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dc.contributor.authorIyakwari, Shekwonyadu
dc.date.accessioned2015-03-04T13:59:14Z
dc.date.issued2014-12-17
dc.description.abstractThe aim of this project was to investigate the potential and suitability of the application of near Infrared spectroscopy/sensors in automatic preconcentration of complex ores. Two ore types (copper and platinum) were considered for investigation. The near infrared region of electromagnetic spectrum has been used for mineral mapping in the minerals industries. However, its application as a sensing technology in the sorting of base and precious metals is still minimal. In practice, a near infrared sensor can measure characteristic features of carbonate, hydroxyl and water groups contained in minerals and rocks. Successful sensor-based sorting requires a good understanding of the minerals and their distribution in an ore. For the copper ores, mineralogical analysis was carried out using QEMSCAN® and qualitative XRD analysis. XRF analysis was used to determine the copper concentration in the various particles. In addition to the XRF elemental analysis, copper values were calculated from copper bearing minerals in the ore. XRD analysis was performed on the platinum ore. Methods of ore sorting based on near infrared readings and near infrared active functional groups (-OH, H2O, and CO32-) were investigated and strategies developed for both ore types. In addition to external environmental influence, most minerals contain water in their chemical structure. Therefore, considering the H2O absorption feature(s) for ore sorting was not considered optimal. Strategies were developed which target the discrimination of either or both carbonate and hydroxyl bearing particles as waste. Individual particles spectra were analysed and absorption features assigned to the various chemical species and minerals responsible for the absorptions. Due to individual particle mineralogical variation, particles were classified either as products, waste or middlings. For copper ore, targeting only the calcite (carbonate) dominated particles for discrimination as waste provided a better option for preconcentration. Application for the platinum ores targeted the discrimination of chlorite, antigorite, and/or calcite dominated samples as waste. Compared with sample mineralogy, samples could be classified as product or waste using near infrared.en_GB
dc.description.sponsorshipNigerian Tertiary Education Trust Fund (TETFUND) and Anglo Americanen_GB
dc.identifier.citationIyakwari, S., Glass, H. J., 2014, ‘Influence of mineral particle size and choice of suitable parameters for ore sorting using near infrared sensors’. Miner Eng, 69, 102-106en_GB
dc.identifier.citationIyakwari, S., Glass, H. J., Kowalczuk, P. B., 2013, ‘Potential for near infrared sensor-based sorting of hydrothermally-formed minerals’. J Near Infrared Spectrosc, 21(3), 223-229en_GB
dc.identifier.citationIyakwari, S., & Glass, H. J., 2015. Mineral preconcentration using near infrared sensor-based sorting Physicochemical Problems of Mineral Processing 51(2), in pressen_GB
dc.identifier.citationIyakwari, S., & Glass, H.J., 2014b. Strategy for copper preconcentration using near infrared sensor-based sorting. Proceedings of the Mineral Engineering Conference (MEC 2014), eds. M. Lutynski, T. Suponik, Istebna (2014) 288 – 296en_GB
dc.identifier.urihttp://hdl.handle.net/10871/16451
dc.language.isoenen_GB
dc.publisherUniversity of Exeteren_GB
dc.rights.embargoreasonCommercial sensitivityen_GB
dc.rightsThesis contain a detailed characterization of the mineralogy and geochemistry of ore from Anglo American mines. Hence, in view of Anglo American stated intention to sell the South American mines, all information regarding the ore and its processing characteristics is considered to be commercially sensitive and as a result, is being locked down.en_GB
dc.titleApplication of Near Infrared Sensors to Minerals Preconcentrationen_GB
dc.typeThesis or dissertationen_GB
dc.contributor.advisorGlass, Hylke. J.
dc.contributor.advisorPascoe, Richard
dc.publisher.departmentMining and Minerals Engineeringen_GB
dc.type.degreetitlePhD in Mining and Minerals Engineeringen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnamePhDen_GB


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