Browsing by Author "Siddique, Asim"

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  • ItemOpen Access
    Correlative X-ray micro-Computed Tomography (X-µCT) scans of Engineered Artificial Minerals (EnAM)
    (Technische Universität Bergakademie Freiberg, 2024-11-07) Siddique, Asim; Schröer, Laurenz
    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.
  • ItemOpen Access
    Magnetic suscptibility classes of WEEE slag and Norra Kärr Ore
    (Technische Universität Bergakademie Freiberg, 2026-02-17) Siddique, Asim; Leißner, Thomas
    This dataset contains particle-scale mineralogical and magnetic characterization data of particulate materials relevant to magnetic separation in mineral processing. It was developed to enable quantitative assessment of magnetic susceptibility variability at both class and particle scales and to support geometallurgical analysis of separation behavior. The dataset integrates experimental magnetic classification, bulk magnetic susceptibility measurements, and SEM-based automated mineralogical analysis. The data were generated from two contrasting material systems: a natural ore (Norra Kärr) and a secondary resource derived from Waste of Electrical and Electronic Equipment (WEEE) slag. For the natural ore, two particle size fractions were investigated (500–1000 µm and 125–250 µm), while for the WEEE slag a finer particle size fraction (63–100 µm) was analyzed. This combination of materials and size fractions allows evaluation of magnetic heterogeneity across different mineralogical complexities and processing-relevant conditions. Components of the Dataset Magnetic Susceptibility Classification Data: • Particles were separated into discrete magnetic susceptibility classes using a Frantz Isodynamic Separator by systematically varying the applied magnetic field strength under controlled chute conditions. • Each susceptibility class represents a population of particles with comparable magnetic response. Bulk Magnetic Susceptibility Measurements: • For each magnetic susceptibility class, bulk magnetic susceptibility was measured using a magnetic susceptibility balance. • Multiple sub-samples and repeated measurements were performed per class to improve representativity and reduce measurement uncertainty. • The resulting values provide class-average magnetic susceptibility used as reference data. SEM-Based Automated Mineralogy (MLA) Data: • Quantitative mineralogical characterization of each magnetic susceptibility class was performed using Mineral Liberation Analysis (MLA). • The data include modal mineral phase proportions for each susceptibility class. • Particle-by-particle mineralogical compositions were extracted, providing phase fractions and mineral associations at the individual particle scale. Metadata and Experimental Context: • The dataset includes metadata describing particle size fractions, magnetic separation conditions, measurement procedures, and material context. • This information enables reproducibility and supports reuse of the data in comparative or methodological studies. The dataset enables analysis of relationships between mineralogical composition and magnetic response, estimation of particle-scale magnetic susceptibility, and assessment of magnetic heterogeneity in mineral feeds. It is suitable for applications in magnetic separation studies, geometallurgical analysis, particle-based mineral processing research, and the development or validation of data-driven characterization methods. Users should note that MLA-derived mineralogical data are based on two-dimensional polished sections and may be subject to stereological effects.