Estimation of volume-weighted average grain size in Fe-based nanocrystalline soft magnetic materials by autocorrelation function

The coercivity of Fe-based nanocrystalline soft magnetic materials depends critically on the grain size of bcc-Fe grains. Accurately estimating the volume-weighted mean grain size is extremely important to develop new Fe based nanocrystalline soft magnetic materials with low coercivity. This article shows that autocorrelation analysis of dark-field transmission electron microscope (TEM) images provides a very good estimation of bcc-Fe grain size in nanocrystalline soft magnetic materials. This method can be used to efficiently estimate the volume weighted average grain size from multiple TEM images with much less inherent bias than manual measurement techniques. The estimated grain sizes show good consistency to the grain sizes estimated by X-ray diffraction (XRD) and manual measurement. In contrast to XRD, this method can also reveal the differences in grain size from different micron-sized regions of a sample.