The influence of the Si and Mn concentrations on the kinetics of the bainite transformation in Fe-C-Si-Mn alloys

Phase Transformation Temperature Prediction in Steels via Machine Learning

The phase transformation temperature plays an important role in the design, production and heat treatment process of steels. In the present work, an improved version of the gradient-boosting method LightGBM has been utilized to study the influencing factors of the four phase transformation temperatures, namely Ac1, Ac3, the martensite transformation start (MS) temperature and the bainitic transformation start (BS) temperature. The effects of the alloying element were discussed in detail by comparing their influencing mechanisms on different phase transformation temperatures. The training accuracy was significantly improved by further introducing appropriate features related to atomic parameters. The melting temperature and coefficient of linear thermal expansion of the pure metals corresponding to the alloying elements, atomic Waber-Cromer pseudopotential radii and valence electron number were the top four among the eighteen atomic parameters used to improve the trained model performance. The training and prediction processes were analyzed using a partial dependence plot (PDP) and Shapley additive explanation (SHAP) methods to reveal the relationships between the features and phase transformation temperature.

Effect of Austempering below and above Ms on the Microstructure and Wear Performance of a Low-Carbon Bainitic Steel

The microstructure and wear performance of a low-carbon steel treated by austempering below and above martensite start temperature (Ms) were investigated. The results show that the bainite, fresh martensite (FM) and retained austenite (RA) were observed in samples austempered above Ms. Except for the three above phases, the athermal martensite (AM) was also observed in samples austempered below Ms. The bainite transformation was accelerated and finer bainite was obtained due to the AM formation in samples austempered below Ms. In addition, the strength and hardness were improved with the decrease of the isothermal temperature and time, whereas the total elongation decreased with the increasing isothermal time and the decreasing isothermal temperature. Moreover, the materials austempered below Ms exhibited better wear performance than the ones treated above Ms, which is attributed to the improved impact toughness by the finer bainite and the enhanced hardness by AM. The best wear resistance was obtained in the samples austempered at 300 °C below Ms for 200 s, due to the highest hardness and considerable impact toughness.

Effect of Austenitizing Temperature and Prior Martensite on Ultra-Fine Bainite Transformation Kinetics

An evaluation method for bainite transformation kinetics was established by theoretical derivation, dilatometric curve analysis, and microstructure observation. The isothermal transformation of ultra-fine bainite under different austenitizing temperatures and contents of prior martensite was studied using a DIL805L dilatometer. The kinetic parameters (activation energy Q*, autocatalytic factor λ, temperature rate constant κ, unit volume transformation rate, and the number density of nucleation sites Ni) of ultra-fine bainite transformation under different austenitizing temperatures and contents of prior martensite were calculated based on the displacement growth bainite dynamics model. It was found that the autocatalytic factor λ is linear with the austenite grain size d, and the number density of nucleation sites Ni is closely related to the average volume of the bainite subunit Vb. Moreover, the formation of prior martensite and its increase can increase the number of nucleation sites and the nucleation rate of the ultra-fine bainite; thus, the ultra-fine bainite transformation can be accelerated.