Unlocking the applications of automated mineral analysis
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Abstract:
Identifying and quantifying the relative abundance of minerals is a fundamental part of many aspects of both pure and applied geology. Historically, quantitative mineralogy could be achieved using optical microscopy and point counting. This is a slow and operator dependent process, and practically impossible to achieve in, for example, very fine grained samples. Over the last decade a range of automated mineralogy technologies have arisen from the global mining industry and are being increasingly used in other branches of geology. These technologies, based on scanning electron microscopy with linked energy dispersive spectrometers, have the potential to revolutionise how we quantify mineralogy. In addition, during measurement, the sample textures are also captured, providing a wealth of valuable data for the geologist. In this article we review the current state of automated mineralogy and highlight the many areas of application for this technology.Keywords:
Geologist
Sample (material)
Gangue
Mineral processing
Sulfide Minerals
Silicate minerals
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The mineral reactive surface area is often quantified through a wide range of approaches (e.g., Brunauer–Emmett–Teller adsorption, geometry approximation, and imaging techniques). As such, values vary 1–5 orders of magnitude which can result in large discrepancies when used in reactive transport models to simulate geochemical reaction rates. Simulations carried out using mineral accessible surface areas (ASAs) determined from a coupled 2D and 3D imaging approach have shown better match with reaction rates measured in core-flood experiments. However, such image processing requires large amounts of time and resources. In this work, the possibility of estimating mineral ASAs from easily measured properties like mineral abundance and porosity is explored. Six sandstone samples of varying compositions were studied along with data from three additional samples from the previous literature. Mineral ASAs were quantified using a combined 2D scanning electron microscopy and 3D X-ray nano-computed tomography imaging approach. Sample properties like mineral accessibility, mineral ASAs, connected porosity, and clay content were compared to explore potential correlations between properties. Overall, it was observed that mineral accessibility can be predicted where feldspar mineral accessibility generally increases with increasing abundance and quartz accessibility decreases with increasing clay content. Mineral ASAs vary between samples, depending on the relative abundance of minerals and overall pore connectivity. While the ASA of quartz decreases with abundance, albite and carbonate mineral ASAs increase with abundance. Quantitative observations, including predictive relationships for ASAs from porosity and mineral volume fraction, are developed. Estimations of ASAs and mineral accessibility from more easily quantifiable properties can largely reduce the required extent of image analysis.
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Abstract Mineralogical and chemical heterogeneity within three standard clay mineral samples have been identified by X-ray diffraction and chemical analysis of various size-fractions. This heterogeneity is partly attributed to accessory minerals, but mostly to structural and compositional variations in the 2:1 layer minerals of different particle size in the same specimen.
Structural formula
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