2020
DOI: 10.1017/s143192762000135x
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Deciphering the Complex Mineralogy of River Sand Deposits through Clustering and Quantification of Hyperspectral X-Ray Maps

Abstract: Alluvial mineral sands rank among the most complex subjects for mineral characterization due to the diverse range of minerals present in the sediments, which may collectively contain a daunting number of elements (>20) in major or minor concentrations (>1 wt%). To comprehensively characterize the phase abundance and chemistry of these complex mineral specimens, a method was developed using hyperspectral x-ray and cathodoluminescence mapping in an electron probe microanalyser (EPMA), coupled with automate… Show more

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Cited by 15 publications
(8 citation statements)
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“…Wavelength-and energy-dispersive spectrometry were acquired in parallel with spectral cathodoluminescence (CL) using a grating spectrometer (MacRae et al, 2013). Extraction of elemental maps, CL maps, and the extraction of X-ray and CL spectra were performed using in-house software Chimage (Torpy et al, 2020). Microanalysis of silicate glass was performed with a 12 kV accelerating voltage, 15 nA beam current, and spot size was at least 1 µm to minimize migration under the electron beam.…”
Section: Methodsmentioning
confidence: 99%
“…Wavelength-and energy-dispersive spectrometry were acquired in parallel with spectral cathodoluminescence (CL) using a grating spectrometer (MacRae et al, 2013). Extraction of elemental maps, CL maps, and the extraction of X-ray and CL spectra were performed using in-house software Chimage (Torpy et al, 2020). Microanalysis of silicate glass was performed with a 12 kV accelerating voltage, 15 nA beam current, and spot size was at least 1 µm to minimize migration under the electron beam.…”
Section: Methodsmentioning
confidence: 99%
“…Wavelength dispersive spectrometers, energy dispersive spectrometers and spectral cathodoluminescence signals were all collected in parallel (MacRae et al 2013). Mapping data were analyzed using Chimage X in-house software (Harrowfield et al 1993, Torpy et al 2020).…”
Section: Epma Mappingmentioning
confidence: 99%
“…A benefit of hyperspectral data collection is that these data sets are amenable to post-hoc examination to find unexpected phases (x-ray data) and defects or centres (CL data) within a sample. There are number of approaches that can be used to examine hyperspectral data sets, and in this work, we have used clustering algorithms to partition and organise the hyperspectral data [8,9].…”
mentioning
confidence: 99%