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Die vorliegende Arbeit beschreibt die Ergebnisse der Synthese und Charakterisierung der Hochdruckphase von Aluminiumnitrid mit Kochsalzstruktur (rs-AlN). Die Versuche wurden mittels Schockwellensynthese unter Verwendung der „flyer-plate-Methode“ mit anschließender Probenrückgewinnung durchgeführt. Für verschiedene Aluminiumnitridpulver mit einer Ausgangsporosität k = rho_solid/rho_porous von 1,5 bis 2,5 wurde bei einem Druck von 15 bis 43 GPa die Phasenumwandlung von der Wurtzitstruktur (w-AlN) in die Kochsalzstruktur (rs-AlN) bewirkt. Es ist damit erstmals gelungen, rs-AlN mit dynamischen HP-HT-Methoden herzustellen und damit Probenmengen im Milligramm- bis Grammbereich zu erhalten. Dadurch ist es möglich Untersuchungen durchzuführen, die zur weiteren Erforschung und Charakterisierung des Materials beitragen sollen. Im Fokus liegen dabei insbesondere die Untersuchung der mechanischen, thermischen und chemischen Stabilität, um die Eignung des Materials zur Herstellung ultraharter Komposite zu evaluieren. Die geschockten Pulver bestehen aus einem Phasengemisch aus dem Ausgangsmaterial (w-AlN), der Hochdruckphase (rs-AlN), Aluminiumoxid und -oxynitriden, sowie amorphen Aluminiumhydroxiden. Die höchste Ausbeute an rs-AlN (~41 Ma% bei 2 mm Probenhöhe) kann bei Drücken von 24 GPa und einer Ausgangsporosität k von 2,1 erhalten werden. Anhand dem Auftreten verschiedener Al-O-N Phasen kann die Schocktemperatur für die einzelnen Versuche abgeschätzt werden (<1700 °C bis <2000 °C). Die Phasenumwandlung wird durch die Temperaturerhöhung aufgrund der Schockkompaktion der Pulver aktiviert. Als entgegenwirkender Prozess wurde die thermisch aktivierte Rückwandlung in die Niederdruckphase w-AlN aufgrund einer zu hohen Post-Schocktemperatur und einem zu langsamen Abkühlen der Probe postuliert. Daraus ergibt sich eine optimale Temperatur für den Versuchsaufbau von 1700 bis 1900 °C, bei der die höchsten rs-AlN Anteile beobachtet wurden. Eine Verringerung der Probenhöhe erhöht den Einfluss von Mehrfachreflektionen in der Probe und trägt damit zur Verbesserung der Umsetzung bei. Für drei Nanopulver (Kristallitgröße <25 nm) wurde die teilweise Umwandlung in die Kochsalzstruktur beobachtet, wohingegen für ein gröberes Nanopulver und ein Submikropulver (Kristallitgröße >45 nm) kein rs-AlN in den geschockten Proben nachgewiesen werden konnte. Es wird ein Stabilisierungsmechanismus der Kochsalzstruktur durch Kristallitgrößeneffekte vorhergesagt. Die Verringerung der Kristallitgröße führt zur Herabsetzung des Umwandlungsdrucks w-AlN -> rs-AlN. Es lässt sich daher schlussfolgern, dass für kleinere Partikel die Hochdruckmodifikation aufgrund der geringeren Entfernung vom chemischen Gleichgewicht bei Normalbedingungen stabilisiert werden kann, wohingegen für größere Kristallite die Rückwandlung in die Ausgangsphase geschieht. Weitere Stabilisierungsmechanismen wurden diskutiert. Mithilfe einer Rietveld-Verfeinerung der Röntgendiffraktogramme wurde die Gitterkonstante des rs-AlN mit a = 4,044 ± 0,001 Å und die Kristallitgröße mit 15,3 ± 0,2nm bestimmt. Die mittels hoch-aufgelöster Transmissionselektronenmikroskopie (TEM) bestimmte Kristallitgröße (10 bis 20 nm) ist in guter Übereinstimmung mit den Ergebnissen der Rietveld-Verfeinerung. Mit 27Al Kernspinresonanzspektroskopie (NMR) wurde die oktaedrische Al–N-Umgebung (AlN6) mit einer korrigierten chemischen Verschiebung von 2 ppm nachgewiesen. Anhand der IR-Spektren wird eine Al–N-Schwingungsbande des rs-AlN bei ca. 490 cm−1 vermutet. Dynamisch-thermische Untersuchungen zeigen, dass nanokristallines rs-AlN bei 600 °C beginnt zu Aluminiumoxid zu oxidieren und damit keine größere Beständigkeit im Vergleich zum w-AlN zeigt. Die thermisch aktivierte Rückwandlung des rs-AlN in die Niederdruckphase wurde ab 1200 °C (in Argon) bzw. 1100 °C (im Vakuum) bei einer Heizrate von 10 K/min beobachtet. Eine gute chemische Beständigkeit des Aluminiumnitrid mit Kochsalzstruktur gegenüber Wasser, Natronlauge und Säuren (HCl, H2SO4, H3PO4, HNO3 und Königswasser) wurde in Langzeit-Löslichkeitsversuchen nachgewiesen. / In the present work the results of the synthesis and characterisation of the high-pressure phase of aluminium nitride with rocksalt structure (rs-AlN) are presented. The experiments were carried out with the flyer-plate-method with subsequently sample recovery. For different aluminium nitride powders with starting porosities k = rho_solid/rho_porous of 1.5 to 2.5 the phase transition from wurtzite structure (w-AlN) to the rocksalt structure (rs-AlN) was induced at a pressure of 15 to 43 GPa. This is to our knowledge the first succesful synthesis of rs-AlN with dynamic HP-HT methods. With this advance, samples in the milligram or gram range can be produced. Therefore further investigations to characterise the material are possible, especially the study of the mechanical, thermal and chemical stability to validate the potential for the production of ultrahard composites. The shocked samples consist of a phase mixture from the starting material (w-AlN), the high-pressure phase (rs-AlN), aluminium oxide and oxynitrides, as well as amorphous aluminium hydroxides. The highest yield of rs-AlN (~41 wt% at 2 mm sample height) can be obtained at a pressure of 24 GPa and a starting porosity k of 2.1. The shock temperature can be estimated by the formation of different Al-O-N phases (<1700 °C to <2000 °C). The phase transition is activated by the raise of temperature due to shock compression. A thermal activated reconversion to the low-pressure phase w-AlN caused by a high post-shock temperature and a slow cooling of the sample is postulated as a contrary process. This results in an optimum temperature of 1700 to 1900 °C for this set-up. A decrease of the sample height increases the influence of multiple reflections and therefore causes a better transformation. A partial conversion to rs-AlN was observed for three nanopowders (crystallite size <25 nm), whereas for a more coarse nanopowder and an submicronpowder (crystallite size >45 nm) no rs-AlN could be found in the shocked samples. A stabilisation mechanism of the rocksalt phase by crystallite size effects is predicted. The reduction of the crystallite size causes a decrease of the transition pressure for w-AlN -> rs-AlN. It can be concluded, that for smaller particles the high-pressure phase can be stabilised at ambient conditions on the basis of the smaller distance from equilibrium, whereas for larger particles the reconversion to the low-pressure phase occurs. By a Rietveld refinement of the X-ray diffractograms, the lattice constant of rs-AlN and the crystallite size was determined to be a = 4.044 ± 0.001 Å respectively 15.3 ± 0.2 nm. The crystallite size of rs-AlN (10 to 20 nm) determined with high-resolution transmission electron microscopy (TEM) is in good agreement with the results of the Rietveld refinement. The octahedral Al–Npolyhedral (AlN6) was demonstrated by 27Al nuclear magnetic resonance spectroscopy (NMR) with a corrected chemical shift of 2 ppm. Based on infrared spectroscopy (FTIR) an AlN vibration band at about 490 cm−1 is assumed. Dynamic thermal analysis show, that the rs-AlN starts to oxidise to alumina at 600 °C and thus have no greater resistance in comparison with w-AlN. The thermal activated reconversion of rs-AlN to the low-pressure phase starts at 1200 °C (in argon) respectively 1100 °C (under vacuum) at a heating rate of 10 K/min. The aluminium nitride with rocksalt structure shows a good chemical resistance against water, caustic soda and acids (HCl, H2SO4, H3PO4, HNO3 and aqua regia).

Die vorliegende Arbeit beschreibt die Ergebnisse der Synthese und Charakterisierung der Hochdruckphase von Aluminiumnitrid mit Kochsalzstruktur (rs-AlN). Die Versuche wurden mittels Schockwellensynthese unter Verwendung der „flyer-plate-Methode“ mit anschließender Probenrückgewinnung durchgeführt. Für verschiedene Aluminiumnitridpulver mit einer Ausgangsporosität k = rho_solid/rho_porous von 1,5 bis 2,5 wurde bei einem Druck von 15 bis 43 GPa die Phasenumwandlung von der Wurtzitstruktur (w-AlN) in die Kochsalzstruktur (rs-AlN) bewirkt. Es ist damit erstmals gelungen, rs-AlN mit dynamischen HP-HT-Methoden herzustellen und damit Probenmengen im Milligramm- bis Grammbereich zu erhalten. Dadurch ist es möglich Untersuchungen durchzuführen, die zur weiteren Erforschung und Charakterisierung des Materials beitragen sollen. Im Fokus liegen dabei insbesondere die Untersuchung der mechanischen, thermischen und chemischen Stabilität, um die Eignung des Materials zur Herstellung ultraharter Komposite zu evaluieren. Die geschockten Pulver bestehen aus einem Phasengemisch aus dem Ausgangsmaterial (w-AlN), der Hochdruckphase (rs-AlN), Aluminiumoxid und -oxynitriden, sowie amorphen Aluminiumhydroxiden. Die höchste Ausbeute an rs-AlN (~41 Ma% bei 2 mm Probenhöhe) kann bei Drücken von 24 GPa und einer Ausgangsporosität k von 2,1 erhalten werden. Anhand dem Auftreten verschiedener Al-O-N Phasen kann die Schocktemperatur für die einzelnen Versuche abgeschätzt werden (<1700 °C bis <2000 °C). Die Phasenumwandlung wird durch die Temperaturerhöhung aufgrund der Schockkompaktion der Pulver aktiviert. Als entgegenwirkender Prozess wurde die thermisch aktivierte Rückwandlung in die Niederdruckphase w-AlN aufgrund einer zu hohen Post-Schocktemperatur und einem zu langsamen Abkühlen der Probe postuliert. Daraus ergibt sich eine optimale Temperatur für den Versuchsaufbau von 1700 bis 1900 °C, bei der die höchsten rs-AlN Anteile beobachtet wurden. Eine Verringerung der Probenhöhe erhöht den Einfluss von Mehrfachreflektionen in der Probe und trägt damit zur Verbesserung der Umsetzung bei. Für drei Nanopulver (Kristallitgröße <25 nm) wurde die teilweise Umwandlung in die Kochsalzstruktur beobachtet, wohingegen für ein gröberes Nanopulver und ein Submikropulver (Kristallitgröße >45 nm) kein rs-AlN in den geschockten Proben nachgewiesen werden konnte. Es wird ein Stabilisierungsmechanismus der Kochsalzstruktur durch Kristallitgrößeneffekte vorhergesagt. Die Verringerung der Kristallitgröße führt zur Herabsetzung des Umwandlungsdrucks w-AlN -> rs-AlN. Es lässt sich daher schlussfolgern, dass für kleinere Partikel die Hochdruckmodifikation aufgrund der geringeren Entfernung vom chemischen Gleichgewicht bei Normalbedingungen stabilisiert werden kann, wohingegen für größere Kristallite die Rückwandlung in die Ausgangsphase geschieht. Weitere Stabilisierungsmechanismen wurden diskutiert. Mithilfe einer Rietveld-Verfeinerung der Röntgendiffraktogramme wurde die Gitterkonstante des rs-AlN mit a = 4,044 ± 0,001 Å und die Kristallitgröße mit 15,3 ± 0,2nm bestimmt. Die mittels hoch-aufgelöster Transmissionselektronenmikroskopie (TEM) bestimmte Kristallitgröße (10 bis 20 nm) ist in guter Übereinstimmung mit den Ergebnissen der Rietveld-Verfeinerung. Mit 27Al Kernspinresonanzspektroskopie (NMR) wurde die oktaedrische Al–N-Umgebung (AlN6) mit einer korrigierten chemischen Verschiebung von 2 ppm nachgewiesen. Anhand der IR-Spektren wird eine Al–N-Schwingungsbande des rs-AlN bei ca. 490 cm−1 vermutet. Dynamisch-thermische Untersuchungen zeigen, dass nanokristallines rs-AlN bei 600 °C beginnt zu Aluminiumoxid zu oxidieren und damit keine größere Beständigkeit im Vergleich zum w-AlN zeigt. Die thermisch aktivierte Rückwandlung des rs-AlN in die Niederdruckphase wurde ab 1200 °C (in Argon) bzw. 1100 °C (im Vakuum) bei einer Heizrate von 10 K/min beobachtet. Eine gute chemische Beständigkeit des Aluminiumnitrid mit Kochsalzstruktur gegenüber Wasser, Natronlauge und Säuren (HCl, H2SO4, H3PO4, HNO3 und Königswasser) wurde in Langzeit-Löslichkeitsversuchen nachgewiesen.:1. Einleitung 2. Grundlagen 3. Methoden und experimentelle Details 4. Ergebnisse 5. Diskussion 6. Schlussfolgerungen und Ausblick / In the present work the results of the synthesis and characterisation of the high-pressure phase of aluminium nitride with rocksalt structure (rs-AlN) are presented. The experiments were carried out with the flyer-plate-method with subsequently sample recovery. For different aluminium nitride powders with starting porosities k = rho_solid/rho_porous of 1.5 to 2.5 the phase transition from wurtzite structure (w-AlN) to the rocksalt structure (rs-AlN) was induced at a pressure of 15 to 43 GPa. This is to our knowledge the first succesful synthesis of rs-AlN with dynamic HP-HT methods. With this advance, samples in the milligram or gram range can be produced. Therefore further investigations to characterise the material are possible, especially the study of the mechanical, thermal and chemical stability to validate the potential for the production of ultrahard composites. The shocked samples consist of a phase mixture from the starting material (w-AlN), the high-pressure phase (rs-AlN), aluminium oxide and oxynitrides, as well as amorphous aluminium hydroxides. The highest yield of rs-AlN (~41 wt% at 2 mm sample height) can be obtained at a pressure of 24 GPa and a starting porosity k of 2.1. The shock temperature can be estimated by the formation of different Al-O-N phases (<1700 °C to <2000 °C). The phase transition is activated by the raise of temperature due to shock compression. A thermal activated reconversion to the low-pressure phase w-AlN caused by a high post-shock temperature and a slow cooling of the sample is postulated as a contrary process. This results in an optimum temperature of 1700 to 1900 °C for this set-up. A decrease of the sample height increases the influence of multiple reflections and therefore causes a better transformation. A partial conversion to rs-AlN was observed for three nanopowders (crystallite size <25 nm), whereas for a more coarse nanopowder and an submicronpowder (crystallite size >45 nm) no rs-AlN could be found in the shocked samples. A stabilisation mechanism of the rocksalt phase by crystallite size effects is predicted. The reduction of the crystallite size causes a decrease of the transition pressure for w-AlN -> rs-AlN. It can be concluded, that for smaller particles the high-pressure phase can be stabilised at ambient conditions on the basis of the smaller distance from equilibrium, whereas for larger particles the reconversion to the low-pressure phase occurs. By a Rietveld refinement of the X-ray diffractograms, the lattice constant of rs-AlN and the crystallite size was determined to be a = 4.044 ± 0.001 Å respectively 15.3 ± 0.2 nm. The crystallite size of rs-AlN (10 to 20 nm) determined with high-resolution transmission electron microscopy (TEM) is in good agreement with the results of the Rietveld refinement. The octahedral Al–Npolyhedral (AlN6) was demonstrated by 27Al nuclear magnetic resonance spectroscopy (NMR) with a corrected chemical shift of 2 ppm. Based on infrared spectroscopy (FTIR) an AlN vibration band at about 490 cm−1 is assumed. Dynamic thermal analysis show, that the rs-AlN starts to oxidise to alumina at 600 °C and thus have no greater resistance in comparison with w-AlN. The thermal activated reconversion of rs-AlN to the low-pressure phase starts at 1200 °C (in argon) respectively 1100 °C (under vacuum) at a heating rate of 10 K/min. The aluminium nitride with rocksalt structure shows a good chemical resistance against water, caustic soda and acids (HCl, H2SO4, H3PO4, HNO3 and aqua regia).:1. Einleitung 2. Grundlagen 3. Methoden und experimentelle Details 4. Ergebnisse 5. Diskussion 6. Schlussfolgerungen und Ausblick

This study investigates various glass objects from the 17th and 18th centuries in Thuringia to gain insight into their manufacturing techniques. The objects include glass beads from the Roten Schmelzzimmer and diverse glass objects from the Schwarzburg-Sondershausen collection. The analytical methods include optical microscopy, CT, SEM-EDX, LA-ICP-MS and Raman spectroscopy. The glass beads from the Roten Schmelzzimmer were identified as soda-lime- and high-lead-silicate glasses, which were made using highly pure sands and halophytic plant ashes as a fluxing agent. These recipes are characteristic from the Mediterranean region. The beads were coloured in 11 different colours with copper, cobalt, manganese, iron, and were possibly opacified with salt and tartrate. The analysed glass objects from the Schwarzburg collection were made using different recipes based on potash-lime-silicate glass with high amounts of potash and calcium, and calcinated-bone ashes as a white opacifier, characteristic of central Europe.

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 almost 130 years. The Per Geijer deposits reveal a high phosphorus content and vary from magnetite-dominated to hematite-dominated ores, respectively. The high phosphorus concentration of these ores results from highly elevated content of apatite as gangue mineral. Reliable, robust, and qualitative characterization of the mineralization is required as these ores inherit complex mineralogical and textural features. The precise mineralogical information obtained by optical microscopy, SEM-MLA and Raman improves the characterization of ore types and will benefit future processing strategies for this complex mineralization. The different approaches demonstrate advantages and disadvantages in classification, imaging, discrimination of iron oxides, and time consumption of measurement and processing. A comprehensive mineral-chemical dataset of magnetite, hematite and apatite obtained by electron microprobe analysis (EPMA) and LA-ICP-MS from representative drill core samples is presented. Magnetite, four different types of hematite and five types of apatite constitute the massive orebodies: Primary and pristine magnetite with moderate to high concentrations of Ti (∼61–2180 ppm), Ni (∼11–480 ppm), Co (∼5–300 ppm) and V (∼553–1831 ppm) indicate a magmatic origin for magnetite. The presence of fluorapatite and associated monazite inclusions and disseminated pyrite enclosed by magnetite with high Co:Ni ratios (> 10) in massive magnetite ores are consistent with a high temperature (∼ 800°C) genesis for the deposit. The different and abundant types of hematite, especially hematite type I, state subsequent hydrothermal events. Chromium, Ni, Co and V in both magnetite and hematite have low concentrations in terms of current product regulations and thus no effect on final products in the future. In terms of a possible future hematite product, titanium seems to be the most critical trace element due to very high concentrations in hematite types I and IV, of which type I is most abundant in zones dominated by hematite. Further interest on other products is generated due to the high variability of hematite and apatite in some of these ores. Information obtained from comminution test works in the laboratory scale can be utilized to characterize ore types and to predict the behavior of ore during comminution circuit in the industrial scale. Comminution tests with a laboratory rod and ball mill of 13 pre-defined ore types from the Per Geijer iron-oxide apatite deposits were conducted in this study. The highest P80 values were obtained by grinding in the rod mill for 10 minutes only (step A). Grinding steps B (25 min ball mill) and C (35 min ball mill) reveal very narrow P80 values. Ore types dominated by hematite have significantly higher P80 values after the primary grinding step (A), which indicates different hardness of the ore types. P80 values are generally lowest after the secondary grinding step C ranging between 26 µm (ore type M1a) and 80 µm (ore type H2a). Generally, Fe content increases in the finer particle size classes while CaO and P contents decrease. The influence of silica or phosphorus seems to be dependent on the dominant iron oxide. Magnetite-dominated ore types are more likely to be affected in their comminution behavior by the presence of the silicates. Contrary, hematite-dominant ore types are rather influenced by the presence of apatite. The difference in the degree of liberation of magnetite and hematite between ore types depends rather on size fractions than the amount of gangue in the ore. Davis tube data indicates that magnetite can be separated from gangue quite efficiently in the magnetite-dominated ore types. Contrary to magnetite ore, hematite-dominated ore types cannot be processed by DT. It is favored to use strong magnetic separation in order to achieve a desirable hematite concentrate. The magnetic material recovered by DT is most efficiently separated at an intensity current of 0.2 A, whereas above 0.5 A the separation process is neglectable. Based on comminution and magnetic separation tests a consolidation to eight ore types is favored which supports possible future mining of the Per Geijer deposits.:Contents ABSTRACT ……………………………………………………………………… I CONTENTS ……………………………………………………………………… II LIST OF FIGURES AND TABLES ……………………………………………… IV LIST OF ABBREVIATIONS ……………………………………………… V 1 INTRODUCTION ……………………………………………………… 1 1.1 Background and motivation of study ……………………………… 2 1.2 Previous and current work on the Per Geijer deposits ……………… 3 1.3 The need for mineral processing and in-situ ore description ……………… 4 1.4 General and generic aspects on iron oxide apatite deposits ……………… 5 Chapter A 2 REGIONAL GEOLOGY ………………………………………………. 7 2.1 Local geology of the Kiruna area ……………………………………… 7 2.2 Geology of the Per Geijer deposits ……………………………………… 9 3 METHODOLOGY ……………………………………………………… 12 3.1 Core sampling and preparation ……………………………………… 12 3.2 SEM – MLA in-situ ore ……………………………………………… 14 3.3 Electron Probe Microanalyses (EPMA) ……………………………… 15 3.3.1 Iron oxide measurements ……………………………………… 15 3.3.2 Apatite measurements ……………………………………… 15 3.4 In-situ LA-ICP-MS ……………………………………………………… 16 3.5 Whole-rock geochemistry ……………………………………………… 18 3.5.1 Exploration drill core assays ……………………………… 18 3.5.2 Chemical assays of rock chips ……………………………… 18 4 RESULTS ……………………………………………………………… 19 4.1 Pre-definition of ore types ………………………………...……………. 19 4.2 Mineralogy of in situ ore ……………………………………………… 21 4.2.1 Ore Type M1a ……………………………………………… 21 4.2.2 Ore Type M1b ……………………………………………… 22 4.2.3 Ore Type M2a ……………………………………………… 23 4.2.4 Ore Type M2b ……………………………………………… 25 4.2.5 Ore Type HM1b ……………………………………………… 26 4.2.6 Ore Type HM2a ……………………………………………… 27 4.2.7 Ore Type HM2b ……………………………………………… 28 4.2.8 Ore Type H1a ……………………………………………… 29 4.2.9 Ore Type H1b ……………………………………………… 30 4.2.10 Ore Type H2a ……………………………………………… 31 4.2.11 Ore Type H2b ……………………………………………… 32 4.2.12 Comparison of ore types ……………………………………… 33 4.3 Geochemistry of in situ ore types ……………………………… 36 4.3.1 Whole-rock chemical assays of drill cores ……………………… 36 4.3.2 Whole-rock geochemistry of rock chips ……………………… 39 4.4 Mineral chemistry of iron oxides ……………………………………… 42 4.4.1 Iron oxides and associated minerals ……………………………… 42 4.4.2 Mineral chemistry of magnetite from Per Geijer ……………… 43 4.4.3 Mineral chemistry of hematite from Per Geijer ……………… 47 4.5 Mineral chemistry of apatite ……………………………………… 51 4.5.1 Apatite and associated minerals ……………………………… 51 4.5.2 Mineral chemistry of apatite from Per Geijer ……………… 53 Chapter B 5 COMMINUTION TESTS ……………………………………………… 58 5.1 Methodology of comminution tests ……………………………………… 59 5.1.1 Sampling for comminution tests ……………………………… 59 5.1.2 Comminution circuit ……………………………………………… 61 5.1.3 Energy consumption calculation ……………………………… 62 5.1.4 SEM – MLA ……………………………………………………… 64 6 MAGNETIC SEPARATION TESTS ……………………………… 65 6.1 Methodology of magnetic separation by Davis magnetic tube ……… 66 6.2 Davis magnetic tube tests for characterization of the Per Geijer ore types 66 6.3 Separation analysis based on the Henry-Reinhard charts .……………... 67 7 RESULTS OF COMMINUTION OF ORE TYPES ……………………… 69 7.1 General characteristics of magnetite-dominated ore types ……………… 69 7.2 General characteristics of hematite-dominated ore types ……………… 72 7.3 General characteristics of magnetite/hematite-mixed ore types ……… 75 7.4 General characteristics of low-grade ore types ……………………… 77 7.5 Mineral liberation characteristics of magnetite-dominated ore types 79 7.6 Mineral liberation characteristics of hematite-dominated ore types 83 7.7 Mineral liberation characteristics of magnetite/hematite-mixed ore types 87 7.8 Mineral liberation characteristics of low-grade ore types ……………… 90 7.9 Total energy consumption of ore types from the Per Geijer deposits 94 8 RESULTS OF MAGNETIC SEPARATION OF ORE TYPES ……… 95 8.1 Magnetic separation of magnetite-dominated ore types ……………… 95 8.2 Magnetic separation of hematite-dominated ore types ……………… 96 8.3 Magnetic separation of magnetite/hematite-mixed ore types ……………… 97 8.4 Magnetic separation of low-grade ore types ……………………………… 98 8.5 Henry-Reinhard charts ……………………………………………… 99 9 DISCUSSION ……………………………………………………… 101 9.1 Mineralogy of the in-situ ore types from the Per Geijer deposits ……… 101 9.2 Geochemistry of the in-situ ore types from the Per Geijer deposits ……… 103 9.3 Mineral chemistry of iron oxides from the Per Geijer deposits ……… 105 9.4 Mineral chemistry of apatite from the Per Geijer deposits ……………… 114 9.5 Comminution of ore types from Per Geijer ……………………… 119 9.6 Magnetic separation of ore types from Per Geijer ……………………… 120 9.7 Issues with process mineralogy of in-situ and grinded ore types ……… 121 10 CONCLUSIONS ……………………………………………………… 128 11 IMPLICATIONS FOR FUTURE WORK ……………………………… 131 12 REFERENCES ……………………………………………………………… 134

Mining will remain indispensable for the foreseeable future. For millennia, our society has been exploring and exploiting mineral deposits. Consequently, most of the easily exploitable high-grade deposits, which were of primary interest given their obvious technical and economic advantages, have already been depleted. For the future, the mining sector will have to efficiently produce metals and minerals from low-grade orebodies with complex mineralogical and microstructural properties -- these are generally referred to as complex orebodies. The exploitation of such complex orebodies carries significant technical risks. However, these risks may be reduced by applying modelling tools that are reliable and robust. In a broad sense, modelling techniques are already applied to estimate the resources and reserves contained in a deposit, and to evaluate the potential recovery (i.e., behaviour in comminution and separation processes) of these materials. This thesis focusses on the modelling of recovery processes, more specifically mineral separation processes, suited to complex ores. Despite recent developments in the fields of process mineralogy and geometallurgy, current mineral separation modelling methods do not fully incorporate the available information on ore complexity. While it is well known that the mineralogical and microstructural properties of individual particles control their process behaviour, currently widely applied modelling methods consider only distributions of bulk particle properties, which oftentimes require much simplification of the particle data available. Moreover, many of the methods used in industrial plant design and process modelling are based on the chemical composition of the samples, which is only a proxy for the mineralogical composition of the ores. A modelling method for mineral separation processes suited to complex ores should be particle-based, taking into consideration all quantifiable particle properties, and capable of estimating uncertainties. Moreover, to achieve a method generalizable to diverse mineral separation units (e.g., magnetic separation or flotation) with minimal human bias, strategies to independently weight the importance of different particle properties for the process(es) under investigation should be incorporated. This dissertation introduces a novel particle-based separation modelling method which fulfills these requirements. The core of the method consists of a least absolute shrinkage and selection operator-regularized (multinomial) logistic regression model trained with a balanced particle dataset. The required particle data are collected with scanning electron microscopy-based automated mineralogy systems. Ultimately, the method can quantify the recovery probability of individual particles, with minimal human input, considering the joint influence of particle shape, size, and modal and surface compositions, for any separation process. Three different case studies were modelled successfully using this new method, without the need for case-specific modifications: 1) the industrial recovery of pyrochlore from a carbonatite deposit with three froth flotation and one magnetic separation units, 2) the laboratory-scale magnetic separation of a complex skarn ore, and 3) the laboratory-scale separation of apatite from a sedimentary ore rich in carbonate minerals by flotation. Moreover, the generalization potential of the method was tested by predicting the process outcome of samples which had not been used in the model training phase, but came from the same geometallurgical domain of a specific ore deposit. In each of these cases, the method obtained high predictive accuracy. In addition to its predictive power, the new particle-based separation modelling method provides detailed insights into the influence of specific particle properties on processing behaviour. To name a couple, the influence of size on the recovery of different carbonate minerals by flotation in an industrial operation; and a comparison to traditional methodologies demonstrated the limitation of only considering particle liberation in process mineralogy studies -- the associated minerals should be evaluated, too. Finally, the potential application of the method to minimize the volume of test work required in metallurgical tests was showcased with a complex ore. The approach developed here provides a foundation for future developments, which can be used to optimize mineral separation processes based on particle properties. The opportunity exists to develop a similar approach to model the comminution of single particles and ultimately allow for the full prediction of the recovery potential of complex ores.:1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 State-of-the-art in particle-based separation models . . . . . . . . . . . 11 1.4 Moving forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.4.1 Particle data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.4.2 Mathematical tools required for the particle-based separation model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.4.3 Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.5 Structure of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2 The method and its application to industrial operations 23 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.2.1 Assumptions and limitations . . . . . . . . . . . . . . . . . . . . 26 2.2.2 Data structure and required pre-treatment . . . . . . . . . . . . 27 2.2.3 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.3.1 Artificial test cases . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.3.2 Real case study . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2.4 Discussion and final considerations . . . . . . . . . . . . . . . . . . . . 39 3 The robustness of the method towards compositional variations of new feed samples 45 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2 Generalization potential of current Particle-based Separation Model (PSM) methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.3 Case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3.1 Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3.2 Dry magnetic separation tests . . . . . . . . . . . . . . . . . . . 53 3.3.3 Sample characterization . . . . . . . . . . . . . . . . . . . . . . 53 3.3.4 Particle-based separation models . . . . . . . . . . . . . . . . . 54 3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4 Flotation kinetics of individual particles 67 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.2.1 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2.2 Cumulative recovery probability . . . . . . . . . . . . . . . . . . 72 4.2.3 Particle-based kinetic flotation model . . . . . . . . . . . . . . . 74 4.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 4.3.1 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . 75 4.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 4.4 Discussion and final thoughts . . . . . . . . . . . . . . . . . . . . . . . 80 5 Conclusions and outlook 85 5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 5.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Bibliography 89