Microstructural phase differentiation of AA7075/ZrC composite using image processing of SEM micrographs

Image processing gives a more in-depth knowledge of the properties of various materials. The method employed in this study was an automated picture processing procedure to carry out quantitative microstructural characterization of AA7075/ZrC composites. Primary AA7075 matrix and secondary ZrC reinforcement phases were objectively divided, imaged and measured through images of the backscattered electron scanning electron microscopy (BSE-SEM). In order to be able to separate the matrix and the reinforcement in the entire area of the image, the methodology was based on Python-based libraries, like NumPy and OpenCV, to further improve thresholding, morphological filtering and create accurate color mapping. The calculations of the areas of pixels along with the Delesse principle of converting the data of two-dimensional images into volumetric quantities allowed the calculation of local ZrC volume fractions. The findings have shown that the reinforcement is not distributed all over the material but it is quite different in different regions. The non-uniformity herein emphasizes the need to carry out site-specific analysis in order to obtain structure-property relations in composite systems. Compared to manual methods, automated phase mapping and measurement proved to be faster, more consistent, and less prone to operator bias.