Subdivision analysis is used to understand the fine composition of a material. It can identify different regions with specific composition, structural characteristics or properties. This helps to assess the suitability of the material for a particular function and its possible limitations. It can also be used for quality control in material manufacturing, as well as to identify weak points when analyzing failed materials.

Segmented analysis is important for synchrotron radiation X-ray computed tomography (SR-CT), which is similar to traditional medical CT scans but uses strongly focused X-ray produced by electrons circulating in a storage ring at close to the speed of light.

The team has shown that machine learning is able to perform segmentation analysis on refraction contrast CT, which is particularly useful for looking at three-dimensional structures of samples with small density differences in the relevant regions.