Xiyuan Geng, Hongcan Chen, Jingjing Wang, Yu Zhang, Qun Luo, and Qian Li, Description of martensitic transformation kinetics in Fe–C–X (X = Ni, Cr, Mn, Si) system by a modified model, Int. J. Miner. Metall. Mater.,(2024). https://doi.org/10.1007/s12613-023-2780-9
Cite this article as:
Xiyuan Geng, Hongcan Chen, Jingjing Wang, Yu Zhang, Qun Luo, and Qian Li, Description of martensitic transformation kinetics in Fe–C–X (X = Ni, Cr, Mn, Si) system by a modified model, Int. J. Miner. Metall. Mater.,(2024). https://doi.org/10.1007/s12613-023-2780-9
Research Article

Description of martensitic transformation kinetics in Fe–C–X (X = Ni, Cr, Mn, Si) system by a modified model

+ Author Affiliations
  • Corresponding authors:

    Qun Luo    E-mail: qunluo@shu.edu.cn

    Qian Li    E-mail: cquliqian@cqu.edu.cn

  • Received: 31 August 2023Revised: 1 November 2023Accepted: 6 November 2023Available online: 10 November 2023
  • Controlling the content of athermal martensite and retained austenite is important to improving the mechanical properties of high-strength steels, but a mechanism for the accurate description of martensitic transformation during the cooling process must be addressed. At present, frequently used semi-empirical kinetics models suffer from huge errors at the beginning of transformation, and most of them fail to exhibit the sigmoidal shape characteristic of transformation curves. To describe the martensitic transformation process accurately, based on the Magee model, we introduced the changes in the nucleation activation energy of martensite with temperature, which led to the varying nucleation rates of this model during martensitic transformation. According to the calculation results, the relative error of the modified model for the martensitic transformation kinetics curves of Fe–C–X (X = Ni, Cr, Mn, Si) alloys reached 9.5% compared with those measured via the thermal expansion method. The relative error was approximately reduced by two-thirds compared with that of the Magee model. The incorporation of nucleation activation energy into the kinetics model contributes to the improvement of its precision.
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