Optimization and Quality Control of Automated Quantitative Mineralogy Analysis for Acid Rock Drainage Prediction
AbstractLow ore-grade waste samples from the Codelco Andina mine that were analyzed in an environmental and mineralogical test program for acid rock drainage prediction, revealed inconsistencies between the quantitative mineralogical data (QEMSCAN®) and the results of geochemical characterizations by atomic absorption spectroscopy (AAS), LECO® furnace, and sequential extractions). For the QEMSCAN® results, biases were observed in the proportions of pyrite and calcium sulfate minerals detected. An analysis of the results indicated that the problems observed were likely associated with polished section preparation. Therefore, six different sample preparation protocols were tested and evaluated using three samples from the previous study. One of the methods, which involved particle size reduction and transverse section preparation, was identified as having the greatest potential for correcting the errors observed in the mineralogical analyses. Further, the biases in the quantities of calcium sulfate minerals detected were reduced through the use of ethylene glycol as a polishing lubricant. It is recommended that the sample preparation methodology described in this study be used in order to accurately quantify percentages of pyrite and calcium sulfate minerals in environmental mineralogical studies which use automated mineralogical analysis. View Full-Text
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Pooler, R.; Dold, B. Optimization and Quality Control of Automated Quantitative Mineralogy Analysis for Acid Rock Drainage Prediction. Minerals 2017, 7, 12.
Pooler R, Dold B. Optimization and Quality Control of Automated Quantitative Mineralogy Analysis for Acid Rock Drainage Prediction. Minerals. 2017; 7(1):12.Chicago/Turabian Style
Pooler, Robert; Dold, Bernhard. 2017. "Optimization and Quality Control of Automated Quantitative Mineralogy Analysis for Acid Rock Drainage Prediction." Minerals 7, no. 1: 12.
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