to 650 degrees C is evaluated, and kinetic equations and a neural network are constructed to describe the softening behavior. The results show that the softening behavior appears as a loss of hardness with increasing isothermal tempering temperature and time. The softening mechanism is ascribed to the decomposition of martensitic laths, annihilation and rearrangement of dislocations, formation of sub-grains, and precipitation and coarsening of secondary carbides. The evolution of secondary carbides includes the coarsening of V-rich MC nanoprecipitates, and the precipitation and coarsening of secondary phases (Cr-rich M23C6 and Mo-rich M6C carbides) during long-term isothermal tempering. Regarding the applicability of the model in precipitation evolution and hardness prediction, the Johnson-Mehl-Avrami model is considered to be more suitable than the Hollomon-Jaffe, Lifshitz-Slyozov-Wagner, and back-propagation neural network models. In this work, the mechanism of microstructural evolution during long-term isothermal tempering is elucidated, and the Hollomon-Jaffe, Lifshitz-Slyozov-Wagner, Johnson-Mehl-Avrami, and back-propagation neural network models are innovatively constructed and evaluated to describe the softening behavior of H13 steel.image (c) 2023 WILEY-VCH GmbH

Automated summary

This study evaluates the microstructural evolution of H13 hot-work die steel during isothermal tempering and constructs kinetic equations and a neural network to describe the softening behavior. The results show that softening occurs with increasing tempering temperature and time, attributed to the decomposition of martensitic laths, dislocation annihilation and rearrangement, sub-grain formation, and precipitation and coarsening of secondary carbides. The study also compares different models and finds the Johnson-Mehl-Avrami model to be the most suitable for precipitation evolution and hardness prediction.