Correlative X-ray micro-Computed Tomography (X-µCT) scans of Engineered Artificial Minerals (EnAM)

Characterizing complex particulate materials like slag using X-ray microcomputed tomography (μCT) is challenging due to minimal grey-scale contrast from similar attenuation properties among phases and intricate microstructures. To address this problem, we developed a standardized multi-scale correlative methodology that combines μCT at different resolutions with scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS) and X-ray fluorescence (XRF). By scanning large samples for statistical significance and sub-samples at higher resolutions, we capture detailed microstructures. Aligning SEM-EDS data with μCT scans using inherent markers enables accurate phase segmentation. Mineral mapping from SEM-EDS can help to train segmentation models for μCT data, overcoming μCT limitations and allowing precise 3D mineralogical characterization. This approach provides a robust framework for analyzing complex slag particles. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101005611 https://excite-network.eu.