Combining Automated Mineralogy with X-ray Computed Tomography for Internal Characterization of Ore Samples at the Microscopic Scale

Abstract

Advanced chemical and mineralogical techniques are necessary to further our understanding of ore deposits and their genesis. Using X-ray micro-computed tomography (µCT) and an automated mineralogy (AM) system based on scanning electron microscopy with an energy-dispersive X-ray spectrometer (SEM–EDX), we investigated the internal mineralogy of Sn–Nb–Ta pegmatites. This paper presents a comprehensive methodology to quantify and visualize the mineral relationships of ore samples in three-dimensional space at the microscopic scale. A list of all possible minerals present, a so-called mineral library, was deduced with a SEM-based AM system and served as the ground truth for the interpretation of µCT data. A reconstructed attenuation coefficient (µrec) was calculated for mineral phases that have been identified and provided a most correct guidance to differentiate between minerals for a given experimental µCT setup. Despite some limitation in sample size and mineral identification, these complementary techniques enabled the differentiation of a Fe–Li mica from biotite based on the chemical attribution of lithium to µrec. Using statistical descriptors, we quantified the general orientation of individual mineral phases and their spatial correlation to comply with the needs of processing large datasets at a low computational expense. Applying this comprehensive methodology to a case study demonstrates the possibilities of combining a SEM-based AM system with µCT analysis to investigate ore samples at the microscopic scale.