Selective leaching of copper from near infrared sensor-based preconcentrated copper ores

This is the final version. Available on open access from Wroclaw University of Science and Technology via the DOI in this recordCopper oxide ore was pre-concentrated using near infrared sensor-based method and classified as product, middling and waste. The product and middling fractions were leached with ammonium chloride reagent. The effect of temperature, ammonium chloride concentration, solid-liquid ratio, stirring speed and particle size experimental variables were investigated. Mineralogical and chemical analysis of the ore fractions indicated that copper content was in accordance with the preconcentration strategy, with the product having a higher concentration than the middling and waste. The rate of copper extraction was found to be higher in the product than in the middling sample which further supports the near infrared classification, QEMSCAN®, X-ray diffraction, SEM mineralogical and X-ray florescence and Inductively coupled plasma Mass spectrometry chemical data. It was revealed that the leaching rate increases with increasing ammonium chloride concentration, temperature and decreasing ore particle size, stirring speed and solid-liquid ratio. Analysis of the experimental data by shrinking core model indicated that the dissolution kinetics follow the heterogeneous reaction model for the chemical control mechanism where the activation energies of 45.9 kJ/mol and 47.5 kJ/mol for product and middling fractions respectively were obtained. Characterization of the residue obtained at optimum leaching condition with X-ray diffraction suggests that copper was selectively leached when compared to the profile of the raw ore. The trace levels of metals associated with abundant X-ray diffraction profiles of residue found in the leachate further confirm the selective leaching process.Natural Environment Research Council (NERC

Discerning mineral association in the near infrared region for ore sorting

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The preconcentration or early rejection of gangue minerals in mineral processing operations is investigated using sorting, based on interpretation of near infrared sensor data collected from ore particles. The success of sorting depends on the distribution of minerals between particles, the arrangement or association of minerals within particles and the ability of near infrared to distinguish relevant minerals. This paper considers minerals association, using common alteration minerals found in a hydrothermally-formed copper ore, with sensitivity in the near infrared region. The selected NIR-active minerals were arranged along the view of NIR line scanner to stimulate adjacent natural minerals association. It was found that spectral dominance may depend on minerals near infrared sensitivity and or the position of a mineral along the NIR scanner line of view. Analysis also revealed that only free occurring waste mineral spectra can be targeted for discrimination as tailings. Where spectra appeared mixed, such spectra are best considered products.The Nigerian Government through the academic support scheme of the Tertiary Education Trust Fund (TETFund) of Nigeria and the management of the Nasarawa State University, Keffi are acknowledged for providing financial support for this research

Influence of mineral particle size and choice of suitable parameters for ore sorting using near infrared sensors

PublishedJournal ArticleNear infrared sensor-based sorting is an emerging preconcentration technology which holds promise for many mineral processing applications, such as elimination of calcite and clay waste from ore. Preconcentration serves to increase the processing efficiency as well as to reduce the total processing cost through the rejection of unwanted gangue. Given small-scale heterogeneity in complex ores, i.e. assorted minerals occurring side-by-side inside an area of measurement, the total mineral composition may not be easily discerned from a near infrared spectrum. Hence, mineral identification and subsequent classification involves the analysis of absorption features in terms of feature depth, width, position, and level of spectral reflectance. This research investigates the near infrared spectral characteristics of minerals as a function of particle size fraction, specifically for individual minerals commonly found in malachite-rich copper ores. Samples of pure minerals are crushed and sieved into different size fractions and scanned with a near infrared line scanner. It was found that the presence of characteristic absorption features and their wavelength position were a better identification parameter than the reflectance level. The implication for preconcentrating a typical malachite-rich copper ore through near-infrared based sorting is discussed. © 2014 Elsevier Ltd. All rights reserved.We wish to thank Anglo American for providing the samples. The Nigerian Government, through the academic staff support scheme of the Tertiary Education Trust Fund of Nigeria (TETFON), and the Management of Nasarawa State University, Keffi, are acknowledged for providing financial support for this research

Mineral preconcentration using near infrared sensor-based sorting

This paper predicts qualitatively and quantitatively the near infrared activity of individual minerals in simple and complex mineral associations using mixtures of common alteration minerals found in a copper ore. It was found that spectra dominance in most cases is dependent on any or combination of mineral composition, relative proportion or concentration and/or mineral accessibility or sensitivity to near infrared radiation. The analysis of results also indicated that, in most cases, only freely occurring waste, such as clays (kaolinite and/or muscovite) and calcite, can be targeted for discrimination. In this paper, a strategy for the application of near infrared for preconcentration of copper bearing minerals like chrysocolla and malachite from coarse ore particles was proposed. Other applications also considered in this paper include preconcentration of hematite from associated clays and carbonate waste, and the determination of moisture content in kaolinitic clays

Qualitative identification of copper bearing minerals using near infrared sensors

Application of sensors for on-site fast identification and discrimination of dominant ore bearing particles from associated gangues in a complex ore is an important route in minerals exploration and extraction industries. This paper considers identification and discrimination of copper bearing minerals from associated gangues using near infrared sensors. Different copper bearing minerals in the Akiri copper ore are differentiated on the basis of their near infrared spectra behaviour. The near infrared spectra of individual samples are correlated with their mineralogy and chemistry as analysed by X-Ray diffraction and X-Ray fluorescence equipment, respectively. The obtained results indicated that the detection limit of the near infrared sensor is better than that of both X-ray diffraction and X-ray fluorescence equipment used. Hence, in addition to the minerals identified by the X-ray diffraction equipment, other near infrared active minerals with concentration below the X-ray diffraction detection limit were also detected by the near infrared sensors