TY - BOOK ID - 134361667 TI - Value of Mineralogical Monitoring for the Mining and Minerals Industry In memory of Prof. Dr. Herbert Pöllmann AU - Pöllmann, Herbert AU - König, Uwe PY - 2022 PB - Basel MDPI Books DB - UniCat KW - Technology: general issues KW - History of engineering & technology KW - Mining technology & engineering KW - barite KW - mineralogy KW - industrial application KW - beneficiation KW - specific gravity KW - bauxite overburden KW - Belterra Clay KW - mineralogical quantification KW - Rietveld analysis KW - machine learning KW - artificial intelligence KW - mining KW - mineralogical analysis KW - bauxite KW - available alumina KW - reactive silica KW - XRD KW - PLSR KW - lithium KW - quantification KW - clustering KW - Rietveld KW - cluster analysis KW - spodumene KW - petalite KW - lepidolite KW - triphylite KW - zinnwaldite KW - amblygonite KW - chalcopyrite KW - ore blending KW - copper flotation KW - nickel laterite KW - ore sorting KW - framboidal pyrite KW - sulfide minerals KW - flotation KW - process mineralogy KW - heavy minerals KW - ilmenite KW - titania slag KW - rietveld KW - Magneli phases KW - n/a UR - https://www.unicat.be/uniCat?func=search&query=sysid:134361667 AB - This Special Issue, focusing on the value of mineralogical monitoring for the mining and minerals industry, should include detailed investigations and characterizations of minerals and ores of the following fields for ore and process control: Lithium ores—determination of lithium contents by XRD methods; Copper ores and their different mineralogy; Nickel lateritic ores; Iron ores and sinter; Bauxite and bauxite overburden; Heavy mineral sands. The value of quantitative mineralogical analysis, mainly by XRD methods, combined with other techniques for the evaluation of typical metal ores and other important minerals, will be shown and demonstrated for different minerals. The different steps of mineral processing and metal contents bound to different minerals will be included. Additionally, some processing steps, mineral enrichments, and optimization of mineral determinations using XRD will be demonstrated. Statistical methods for the treatment of a large set of XRD patterns of ores and mineral concentrates, as well as their value for the characterization of mineral concentrates and ores, will be demonstrated. Determinations of metal concentrations in minerals by different methods will be included, as well as the direct prediction of process parameters from raw XRD data. ER -