J. Inoue Lab.
J. Inoue Lab.

Identification of phase transformation kinetics using data-driven approach

Unsupervised machine learning applied for automatic identification of steel microstructures

Enhancement of strength of structural materials meets the requirements in many applications, and especially contributes to the improvement of the resource and energy problem from the body-in-white weight reduction of automobiles. To enhance deformability of structural materials without losing strength, our lab aim to develop a new structural materials with enhanced performance by characterizing defects, deformation, and fracture in structural metals and alloys with a help of data-driven material science.

In-situ observation of bainitic/ferritic phase transformation

Since the mechanical properties of alloys are highly dependent on the morphology and fraction of constituent phases, it is important to clarify the mechanism of their formations. The example on the right shows the application of the newly developed DHM to clearly capture the difference in the microstructural formation between ferrite plate and bainitic ferrite at nanoscale.