An image processing pipeline for in-situ dynamic X-ray imaging of directional solidification of metal alloys in thin cells

The interplay between solidification and convection, which are usually strongly coupled, occurs via many different mechanisms resulting in very complex dynamics. Melt convection changes the solutal field near the solidification front leading to different microstructures or formation of freckle defects. Quantitative of dendritic structure evolution and melt flow during in situ solidification experiments is rather challenging and requires new/improved approaches to image processing. We present an image processing algorithm designed for quantitative analysis of meso-scale solidification of metal alloys in thin cells via X-ray imaging. Our methodology enables one to identify the bulk liquid volume, liquid channels and cavities, and separate them from the solidified structures. It also enables morphological analysis within the solid domain, including automatic decomposition into dominant grains by orientation and connectivity. Furthermore, convective plumes within the bulk liquid can also be studied. The applied image filters enable the developed code (will be made open-source) to reliably operate even for single images with low signal- and contrast-to-noise ratio at low image resolution. This is demonstrated by applying the code to several in situ dynamic X-ray imaging experiments involving a solidifying gallium-indium alloy in a thin cell. We show that primary spacings, grain (and global) dendrite orientation statistics, convective plume parametrization, etc. can be obtained. The limitations of the presented approach are also explained.