Stochastic Modeling of Multidimensional Particle Properties Using Parametric Copulas.

In this paper, prediction models are proposed which allow the mineralogical characterization of particle systems observed by X-ray micro tomography (XMT). The models are calibrated using 2D image data obtained by a combination of scanning electron microscopy and energy dispersive X-ray spectroscopy in a planar cross-section of the XMT data. To reliably distinguish between different minerals the models are based on multidimensional distributions of certain particle characteristics describing, for example, their size, shape, and texture. These multidimensional distributions are modeled using parametric Archimedean copulas which are able to describe the correlation structure of complex multidimensional distributions with only a few parameters. Furthermore, dimension reduction of the multidimensional vectors of particle characteristics is utilized to make non-parametric approaches such as the computation of distributions via kernel density estimation viable. With the help of such distributions the proposed prediction models are able to distinguish between different types of particles among the entire XMT image.

Description of Ore Particles from X-Ray Microtomography (XMT) Images, Supported by Scanning Electron Microscope (SEM)-Based Image Analysis.

In this paper, three-dimensional (3D) image data of ore particle systems is investigated. By combining X-ray microtomography with scanning electron microscope (SEM)-based image analysis, additional information about the mineralogical composition from certain planar sections can be gained. For the analysis of tomographic images of particle systems the extraction of single particles is essential. This is performed with a marker-based watershed algorithm and a post-processing step utilizing a neural network to reduce oversegmentation. The results are validated by comparing the 3D particle-wise segmentation empirically with 2D SEM images, which have been obtained with a different imaging process and segmentation algorithm. Finally, a stereological application is shown, in which planar SEM images are embedded into the tomographic 3D image. This allows the estimation of local X-ray attenuation coefficients, which are material-specific quantities, in the entire tomographic image.

Advanced Identification and Quantification of In-Bearing Minerals by Scanning Electron Microscope-Based Image Analysis.

The identification and accurate characterization of discrete grains of rare minerals in sulfide base-metal ores is usually a cumbersome procedure due to the small grain sizes (typically <10 µm) and complex mineral assemblages in the material. In this article, a new strategy for finding and identifying indium minerals, and quantifying their composition and abundance is presented, making use of mineral liberation analysis (MLA) and electron probe microanalysis (EPMA). The method was successfully applied to polymetallic massive sulfide ores from the Neves-Corvo deposit in Portugal. The presence of roquesite and sakuraiite could be systematically detected, their concentration quantified by MLA measurements, and their identity later confirmed by EPMA analyses. Based on these results, an almost complete indium deportment could be obtained for the studied samples. This validates the approach taken, combining automated mineralogy data with electron microprobe analysis. A similar approach could be used to find minerals of other common minor and trace elements in complex base-metal sulfide ores, for example Se, Ge, Sb, or Ag, thus permitting the targeted development of resource technologies suitable for by-product recovery.

Efficient and Accurate Identification of Platinum-Group Minerals by a Combination of Mineral Liberation and Electron Probe Microanalysis with a New Approach to the Offline Overlap Correction of Platinum-Group Element Concentrations.

Identification and accurate characterization of platinum-group minerals (PGMs) is usually a very cumbersome procedure due to their small grain size (typically below 10 µm) and inconspicuous appearance under reflected light. A novel strategy for finding PGMs and quantifying their composition was developed. It combines a mineral liberation analyzer (MLA), a point logging system, and electron probe microanalysis (EPMA). As a first step, the PGMs are identified using the MLA. Grains identified as PGMs are then marked and coordinates recorded and transferred to the EPMA. Case studies illustrate that the combination of MLA, point logging, and EPMA results in the identification of a significantly higher number of PGM grains than reflected light microscopy. Analysis of PGMs by EPMA requires considerable effort due to the often significant overlaps between the X-ray spectra of almost all platinum-group and associated elements. X-ray lines suitable for quantitative analysis need to be carefully selected. As peak overlaps cannot be avoided completely, an offline overlap correction based on weight proportions has been developed. Results obtained with the procedure proposed in this study attain acceptable totals and atomic proportions, indicating that the applied corrections are appropriate.

Electron Probe Microanalysis of REE in Eudialyte Group Minerals: Challenges and Solutions.

Accurate quantification of the chemical composition of eudialyte group minerals (EGM) with the electron probe microanalyzer is complicated by both mineralogical and X-ray-specific challenges. These include structural and chemical variability, mutual interferences of X-ray lines, in particular of the rare earth elements, diffusive volatility of light anions and cations, and instability of EGM under the electron beam. A novel analytical approach has been developed to overcome these analytical challenges. The effect of diffusive volatility and beam damage is shown to be minimal when a square of 20×20 µm is scanned with a beam diameter of 6 µm at the fastest possible speed, while measuring elements critical to electron beam exposure early in the measurement sequence. Appropriate reference materials are selected for calibration considering their volatile content and composition, and supplementary offline overlap correction is performed using individual calibration factors. Preliminary results indicate good agreement with data from laser ablation inductively coupled plasma mass spectrometry demonstrating that a quantitative mineral chemical analysis of EGM by electron probe microanalysis is possible once all the parameters mentioned above are accounted for.

Life on a Mesoarchean marine shelf - insights from the world's oldest known granular iron formation.

The Nconga Formation of the Mesoarchean (~2.96-2.84 Ga) Mozaan Group of the Pongola Supergroup of southern Africa contains the world's oldest known granular iron formation. Three dimensional reconstructions of the granules using micro-focus X-ray computed tomography reveal that these granules are microstromatolites coated by magnetite and calcite, and can therefore be classified as oncoids. The reconstructions also show damage to the granule coatings caused by sedimentary transport during formation of the granules and eventual deposition as density currents. The detailed, three dimensional morphology of the granules in conjunction with previously published geochemical and isotope data indicate a biogenic origin for iron precipitation around chert granules on the shallow shelf of one of the oldest supracratonic environments on Earth almost three billion years ago. It broadens our understanding of biologically-mediated iron precipitation during the Archean by illustrating that it took place on the shallow marine shelf coevally with deeper water, below-wave base iron precipitation in micritic iron formations.