Articles | Volume 6, issue 2
https://doi.org/10.5194/gi-6-429-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gi-6-429-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| Highlight paper
| 
18 Oct 2017
Research article | Highlight paper |
| 18 Oct 2017
Automated mineralogy based on micro-energy-dispersive X-ray fluorescence microscopy (µ-EDXRF) applied to plutonic rock thin sections in comparison to a mineral liberation analyzer
Wilhelm Nikonow
CORRESPONDING AUTHOR
Federal Institute for Geosciences and Natural Resources (BGR),
Stilleweg 2, 30655 Hanover, Germany
Dieter Rammlmair
Federal Institute for Geosciences and Natural Resources (BGR),
Stilleweg 2, 30655 Hanover, Germany
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Cited
23 citations as recorded by crossref.
- Atomic Spectrometry Update – a review of advances in environmental analysis J. Bacon et al.
- Analytical approach for the characterization of the chemical and mineralogical composition of Al2O3–SiO2–CaO–MnO–Li2O–type lithium-ion battery (LIB) slags M. Ranneberg et al.
- Basalt weathering as the key to understand the past human use of hematite-based pigments in southernmost Patagonia S. Oriolo et al.
- Steel Plant Wastes as a Resource of Rare Earth Elements and Rare Metals–Characterisation, Resource Estimation, and Economic Assessment . Abhilash et al.
- Method for evaluation of geological strength index of carbonate cliff rocks: Coupled hyperspectral-digital borehole image technique H. Yang et al.
- The fate of molybdenum in the residues of a Chilean copper ore processing plant W. Nikonow & D. Rammlmair
- Data fusion method to identify light elements bearing minerals from the Li-Beauvoir granite based on SEM, µXRF, and µLIBS C. Korbel et al.
- Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping I. Contreras Acosta et al.
- Advanced mineral characterization and petrographic analysis by μ-EDXRF, LIBS, HSI and hyperspectral data merging W. Nikonow et al.
- Mineral Characterization Using Scanning Electron Microscopy (SEM): A Review of the Fundamentals, Advancements, and Research Directions A. Ali et al.
- A free, open-source method for automated mapping of quantitative mineralogy from energy-dispersive X-ray spectroscopy scans of rock thin sections M. Reed et al.
- Green Synthesis of Manganese Oxide Nanoparticles Using Plant Extracts: Synthesis Methods, Characterization, and Biomedical Applications — A Review A. Verma
- A Machine Learning Framework for Drill-Core Mineral Mapping Using Hyperspectral and High-Resolution Mineralogical Data Fusion I. Acosta et al.
- Optimizing μ-EDXRF spectra: A new approach for automatic diffraction identification and correction with implications on chemical quantification and grain identification W. Nikonow & D. Rammlmair
- Secondary minerals in a calcareous environment: an example from Um Gheig Pb/Zn mine site, Eastern Desert, Egypt M. Redwan et al.
- Chemical and Mineralogical Analysis of Samples Using Combined LIBS, Raman Spectroscopy and µ-EDXRF V. Merk et al.
- The In-Ga-Sb association of the post-Variscan Zn-Pb-Ag vein deposit at Lautenthal, Upper Harz Mountains, Germany: sphalerite mineral chemistry T. Graupner et al.
- Automated Quantitative Mineralogy Applied to Metamorphic Rocks N. Keulen et al.
- The new critical metals database “HTMET”: High tech trace element characteristics of sulphides from base metal provinces in the Variscan basement and adjacent sedimentary rocks in Germany S. Henning et al.
- SMART mineral mapping: Synchrotron-based machine learning approach for 2D characterization with coupled micro XRF-XRD J. Kim et al.
- Drill-Core Hyperspectral and Geochemical Data Integration in a Superpixel-Based Machine Learning Framework I. Acosta et al.
- Anomaly Detection in Mineral Micro-X-Ray Fluorescence Spectroscopy Based on a Multi-Scale Feature Aggregation Network Y. Lu et al.
- Magnetitites in the Upper Zone of the Bushveld Complex – continuous LIBS and µXRF data of magnetitite layer 17 with a focus on cryptic variation of mineral chemistry W. Nikonow et al.
23 citations as recorded by crossref.
- Atomic Spectrometry Update – a review of advances in environmental analysis J. Bacon et al.
- Analytical approach for the characterization of the chemical and mineralogical composition of Al2O3–SiO2–CaO–MnO–Li2O–type lithium-ion battery (LIB) slags M. Ranneberg et al.
- Basalt weathering as the key to understand the past human use of hematite-based pigments in southernmost Patagonia S. Oriolo et al.
- Steel Plant Wastes as a Resource of Rare Earth Elements and Rare Metals–Characterisation, Resource Estimation, and Economic Assessment . Abhilash et al.
- Method for evaluation of geological strength index of carbonate cliff rocks: Coupled hyperspectral-digital borehole image technique H. Yang et al.
- The fate of molybdenum in the residues of a Chilean copper ore processing plant W. Nikonow & D. Rammlmair
- Data fusion method to identify light elements bearing minerals from the Li-Beauvoir granite based on SEM, µXRF, and µLIBS C. Korbel et al.
- Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping I. Contreras Acosta et al.
- Advanced mineral characterization and petrographic analysis by μ-EDXRF, LIBS, HSI and hyperspectral data merging W. Nikonow et al.
- Mineral Characterization Using Scanning Electron Microscopy (SEM): A Review of the Fundamentals, Advancements, and Research Directions A. Ali et al.
- A free, open-source method for automated mapping of quantitative mineralogy from energy-dispersive X-ray spectroscopy scans of rock thin sections M. Reed et al.
- Green Synthesis of Manganese Oxide Nanoparticles Using Plant Extracts: Synthesis Methods, Characterization, and Biomedical Applications — A Review A. Verma
- A Machine Learning Framework for Drill-Core Mineral Mapping Using Hyperspectral and High-Resolution Mineralogical Data Fusion I. Acosta et al.
- Optimizing μ-EDXRF spectra: A new approach for automatic diffraction identification and correction with implications on chemical quantification and grain identification W. Nikonow & D. Rammlmair
- Secondary minerals in a calcareous environment: an example from Um Gheig Pb/Zn mine site, Eastern Desert, Egypt M. Redwan et al.
- Chemical and Mineralogical Analysis of Samples Using Combined LIBS, Raman Spectroscopy and µ-EDXRF V. Merk et al.
- The In-Ga-Sb association of the post-Variscan Zn-Pb-Ag vein deposit at Lautenthal, Upper Harz Mountains, Germany: sphalerite mineral chemistry T. Graupner et al.
- Automated Quantitative Mineralogy Applied to Metamorphic Rocks N. Keulen et al.
- The new critical metals database “HTMET”: High tech trace element characteristics of sulphides from base metal provinces in the Variscan basement and adjacent sedimentary rocks in Germany S. Henning et al.
- SMART mineral mapping: Synchrotron-based machine learning approach for 2D characterization with coupled micro XRF-XRD J. Kim et al.
- Drill-Core Hyperspectral and Geochemical Data Integration in a Superpixel-Based Machine Learning Framework I. Acosta et al.
- Anomaly Detection in Mineral Micro-X-Ray Fluorescence Spectroscopy Based on a Multi-Scale Feature Aggregation Network Y. Lu et al.
- Magnetitites in the Upper Zone of the Bushveld Complex – continuous LIBS and µXRF data of magnetitite layer 17 with a focus on cryptic variation of mineral chemistry W. Nikonow et al.
Saved (final revised paper)
Latest update: 11 May 2026
Short summary
This work describes a new approach to use fast X-ray fluorescence mapping as a tool for automated mineralogy applied on thin sections of plutonic rocks. Using a supervised classification of the spectral information, mineral maps are obtained for modal mineralogy and image analysis. The results are compared to a conventional method for automated mineralogy, which is scanning electron microscopy with mineral liberation analyzer, showing a good overall accuracy of 76 %.
This work describes a new approach to use fast X-ray fluorescence mapping as a tool for...
