3D Quantitative Mineral Characterization of Particles Using X-ray Computed Tomography

Abstract

A new method to measure and quantify the 3D mineralogical composition of particulate materials using X-ray computed micro-tomography (CT) is presented. The new method is part of a workflow designed to standardize the analysis of particles based on their microstructures without the need to segment the individual classes or grains. Classification follows a decision tree with criteria derived from particle histogram parameters that are specific to each microstructure, which in turn can be identified by 2D-based automated quantitative mineralogy. The quantification of mineral abundances is implemented at the particle level according to the complexity of the particle by taking into consideration the partial volume effect at interphases. The new method was tested on two samples with different particle size distributions from a carbonate rock containing various microstructures and phases. The method allowed differentiation and quantification of more mineral classes than traditional 3D image segmentation that uses only the grey-scale for mineral classification. Nevertheless, due to lower spatial resolution and lack of chemical information, not all phases identified in 2D could be distinguished. However, quantification of the mineral classes that could be distinguished was more representative than their 2D quantification, especially for coarser particle sizes and for minor phases. Therefore, the new 3D method shows great potential as a complement to 2D-based methods and as an alternative to traditional phase segmentation analysis of 3D images. Particle-based quantification of mineralogical and 3D geometrical properties of particles opens new applications in the raw materials and particle processing industries.