Supplemental SEM-EDS (MLA) and CT data for the publication "CNN-based 3D characterization and liberation analysis of lithium-bearing slag particles using correlative CT and SEM imaging"
Contributing person | Ralf Ditscherlein | |
Contributing person | Tom Kirstein | |
Contributing person | Cindytami Rachmawati | |
Contributing person | Urs A. Peuker | |
Contributing person | Volker Schmidt | |
Contributing person | Kai Bachmann | |
Contributing person | Erik Löwer | |
Contributing person | Orkun Furat | |
References to related material | “CNN-based 3D characterization and liberation analysis of lithium-bearing slag particles using correlative CT and SEM imaging” by Tom Kirstein et al. | |
Description of the data | The repository contains particle-resolved imaging data, processed image stacks, mineral classification outputs, and supporting datasets for image-based analysis, particle characterization, and method development in mineral processing. | |
Type of the data | Image | |
Total size of the dataset | 9437569934 | |
Author | Ditscherlein, Ralf | |
Upload date | 2026-05-13T13:19:56Z | |
Publication date | 2026-05-13T13:19:56Z | |
Publication date | 2026-05-13 | |
Abstract of the dataset | This dataset provides the underlying X-ray CT data and processed image stacks used for particle-scale characterization and evaluation of the proposed workflow. The study addresses the challenge of accurately characterizing lithium-bearing slag particles to improve recovery of critical raw materials. A correlative workflow combining 3D CT imaging with 2D SEM-based mineral maps is used to train convolutional neural networks for phase-wise and particle-wise segmentation. This enables scalable 3D characterization with minimal manual labeling effort. The models are applied to particle size fractions of 63–100 µm and 100–250 µm. Results show that conventional 2D approaches systematically overestimate mineral liberation, while the presented 3D approach reduces stereological bias and provides more reliable input for process optimization. | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2260 | |
Public reference to this page | https://doi.org/10.25532/OPARA-1190 | |
Publisher | Technische Universität Bergakademie Freiberg | |
Licence | Attribution 4.0 International | en |
URI of the licence text | http://creativecommons.org/licenses/by/4.0/ | |
Specification of the discipline(s) | 3::34::316::316-01 | |
Specification of the discipline(s) | 4::42::403::403-03 | |
Title of the dataset | Supplemental SEM-EDS (MLA) and CT data for the publication "CNN-based 3D characterization and liberation analysis of lithium-bearing slag particles using correlative CT and SEM imaging" | |
Research instruments | Xradia 510 VERSA (Zeiss) | |
Research instruments | FEI Quanta 650F (Thermo Fisher Scientific) + EDS detector (Bruker) | |
Underlying research object | lithium-bearing slag particles | |
Funding Acknowledgement | This research is partially funded by the German Research Foundation (DFG) through the research projects 470552553 and 470322626 within the priority programs SPP 2315 “Engineered Artificial Minerals (EnAMs): A Geo-Metallurgical Tool to Recycle Critical Elements from Waste Streams: Synthesis, Characterization, Metallurgical and Mechanical Processing” |
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