This paper demonstrates a new method to classify mineral phases in 3D images of particulate materials obtained by X-ray computed micro-tomography (CT), here named mounted single particle characterization for 3D mineralogical analysis (MSPaCMAn). The method allows minimizing the impact of imaging artefacts that make the classification of voxels inaccurate and thus hinder the use of CT to characterize natural particulate materials. MSPaCMAn consists of (1) sample preparation as particle dispersions; (2) image processing optimized towards the labelling of individual particles in the sample; (3) phase identification performed at the particle level using an interpretation of the grey-values of all voxels in a particle rather than of all voxels in the sample. Additionally, the particle’s geometry and microstructure can be used as classification criteria besides the grey-values. The result is an improved accuracy of phase classification, a higher number of detected phases, a smaller grain size that can be detected, and individual particle statistics can be measured instead of just bulk statistics. Consequently, the method broadens the applicability of 3D imaging techniques for particle analysis at low particle size to voxel size ratio, which is typically limited due to unreliable phase classification and quantification. MSPaCMAn could be the foundation of 3D semi-automated mineralogy similar to the commonly used 2D image-based semi-automated mineralogy methods.

The Mt. Rudnaya MSS-ISS (monosulfide and intermediate solid solution) fine-grained ores from a NE termination of Norilsk 1 deposit were analyzed using a combination of X-ray computed micro tomography, spectral X-ray computed micro tomography and scanning electron microscopy to achieve both, 2D and 3D data. The ores consist of ISS composed of tiny lamellar intergrowths of cubanite and chalcopyrite solid solutions, which form up to 4-mm distinct globules surrounded by an ISS-MSS matrix. Our X-ray computed micro tomography results may provide 3D textural evidence of a possible natural sulfide-sulfide liquid immiscibility between Cu-rich and Cu-poor sulfide liquids that occurred before MSS and ISS were crystallized. The platinum group minerals (PGM) distribution shows that 20.6 vol% of all PGM occur in the ISS-MSS matrix and 79.4 vol% in the ISS globules. We suggest that this distributional behavior is due to the fact that the platinum group elements (PGE) cannot be dissolved in ISS, which led to the formation of the large PGM grains, which are up to 120 μm on their longest axis. The initial enrichment of ISS in PGE was controlled by differences in the partition coefficients of platinum and palladium between Cu-poor and Cu-rich liquids.

Magnetic separation has wide-ranging applications in both mineral processing and recycling industries. Nevertheless, its conventional utilization often overlooks the interplay between mineral and particle characteristics and their impact on operational conditions, ultimately influencing the efficacy of the separation process. This work describes a methodology able to achieve the comprehensive characterization and classification of Waste Electrical and Electronic Equipment (WEEE) slag. The primary objective is to establish a meaningful connection between the distinct properties of slag phases and their influence on the separation process. Our methodology consists of several stages. Firstly, the WEEE slag is sieved into distinct size classes, followed by classification into magnetic susceptibility classes by using the Frantz Isodynamic separator. To quantify the magnetic susceptibility of each class, we used a magnetic susceptibility balance, and to identify paramagnetic and ferromagnetic fractions and phases within these magnetic susceptibility classes, we conducted vibrating-sample magnetometer measurements. Finally, to establish a meaningful link between the magnetic characterization, mineralogical, and particle-level details, Mineral Liberation Analysis was conducted for each magnetic susceptibility class. This in-depth analysis, encompassing both particle properties and magnetic susceptibility classes, provides a better understanding of the separation behavior of different phases and can help to enrich phases with a specific range of magnetic susceptibility values. This knowledge advances progress towards the development of predictive separation models that are capable of bridging the gap between theoretical understanding and practical application in the field of magnetic separation.

This study was undertaken to assess the cleaning potential of Dulmial-Punjab coal by froth flotation.Release analysis was performed to determine the optimum flotation response of the coal. Number of batchflotation tests were performed to investigate the effects of various parameters such as particle size, impellerspeed, collector dosage, frother dosage and conditioning time on clean coal yield and ash content. It wasfound that maximum yield of 51.25% with 39.5% ash content was achieved at impeller speed, collectordosage, frother dosage and conditioning time of 1600 RPM, 1200 g/t, 200 g/t and 10 min, respectively.