Combining chemical assays (XRF) and quantitative X-ray diffraction (Rietveld) in modal analysis of iron ores for geometallurgical purposes in Northern Sweden (original) (raw)
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Minerals, 2019
The Per Geijer iron oxide apatite deposits are important potential future resources for Luossavaara-Kiirunavaara Aktiebolag (LKAB) which has been continuously mining magnetite/hematite ores in northern Sweden for over 125 years. Reliable and quantitative characterization of the mineralization is required as these ores inherit complex mineralogical and textural features. Scanning electron microscopy-based analyses software, such as mineral liberation analyzer (MLA) provide significant, time-efficient analyses. Similar elemental compositions of Fe-oxides and, therefore, almost identical backscattered electron (BSE) intensities complicate their discrimination. In this study, MLA and Raman imaging are compared to acquire mineralogical data for better characterization of magnetite and hematite-bearing ores. The different approaches demonstrate advantages and disadvantages in classification, imaging, discrimination of iron oxides, and time consumption of measurement and processing. The ob...
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Building a Geometallurgical Model in Iron Ores using a Mineralogical Approach with Liberation Data
A geometallurgical model is currently built in two different ways. The first and the most common way relies on geometallurgical testing, where a large number of samples are analysed for metallurgical response using small-scale laboratory tests, eg Davis tube testing. The second, mineralogical approach focuses on collecting mineralogical information over the orebody and building the metallurgical model based on mineralogy. At Luleå University of Technology, Sweden, the latter method has been adopted and taken further in four ongoing PhD studies. The geological model gives modal composition by the help of element-to-mineral conversion and Rietveld X-ray diffraction. Texturally, the orebody is divided into different archetypes, and liberation measurements for each of them are carried out in processing fineness using IncaMineral, a SEM-based technique. The grindability and liberation spectrum of any given geological unit (sample, ore block, domain) are extrapolated from the archetypes. The process model is taken into a liberation level by mass balancing selected metallurgical tests using the particle tracking technique. The approach is general and can be applied to any type of ores. Examples of ongoing studies on iron and massive sulfide ores are given.
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Iron Ore Quantitative Characterisation Through Reflected Light- Scanning Electron Co-Site Microscopy
Ninth International Congress for Applied Mineralogy (ICAM-2008), 2008
The traditional trading of iron ores is based on chemical specifications and particle size distribution. However, recent characterisation studies, that bring additional information like mineralogical composition and microstructural (textural) aspects, have become important. They contribute to determination of the iron ores downstream beneficiation operations and subsequent steelmaking processing, allowing improvements on both new and existing processes. Despite progress in commercial scanning electron microscope/energy dispersive spectrometer (SEM/EDS) automatic instruments in the last decade, these systems are not capable of performing the identification and discrimination of major iron ore minerals (haematite and magnetite) and the consequent description of its microstructure. On the other hand, reflected light microscopy (RLM) can easily distinguish the iron oxides by their reflectancies, but it cannot discriminate quartz and epoxy resin, which present similar colour on images. The present work proposes an innovative method to perform a quantitative mineralogy characterisation of iron ore based on RLM-SEM co-site microscopy. This technique combines images obtained by RLM and SEM through an automatic registration procedure that accurately aligns the two kinds of images of each field. In fact, it creates multi-dimensional images, which are then analysed using image processing and pattern recognition techniques. The case study is an itabiritic iron ore from Quadrilátero Ferrífero (Brazil) which contains mainly quartz, goethite, magnetite and haematite. The discrimination of phases that are not distinguishable with either RLM (epoxy resin and quartz) or SEM (haematite and magnetite) can be performed through this multimodal approach, allowing the subsequent mineralogical quantification. The mineralogical quantification computed by image analysis was consistent with independently obtained results based on the Rietveld technique.
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CHAPTER-2 Mineralogical Characterization of Iron Ores
2012
Mineralogical characterization of iron ore is a very important and basic aspect that has to get due attention before any attempt for its processing and has become almost inevitable these days because of the increasing demand of the ore. Mineral processing technology is evolved to separate and recover ore minerals from gangue in a commercially viable method and is mainly based on the process of mineral liberation and the process of mineral separation. Therefore, it is important to first get a clear understanding about oreand gangue minerals. A mineral is a natural inorganic substance having definite chemical composition and atomic structure. If the internal atomic arrangement is lacking, then it is an amorphous substance. A rock is generally composed of various minerals and if the rock contains valuable minerals frOm which metals can be extracted at a profit, it is called an 'ore'. The unwanted mineral in an ore is called gangue (i.e., generally rock forming minerals). For ex...
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2014
A preliminary characterisation of the iron ore assets of Atlantica Geologia e Mineração SA (AGEMISA) Campo Grande Project was performed on a sample composed from drill cores, to evaluate possible products and processing requirements. Magnetite largely predominates over hematite, and major gange minerals are quartz, amphibole and feldspar. Liberation spectra starting at 1⁄4” indicate there is no liberation above 1 mm, therefore no lump ore can be expected. For the sinter feed fraction (850x150 μm) an overall magnetite+hematite recovery close to 90% can be attained for a similar grade of the minerals, corresponding to 61% of Fe. The liberation is excellent for the pellet feed size range, granting recoveries better than 99% for 96% iron oxides, or a 66% Fe grade. The results are comparable to heavy liquid concentrates.
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Geometallurgy, 2018
Increasing competition in the minerais industry and fluctuating coramodity prices require new ways of saving energy, lime, and general operational costs. A good understanding of physical processing or pre-processing streams that can potentially cut these costs requires detailed analyses of chemical and physical behaviours and processing responses during rainera]. processing. It is very useful to perform a detailed mineralogical and micro-textural characterization of materials (ore, tailings, and waste) that addresses, among other parameters, particle and grain sizes, as well as particle densifies. The choice and/or corabination of the 'best' processing approaches is crucial for processing efficiencies, and can be established and verified by using automated mineralogy with the associated software. A sample of low-grade iron ore from El Volcan, Mexico, serves as an example to demonstrate in a step-by-step approach how QEMSCAN® analyses provide processing information. Elements under consideration include iron, phosphorus, and sulphur.
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Computers and Geosciences, 2018
We present a new ArcGIS ®-based tool developed in the Python programming language for calibrating EDS/WDS X-ray element maps, with the aim of acquiring quantitative information of petrological interest. The calibration procedure is based on a multiple linear regression technique that takes into account interdependence among elements and is constrained by the stoichiometry of minerals. The procedure requires an appropriate number of spot analyses for use as internal standards and provides several test indexes for a rapid check of calibration accuracy. The code is based on an earlier image-processing tool designed primarily for classifying minerals in X-ray element maps; the original Python code has now been enhanced to yield calibrated maps of mineral end-members or the chemical parameters of each classified mineral. The semi-automated procedure can be used to extract a dataset that is automatically stored within queryable tables. As a case study, the software was applied to an amphibolite-facies garnet-bearing micaschist. The calibrated images obtained for both anhydrous (i.e., garnet and plagioclase) and hydrous (i.e., biotite) phases show a good fit with corresponding electron microprobe analyses. This new GIS-based tool package can thus find useful application in petrology and materials science research. Moreover, the huge quantity of data extracted opens new opportunities for the development of a thin-section microchemical database that, using a GIS platform, can be linked with other major global geoscience databases.
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