Effect of Nb and Mo on Austenite Microstructural Evolution During Hot Deformation in Boron High Strength Steels

This work has focused on the study of hot working behavior of boron high strength steels microalloyed with different combinations of Nb and/or Mo. The role of Nb and Mo during the hot deformation of low carbon steels is well known: both mainly retard austenite recrystallization, leading to pancaked austenite microstructures before phase transformation and to refined room temperature microstructures. However, the design of rolling schedules resulting in properly conditioned microstructures, requires microstructural evolution models that take into account the effect of the different alloying elements. In this specific case, the effect that high levels of molybdenum (0.5 pct) have in the recrystallization delay was evaluated. In that respect, hot torsion tests were performed in this work to investigate the microstructural evolution during hot deformation of four boron steels, with different Nb (0.025 pct) and Mo (0.5 pct) combinations. The retardation in recrystallization kinetics was modeled in all cases and measured kinetics agree with those predicted by equations previously developed for Nb-Mo microalloyed steels with lower Mo concentrations (< 0.3 pct). The strain-induced precipitation in the Nb and Nb-Mo bearing steels was also characterized. Finally, the fractional softening evolution during multipass rolling simulations was compared with MicroSim (R) model predictions, showing a good agreement with experimental results. (C) The Author(s) 2022

Automated summary

This work focuses on studying the behavior of boron high strength steels microalloyed with different combinations of Nb and/or Mo during hot working. The role of Nb and Mo in the hot deformation of low carbon steels is well-known and the design of rolling schedules requires microstructural evolution models that consider the effect of these alloying elements. Experimental tests and modeling were conducted in this work, and the results provide insights for optimizing hot working processes.