Abstract

In this work, different heat treatments were performed in order to study two different bainite morphologies, granular and lath-like, obtained at different cooling rates in a low carbon microalloyed steel. For that purpose, advanced crystallographic characterization and quantitative metallography using SEM, EBSD and TEM were carried out. The evolution of the volume percentage, size, aspect ratio, retained austenite volume percentage and crystallography of the M/A constituents was studied as a function of the cooling rate and classified according to a machine learning algorithm. For the characterization of the crystallography and morphology of the bainitic ferrite matrix, two microstructures were selected as representative of granular and lath-like bainite. The results show that the main differences between granular and lath-like bainite are the size and shape of the M/A constituents, that change progressively from a mixture of large grains, coarse blocks and fine roughly equiaxed grains at low cooling rates to short and long films at high cooling rates. The crystallographic and morphological differences between both microstructures can be explained based on the different driving force and amount of bainitic ferrite formed at the different temperature ranges. These results confirm that the mechanisms by which granular bainite forms are not different from the transformation mechanisms of lath-like bainite.

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