The potential of Near Infrared (NIR) spectroscopy for application in automated sorting was investigated on a sample of iron oxide copper-gold ore. The ore contains a substantial amount of carbonate material which results in excessive acid consumption in the leaching circuit during copper extraction, thereby increasing the processing cost. To separate this unwanted gangue material (carbonate) from the valuable metal (copper), a strategy for classification of ore according to copper and carbonate content was developed. The chemical and mineralogical composition of the ore was determined using XRF, respectively XRD. This data was correlated with NIR spectra measured on the surface of ore particles. NIR spectra showed distinct characteristic absorption features for carbonate rich particles that distinguish these from copper bearing particles, which are fairly featureless at longer NIR wavelengths (range 2000nm -2405nm). Combined interpretation of spectral features and chemical and mineralogical data indicates that NIR-based sorting has potential forthis type of ore.
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