EGU2020-20410
https://doi.org/10.5194/egusphere-egu2020-20410
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Spectral X-ray tomography for 3D mineral analysis

Jonathan Sittner1, Jose R. A. Godinho1, Axel D. Renno1, Veerle Cnudde2,3, Marijn Boone4, Thomas De Schryver4, Antti Roine5, and Jussi Liipo5
Jonathan Sittner et al.
  • 1Helmholtz-Zentrum Dresden Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Analytics, Germany
  • 2PProGRess-UGCT, Geology Department, Ghent University, Krijgslaan 281/Building S8, B-9000, Ghent, Belgium
  • 3Department of Earth Sciences, Utrecht University, Princetonlaan 8a, 3584 CB Utrecht, The Netherlands
  • 4TESCAN XRE, Bollebergen 2B box 1, 9052 Ghent, Belgium
  • 5Outotec, Rauhalanpuisto 9, 02230 Espoo, Finland

Image based analytical tools in geoscience are indispensable for the characterization of minerals but most of them are 2D techniques, limited to the surface of a polished plane in a sample. X-ray micro computed tomography (micro-CT) is becoming a common analysis technique in geoscience and provides direct 3D information of the internal structure of a sample. A major drawback of micro-CT in the characterization of minerals, however, is the lack of chemical information. There have been different approaches to obtain chemical data using micro-CT but most of them are time consuming and difficult to adapt to regular use.

Therefore we introduce a potential new analytical tool: Laboratory-based Spectral X-ray Micro Computed Tomography (Sp-CT). Results from a spectral imaging detector prototype, installed inside a TESCAN CoreTOM micro-CT scanner, will be shown. This new analytical technique enables to obtain both high resolution structural and chemical information in 3D. With this information, the mineral distribution inside unbroken rocks and particles can be identified and quantified.

Based on the transmitted energy spectrum of a sample, main elements can be distinguished and minerals classified. It is also possible to quantify heavy elements within particles of complex composition and the measured sample volume is significantly larger compared to conventional analytical 2D techniques. Furthermore, Sp-CT is non-destructive and does not require sample preparation.

Sp-CT will open exciting new possibilities for mineral analysis. With this new technique, the 3D properties of the particles can now be measured and used for example in process mineralogy simulations. This is a major improvement to current simulations that predominantly use less representative 2D or bulk particle properties. Moreover, the Sp-CT could potentially be used as an alternative technique for regular characterization of ore deposits and processed ores since more representative volumes can be analyzed in a fast manner relative to existing techniques.

This research is part of the upscaling project “Resource Characterization: from 2D to 3D microscopy” and has received funding from European Institute of Innovation and Technology (EIT), a body of the European Union, under the Horizon 2020, the EU Framework Programme for Research and Innovation.

How to cite: Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Roine, A., and Liipo, J.: Spectral X-ray tomography for 3D mineral analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20410, https://doi.org/10.5194/egusphere-egu2020-20410, 2020

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Presentation version 1 – uploaded on 04 May 2020
  • CC1: Comment on EGU2020-20410, R.Valli Divya, 07 May 2020

    How many minerals can be analysed by Sp-CT?

    • AC1: Reply to CC1, Jonathan Sittner, 07 May 2020

      It depends on the sample. In theory, all minerals containing elements from silver to up to actinides can be analyzed with Sp-CT. But there are important factors that can influence the measurement e.g. sample composition, matrix minerals, dimensions of the minerals, sample size, and shape.

      • CC2: Reply to AC1, R.Valli Divya, 07 May 2020

        Thank you.

        Regards,

        Divya