Contributing person datacite.contributor.ProjectLeader	Dr. Thomas Leißner
Contributing person datacite.contributor.Researcher	Asim Siddique
Contributing person datacite.contributor.Supervisor	Prof. Urs A. Peuker
Description of the data datacite.resourceType	This dataset contains multi-scale correlative imaging data of complex particulate slag samples. It was developed to enable precise 3D characterization. This correlative analysis was performed on two types of slag samples: Fayalite slag and Waste of Electronic and Electrical Equipment (WEEE) slag. From each slag type, two different particle size fractions were used: 63–100 μm and 100–160 μm. The data integrates X-ray microcomputed tomography (μCT) scans at different resolutions, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) analyses, and micro X-ray fluorescence computed tomography (μXRF-CT) measurements. Components of the Dataset: Large Sample µCT Scan: A slag particulate sample approximately 10 mm in diameter was scanned at a voxel size of 6.5 μm and 7.5 µm. This scan captures a statistically significant number of particles to represent the overall mineralogical and microstructural variation. High-Resolution Sub-Sample µCT Scan: A sub-sample around 2 mm in diameter was extracted and scanned at a higher resolution of 2 μm voxel size. This scan provides detailed structural information of individual particles. SEM-EDS Data: High-resolution backscattered electron (BSE) images and elemental maps of the polished cross-section of the larger sample. µXRF-CT Measurements: µXRF-CT analysis of the sub-sample, providing elemental composition data from smaller sample.
Type of the data datacite.resourceTypeGeneral	Image
Total size of the dataset datacite.size	45928907853
Author dc.contributor.author	Siddique, Asim
Author dc.contributor.author	Schröer, Laurenz
Upload date dc.date.accessioned	2024-11-07T13:41:23Z
Publication date dc.date.available	2024-11-07T13:41:23Z
Data of data creation dc.date.created	2022-08-01
Publication date dc.date.issued	2024-11-07
Abstract of the dataset dc.description.abstract	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.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/1058
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-661
Publisher dc.publisher	Technische Universität Bergakademie Freiberg
Licence dc.rights	Attribution 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
Specification of the discipline(s) dc.subject.classification	4::42::403::403-03
Title of the dataset dc.title	Correlative X-ray micro-Computed Tomography (X-µCT) scans of Engineered Artificial Minerals (EnAM)
Research instruments opara.descriptionInstrument	https://www.ugent.be/we/ugct/en/research/ctscanners
Underlying research object opara.descriptionObject.Other	3D Particle Characterization
Project abstract opara.project.description	To establish a sustainable circular economy and to decrease our dependence on primary raw materials, recycling is essential. High-Technology products usually contain some concentration of diverse valuable raw materials and with current recycling processes these valuable elements are not fully recovered and thus lost in the waste stream (e.g., Slag produced during pyrometallurgical recycling). These slag systems can be tailored to produce known mineral phases (Engineered artificial Minerals - EnAM) containing valuable elements, eventually enabling us to treat them as a primary raw material resource. Thus, applying mineral processing operations should enable us to concentrate the valuable EnAM from the rest of the gangue phases. The separation of particle systems into two or more products with different properties or compositions requires a difference in the characteristics of particles to be separated, e.g. size shape, morphology, density, and magnetic susceptibility. These particle properties will be investigated by using X-ray micro-computed tomography, automated mineralogy (MLA), X-ray diffraction (XRD), and magnetic susceptibility balance (MSB). These individual particle properties will then be utilized to optimize the separation process with the help of multidimensional partition maps and particle-based statistical modeling of mechanical processing operations. This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the priority program 2315 “Engineered artificial minerals (EnAM)—A geo-metallurgical tool to recycle critical elements from waste streams” with grant number 470202518.
Public project website(s) opara.project.publicReference	https://tu-freiberg.de/fakult4/mvtat/spp-2315-enam
Project title opara.project.title	Single particle analysis for predictive EnAM processing (SPA-4-EnAM)

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

Files

Original bundle

License bundle

Collections