The evaluation of the mineral abundances and metal deportments in Ni-Co laterite ores by means of routine analytical techniques, such as X-Ray Powder Diffraction-based Quantitative Phase Analysis (XRPD-QPA), could be quite challenging or also ineffective, due to occurrence of ore minerals characterized either by complex crystal structures (e.g. smectite and certain Mn-oxy-hydroxides) or by poor structural order (Fe-oxy-hydroxides). In this context, automated Scanning Electron Microscopy (automated SEM)-based methods, which are based on the chemistry and density of various mineral species, could offer breakthroughs in defining the mineralogy and the metal deportments, bypassing the issues related to the presence of phases not evaluable by using solely XRPD-based approaches. For this study we conducted the mineralogical and chemical evaluation of oxide- and clay-dominated mineralised facies occurring in the Wingellina deposit through XRPD-QPA and automated SEM. The results show that the main benefit of using automated SEM is the possibility to directly detect and identify Ni-Co-bearing Mn-oxy-hydroxides (lithiophorite, lithiophorite-asbolane and asbolane) and Ni-bearing clays, which are hardly distinguished at the XRPD-QPA because of their poorly-crystalline structure. Moreover, the use of automated SEM for the analysis of Mn-oxy-hydroxide-dominated samples also allowed determining the Co deportment, which is essential to predict the optimum achievable metals recoveries. The main limitation encountered during the application of the automated SEM in this study was the fine-grained nature of the ore samples, leading to the detection of mixed mineral classes not corresponding to mineral phases sensu stricto.

Quantitative mineralogical evaluation of Ni-Co laterite ores through XRPD-QPA- and automated SEM-based approaches: The Wingellina (Western Australia) case study

Santoro L.;
2021-01-01

Abstract

The evaluation of the mineral abundances and metal deportments in Ni-Co laterite ores by means of routine analytical techniques, such as X-Ray Powder Diffraction-based Quantitative Phase Analysis (XRPD-QPA), could be quite challenging or also ineffective, due to occurrence of ore minerals characterized either by complex crystal structures (e.g. smectite and certain Mn-oxy-hydroxides) or by poor structural order (Fe-oxy-hydroxides). In this context, automated Scanning Electron Microscopy (automated SEM)-based methods, which are based on the chemistry and density of various mineral species, could offer breakthroughs in defining the mineralogy and the metal deportments, bypassing the issues related to the presence of phases not evaluable by using solely XRPD-based approaches. For this study we conducted the mineralogical and chemical evaluation of oxide- and clay-dominated mineralised facies occurring in the Wingellina deposit through XRPD-QPA and automated SEM. The results show that the main benefit of using automated SEM is the possibility to directly detect and identify Ni-Co-bearing Mn-oxy-hydroxides (lithiophorite, lithiophorite-asbolane and asbolane) and Ni-bearing clays, which are hardly distinguished at the XRPD-QPA because of their poorly-crystalline structure. Moreover, the use of automated SEM for the analysis of Mn-oxy-hydroxide-dominated samples also allowed determining the Co deportment, which is essential to predict the optimum achievable metals recoveries. The main limitation encountered during the application of the automated SEM in this study was the fine-grained nature of the ore samples, leading to the detection of mixed mineral classes not corresponding to mineral phases sensu stricto.
2021
223
106695
106695
https://www.sciencedirect.com/science/article/pii/S0375674220306555
Automated Scanning Electron Microscopy; Metal deportment; Ni-Co laterite; Western Australia; Wingellina; XRPD-Rietveld analysis
Santoro L.; Putzolu F.; Mondillo N.; Herrington R.; Najorka J.; Boni M.; Dosbaba M.; Maczurad M.; Balassone G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1769740
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