Dynamically recrystallized grains identified via the application of Gaussian mixture model to EBSD data

Abstract

Crystals formed during ductile deformation known as the recrystallized grains have been revealed to provide syn-deformational stress and strain information. Despite its importance, current methods of distinguishing recrystallized grains are subjective and lack consideration to the evolving microstructures. Using data obtained from electron backscattered diffraction mapping, we provide an unsupervised method to estimate the recrystallized fraction and the recrystallized grain size. The Gaussian mixture model was utilized to upon the grain orientation spread that measures intragranular lattice distortion to separate the grains into clusters. The counterpart of the recrystallized grain, the relict grains which are grains present prior to deformation are identified as grains distributed under the cluster with the largest mean grain orientation spread. Three zones could be separated from the Gaussian mixture model results representing the recrystallized zone, mixture zone and relict zone. Grains located within the mixture zone have an innate probability to be classified as either relict or recrystallized grains. The application of the Monte Carlo approximation enables the evaluation of error for the recrystallized fraction and grain size. Comparison to previously available methods shows that the current method avoids ambiguity in the selection of the cut-off threshold when identifying the recrystallized grains.