Articles | Volume 6, issue 2
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 and Dieter Rammlmair

Abstract. Recent developments in the application of micro-energy-dispersive X-ray fluorescence spectrometry mapping (µ-EDXRF) have opened up new opportunities for fast geoscientific analyses. Acquiring spatially resolved spectral and chemical information non-destructively for large samples of up to 20 cm length provides valuable information for geoscientific interpretation. Using supervised classification of the spectral information, mineral distribution maps can be obtained. In this work, thin sections of plutonic rocks are analyzed by µ-EDXRF and classified using the supervised classification algorithm spectral angle mapper (SAM). Based on the mineral distribution maps, it is possible to obtain quantitative mineral information, i.e., to calculate the modal mineralogy, search and locate minerals of interest, and perform image analysis. The results are compared to automated mineralogy obtained from the mineral liberation analyzer (MLA) of a scanning electron microscope (SEM) and show good accordance, revealing variation resulting mostly from the limit of spatial resolution of the µ-EDXRF instrument. Taking into account the little time needed for sample preparation and measurement, this method seems suitable for fast sample overviews with valuable chemical, mineralogical and textural information. Additionally, it enables the researcher to make better and more targeted decisions for subsequent analyses.

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 %.