Development of a geometallurgical framework to quantify mineral textures for process prediction

Lund, Cecilia; Lamberg, Pertti; Lindberg, Therése

doi:10.1016/j.mineng.2015.04.004

Cited by 42 publications

(21 citation statements)

References 15 publications

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“…Geometallurgical approaches are increasingly applied to a wide range of different deposit types. Key geometallurgy publications highlighting the importance of ore textures for mineral processing include [178][179][180].…”

Section: New Sub-disciplinesmentioning

confidence: 99%

Advances and Opportunities in Ore Mineralogy

et al. 2017

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Abstract:The study of ore minerals is rapidly transforming due to an explosion of new microand nano-analytical technologies. These advanced microbeam techniques can expose the physical and chemical character of ore minerals at ever-better spatial resolution and analytical precision. The insights that can be obtained from ten of today's most important, or emerging, techniques and methodologies are reviewed: laser-ablation inductively-coupled plasma mass spectrometry; focussed ion beam-scanning electron microscopy; high-angle annular dark field scanning transmission electron microscopy; electron back-scatter diffraction; synchrotron X-ray fluorescence mapping; automated mineral analysis (Quantitative Evaluation of Mineralogy via Scanning Electron Microscopy and Mineral Liberation Analysis); nanoscale secondary ion mass spectrometry; atom probe tomography; radioisotope geochronology using ore minerals; and, non-traditional stable isotopes. Many of these technical advances cut across conceptual boundaries between mineralogy and geochemistry and require an in-depth knowledge of the material that is being analysed. These technological advances are accompanied by changing approaches to ore mineralogy: the increased focus on trace element distributions; the challenges offered by nanoscale characterisation; and the recognition of the critical petrogenetic information in gangue minerals, and, thus the need to for a holistic approach to the characterization of mineral assemblages. Using original examples, with an emphasis on iron oxide-copper-gold deposits, we show how increased analytical capabilities, particularly imaging and chemical mapping at the nanoscale, offer the potential to resolve outstanding questions in ore mineralogy. Broad regional or deposit-scale genetic models can be validated or refuted by careful analysis at the smallest scales of observation. As the volume of information at different scales of observation expands, the level of complexity that is revealed will increase, in turn generating additional research questions. Topics that are likely to be a focus of breakthrough research over the coming decades include, understanding atomic-scale distributions of metals and the role of nanoparticles, as well how minerals adapt, at the lattice-scale, to changing physicochemical conditions. Most importantly, the complementary use of advanced microbeam techniques allows for information of different types and levels of quantification on the same materials to be correlated.

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Section: New Sub-disciplinesmentioning

confidence: 99%

Advances and Opportunities in Ore Mineralogy

et al. 2017

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“…This geometallurgical block model was built based on the Malmberget iron deposit in northern Sweden using simulation modules for geology, sampling, production and mining economics. The complete methodology used to build this geometallurgical block can be found in (Lishchuk 2016;Lund et al 2015).…”

Section: Simulated Geometallurgical Block Model Examplementioning

confidence: 99%

Fuzzy Clustering with Spatial Correction and Its Application to Geometallurgical Domaining

Sepúlveda

Dowd

2018

Math Geosci

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Self-archiving for articles in subscription-based journals Springer journals' policy on preprint sharing. By signing the Copyright Transfer Statement you still retain substantial rights, such as self-archiving: Author(s) are permitted to self-archive a pre-print and an author's accepted manuscript version of their Article. ………. b. An Author's Accepted Manuscript (AAM) is the version accepted for publication in a journal following peer review but prior to copyediting and typesetting that can be made available under the following conditions: (i) Author(s) retain the right to make an AAM of their Article available on their own personal, selfmaintained website immediately on acceptance, (ii) Author(s) retain the right to make an AAM of their Article available for public release on any of the following 12 months after first publication ("Embargo Period"): their employer's internal website; their institutional and/or funder repositories. AAMs may also be deposited in such repositories immediately on acceptance, provided that they are not made publicly available until after the Embargo Period.

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“…Recognition of the importance of textural information for the prediction of downstream processing is steadily increasing among the industry and academics [3,13]. Fig.…”

Section: Importance Of Textural Classificationmentioning

confidence: 99%

Mineral 4/Recognition 4: A Universal Optical Image Analysis Package for Iron Ore, Sinter and Coke Characterization

Donskoi¹,

Poliakov²,

Vining³

et al. 2017

JEPE

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OIA (optical image analysis) has traditionally been used for reliable identification of different iron oxides and oxyhydroxides in iron ore. The automated CSIRO OIA system Mineral 4/Recognition 4 was created for rapid mineral and textural characterisation of iron ore providing identification of different minerals and different morphologies. The technique has further been applied to processed iron ore products such as iron ore sinter to determine key parameters such as porosity, different morphologies of hematite (primary and secondary), and different morphologies of SFCA (silicon ferrite of calcium and aluminium). Application of textural identification has recently been extended to coke characterisation where the software gives comprehensive characterisation of porosity, IMDC (inert material derived components), RMDC (reactive material derived components) and the boundaries between IMDC and RMDC. The software also has many unique features needed for iron ore research including characterisation of large objects like pellets and ore lumps; automated gangue (including quartz) identification; automated particle separation; multiple image set processing and on-line measurements. All these features make the Mineral 4/Recognition 4 OIA system a unique, reliable, industry/research focused tool for ore, sinter, pellet and coke characterisation.

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Development of a geometallurgical framework to quantify mineral textures for process prediction

Cited by 42 publications

References 15 publications

Advances and Opportunities in Ore Mineralogy

Advances and Opportunities in Ore Mineralogy

Fuzzy Clustering with Spatial Correction and Its Application to Geometallurgical Domaining

Mineral 4/Recognition 4: A Universal Optical Image Analysis Package for Iron Ore, Sinter and Coke Characterization

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