THE RECOVERY of INDIUM from MINING WASTES by Evody Tshijik

THE RECOVERY OF INDIUM FROM MINING WASTES

by Evody Tshijik Karumb A thesis submitted to the faculty and the Board of Trustees of the Colorado School of Mines in the partial fulfilment of the requirements for the degree of Master of Science (Metallurgical and Materials Engineering).

Golden, Colorado

Date ______

Signed: ______Evody Tshijik Karumb

Signed: ______Dr. Patrick R. Taylor Thesis Advisor

Golden Colorado Date ______

Signed: ______Dr. Ivar Reimanis Professor and Department Head Department of Metallurgical and Materials Engineering

ABSTRACT

Scarcity and high demand has placed an economic pressure on the supply of indium worldwide; therefore, there is a global interest in increasing the recycling capacity for indium. This project’s main goal is the identification of secondary raw material resources for indium production; investigations were conducted on three zinc processing wastes namely a “tailings” sample which is a waste from flotation plant, a “jarosite” sample which is a waste from a hydrometallurgical plant, and a “ferrite” sample which is a waste from pyro-hydrometallurgical plant. Characterization work conducted showed that the tailings sample was mainly comprised of silicates minerals such as quartz, muscovite, and feldspar, that the jarosite sample was mainly comprised of natrojarosite and sulfate minerals, and that the ferrite sample was mainly comprised of franklinite. Results from the chemical analysis showed that the indium content in the tailings, jarosite, and ferrite samples was 18.3, 246, and 783 ppm, respectively. Investigation on the potential for indium beneficiation via physical separation methods was conducted on all three samples; this project looked at gravity, magnetic, and electrostatic separation.

It was concluded that physical separation did not achieved appreciable beneficiation. The indium head grade in the tailings sample was very low, and liberation of contained zinc minerals was also low; consequently this sample has a no economic incentive for processing. For the jarosite sample, it was concluded that a large portion of indium was contained in the lattice of natrojarosite; therefore, enrichment ratios were thought to be not high enough for commercial exploitation. It was determined that the sample should be leached as received. For the ferrite sample, it was concluded that physical separation would not work; however, it was determined that the sample could be screened at 297 um in to remove a portion of the coarser gangue minerals followed by leaching of the fines fraction. Indium was successfully extracted into solution via a sulfuric acid leach for both the jarosite (95% extraction) and the ferrite (90% extraction) samples. However, high acid consumption and high co-extraction of iron renders the process uneconomical. It is suggested for future work to employ a magnetizing roast process followed by a magnetic separation in order to separate out iron leaving a non-magnetic product possibly enriched in indium and perhaps more suitable for a low acid consuming leaching process, thus reducing the complexity of the purification step.

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TABLE OF CONTENTS

ABSTRACT…………...... iii LIST OF FIGURES…… ...... viii LIST OF TABLES…… ...... xii AKNOWLEDGMENT ...... xvi CHAPTER 1 INTRODUCTION ...... 1 1.1 Background ...... 1 1.2 Justification of Research ...... 1 CHAPTER 2 LITERATURE SURVEY ...... 3 2.1 Primary Production of Indium ...... 3 2.2 The Indium market, its Applications and Substitutability ...... 5 2.2.1 Applications ...... 5

2.2.2 Overview of Indium’s Market ...... 7

2.2.3 Substitutability ...... 9

2.4 Recycling of Indium ...... 10 2.4.1 Recovery of Indium from Various Plant Residues ...... 10

2.4.2 Leaching of Indium from Jarosite Residues ...... 12

2.4.3 Recovery of Indium from Indium –bearing Zinc Ferrite Residues ...... 15

CHAPTER 3 PROCESS DEVELOPMENT AND EXPERIMENTAL METHODS 19 3.1 Materials Characterization ...... 19 3.1.1 Particle Size Analysis ...... 19

3.1.1.1 Wet Sieve Size Analysis ...... 20 3.1.1.2 Microtrac Size Analysis ...... 21 3.1.2 X-Ray Diffraction (XRD) Spectroscopy ...... 23

3.1.3 Mineralogical Data ...... 24

3.1.3.1 Qualitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN®) ...... 24 3.1.3.2 Mineral Liberation Analyzer (MLA) ...... 25

3.2 Physical Separation ...... 26 3.2.1 Gravity Separation ...... 26

3.2.1.1 Float/Sink Gravity Separation...... 26 3.2.1.2 Falcon Gravity Separation ...... 28 3.2.2 Magnetic Separation ...... 29

3.2.3 Electrostatic Separation ...... 29

3.3 Leaching ...... 31 3.3.1 Proposed Reactions ...... 31

3.3.2 Thermodynamics ...... 31

3.3.3 Experimental Setup ...... 32

3.3.4 Parameters ...... 33

3.4 Analytical Chemical Analysis ...... 34 CHAPTER 4 MATERIALS CHARACTERIZATION AND CHEMICAL ANALYSIS ...... 36 4.1 Tailings Sample ...... 36 4.1.1 Particle Size Distribution ...... 36

4.1.2 X-Ray Diffraction Analysis ...... 37

4.1.3 Mineralogical Analysis ...... 38

4.1.3.1 QEMSCAN Mineralogy Data ...... 38 4.1.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) ...... 44 4.1.3.3 Comparison of QEMSCAN and MLA Data ...... 52 4.1.4 Chemical Analysis ...... 52

4.2 Jarosite Sample ...... 54 4.2.1 Particle Size Distribution ...... 54

4.2.2 X-Ray Diffraction Analysis ...... 55

4.2.3 Mineralogical Analysis ...... 56

4.2.3.1 QEMSCAN Mineralogy Data ...... 56

4.2.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) ...... 61 4.2.3.3 Comparison of QEMSCAN and MLA Data ...... 70 4.2.4 Chemical Analysis ...... 70

4.3 Ferrite Sample ...... 72 4.3.1 Particle Size Distribution ...... 72

4.3.2 X-Ray Diffraction Analysis ...... 73

4.3.3 Mineralogical Analysis ...... 74

4.3.3.1 QEMSCAN Mineralogy Data ...... 74 4.3.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) ...... 80 4.3.3.3 Comparison of QEMSCAN and MLA Data ...... 90 4.3.4 Chemical Analysis ...... 90

CHAPTER 5 RESULTS AND DISCUSSION ...... 93 5.1 Physical Separation ...... 93 5.1.1 Gravity Separation ...... 93

5.1.1.1 Float/Sink Gravity Separation...... 93 A Tailings Sample ...... 93 B Jarosite Sample ...... 94 C Ferrite Sample ...... 96 5.1.1.2 Falcon Gravity Separation ...... 97 A Tailings Sample ...... 97 B Jarosite Sample ...... 98 C Ferrite Sample ...... 100 5.1.2 Magnetic Separation ...... 102

5.1.2.1 Tailing Sample ...... 102 5.1.2.2 Jarosite Sample ...... 104 5.1.2.3 Ferrite Sample ...... 105 5.1.3 Electrostatic Separation ...... 106

5.1.3.1 Tailings Sample ...... 106 5.1.3.2 Ferrite Sample ...... 108

5.1.4. Conclusions on physical separation Experiments ...... 109

5.2 Leaching ...... 111 5.2.1 Jarosite Sample ...... 111

5.2.1.1 Effect of Temperature ...... 111 5.2.1.2 Effect of Initial Acid Concentration ...... 112 5.2.1.3 Effect of Pulp density...... 114 5.2.2 Ferrite Sample ...... 114

5.2.2.1 Effect of Temperature ...... 115 5.2.2.2 Effect of Initial Acid Concentration ...... 116 5.2.2.3 Effect of Pulp Density ...... 117 5.2.3 Leached Solutions from leaching of the Jarosite and Ferrite Samples ...... 118

5.2.4 Revisiting Magnetic Separation ...... 119

CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS ...... 121 6.1 Conclusions ...... 121 6.2 Recommendations and Future Work ...... 123 6.2.1 Recommendations ...... 123

6.2.2 Considerations for the Recovery of Indium from the Leach Solution ...... 123

REFERENCES………...... 127 APPENDIX A PHYSICAL PROPERTIES OF MINERALS IDENTIFIED BY XRD IN THE RECEIVED SAMPLES ...... 130 APPENDIX B PHYSICAL SEPARATION COMPLETEMENTAL DATA...... 132 APPENDIX C ELECTRICAL PROPERTIES OF MINERALS IDENTIFIED BY QEMSCAN ...... 137 APPENDIX D ACID CONSUMPTION FROM LEACHING OF THE JAROSITE ANS FERRITE SAMPLES ...... 140

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LIST OF FIGURES

Figure 2.1 A typical flowsheet from a zinc processing plant that include an indium recovery circuit; this is the flowsheet of the Kidd Creek zinc plant in Canada (Jorgenson et al. 2004) ...... 4

Figure 2.2 Critical material assessment by the European Commission (European Commission, 2014) ...... 4

Figure 2.3 Worldwide Use of virgin indium in 2011 (European Commission 2014) ...... 5

Figure 3.1 Typical wet sieve shaker used in wet sieve testing ...... 20

Figure 3.2 Illustration of a Microtrac S3500 unit with flow direction (Microtrac 2016) ...... 22

Figure 3.3 Schematic of a typical x-ray diffractometer (Poppe et al., 2001) ...... 24

Figure 3.4 Experimental setup for float/sink gravity separation ...... 28

Figure 3.5 Schematic of a typical high tension roll separator (Waal et al. 2005) ...... 30

Figure 3.6 Experimental setup for leaching experiments ...... 33

Figure 4.1 Particle size analysis of the tailings sample via microtrac size analysis ...... 36

Figure 4.2 Cumulative particle size distribution of the tailings sample via a wet sieve procedure...... 37

Figure 4.3 XRD generated pattern for the tailings sample ...... 38

Figure 4.4 Graphic illustration of the tailings sample results from QEMSCAN analysis ...... 39

Figure 4.5 Grain size distribution of zinc minerals in tailings ...... 42

Figure 4.6 Locking and liberation of minerals in tailings ...... 43

Figure 4.7 Mineral associations of zinc minerals in tailings ...... 44

Figure 4.8 Classified MLA image from the tail sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage...... 45

Figure 4.9 BSE image from the tail sample 200 X 400 mesh fraction ...... 45

Figure 4.10 Mineral grain size distributions for franklinite, smithsonite, and sphalerite ...... 50

Figure 4.11 Zinc mineral liberation in the tail sample ...... 50

Figure 4.12 Particle size distribution of the jarosite sample via Microtrac size analysis ...... 55

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Figure 4.13 XRD generated pattern for the jarosite sample ...... 56

Figure 4.14 Graphic Illustration of jarosite sample ...... 57

Figure 4.15 Grain size distribution of In-bearing minerals in jarosite ...... 60

Figure 4.16 Locking and liberation of minerals in jarosite ...... 60

Figure 4.17 Mineral associations of zinc minerals in jarosite ...... 61

Figure 4.18 Classified MLA image from the jarosite sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage...... 62

Figure 4.19 BSE image from the jarosite sample 200 X 400 mesh fraction ...... 62

Figure 4.20 BSE from the jarosite sample -400 mesh fraction ...... 63

Figure 4.21 Mineral grain size distributions for franklinite, gahnite, and sphalerite ...... 68

Figure 4.22 Liberation for the zinc minerals in the jarosite sample ...... 68

Figure 4.23 Cumulative particle size distribution of the ferrite sample via wet sieve ...... 73

Figure 4.24 XRD pattern for the ferrite sample ...... 74

Figure 4.25 Graphic illustration of the ferrite sample...... 75

Figure 4.26 Grain size distribution of zinc minerals in ferrite ...... 78

Figure 4.27 Locking and liberation of minerals in ferrite ...... 79

Figure 4.28 Mineral associations of zinc minerals in the ferrite sample ...... 79

Figure 4.29 Classified MLA image from the ferrite sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage...... 80

Figure 4.30 BSE image from the ferrite sample 200 X 400 mesh fraction ...... 81

Figure 4.31 Iron mineral grain size distribution ...... 86

Figure 4.32 Iron mineral liberation ...... 86

Figure 4.33 Zinc mineral grain size distributions ...... 87

Figure 4.34 Zinc mineral liberation ...... 87

Figure 4.35 Sphalerite coated by complex iron-zinc oxides containing silicates and lead sulfates ...... 89

Figure 4.36 Micron-sized silver-copper sulfide in quartz ...... 89

Figure 5.1 Grade vs recovery curve for indium in the sinks fraction of the tailings sample .. 94

Figure 5.2 Grade vs recovery curve for indium in the floats fraction of the jarosite sample . 95

Figure 5.3 Grade vs recovery curve for indium in the sinks fraction of the ferrite sample .... 96

Figure 5.4 Grade vs. recovery of indium in the heavies fraction of the tailings sample ...... 98

Figure 5.5 Grade vs. recovery of indium in the heavy minerals fraction of the jarosite sample ...... 99

Figure 5.6 Grade vs recovery of indium in the heavy minerals fraction of the ferrite sample. Data illustrated here are from the first set of experiments ...... 101

Figure 5.7 Grade vs recovery of indium in the heavy minerals fraction of the ferrite sample. Data illustrated here are from the second set of experiments ...... 102

Figure 5.8 Grade vs recovery of indium in the non-magnetic fraction of the tailings sample ...... 103

Figure 5.9 Grade vs recovery graph for indium in the magnetic fraction of the jarosite sample ...... 105

Figure 5.10 Grade vs recovery for indium in the non-magnetic fraction of the ferrite sample ...... 106

Figure 5.11 Grade vs recovery data for indium in the non-conductive fraction of the tailings sample ...... 108

Figure 5.12 Grade vs recovery data for indium in the conductive fraction of the ferrite sample ...... 109

Figure 5.13 Effect of temperature on indium extraction during jarosite sample leaching ..... 112

Figure 5.14 Effect of initial acid concentration on indium extraction during jarosite sample leaching ...... 113

Figure 5.15 Sample color evolution with increase in initial acid concentration ...... 113

Figure 5.16 Effect of pulp density on indium extraction during jarosite sample leaching ..... 114

Figure 5.17 Effect of temperature on indium extraction during ferrite sample leaching ...... 115

Figure 5.18 Effect of Initial acid concentration on indium extraction during ferrite sample leaching ...... 116

Figure 5.19 Effect of pulp density on indium extraction during ferrite sample leaching ...... 117

Figure 6.1 Process route 1 considered for the recovery of indium from the leach solution in reference to (Koleini et al., 2010) ...... 124

Figure 6.2 Process route 2 considered for the recovery of indium from the leach solution in reference to (Li et al., 2015) ...... 125

Figure D-1 Effect of temperature on acid consumption during jarosite sample leaching ..... 140

Figure D-2 Effect of Initial acid concentration on acid consumption during jarosite sample leaching ...... 140

Figure D-3 Effect of pulp density on acid consumption during jarosite sample leaching ..... 141

Figure D-4 Effect of temperature on acid consumption during ferrite sample leaching ...... 141

Figure D-5 Effect of Initial acid concentration on acid consumption during ferrite sample leaching ...... 142

Figure D-6 Effect of pulp density on acid consumption during ferrite sample leaching ...... 142

LIST OF TABLES

Table 2.1 Indium worldwide refinery production, tons, 2010 to 2012 (European Commission 2014) ...... 8

Table 2.2 Indium average annual prices 2008-2015 ...... 9

Table 2.3 Available substitutes for indium applications (European Commission 2014) ..... 10

Table 2.4 Chemical composition of the zinc ferrite residue ...... 16

Table 3.1 Size chart for the conversion from US to Tyler mesh series ...... 21

Table 3.2 Parameters for locking and liberation from QEMSCAN analysis ...... 25

Table 3.3 Parameters used for float/sink testing ...... 28

Table 3.4 Experimental parameters for Falcon gravity separation tests ...... 29

Table 3.5 Experimental Matrix layout for Falcon gravity experiments ...... 29

Table 3.6 Experimental matrix for electrostatic separation of the tailings and ferrite sample ...... 31

Table 3.7 Thermodynamic data for reaction 3.4 ...... 32

Table 3.8 Thermodynamic data for reaction 3.5 ...... 32

Table 3.9 Jarosite and ferrite samples leaching parameters ...... 34

Table 4.1 Minerals identified by XRD analysis in the tailings sample ...... 38

Table 4.2 Mineral abundance in the tailings sample...... 40

Table 4.3 Elemental abundance in the tailings sample ...... 41

Table 4.4 Mineral distribution of zinc in the tailings sample ...... 42

Table 4.5 Mineral content of the tails sample (wt. %) ...... 46

Table 4.6 Tail composition by mineral groupings (wt. %) ...... 48

Table 4.7 Tail MLA-calculated bulk elemental analysis (wt. %) ...... 49

Table 4.8 Zinc distribution by mineral for the tail sample (wt. %) ...... 50

Table 4.9 Selected mineral associations for the tail sample...... 51

Table 4.10 Chemical analysis of the tailings sample provided by the sponsor ...... 52

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Table 4.11 Chemical analysis of the tailings sample provided by CSM ...... 53

Table 4.12 Minerals identified by XRD for the jarosite sample ...... 55

Table 4.13 Mineral abundance in the jarosite sample ...... 57

Table 4.14 Elemental abundance in the jarosite sample ...... 58

Table 4.15 Mineral distribution of zinc in the jarosite sample ...... 59

Table 4.16 Mineral content of the jarosite sample (wt. %) ...... 64

Table 4.17 Jarosite composition by mineral groupings (wt. %) ...... 66

Table 4.18 Jarosite MLA-calculated bulk elemental analysis (wt. %) ...... 66

Table 4.19 Zinc distribution by mineral for the jarosite sample (wt. %) ...... 67

Table 4.20 Mineral associations for selected phases in the jarosite sample ...... 69

Table 4.21 Chemical analysis of the jarosite sample provided by the sponsor ...... 70

Table 4.22 Chemical analysis of the jarosite sample provided by CSM ...... 71

Table 4.23 Minerals identified by XRD for the ferrite sample ...... 73

Table 4.24 Minerals abundance in the ferrite sample ...... 76

Table 4.25 Elemental abundance in the ferrite sample……..…………………………….….77

Table 4.26 Mineral distribution of zinc in the ferrite sample ...... 77

Table 4.27 Mineral content of the ferrite sample (wt. %) ...... 82

Table 4.28 Ferrite composition by mineral groupings (wt. %) ...... 84

Table 4.29 Ferrite sample MLA-calculated bulk elemental analysis (wt. %) ...... 84

Table 4.30 Iron distribution by mineral for the ferrite sample (wt. %) ...... 85

Table 4.31 Zinc distribution by mineral for the ferrite sample (wt. %) ...... 85

Table 4.32 Selected mineral associations for the ferrite sample…………………..…………88

Table 4.33 Chemical analysis of the ferrite sample provided by the sponsor ...... 90

Table 4.34 Chemical analysis of the ferrite sample provided by CSM ...... 91

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Table 5.1 Weight distribution between the sinks and floats fractions of the tailings sample…………………………………………………………………….……..93 3

Table 5.2 Weight distribution between the sinks and floats fractions of the jarosite sample ...... 95

Table 5.3 Weight distribution between the sinks and float fractions of the ferrite sample ...... 96

Table 5.4 Weight distribution between the heavies ad lights fractions of the tailings sample ...... 97

Table 5.5 Weight distribution between the heavies and lights fractions of the jarosite sample ...... 99

Table 5.6 First set of weight distributions between the heavies and lights fractions of the ferrite sample ...... 100

Table 5.7 Second set of weight distribution between the heavies and lights fractions of the ferrite sample ...... 101

Table 5.8 Weight distribution between the magnetic and non-magnetic fractions of the tailings sample ...... 103

Table 5.9 Weight distribution between the magnetic and non-magnetic fractions of the jarosite sample ...... 104

Table 5.10 Weight distribution between the magnetic and non-magnetic fractions of the ferrite sample ...... 106

Table 5.11 Weight distribution between the conductive and non-conductive fractions of the tailings sample ...... 107

Table 5.12 Weight distribution between the conductive and non-conductive fractions of the ferrite sample ...... 109

Table 5.13 Summary of physical separation work on all received samples ...... 110

Table 5.14 Ferrite sample sieve fraction analysis ...... 114

Table 5.15 Summary of impurities in leachate at parameters yielding the highest indium recovery ...... 118

Table 5.16 Ferrite sample sieve fractions analysis ...... 119

Table 5.17 Summary of magnetic separation experiments ...... 119

Table A-1 Physical properties of minerals in the tailings sample ...... 130

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Table A-2 Physical properties of minerals in the jarosite sample ...... 130

Table A-3 Physical properties of minerals in the ferrite sample ...... 131

Table B-1 Summary table of float/sink gravity separation experimental results for the tailings sample ...... 132

Table B-2 Summary table of float/sink gravity separation experimental results on the jarosite sample...... 132

Table B-3 Summary table of float/sink gravity separation experimental results on the ferrite sample ...... 132

Table B-4 Summary table of Falcon gravity separation experimental results for the tailings sample ...... 133

Table B-5 Summary table of Falcon gravity separation experimental results for the jarosite sample ...... 133

Table B-6 Summary table of Falcon gravity separation experimental results for the ferrite sample (Set # 1) ...... 134

Table B-7 Summary table of Falcon gravity separation experimental results for the ferrite sample (Set # 2) ...... 134

Table B-8 Summary table of magnetic separation results for the tailings sample ...………135

Table B-9 Summary table of magnetic separation results for the tailings sample …...……135

Table B-10 Summary table of magnetic separation results for the tailings sample……....…135

Table B-11 Summary table of electrostatic separation results for the tailings sample…...…136

Table B-12 Summary table of magnetic separation results for the tailings sample……...…136

Table C-1 Electrical properties of mineral in the tailings sample ...... 137

Table C-2 Electrical properties of minerals in the ferrite sample ...... 138

AKNOWLEDGMENT

I would like to extend my humble gratitude to Dr. Patrick R. Taylor for being my advisor and mentor. He reminded me that failure is not when things don’t go the way you planned them, and has provided me sound critics of my work and guided me through it all while teaching me to figure things out on my own.

My special gratitude goes to the Center for Resource Recovery and Recycling (CR3) for funding this project, and my focus group members for their guidance and feedback.

I would like to thank other members of my committee professor D. Erik Spiller and Dr. Corby G. Anderson. I would not have completed this work so fashionably without their professional and academic support.

I would also like to thank KIEM colleagues for their support and collaboration while making time to listen to me when needed a second opinion on my ideas. I am forever grateful to my parents and family who supported from another continent as well on American land. Their support and encouragement were most precious to me.

I would like to dedicate this work to my late grandmother Vickcynthia Tshijik Karumb whose strength, boldness, determination, and courage have always been an inspiration to me.

Above all else, I am forever grateful to the almighty GOD in heaven for showing me the way and strengthening me when I needed it.

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CHAPTER 1 INTRODUCTION

Chapter 1 gives an overview of the project in terms of background information. It also provides a motif for making to decision to undertake this particular project.

1.1 Background

Indium is a rare silvery white metal that was discovered in 1863 by German chemists Ferdinand Reich and Hieronymus Theodor Richter while they were studying zinc ore samples. It is soft, malleable, and has a low melting point. It belongs to the group 13 of elements in the periodic table; these elements have unique chemical properties that has sparked interest worldwide. Indium’s abundance in the earth’s crust has been estimated at 0.05-0.24 ppm, and is such that it is disseminated across the crust making it difficult to produce it as primary product.

According to the United States Geological Survey (USGS) bureau, the geochemical properties of indium are such that it mostly occurs with base metals such as copper, tin, lead, and zinc. It occurs with bismuth, cadmium, and silver. For economic reasons, indium is mainly produced as a by-product from the processing of zinc concentrates.

Because of its physico-chemical properties, indium is primarily used in the electronic industry as indium tin oxide (ITO) which is used in the manufacturing of liquid crystal displays (LCDs), flat panel displays (FPDs), solar panels, etc. Indium is also used in soldering, low- temperature alloys, semiconductors, phosphors, nuclear, and medical purposes. It is worth noting here that the indium’s market is closely related to that of the electronic products aforementioned. Consequently, during the expansion of FPDs market in the 90s, the demand for indium metal increased as well; nonetheless, the supply did grow as much as the demand. Following this sequence of events, it became important to recycle indium from various materials where it was used, especially ITO in LCDs.

1.2 Justification of Research

The growth of the market for indium is dependent on the market for the manufacturing of electronic goods such as LCDs, FDPs, LEDs, and solar panels which use ITO. Demand for these goods has been projected to increase due to the increase in demands for goods such as smart phones and gadgets; consequently the demand for indium is also projected to increase in the near

1 future. Unfortunately, the supply side has not kept up with the increase in demand; therefore efforts have been done by countries such as japan and South Korea to increase recycling of indium.

Despite the existing recycling of indium from ITO in FPDs, the supply of indium is still under pressure. Also, when it is substituted for by other metals, there is often a loss in product performance and quality, therefore the need to consider recycling from others sources such as flue dusts, hydrometallurgical wastes, and other metallurgical wastes from processing of metal such as tin, zinc, and copper. The issue encountered so far with recycling from solid wastes is the low content of indium and the presence of many contaminants which drive processing costs high.

The aim of this project is first to identify a secondary raw material for the recovery of indium. The next goal is the investigation of physical and chemical processes to extract indium from such wastes while meeting environmental guidelines and conditions, and in an economic fashion

CHAPTER 2 LITERATURE SURVEY

In order to tailor and shape the scope of this project, the research team conducted a search in the literature to understand how indium is produced, used, and recycled. Section 2.1 will focus on the primary production of indium which is mostly as a by-product of zinc processing. Section 2.2 will highlights the applications of indium as a metal, compound, or in alloys as well as some effort done on its substitution in the electronic industry. Section 2.3 will give an overview of indium’s market, and section 2.4 will focus on the recycling of indium from FPDs, and various wastes streams relative to the materials that were received for this study.

2.1 Primary Production of Indium

Indium’s geochemical properties are such that it associates itself with metals which have a comparable atomic radius in their respective minerals. Consequently a lot of occurrence of indium is reported in ore deposits of tin, copper, zinc, and lead-zinc. It has also been reported that the amount of indium in a deposit is directly related to the amount of copper present in the deposit (Schwartz-Schampera and Herzig 2002).

One common example of indium primary production is the case of the Kidd Creek roasting and refining plant in Canada for which the flow sheet is shown in figure 2.1 below (Jorgenson et al. 2004). In this operation, indium content was estimated to be 270 ppm, and iron is removed via the jarosite precipitation process in the first stage of leaching. Zinc oxide (Cottrell dust) from a copper smelter is added to the second stage leaching for the precipitation of a silver lead residue which is a salable intermediate product. The indium rich solution is then passed through a solvent extraction stage for the production of indium metal.

Also reported is the production of indium from tin concentrates. The process aims at treating a concentrate assaying 100 ppm indium to produce an In-Pb-Sn alloy assaying 0.1-0.2 %. For this purpose, a specialized vacuum refining process is used. Later on the alloy is to be melted for the recovery of electrolytic indium metal. It is reported that the special apparatus is capable of treating tailings with an indium content of 1000 ppm and higher (Jorgensonet al. 2004). According to the USGS, the highest known concentration of indium are found in vein stockwork deposits of tin and tungsten, but the recovery of indium from such deposit it not economical (USGS 2013).

Figure 2.1 A typical flowsheet from a zinc processing plant that include an indium recovery circuit; this is the flowsheet of the Kidd Creek zinc plant in Canada (Jorgenson et al. 2004)

Figure 2.2 Critical material assessment by the European Commission (European Commission 2014)

In 2013 the European Commission updated the list of critical materials which were defined according to two criteria namely the economic importance and the supply risk (European Commission 2014); according to figure 2.2 above, indium is a rare and near critical metal. In its 2014 report on critical raw materials, the European commission stated that indium reserves amounted to 50,000 tons at existing zinc and copper mines, and that tailings and residues had an additional 15,000 tons of reserve (European Commission 2014). Furthermore, it stated that only 25-30 % of total indium mined (excluding China and Russia) is refined, that 25-30 % of it reports to residues, and that 40-50 % is sent to plants that do not have the capacity of indium refining and are lost to residues.

2.2 The Indium market, its Applications and Substitutability

This section highlights major and minor applications of indium, as well as substitutions that have been reported for indium in its various applications. Furthermore, an overview of the market for indium is provided.

2.2.1 Applications Indium metal has a broad spectrum of applications from the electronic industry to medical applications as shown in figure 2.3. According to the data presented, the number one application of indium metal in the manufacturing of flat panel displays; other important applications are in the solders industry and the photovoltaics.

Figure 2.3 Worldwide Use of virgin indium in 2011 (European Commission 2014)

Indium tin oxide (ITO): doping of indium with tin oxide (≈10%) increases the electrical conductivity and the heat reflectivity of the resulting indium tin oxide compound. ITO thin films absorb less than 20 % of light passing through; with such properties, these films are applied in the manufacture of flat panel displays (FPDs), liquid crystal displays (LCDs, electrophoretic displays (EPDs), electroluminescent displays (ELDs), plasma display panels (PDPs), electrochromic displays (ECs), and the list is exhaustive. Other than displays, ITO thin films are also used in glass coating, solar collectors, cathode ray tubes, low pressure sodium lamps, and windshield glasses (Schwartz-Schampera and Herzig 2002). ITO has many been produced in Japan; however, considerable amount if indium, was also produced in China, South Korea, and Taiwan. USGS signaled some production of indium also in the United States (Tolcin 2013).

Indium plating: indium and its alloys are also applied in the surface coating industry. Some examples include plating of vehicles and aircrafts engine bearings, decorative plating, inhibitors in corrosion applications, and plating on aluminum. The application of indium in the plating industry was estimated at 4% of total consumption (Schwartz-Schampera and Herzig 2002).

Alloying: because of its low melting point, the addition of indium to a variety of base and precious metals decreases the melting point of the alloys formed. These alloys are applied in the electronic industry as solders and fusible alloys, and in some other specialized applications such as metal forming, optical grinding, etc. Indium is added to the lead free solders in order to improve their resistance to thermal fatigue as well as reduce crack propagation (Commission 2014). Between 1995 and 2000, the application of indium to low melting point alloys and solders was estimated to be 20% of the total annual consumption (Schwartz-Schampera and Herzig 2002).

Indium compounds: in the semiconductors and phosphors industry, indium compounds of phosphorus, arsenic, and antimony are used in the form of thin films and single crystal wafers. Applications of indium in semiconductors was the third largest annual consumption of indium in 1995 per the Roskill report (Schwartz-Schampera and Herzig 2002).

Photovoltaics: in the photovoltaic industry, indium is used in the production of thin films copper indium selenide (CIS) and copper indium gallium selenide (CIGS) solar cells. These cells have an advantage over the silicon-based cells in terms of weight, durability, flexibility, and

6 easiness to integrate in building materials. Though silicon-based solar cells captures 80 % of the photovoltaics, an increase in in CIGS cells is expected in the future (European Commission 2014).

2.2.2 Overview of Indium’s Market

Table 2.1 shows the worldwide production of refined indium from 2010 to estimated values in 2012. As shown in the table, China is the largest producer of refined indium at all time. Other notable producers include Japan, the Republic of Korea, Canada, and Belgium. According to the report, China provides 81 % of indium on the market worldwide (European Commission 2014). USGS reported that indium production in the US was not reported, data being proprietary to the two major secondary producers; however, in 2000 there were six companies in the United States that produced indium in its various forms. These companies are Indium Corporation of America, Asarco, Atomergic Chemicals, MCP Metalspecialties, the Wilkinson Company, and Umicore Advance Materials (Jorgenson et al. 2004).

From the same report, a forecast was generated on the demand growth of each identified critical materials for 2020. The average annual demand growth (% per year) for indium was forecasted at 5.0 %, owing the growth to the increase in demand for smart phones, tablets, and TVs; it was also estimated that indium would experience a supply deficit by the year 2020.

As it has already been mentioned, China has the largest share of the market for indium. Unfortunately, indium’s market in China is strictly restrained; domestic export of indium is restricted through an export licensing and quota system (Tolcin 2013; European Commission 2014). The uncertainty on the export quota from China puts pressure on the supply of indium worldwide; therefore, major consumers have to increase their recycling capacity or consider expanding the capacity of indium refineries. In order to offset the supply deficit, extensive effort has been invested in the recycling of indium from many of its end of life products such as LCDs, mobile phones, as well as solar cells. It was reported that of the 950 estimated tons of indium produced in 2010, 63% was from secondary production.

Table 2.1 Indium worldwide refinery production, tons, 2010 to 2012 (European Commission 2014) Refinery production, tons Country 2010 2011 20121e Belgium 30 30 30 Brazil 5 5 5 Canada 67 75 70 China 340 380 390 Germanye 10 10 - Italy 5 5 - Japan 70 70 70 Netherlands 5 5 - Republic of Korea 70 70 70 Russia NA 5 5 Peru 2 2 - Other - - 30 World Total 609 662 670 Source: USGS (2013), Minerals Yearbook 2011, Indium 1USGS (2013), Minerals Commodity Summaries 2013, Indium e- Estimated

It has also been considered to recover indium from tailings; the issue with these materials is the presence of a large amount of contaminants which increase the cost of processing. Consequently, recycling of tailings is currently insignificant. The recovery of indium from such tailings relies heavily on the development if improved technologies and high indium prices (European Commission 2014). The price of indium however is volatile. Table 2.2 shows the evolution if indium’s price from 2008 to 2015; it can be seen how indium’s price is cyclical. From 2012, the price experience a gradual increase from $510 to $720 in 2015. With the uncertainty of price constant increase, more effort should be concentrated on the development and/or improvement of technologies for the efficient recovery of indium from tailings.

Table 2.2 Indium average annual prices 2008-2015 Year 20081 20091 20101 20111 20121 20131 20142 20153 Price(US $/Kg) 479 348 546 680 510 580 700 720 1 USGS Mineral Commodity Summaries, Indium 2013 and 2014 2Source: Metals Bulletin: Indium price 2014 3Source: Mineral Prices: Indium price (data provided by the northernminer.com) 2015

2.2.3 Substitutability Indium being produced as a byproduct of base metals processing and mainly zinc processing, its supply and price is related to the market of such metals. Consequently indium prices are very volatile. With the uncertainty in continuous supply of indium, research has been conducted on the substitution of indium in its main applications.

Gallium arsenide has been reported as a replacement of indium phosphide in photovoltaic cells and semiconductors. Hafnium was reported as a substitution for indium in nuclear reactor rods For the replacement of ITO compounds in LCDs, the use of silver zinc oxide, tin oxide, and zinc tin oxide have been reported (Jorgenson et al. 2004; USGS 2013, Schwartz-Schampera and Herzig, 2002). Table 2.3 shows potential substitutions for indium in its main uses as reported by the European commission (European Commission 2014). The higher the substitutability score, the more difficult it is to substitute indium with other metals or compounds. Therefore, it is easier to replace indium in batteries, alloys, and thermal interface materials than it is to replace it in FPDs. Substitutability as mentioned in this table is also reported in the USGS commodity report for indium (USGS 2013). The report also mentioned the use of Poly(3,4-ethylene dioxithiophene) (PEDOT) as a substitute for ITO in flexible displays and organic light-emitting diodes.

Indium replacement by Single-Walled Carbon nanotube Thin Films (IRENA) is an initiative put in place as a consortium of academia from Europe and Japan, and is funded under the European Union Seventh framework. As its name tells, the initiative’s primary goals are the replacement of indium in conductive thin films, and the replacement of indium and gallium as semiconductor In-Ga-Zn-O in film field effect transistors by single-walled carbon nanotube (SWCNT). This project aims at helping the electronic industry of Europe and japan to decrease their dependence on indium resources and manufacturing costs. (European commission 2014).

Table 2.3 Available substitutes for indium applications (European Commission 2014) Use Substitutes/Rationale Substitutability Score Flat Panel Displays No available alternatives 1.0 Photovoltaics Gallium arsenide: currently competing 0.7 Semiconductors Gallium arsenide: currently competing 0.7 Solders Non-indium based solders 0.7 Batteries (alkaline) Alternative battery types 0.3 Alloys/compounds Various other compositions available 0.3 Thermal interface materials Alternative materials based on other metals 0.3 Others Arbitrary assumption 0.5

2.4 Recycling of Indium

This section highlights major findings obtained from literature on the recovery on indium from different indium containing waste streams.

2.4.1 Recovery of Indium from Various Plant Residues

More often than not, indium will be associated with precious metal, platinum group metals as well as its horizontal, diagonal and vertical neighbors on the periodic table, namely Ga, Tl, Ge, Sn, Cd, Zn, and Pb, thus the processing of such wastes involves meticulous processes that often require numerous purification stages (Alfantazi et al. 2003). On a commercial scale, indium is recovered after the pyrometallurgical refining of lead; indium reports to the slag phase during treatment of the lead bullion, then it is recovered from the drosses electrolyticaly with an indium anode assaying 20-25 % indium. Further refining can be done in order to improve the quality of the product. Treatment of wastes from the tin industry involves a chlorination process through which an indium containing slag is produced; indium is precipitated as a sponge by zinc cementation. The sponge is electrorefinned to meet the purity required for its electronics application.

Extensive amount of research has been conducted on the recovery of indium from different types of wastes from zinc processing. A zinc oxide wastes was subjected to sulfation

10 roasting followed by leaching of the sulfate to obtain a solution 50-70 mg/L of indium; the leachate went through two stages of carbonate neutralization followed by solvent extraction to produce an electrolyte containing 20-30 g/L indium that was plated onto aluminum sheets; the final product’s purity was 99.99%. Alternatively, the zinc oxide is dissolved in a dilute sulfuric media to put indium into solution; a series of neutralization tests are carried out afterward and indium is precipitated. The precipitate is later subjected to a caustic soda leach to produce

In(OH)3. This intermediate product is then leached in hydrochloric acid; iron cementation is used to remove arsenic, and Pb and after that indium cementation is used to remove Sn and Cu. The final indium product is recovered by cementation with aluminum.

Flue dust from copper and zinc smelters are also good sources of indium; the off gases from the smelting process are sent to an electrostatic separator from which the dust is collected; the SO2 is sent to sulfuric acid production as is done at the Kidd Creek facility in Canada. A dilute sulfuric leach allows the recovery of most of the copper and zinc; the leach residue is then leached in hot sulfuric acid to recovery the remaining copper and zinc, as well as to recovery the indium present. The pregnant leach solution is put into a reducing environment for the conversion of ferric to ferrous; the solution is then sent to a solvent extraction process to extract indium. Na2S2O4 is used to remove most of the impurities remaining before indium is precipitated as a sponge that will be later refined to 3N8 and 4N grades.

In the early 80s, a hydrometallurgical process was studied for the processing of copper smelters flue dust via pressure leaching for the recovery of metals such as Zn, Cd, In, Bi, Sb, and Pb (Ke et al. 1984). The parameters that were investigated are temperature, oxygen partial pressure, solids to liquid ratio, acid concentration, and time. The study showed that temperature improved the kinetics of the leaching process; potential removal and separation of arsenic could be achieved by using oxygen pressure. Under pressure, about 91% arsenic went into solution at 120 °C; moreover, in the presence of oxygen during the leaching promotes the precipitation of iron arsenate. An inverse behavior of indium and cadmium, compared to zinc, was observed when it came to acid concentration and pulp density. A change in acid concentration had greater effect on the dissolution for zinc, and a change in pulp density has stronger effect on indium and cadmium dissolution.

Indium was extracted from the PLS by solvent extraction with D2EHPA and there was a coextraction of bismuth which was taken care of by scrubbing the organic in a 2N sulfuric acid then an acidified NaCl solution. Stripping was done with a 6N HCl solution. The final PLS was went to aluminum cementation for the recovery of indium on aluminum plates; the raffinate is treated for iron and arsenic removal as an arsenate before cadmium is recover from it via zinc cementation. The final solution, then rich in zinc, is sent to an evaporation process in order to produce a hydrated zinc sulfate. The leaching residue still contain some valuable metals, thus it is leached in a concentrated sulfuric bath from which bismuth is recovered via iron cementation. The filter cake is sent to a smelter or to a flotation circuit for copper and lead recovery.

Other treatment of zinc wastes include the reductive leaching with Na2S. Santos and coworkers investigated leaching of zinc plant residues in sulfates and chloride media (Santos et al. 2010). The parameters investigated were temperature, time, pulp density, minor elements, external oxidants, and ferric iron concentration. The study showed that dissolution of zinc, and indium increased with an increase in temperature, and ferric concentration, both effect increasing with time. An increase in pulp density decreased the extraction extent of both zinc and indium. Minor elements such as arsenic, antimony, and bismuth, when present, also went into solution, but lead stayed in the precipitate. A comparison with chloride leaching showed that extraction was higher for zinc, copper and silver due to the formation of their respective chloride complexes.

In their analysis of indium recovery from wastes, Koleini and coworkers used Na2S+

H2SO4 leaching (Koleini et al. 2010). The feed sample contained 145 ppm indium, and a reductive leaching scheme with Na2S in sulfuric media was used. They found that indium recovery increased with an increase in sulfuric acid concentration (100 g/L being the optimum,

95% extracted), temperature, and time. An increase in Na2S concentration increased ferric reduction to ferrous, but slowed the kinetics of indium dissolution.

2.4.2 Leaching of Indium from Jarosite Residues

Most zinc hydrometallurgical operations have an iron control section to the flowsheet. The iron is commonly precipitated as jarosite, goethite, or ferrite, jarosite being the widely used process. During the jarosite process, divalent and trivalent metals present in solution tend to co- precipitate with iron. The jarosite produced raise environmental concern due to its content in

12 heavy metals such as Zn, Cu, Pb, In, Cd, etc.; nonetheless, it has economic attraction for the recycling of metals such as Zn, Pb, Ga, In, Ge, etc. depending on which metal was in solution during precipitation.

Understanding the thermodynamics and kinetics and of jarosite is vital for the prediction of its dissolution. Authors such as J.E. Dutrizac and T.T. Chen have extensively studied jarosite precipitation of jarosite for the past 35 years. In metallurgical practices, interest is taken in factors such as temperature, seeding, pH, acid concentration, etc. that affect the precipitation of iron as jarosite for purification of sulfate or chloride media. In a study of alkali jarosite precipitation, it was shown the process was dependent on physical factors and chemical factors (Dutrizac 1983). An increase in temperature sharply increased the extent of iron precipitation; the amount of product yielded increased with an increase in retention time, longer time having no further effect. Minimum stirring was required in order to promote mass transfer and have adequate iron precipitation. Overall the composition of the precipitate was constant despite a slight increase in alkali metal content with the increase in temperature and retention time.

The initial acid concentration as well as the pH of the solution had a significant impact on the amount of iron precipitated (an increase in initial acid concentration or a decrease in pH decreases the amount of jarosite precipitated) with little effect on the composition of the product. At lower ferric concentration there is an increase in the iron concentration in the product, but the amount of precipitated iron is constant; this inferred the precipitation of goethite. An increase of the concentration of dissolved alkali sulfates increased the product yield and the alkali content of the jarosite up to 0.15 M in the case of Na2SO4, but levels off after that. It was found that with proper control of the pH, and the alkali concentration, the amount of jarosite precipitated is directly related to the amount of iron precipitated.

In normal hydrometallurgical operations, the leachate fed to the jarosite precipitation plant contains a wide range of monovalent, divalent, and trivalent cations such as Pb2+, Zn2+, In3+, Cd2+, Ag+, Fe2+, Fe3+, Ga3+, Ge3+, etc. depending on the composition of the ore leached. These metals have an impact on the jarosite process and result in other forms of jarosite such as jarosite KFe3(SO4)2(OH)6, natrojarosite NaFe3(SO4)2(OH)6, hydromium jarosite

(H3OFe3(SO4)2(OH)6, argentojarosite AgFe3(SO4)2(OH)6, plumbojarosite Pb[Fe3(SO4)2(OH)6]2, beaverite PbCu(Fe, Al2)(SO4)2(OH)6, etc. Dutrizac and coworker study on the precipitation of

13 potassium jarosite showed that Cu(II), Zn(II), and Pb(II) were incorporated in the jarosite structure, and that their amount increased with an increase in their content in the solution fed to the process (Dutrizac 2008). Another study showed that cobalt and nickel also reported to jarosite (Dutrizac and Chen 2004), cobalt content being higher than that of nickel; it was also shown that more of both metals reported to potassium and ammonium jarosite than to sodium jarosite, and the incorporation of cobalt increased with an increase in temperature, pH, and a decrease in ferric sulfate concentration. In the case of cupric ion presence in the solution copper reported as well to the jarosite, and there was an inversely proportional relation of amount of cobalt incorporation to that of copper incorporation.

A recent European patent application investigated the separation and concentration of gallium and indium by jarosite precipitation (Yoshito 2000). Ferrous, ferric, sulfate ions, monovalent cations and oxidizing agent (air, oxygen, KMnO4) are added to a Ga-In containing solution; the pH is adjusted by the addition of mineral acid or an alkali agent to 2-4. Jarosite seeds are also added to the mixture which is vigorously stirred while the temperature is adjusted to the operation temperature (70-100 °C). Solid liquid separation of the mixture result in a filtrate and jarosite containing gallium and indium. The gallium and indium content of jarosite is increased with an increase in ferric ions content and monovalent cation content with higher gallium incorporation than indium.

The solid is leached in alkaline media (with NaOH or KOH), or in acidic media (with

H2SO4 or HCl); an investigation of each leaching procedures showed that gallium and indium are separated during caustic soda leach of jarosite because indium and iron do not dissolved while zinc barely dissolves; 100% Ga and nearly 77% Al are leached with 200 g/L NaOH at 80 °C for 2 hours; with alkaline leach, iron hydroxide is precipitated. A solution containing Ga is collected, and calcium hydroxide is added for aluminum and zinc removal; the amount of aluminum precipitated increased with an increase temperature and Ca(OH)2 addition accompanied however with Ga co-precipitation up to 2.1 %. In the case germanium is present in the solution, Mg(OH)2 is added for germanium removal; the extent of which increases with an increase in magnesium oxide addition. The resulting filtrate is neutralized by the addition of sulfuric acid which precipitates insoluble sulfates; at pH 6-7, the precipitate had higher aluminum, zinc, sodium, and iron content, while at pH 1-4 it had higher gallium and potassium content. The Ga-containing

14 residue is then leached with 150 g/L NaOH for an hour at 80 °C, pH of 13, and at a pulp density of 200 g/L. The final leached solution contains 55 g/L gallium and is sent to electrowinning for the recovery of Gallium.

2.4.3 Recovery of Indium from Indium –bearing Zinc Ferrite Residues

During roasting of zinc sulfide ores, at 950°C, zinc is completely roasted to zinc ferrite

(ZnO.Fe2O3) which is a very stable phase and is insoluble in most acidic, alkaline, and chelating media. It has been observed that a cationic substitution of iron by indium takes place resulting in indium bearing zinc ferrite (Zn Fe(2-x)InxO4). Most industrial practices leach the zinc ferrite in a hot sulfuric media, removed iron by jarosite, goethite or hematite precipitation then, deposition of electrolytic zinc. Problems with these processes are the volume and environmental stability of the iron residue that is produced. Holloway and coworkers proposed and conducted a study on transformational roasting of zinc ferrite with the goal of increasing the leachability of the product in acidic or alkaline media as well as the production of a more disposable residue (Holloway et al. 2007). The residue contained mainly franklinite (ZnFe2O4), PbSO4 as well as unreacted zincite (ZnO), 286 ppm of Ag, 520 ppm of Ga, and 750 ppm of In. The roasting process utilized

Na2CO3 according to the reaction 2.1 below:

(2.1)

+ → + + 0 ∆ = A mixture− . of ferrite ⁄ and sodium carbonate was put in an alumina crucible and roasted in the presence of air in a muffle furnace for 5 hours at temperatures ranging from 750 to 900 °C; the roasted product is then leached in 200 g/L H2SO4. Extractions of zinc and iron were achieved up to more than 90 % each when the carbonate additions as well as the temperature were increased. At 950 ° and with 80 % addition of carbonate, 90 % and 70-90 % zinc and iron were extracted respectively. With those conditions, indium and gallium were also extracted at 87.8 and 84.7 % respectively. Studies on the thermodynamic decomposition of sodium carbonate, and pH testing of the leaching of the roasted ferrite in water infer the presence of Na2O in the product. Leaching with sulfuric would solubilize the iron that would have to be precipitated either as jarosite, goethite or hematite; leaching with caustic would leave iron in the form of NaFeO2, which is environmentally stable, yet prone to be partially leached under long exposure to acidic conditions.

Other cases of reduction of zinc ferrite with other reagents have been reported to literature. Stopić and coworkers undertook a study of the kinetics and mechanism of thermal zinc ferrite decomposition in neutral nitrogen atmosphere (Stopić et al. 2009). Differential thermal and thermogravimetric analysis were conducted to study phase changes occurring during the reduction process. The chemical composition of the residue is shown in table 2.4 below; zinc present as ZnFeO4, ZnS, and Zn2SiO4; lead was present as PbS, and PbSO4; iron was present in the ferrite phase as well as Fe2O3.

Table 2.4 Chemical composition of the zinc ferrite residue Element Zn Fe Pb Cu Cd As Al S Ca Si Ge* Ag* Comp. (%), 18.6 19.8 6.7 0.6 0.2 0.2 10.9 7.3 2.4 2.1 121 558 * ppm

The decomposed product were pulverized and screened to recuperate 50 g fraction samples of <90 micrometers to be leached in 500 mL of acidic media. Tests were run at a pH of 3.6-4.5 and 60°C to achieve high selectivity of zinc to iron. Products leached at pH 3.6 showed approximately 72% recovery of zinc with minor Fe, Pb, and Al recovery, and those leached at pH 4.5 reached approximately 95 % and 8% zinc and iron recovery respectively. The dissolution of zinc was observed to be controlled by the diffusion through the solid layer while that of Al, Pb, and Fe were controlled by the chemical reaction with sulfuric acid.

Donald and Pickles investigated the reduction of zinc ferrite with iron (Donald and Pickles 1995); occasionally lime was added as a flux according to the following reaction 2.2 below: (2.2)

A. flux containing + zinc ferrite, + lime, calcium → fluoride + and + calcium chloride. were thoroughly mixed and formed in briquettes of 25.4mm internal diameter; the briquettes were treated in a furnace at 1100 °C for 3 hours. The roasted briquettes were crushed to less than 200 Tyler mesh size. The study showed that the reduction rate of ZnO in zinc ferrite was dependent on and increased with a decrease in the ferrite particle size, an increase in temperature, an increase in iron to zinc ferrite ratio, and for a briquette aspect ratio (l/d) less than 1.0. The reaction was found to be chemically controlled in the first few hours of the experiment, and then controlled by the diffusion of zinc vapor once the product layer was formed. Addition of lime and sodium

16 chloride promoted the reaction by the production of a highly stable calcium ferrite (lowering the mobility of iron) thus decreasing the activation energy of the reaction; sodium chloride produced cracks in the product layer which promoted the diffusion of the zinc vapor.

Ning Peng and coworkers looked at the decomposition of ZnFeO4 into ZnO and magnetite (Fe3O4) using a mixture of carbon monoxide (CO) and argon gas as reducing agents (Peng et al. 2012). They looked at the effect of roasting -temperature (700-900 °C) and time (1- 3.5 hours). The material tested contained zinc ferrite and magnetite predominantly with some Pb as sulfide, sulfate and silicate, calcium as sulfate, and zinc as oxide, sulfide and hydrated sulfate.

The roasted samples were leached in 150 g/L H2SO4, under 600 rpm mechanical stirring, at room temperature, at a solid to liquid ratio of 15:1, and for 2 hours. The leaching residues were washed, dried and analyzed.

The experiment showed that iron reached a maximum extraction of high 20s percent at 800 °C then extraction decreased; meanwhile zinc reached a maximum extraction in the high 70s percent at 850 °C, thus optimum roasting temperature was set to 850 C. In order to avoid coextraction of iron that would require a long purification process downstream, optimum roasting time was set at 2 hours where 75.5 % and 25.0 % of zinc and iron are extracted respectively. The particle size had no significant effect on the extraction of zinc and iron nor did it achieve selectivity of zinc against iron; the study showed that zinc and iron followed the same size distribution pattern in the roasted product at different roasting temperatures.

This observation was confirmed by Zhang and coworkers on the study of kinetics of zinc and indium extraction from synthetic indium bearing zinc ferrite (IZBF) (Zhang et al. 2010). The study investigated the effect of particle size (-100+140 mesh, -160+200 mesh, -230+270 mesh, and -300+325 mesh), temperature (70-90 °C) and sulfuric acid concentration (0.5-2.5 M). The expected reaction was:

Aside from−� the� discovery + of little → to no effect + of −the � particle size on+ �the leaching +of zinc and . indium, the study showed that the dissolution of these element were greatly promoted by the increase in reaction temperature and acid concentration, which similarities suggested that indium was substituted in the lattice of zinc ferrite. Using Sharp’s half reaction kinetic model, the

17 reaction was found to be chemically controlled, and the calculated activation energies for zinc and indium were 76.4 kJ/mole and 68.8 kJ/mole respectively; the reaction was found to be of the 0.79 order with respect to the concentration of sulfuric acid.

Leaching of zinc ferrite residues as received yield low extraction of metals, thus the investigation of methods to increase the leachabilities of such waste as mentioned above. Also reported in the literature if the mechanical activation of the zinc ferrite by milling. In their series of studies, Yao and coworkers (Yao et al. 2012) investigated the enhancement of physicochemical properties of IBZF by tumbling as well as the effect on the extraction of zinc and indium from the ferrites. Grinding was done using 5.0 mm diameter zirconia balls in an effective reactor volume of 1000 mL. Grinded samples were leached in 1.5 M H2SO4 between 79.9 and 80.1 °C, and at 400 rpm stirring.

The study showed that rotation speed, milling time, media filling and ball to charge ratio has an important impact on the activation of zinc ferrites. Tumbling milling achieved the particle size reduction, the increase in defects or breakage of the crystalline network and the redistribution of Zn2+ and Fe2+ cations which result in a metastable phase that has higher reactivity of zinc and indium. The same results were observed for planetary ball milling; narrow particle size range, high specific surface area, crystal structure change, improved leachabilities of zinc and indium.

The study also confirmed the result presented in Zhang et al.’s study on the kinetics of indium extraction from IBZF (Zhang et al. 2010); tumbling activation reduced the activation energies for zinc and indium from 78.1- to 73.5 kJ/mole and 73.9 to 70.3 kJ/mole respectively; The reaction orders were decreased from 0.72 to 0.70 for Zn and from 0.82 to 0.69 for indium. Mechanical activation of zinc ferrite decreases the dependence of zinc and indium leaching in temperature and acid concentration.

Based on the investigation of literature, indium is mostly recovered from solutions using cementation; it being precipitated as a hydroxide. After subsequent acidic or alkaline leach, the solution would be highly concentrated in indium, and ready to be sent to the electrowinning circuit or to cementation. Suffice it to say that solvent extraction (mostly with D2EHPA) and ion exchange have also been extensively studied.

CHAPTER 3 PROCESS DEVELOPMENT AND EXPERIMENTAL METHODS

Chapter 3 provides information used in the process development of this project. Section 3.1 briefly describes steps taken in the characterization of all three samples received, section 3.2 details physical properties of minerals in each sample, and their use in the design of gravity, magnetic, and electrostatic experiments. Section 3.3 provides thermodynamics data on the leaching for the jarosite and ferrite samples, and section 3.4 details the procedure for analytical analysis pertaining to all experiments undertaken for this project. The materials that were acquired for this project are:

 The “tailings sample” which is a residue from a zinc floatation plant in Bolivia.  The “jarosite sample” which is a residue from a zinc hydrometallurgical plant. The exact origin of the jarosite sample was not disclosed to the research team because of the proprietary nature of the agreement with the provider.

 The “ferrite sample” which is a residue from a pyro-hydrometallurgical zinc plant. The exact origin of the sample was not disclosed to the research team for the same reasons as the jarosite sample.

3.1 Materials Characterization

Section 3.1 details procedures used for particle size distribution analysis, X-ray diffraction (XRD), Qualitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN), and mineral liberation analyzer (MLA).

3.1.1 Particle Size Analysis One of the first steps taken in the characterization of materials is the size distribution. Size distribution is important in operations when there is need to assess the efficiency of grinding for example (Wills 2006). To that purpose there exists a wide range of methods that can be used. For the purpose of this project, two methods were used, namely a wet test sieving, and a wet laser diffraction.

3.1.1.1 Wet Sieve Size Analysis Sieving is recognized as one of the oldest methods of determining particle size distribution. This method can be used both dry and wet, and is normally carried out by charging a known amount of material on a sieve. The sieve distribution will be computed using the collected weight fractions on each sieve used. For this project, wet sieving was used in order to insure the accuracy of the measurement given the fact that particles in the sample for which wet sieving was used had a tendency to agglomerate when dry sieving was attempted. Figure 3.1 shows a typical setup for wet sieving; a vibrator is used to agitate the sieve, and a water jet is used at low to medium pressure to ensure that all fines are passed through the sieve.

Figure 3.1 Typical wet sieve shaker used in wet sieve testing

For the purpose of this project, a U.S. standard sieve series was used, and the data was converted to Tyler sieve series for reporting (table 3.1). The average particle size was calculated according to equation 3.1 below and is shown in table 3.1.

�� + �� = .

Table 3.1 Size chart for the conversion from US to Tyler mesh series US Sieve # Tyler Equivalent Sieve # Opening (um) Average Particle Size (um) 12 10 1680 1840 30 28 595 651 50 48 297 326 60 60 250 274 70 65 210 230 80 80 177 194 100 100 149 163 120 115 125 137 140 150 105 115 200 200 74 81 325 325 44 49 400 400 37 41

Procedure

Wet sieve testing was carried according to the following procedure:

1. Acquire a representative split for the sample of interest. 2. Prepare a stack of sieve to be used arranging them in ascending order from to bottom. 3. Take the top sieve and place it on the vibrator, and place the two on a 5 gallon bucket designed to hold the vibrator’s side arms. Turn on the vibrator and water jet. Gently pour water on the sieve as it is vibrating until the water passing through is fairly clear. 4. Collect the pulp containing the fines fraction, filter it (a filter press is faster and more reliable), and dry. 5. In another bucket, collect the coarse material to be fed on the next sieve on the stack. Place that sieve on the vibrator, and repeat steps 3 to 4. Perform the repetition until the last sieve in the stack. 6. Weight and record the weight of each fraction then calculate the total weight with which you will compute the rest of the data needed for the particle size distribution.

3.1.1.2 Microtrac Size Analysis For samples that contained a large fraction of apparent fine particles, a laser diffraction method was used for the determination of size distribution. The equipment used for this purpose

21 was the Microtrac S3500 (figure 3.2). This unit is equipped the patented Tri-Laser system that ensures the accuracy and repeatability of the size analysis by using the theory of Mie compensation for spherical particle, and the Modified Mie compensation for non-spherical particles. Advantages of this method are:

 Wide size range that can be measured (0.02-2800 um)  Capability to measure complex shapes made possible with the Tri-Laser system  Wet or dry measurements  Ease of operation  Particles can be sonicated to ensure particle dispersion during analysis (Microtrac 2016).

Laser SDC Diffraction PartAn SI Analyzer

Flow Direction

Figure 3.2 Illustration of a Microtrac S3500 unit with flow direction (Microtrac 2016)

SDC is the sample distribution chamber were the sample is introduced into the system. The solution containing the sample flows from the SDC trough, the laser diffractometer were data is collected, and flow back through the SDC. The analysis is shown in real time with the SI software which is a modular design which allows connection to any microtrac sample analyzer (S3500, Bluewave, and TRI-BLUE)

Procedure

1. Acquire a representative sample for analysis. 2. Turn on the SDC and the diffraction analyzer in the particle order. Open the Size analyzer software on the computer. 3. Before running samples, first run a system and detector status (all responses should show “OK” in green). In case a “NO” appears next to the status for laser alignment, a

correction can be made by clicking on the icon for laser alignment; rerun the detector status again until an “OK” is signaled on all parts. 4. Input any known data and parameters (shape factor, sonication power, water flow, etc.) that best describes the sample by clicking in the “Set UP” icon. 5. A set of icons pertaining to the flow of water in the SDC is located on the right side of the window. Click on the “FLOW” icon, let the flow stabilize for 10 seconds, then click on the “SET ZERO” icon to establish a base for the calculations. The set zero run will last approximately 2 minutes. While it is running, weight approximately 0.02 g of the sample, put in in a small beaker with a small amount of water. Mix and swirl the pulp as much as necessary to achieve a good dispersion. 6. After the set zero is completed, click on the “FLOW” icon again, then click on the “LOAD” icon which will prompt open another window with parameters of the loading step. Open the SDC and slowly introduce the sample in the system (watch the green vertical bar on the left of the window; the height of the bar has to fall between the two red horizontal lines for a good analysis). Sonicate the sample to achieve maximum dispersion to last for the analysis. 7. After sonication, close the load window and remember to name the sample and run. Finally, click on the “RUN” icon to start the collection of data (A single analysis has a duration of approximately 10-30 seconds, and an average a 3 runs are performed in one analysis). 8. At the end of the analysis, save the graphs or export the data into an excel spreadsheet for reporting.

3.1.2 X-Ray Diffraction (XRD) Spectroscopy X-Ray Diffraction (XRD) is a spectroscopy tool that is used for the determination of atomic structure of a crystalline material (Fultz et al. 2007). Figure 3.3 shows a schematic of a typical x-ray diffractometer; when the incident beam intercepts a crystalline material towards which it has been directed, general scattering can occur. The detector is moved about as the sample is rotated in order to collect diffracted waves.

Figure 3.3 Schematic of a typical x-ray diffractometer (Poppe et al. 2001)

Bragg’s law is used to relate the incident angle θ to the lattice interplanar spacing d as shown in equation 3.2 below. Materials have their own crystal structure that act as their DNA for analogy. Consequently, they will diffract x-ray in a unique fashion; the collected x-ray pattern will then be compared to a wide variety of known and certified patterns from the database for the identification of phases and minerals present in the sample.

sin �For = the � purpose of this project, an X’pert Panalytical x -ray diffractometer was used. The. 2θ range, the step size and the dwell time were adjusted for each sample so as to attain acceptable resolution on the graph. Samples, crushed to 100% passing 100 Tyler mesh size, were mounted such that a leveled flat surface was obtained and had a thickness about 0.5 cm.

3.1.3 Mineralogical Data 3.1.3.1 Qualitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN®) QEMSCAN® is a registered trademark under FEI and it combines scanning electron microscopy with a qualitative evaluation of minerals hence the name QEMSCAN. It provides a non- destructive, fully automated, reliable and repeatable analysis, and is highly sought after in the mining and metallurgical industries (FEI, 2016). For the purpose of this project, QEMSCAN analysis was performed at the automated mineral laboratory at the Colorado School of Mines (CSM) in the geology & geological engineering department.

Sample Preparation Procedure (Dr. Katharina Pfaff)

1. From the provided material, obtain a 1.0 g of representative sample using a Micro Riffle 2. Mix the obtained 1.0 g of sample with graphite powder of an approximate grain size with a graphite to sample weight ratio of 3:1. 3. Combine the obtained mixture with epoxy in order to form a grain mount. 4. Grind and polish the mount to a 1.0 um finish using alcohol based diamond polishing fluids 5. Once the mount has been polished, apply a carbon coating on it in order to provide an electrically conductive surface for analysis under the SEM.

After collecting data, the results were analyzed and exported using the iDiscover® software registered under FEI as well. Results of interest for this project were the modal abundance, zinc minerals grain size distribution, minerals associations of zinc minerals, elemental abundance, minerals locking and liberation. For locking and liberation data, parameters were set for each sample as detailed in table 3.2 below.

Table 3.2 Parameters for locking and liberation from QEMSCAN analysis Area percent of mineral Minerals Locked Middling Liberated Tailings <30 >=30 to <95 >= 95 Jarosite <30 >=30 to <99 >=99 Ferrite <30 >=30 to <95 >=95

3.1.3.2 Mineral Liberation Analyzer (MLA) The mineral liberation analyzer (MLA) is another tool used for automated mineral analysis. Information provided by the MLA includes but is not limited to mineral abundance, grain size, and liberation. MLA testing was conducted analysis was conducted at the University of Montana tech in Butte MT, at the Center for Advanced Minerals & Metallurgical Processing (CAMP) in order to compare and contrast with QEMSCAN analysis. In order to simplify and ease the comparison, samples sent to MLA and QEMSCAN were taken from the same quartered lot.

Sample Preparation and Analysis Procedure (Gary Wyss, Montana Tech)

1. The as-received materials were wet-sieved into four different size fractions ( +100 US mesh, -100+200 US mesh, -200+400 US mesh, and -400 US mesh) 2. Transverse particle mounts were prepared out of material from each size fraction for MLA analysis 3. MLA data was obtained using XBSE where backscatter electron (BSE) is used to differentiate mineral phases based on the gray level variation due to the composition of the phases. 4. An X-ray spectrum was obtain for each phase and was compared to an X-ray mineral database for a qualitative determination of mineral 5. Surface area data for each mineral was used to quantify the identified minerals.

3.2 Physical Separation

Physical separation can be achieved by manipulated physical properties such as specific gravity, magnetism, electrical affinity, etc. of minerals present in the sample. A quick survey of physical properties of minerals in all three samples was conducted on the XRD results (tables A- 1 to A-3 in appendix A).

3.2.1 Gravity Separation Gravity separation uses the differences in specific gravity between minerals in the sample to make a separation. The efficiency of such a separation is often computed using the concentration criterion defined by equation 3.3 where Dh is the specific gravity of the heavy mineral, Dl is the specific gravity of the light mineral, and Df is the specific density of the fluid used. It is considered that for an easy separation, the criterion has to equal 2.5 and higher (Wills. 2006.

ℎ − � �� = . 3.2.1.1 Float/Sink Gravity Separation − Float/sink gravity separation testing was conducted in order to investigate the potential of making a separation on each sample. For this project, sodium polytungstate with a chemical formula Na6(H2W12O40) (SPT) which can reach a maximum specific gravity of 3.1 at 25°C was

26 used. The particular SPT used in for experiment for this project was purchased through GEOLiquids Inc. (Catalog number SP006); SPT has the advantage of being less toxic than many other competing dense media, being odorless, being a low viscosity fluid, easy to handle, and can be reused for a series of experiments.

Medium Preparation

1. In a 500 mL beaker, put a magnetic stirrer, 1 lb. (454 g) of SPT with 101 g of water following instructions given on the safety data sheet. 2. Place the beaker on a hot plate set to 70°C and stir between 400 and 600 rpm depending on the amount if SPT dissolved. 3. When it is visible that there are no more solids, pipet 10 mL to be weighted on a tared balance in a 10 mL graduated cylinder. Calculated the density obtained; if the density is higher than the desired density, use water to dilute the medium to the required density. 4. The medium is now ready to be used for experiment. It was established during experimenting that it was better to start with the highest density medium and diluting it down as needed. Attempting to increase the density by driving off water often took a full day thus causing delays. 5. At the end of the experiment, use a spatula to carefully remove the float fraction from the vial. In reference to the third picture on figure 3.4 below, recover the medium with the smallest fraction recovered so as to decrease filtering time. 6. After filtering the smallest fraction, recover the medium. Afterwards, wash each fraction in water, then filter them again. 7. Dispose of the waste water according to EHS rules and regulations.

Experimental Setup and Parameters

Figure 3.4 shows the experimental setup for float/sink testing. The setup consisted on putting the medium and the sample in a 15 mL vial, then using a centrifuge to enhance the separation given the large fraction of fines in each sample. For this project, a VWR centrifuge was used. The centrifuge had a rotation arm of 8 cm, the rotation speed was set to 3000 rpm, and time was set to 30 minutes. Table 3.3 shows parameters used in testing for all three samples.

Figure 3.4 Experimental setup for float/sink gravity separation

Table 3.3 Parameters used for float/sink testing Sample Medium Density used (g/cm3) Tailings 2.31, 2.77, 3.06 Jarosite 2.25, 2.50, 2.79, 3.08 Ferrite 2.31, 2.77, 3.06

3.2.1.2 Falcon Gravity Separation Most of the time in gravity separation, the particle size and particle density duality needs to be overcome. To achieve this goal gravity can be enhanced by using a centrifugal force; this is the principle of the falcon separator.

A 2k factorial experimental matrix was designed with 3, and the parameters that were explored in these experiments are: (1) gravitational acceleration (AKA G force), (2) feed pulp density, and (3) fluidization water. Table 3.4 below shows a detailed description of the parameters used; the first number is the lower limit (L) setting and the second number upper limit (U), and the layout matrix is shown in table 3.5. Due to the equipment limitation on the size of particles that can be fed, the ferrite sample was sieved on an Tyler 4 mesh sieve; the oversize materials were grinded until 100% passing on the same mesh sieve; the tailings and jarosite samples were originally 100 % passing 60 mesh thus could be fed directly as a pulp.

Table 3.4 Experimental parameters for Falcon gravity separation tests Feed Pulp Fluidization Fluidization Sample G force Density (% sol.) water (psi) water (Lpm) Tailings 150-200 10-30 5-7 11.9-13.4 Jarosite 200-250 10-30 3-5 10.5-11.9 Ferrite 80-100 10-30 8-10 14.3-16.2

Table 3.5 Experimental Matrix layout for Falcon gravity experiments Exp. G Feed pulp Fluidization # force density (% sol.) Water (L/min) 1 L L L 2 U 3 L U 4 U 5 L L U 6 U 7 L U 8 U

3.2.2 Magnetic Separation Magnetic separation has been proposed as one of the routes to be taken into account for the investigation of physical beneficiation of the samples. Magnetic separation on the tailings and jarosite sample was operated under voltage control using wet high intensity magnetic separation (WHIMS) at 30, 60, 90, and 120 volts of magnetic field induction. The experiments were run using a model L4 WHIMS unit with 6 mm diameter steel balls as the matrix.

The ferrite sample, unlike the other two, was investigated using a low intensity magnetic separation (LIMS) using a model EDT Davis tube tester unit. The separation was investigated in current control at 1.0 and 1.5 amps with two different oscillation rates (60 and 100 strokes per minutes) as well as two different wash water rates (0.4 and 0.8 L/min). In all cases the field intensity was converted to gauss units using a calibration curve. The sample was grinded to 100 % passing 100 microns before being fed to the equipment.

3.2.3 Electrostatic Separation Electrostatic separation, in this case, high tension separation uses the difference in surface conductivity of each mineral to make a separation. Samples (dry or with a small percentage of

29 moisture) are fed in a monolayer as much as at possible. Charging is done through a corona wire, then the high tension plate exert a force on the nonconductive materials so they stick on the separation roll. The conductive material are attracted to the plate and lose their charge; Depending on the speed of the roll, they are thrown from the roll either by centrifugal force or gravity. A 2k factorial experimental matrix with two levels and three factors was design to carry out the study on separation by conductivity.

Figure 3.5 Schematic of a typical high tension roll separator (Waal et al. 2005)

In the case of separation of tailings, and ferrite, a Carrara HTR separator was utilized; a typical high tension roll separator is illustrated in figure 3.5 above. The maximum particle size that could exit the feeder hopper was 3 mm which would represent no problem for the tailings and jarosite sample. Nonetheless, the ferrite sample was sieved to 100 % passing 7 Tyler mesh; the oversize were grinded for 10 min using ½ and ¼ in ceramic balls then sieved again in order to satisfy the 100 passing requirement. The feeding system on the equipment is through a rotating load shaft; that way even layers of material are fed on the roll. A series of test were done on all three samples in order to determine a feed rate low enough to make a separation. Due to their high volume of very fine particles, the feed rate could not be varied on the tailings and ferrite sample because some material were stuck on the feed bin. A vibrational type of feeding was provided by whacking on the rear edge of the feed bin to deliver every bit of the sample on the roll. The combination of normal plus vibrational feed was time so as to get an estimate and

30 constant feed rate for all experiments on each sample. The feeding combination did not work on the jarosite sample even at high load shaft speed; therefore jarosite HTR tests were cancelled.

Initially the variable that were to be explored in these experiments were (1) the feed rate, (2) corona voltage, (3) the separation roll speed. The feed rate was substituted with the corona wire position with respect to the separating roll. Table 3.6 below shows the experimental design matrix that was used for each sample. The high tension plate was fixed at 30 mm for the tailings sample and 25 mm for the ferrite sample using the HT templates provided by the manufacturer.

Table 3.6 Experimental matrix for electrostatic separation of the tailings and ferrite sample Test A: High B: Separation C: Corona wire # tension (kV) Roll speed (rpm) position (mm) 1 20 130 2 25 60 3 20 150 4 25 5 20 130 6 25 50 7 20 150 8 25

3.3 Leaching

3.3.1 Proposed Reactions For leaching experiments, a reaction was proposed for the dissolution the main mineral in both the jarosite and ferrite sample. It should be noted however that there exist other reactions occurring during the leaching that were assumed to have little impact due to the low content of the mineral dissolving. Reaction 3.4 was proposed for leaching of the natrojarosite mineral which is predominant in the jarosite sample, and reaction 3.5 was proposed for leaching of the franklinite mineral which is predominant in the ferrite sample.

6 � � � + → . + . + .

� � � 3.3.2 Thermodynamics + → + + .

Thermodynamics data for the leaching of the jarosite and ferrite sample were acquired using HSC Chemistry 5.1, and the data is presented in tables 3.7 and 3.8. As seen table 3.7,

31 reaction 3.4 thermodynamics showed that the reaction becomes more thermodynamically favorable as temperature in increased. The high equilibrium constant of this reaction is such that it could be considered a spontaneous one. The reaction is shown to be exothermic as well.

Table 3.7 Thermodynamic data for reaction 3.4

NaFe3(SO4)2(OH)6 + 3 H2SO4 = 0.5 Na2SO4 + 1.5 Fe2(SO4)3 + 6 H2O T (°C) ΔH (kJ/mole) ΔS (J/mole-K) ΔG (kJ/mole) K Log(K) 25 -168.4 102.7 -199.0 7.25E+34 34.9 30 -168.0 104.0 -199.5 2.37E+34 34.4 40 -167.3 106.2 -200.5 2.83E+33 33.5 50 -166.7 108.1 -201.6 3.89E+32 32.6 60 -166.2 109.6 -202.7 6.06E+31 31.8 70 -165.8 110.9 -203.8 1.06E+31 31.0 80 -165.4 111.8 -204.9 2.04E+30 30.3 90 -165.2 112.6 -206.0 4.34E+29 29.6 100 -165.0 113.1 -207.2 1.00E+29 29.0

As shown the table 3.8, thermodynamic data showed that reaction 3.5 becomes less thermodynamically favorable as temperature in increased. This reaction also suggests spontaneity based on the very large value of the equilibrium constant. It also showed that the reaction is exothermic which means lower yield as temperature is increased.

Table 3.8 Thermodynamic data for reaction 3.5 ZnFe2O4 + 4H2SO4 = ZnSO4 + Fe2(SO4)3 + 4H2O T (°C) ΔH (kJ/mole) ΔS (J/mole-K) ΔG (kJ/mole) K Log(K) 25 -269.9 -65.6 -250.4 7.45E+43 43.9 30 -270.0 -65.8 -250.1 1.24E+43 43.1 40 -270.2 -66.4 -249.4 4.03E+41 41.6 50 -270.4 -67.0 -248.7 1.62E+40 40.2 60 -270.7 -67.8 -248.1 7.90E+38 38.9 70 -270.9 -68.7 -247.4 4.57E+37 37.7 80 -271.3 -69.6 -246.7 3.10E+36 36.5 90 -271.6 -70.6 -246.0 2.43E+35 35.4 100 -272.0 -71.6 -245.3 2.18E+34 34.3 3.3.3 Experimental Setup Figure 3.6 below shows the experimental setup used for leaching experiments of the jarosite and the ferrite samples. The volume of sulfuric acid was fixed at 100 mL for each test, and a water bath was used to heat the solution to the desired temperature. A hot plate equipped

32 with a type K temperature probe was used as the heat source. Temperature was measured by the probe from the hot plate, and verified with a mercury general purpose thermometer.

Figure 3.6 Experimental setup for leaching experiments

In order to minimize loss of the leaching solution, a reflux condenser was used. Water flow through the condenser was set to 0.5 L/min. Free acid in the starting as well as the pregnant leach solution was determined using an end point titration with methyl orange as the indicator. Using the recorded data, acid consumption was calculated from the difference between the starting and ending free acid levels.

3.3.4 Parameters Leaching experiments in sulfuric media were conducted on jarosite and ferrite samples; the jarosite sample was leached as received. The ferrite sample was sieved into two size fraction (+10 and -10 mesh-Tyler) to remove the majority of gangue minerals; the -10 mesh fraction provided feed to the leaching experiments. Factors investigated were time, temperature, initial acid concentration, and pulp density. An attempt to increase agitation to 600 rpm produced splashing of the pulp up in the mouth of the condenser which resulted in higher loss of material after the test; therefore, agitation was fixed at 500 rpm.

Table 3.9 below shows in details each parameter. During investigation of the effect of temperature, parameters were fixed at 1M H2SO4 and 20 %wt. /vol. solids; time was varied from 1 to 8 hours. During the investigation of the effect of initial acid concentration, parameters were fixed at 80°C, 500 rpm, 20 %wt. /vol. solids; time was varied from 1to 4 hours. During the investigation of the effect of pulp density, parameters were fixed at 80°C, 500 rpm, 2 hours, and

2M H2SO4.

Table 3.9 Jarosite and ferrite samples leaching parameters Parameters Levels Time (Hrs.) 1, 2, 4, 6, 8 Agitation (rpm) 500 Temperature (°C) 70, 80, 90 Initial acid concentration (M) 1, 2, 3, 4 Solid/liquid ratio (wt. %/vol.) 15, 20, 25,30

3.4 Analytical Chemical Analysis

Significant time and effort were invested in the establishment of a reliable chemical analysis for indium and other elements as well. A variety of sample preparation methods were used namely, borate fusion, aqua regia digestion and near total dissolution. Digestion with borate fusion uses 0.1 g of sample size to be analyzed; though it achieved dissolution of more than 99.0 % of the sample, by the time dilutions were made to meet the total dissolved solids (TDS) requirement for the analytical measurements, the accuracy was very low. Aqua regia barely dissolved 10 % of the tailings and the ferrite sample, and did not dissolve the silicates present in the jarosite sample.

In the end, near total dissolution scheme was adapted in reference to Farrell, Matthes, and Mackies’s procedure for sample dissolution in pressure vessel (Farrell et al., 1983). This method used concentrated nitric acid (HNO3), hydrochloric acid (HCl), hydrofluoric acid (HF), and boric acid (H3BO3) which reacts with excess HF according to reaction 3.6 below. Modification to this method included:

 The use of a 125 mL polypropylene bottle as the vessel.  Each vessel was introduced into a 150 mL beaker filled with approximately 15 mL of water as the water bath instead of a single water bath unit.

 An increase in the volumetric ratio of HCl to HF from 5:3 to 13:7 in mL.  A sample size of 0.5 was used.

Procedure + → + .

1. Grind the sample to be analyzed to 100 % passing 100 Tyler mesh. On a tared balance, weight 0.5 of the sample. 2. Prepare a mixture of 38 % HCl and 48 % HF with a volume ratio of 13:7 in mL. 3. In a 125 mL polypropylene bottle, add the weighed sample together with a

magnetic stirrer and 20 mL of the HCl-HF. Add 7 mL of HNO3, gently swirl the bottle, then close it tightly. 4. Put the bottle in a 150 mL beaker filled with about 15mL of water, place the beaker on a hot plate, and let the mixture is react at 200 °C for approximately 15 minutes.

5. After cool down, add 50 mL of a 30 g/L H3BO3 solution to the mixture, then let it react for another 15 minutes. 6. After cool down, filter the solution and adjust the volume 100 mL or 120 mL (tailings sample which required occasional addition of 2 mL HF) with another

aliquot of 30 g/L H3BO3. The solution is then ready for analysis.

For the purpose of this project, analytical analysis was performed using Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). An iCAP-Q ICP-MS from Thermo Fisher Scientific was utilized. The research team consulted chemists from the vendor about the use of hydrofluoric acid in relation to (ICP-MS); guidance was provided about the proper way and proper equipment accessories to use when using hydrofluoric acid with the ICP-MS. As long as all the unreacted HF is reacted with H3BO3, ICP-MS can be used without special injection systems; therefore, it is preferred to have excess H3BO3 in the solution. On rare occasion, Atomic Absorption Spectroscopy (AAS) was used to determine silver and copper when higher TDS were required.

CHAPTER 4 MATERIALS CHARACTERIZATION AND CHEMICAL ANALYSIS

Chapter 4 gives an overview of the materials used in this study and provide characterization work used to design experiments further throughout the project.

4.1 Tailings Sample

Upon receipt, the tailings sample was dried overnight. The sample was homogenized by mixed using a Jones Splitter. Afterwards, the sample was split in 1.0 kg lots and was stored.

4.1.1 Particle Size Distribution From one of the representative splits, a representative sample was taken for Microtrac size analysis. The results are shown in figure 4.1 below. The figure shows that 50 % of particles in the sample are smaller than 30 um, and that the P80 was determined to be 105.9 um.

Figure 4.1 Particle size analysis of the tailings sample via microtrac size analysis

In order to confirm that larger size particles were well mixed in the pulp and that their presence was not due to agglomeration during the microtrac analysis, a wet sieve size analysis was also conducted. Tyler sieves were used in this analysis from size 60 to size 400; the results are shown in figure 4.2 below.

Figure 4.2 Cumulative particle size distribution of the tailings sample via a wet sieve procedure

Figure 4.2 shows that more than 50 wt. % of particles in the sample are smaller than 50 um, and that in this case the P80 was determined to be 104.5 um. The microtrac and the wet sieve data were well in agreement in terms of the P80 size.

4.1.2 X-Ray Diffraction Analysis Figure 3.3 below shows results from the XRD analysis pf the tailings sample. A list of potential minerals matching with the pattern in the figure was established, and is detailed in table 4.1. The tailings sample is shown to be comprised mainly of silicates and spinel compounds containing zinc, iron, manganese, nickel, and cadmium; sphalerite occurred as enriched in iron and cadmium. In this case it is expected that indium would be associated with sphalerite and the ferrite minerals.

Figure 4.3 XRD generated pattern for the tailings sample

Table 4.1 Minerals identified by XRD analysis in the tailings sample Compound Name Chemical Formula Score Mineral Name Silicon Oxide SiO2 40 Quartz Cadmium Copper Gallium Oxide Cu0.25Cd0.75Ga2O4 36 Cadmium Nickel Zinc Iron Oxide Zn0.1Cd0.4Fe2Ni0.5O4 30 Cd-Zn-Ni ferrite Zinc Oxide ZnO 26 Zincite Zinc Iron Oxide Zn0.98Fe2.02O4 23 Lead Copper Aluminum Sulfate Hydroxide Pb(Al, Cu)3(SO4)2(OH)6 21 Osarizawaite Zinc Manganese Iron Oxide Zn0.2Mn0.8Fe2O4 21 Jacobsite, zincian Potassium Aluminum Silicon Oxide KAl3Si3O11 19 Muscovite Cadmium Iron Zinc Sulfide (Cd0.04Fe0.24Zn0.72)S 18 Sphalerite, ferroan

4.1.3 Mineralogical Analysis 4.1.3.1 QEMSCAN Mineralogy Data Modal Abundance Figure 4.4 below shows a field image of the tailings sample after SEM scan; the sample is comprised mostly of different shades of brown which relate to gangue minerals in the legend.

It is seen that zinc minerals are trapped in the gangue mineral grains with a small portion liberated. There is a significant spread of liberated minerals which are pyrite and iron oxides mainly in the purple and green colors respectively.

Figure 4.4 Graphic illustration of the tailings sample results from QEMSCAN analysis

Table 4.2 shows the modal abundance of minerals in the tailings sample. Here, the trends seen in figure 4.4 can be verified in terms of the dominant presence of silicates minerals. It can be seen that quartz, muscovite, feldspar, and pyrite (highlighted in yellow) are the predominant minerals. There are some occurrences of tin oxide, iron oxides as well as minerals of silver, lead,

39 and titanium. The zinc sulfide and oxide minerals (sphalerite, Fe-rich sphalerite, and franklinite) which are believed to carry the indium value amount to a total of 1.73 wt. % in the sample.

Table 4.2 Mineral abundance in the tailings sample Minerals Chemical Formula Mass % Sphalerite ZnS 1.23 Franklinite ZnFe2O4 0.46 High Fe Sphalerite (Zn,Fe)S 0.04 Secondary Zn Zn4Si2O7(OH)2. H2O, Zn2(SiO4), 0.08 minerals ZnCO3.FeCO3,…etc. Ag-sulfide Ag2S 0.05 Arsenopyrite FeAsS 0.18 Chalcopyrite CuFeS2 0.01 Galena PbS 0.05 Pyrite FexSy, and FeS 12.3 Alunite KAl3(SO4)2(OH)6 4.79 Barite BaSO4 0.06 Celestine SrSO4 0.01 3+ Other sulfates CaCO3.MgCO3, (H3O)Fe 3(SO4)2(OH)6 0.24 Calcite CaCO3 0.10 Cassiterite SnO2 0.16 Fe-oxide Fe3+OOH 3.22 Mn-oxide Variety of Manganese oxides 0.20

Ti-minerals TiO2, CaTiSiO5, FeTiO3,… etc. 1.34 Quartz SiO2 32.5 Feldspar (Na, K)AlSiO8 15.2 Muscovite KAl2(Si3Al)O10(OH,F)2 25.7 Mafic Minerals Various silicates of Fe, Ca, and Mg. 1.97 Others Minerals with low pixels 0.06 Total 100.0

Elemental Abundance

Aside from oxygen, silicon was the most abundant element in the tailings sample followed by aluminum, iron and sulfur (see table 4.3). In this sample, zinc was determined semi quantitatively to be 1.01 wt. %.

Table 4.3 Elemental abundance in the tailings sample Element Tailings Mass % O 42.9 Si 25.4 Al 8.41 Fe 7.97 S 7.45 K 3.51 Na 1.09 Zn 1.01 Ti 0.80 Mg 0.31 H 0.30 F 0.24 Sn 0.10 Mn 0.09 As 0.07 Ca 0.07 Ba 0.07 C 0.04 Pb 0.04 Ag 0.03 Au 0.02 Sr 0.02 Cu P P P B P Mo P Sb P P: Element present below 0.01 wt. %

Of the 1.01 % of zinc the tailings sample, 80 % is found in sphalerite alone as shown in table 4.4 below; a total of 97.2 % of zinc is found in desired minerals for the beneficiation of indium.

Table 4.4 Mineral distribution of zinc in the tailings sample Zn Minerals Distribution (%) Sphalerite 80.9 Franklinite 13.5 Secondary Zn minerals 2.8 High Fe Sphalerite 2.8 Total 100.0

Grain size Distribution and Liberation

Figure 4.5 shows the size distribution of zinc minerals in the tailings sample. It can be seen that more than 50 % of all the minerals shown have grains with a size ranging from 20 to 30 um. Sphalerite makes the exception by having a widely spread grain size distribution, and its P80 lies in the range of 80-85 um according to the QEMSCAN results.

Zn Minerals Grain Size Distribution in Tailings 100.0

90.0

80.0 Sphalerite 70.0

60.0 High Fe Sphalerite

50.0 Franklinite

Volume % Volume 40.0 Secondary Zn Minerals

30.0

20.0

10.0

0.0

Grain Size (um)

Figure 4.5 Grain size distribution of zinc minerals in tailings

Figure 4.6 shows the liberation data of minerals in the tailings sample. It can be seen that zinc minerals are m ostly partially or totally locked. The gangue minerals are for the most part liberated or partially locked.

Locking and Liberation in Tailings

90.0

80.0

70.0

60.0 Locked 50.0 Middling 40.0

Volume % Volume Liberated 30.0

20.0

10.0

0.0

Degree of Liberation

Figure 4.6 Locking and liberation of minerals in tailings

Minerals Association

Figure 4.7 shows the minerals association of zinc minerals in the tailings sample. The Fe- rich sphalerite phase is mainly associated with pyrite and sphalerite in this sample. Sphalerite and franklinite are mainly associated with the gangue minerals which explains their low liberation status. For the gangue minerals, their association with most of the minor minerals in the sample explains their high “middling” status in terms of liberation.

Zn Minerals Associations in Tailings 40.0

35.0

30.0

25.0

20.0

Volume % 15.0Volume

10.0

5.0

0.0

Associated Minerals

Sphalerite Franklinite High Fe Sphalerite Secondary Zn minerals

Figure 4.7 Mineral associations of zinc minerals in tailings

4.1.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) In this report, the sample was designated as “Tail.” Data presented here was taken directly from the generated report.

Gangue minerals were most abundant in the tail, including pyrite. The highlighted sulfide particle consisted of the pyrite and attached sphalerite. The circled particle is the sphalerite- containing pyrite particle correlating to the above MLA false color image. Several other minerals are identified BSE image in Figure 4.8 which includes cassiterite (SnO).

Figure 4.8 Classified MLA image from the tail sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage

FeO Py

Frk

ZnS Qtz

Py SnO

Figure 4.9 BSE image from the tail sample 200 X 400 mesh fraction

Modal Analysis Quartz was the predominant mineral in the tail at 53%, followed by pyrite at 16%, and then muscovite at 13%. In descending order of content in the tail, the minor phases were K-feldspar, siderite, iron oxide, and alunite, ranging from 5% down to 2%. Total sphalerite was 0.88%.

Table 4.5 Mineral content of the tails sample (wt. %) Mineral Formula +100 100 X 200 200 X 400 -400 Comp mesh mesh mesh mesh Quartz SiO2 59.2 56.1 54.1 49.5 52.8 Pyrite FeS2 4.47 13.3 18.6 17.7 15.6 Muscovite KAl2(AlSi3O10)(OH)2 13.7 11.2 10.4 14.2 12.8 K_Feldspar KAlSi3O8 12.6 7.19 4.8 2.93 5.18 Siderite FeCO3 1.65 2.94 2.86 3.38 3.01 FeO Fe2O3 2.24 2.73 2.75 2.89 2.77 Alunite KAl3(SO4)2(OH)6 1.72 1.52 1.36 3.14 2.33 Sphalerite ZnS 1.37 1.12 0.59 0.33 0.65 Arsenopyrite FeAsS 0.12 0.52 0.84 0.51 0.53 Cassiterite SnO2 0.05 0.3 0.3 0.67 0.46 Rutile TiO2 0.13 0.23 0.36 0.66 0.46 Crandallite CaAl3(PO4)(PO3OH)(OH)6 0.21 0.35 0.4 0.57 0.45 Calcite CaCO3 0.23 0.25 0.2 0.39 0.31 FeMnO (Fe,Mn)OOH 0.22 0.37 0.3 0.28 0.3 Chlorite (Mg3,Fe2)Al(AlSi3)O10(OH)8 0.14 0.19 0.2 0.38 0.28 Albite NaAlSi3O8 0.19 0.18 0.16 0.33 0.25 Biotite K(Mg,Fe)3(AlSi3O10)(OH)2 0.23 0.26 0.2 0.24 0.23 Sphalerite_Fe Zn0.8Fe0.2S 0.41 0.24 0.23 0.19 0.23

Table 4.5 Continued +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Franklinite (Zn,Mn,Fe)(Fe,Mn)2O4 0.12 0.05 0.15 0.35 0.23 Plumbogummite PbAl3(PO4)2(OH)5 . H2O P 0.07 0.12 0.31 0.2 Natrojarosite NaFe3(SO4)2(OH)6 0.13 0.16 0.16 0.22 0.19 Plagioclase (Na,Ca)(Al,Si)4O8 0.25 0.21 0.2 0.06 0.14 Topaz Al2SiO4(F,OH)2 0.12 0.13 0.09 0.14 0.13 Grossular Ca3Al2Si3O12 0.12 0.06 0.12 0.08 0.09 Scorodite FeAsO4 . 2H2O 0.06 P 0.09 0.06 0.06 Zircon ZrSiO4 P P 0.08 0.07 0.06 Smithsonite ZnCO3 P P 0.05 0.06 0.05 Barite BaSO4 P P P 0.07 P Apatite Ca5(PO4)3F P P P P P MnO MnOOH P P P P P Galena PbS P P 0.06 P P CuS Cu2S P P P P P Gahnite ZnAl2O4 P P P P P Hemimorphite Zn4Si2O7(OH)2 . H2O P P P P P Andradite Ca3Fe2(SiO4)3 P P P P P Pyroxene CaMgSi2O6 P P P P P Xenotime YPO4 P P P P P Ankerite CaFe(CO3)2 P P P ND P Kyanite Al2SiO5 P P P ND P Magnetite_Ti Fe(Fe,Ti)2O4 P P P ND P Chalcopyrite CuFeS2 P ND P ND P Titanite CaTiSiO5 P P P P P

Table 4.5 Continued +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Dolomite CaMg(CO3)2 ND P P ND P Bismuth Bi ND ND P ND P Anglesite PbSO4 P P P P P Perovskite CaTiO P P ND P P Boulangerite Pb5Sb4S11 P P ND ND P Spessartine Mn3Al2(SiO4)3 P P P P P Monazite (La,Ce)PO4 P P P ND P Chromite FeCr2O4 P ND ND ND P Mass Distribution (%) 10.2 21.9 17.8 50.1 100 P – Mineral present, calculated at less than 0.01%, ND – mineral not encountered

Total silicates in the tail were 72% and the sulfides were 17%. Collectively, oxides, carbonates, sulfates, phosphates and the remaining minerals comprised 11% of the tail (Table 4.6).

Table 4.6 Tail composition by mineral groupings (wt. %) Mineral Group Tail Silicates 72.0 Sulfides 17.0 Oxides 4.26 Carbonates 3.39 Sulfates, phosphates, others 3.32

MLA-calculated Elemental Content

The MLA-calculated zinc was 0.62% in the tail, due essentially to the residual sphalerite.

Table 4.7 Tail MLA-calculated bulk elemental analysis (wt. %) Element Tail Oxygen 41.7 Silicon 29.2 Iron 11.2 Sulfur 9.11 Aluminum 3.83 Potassium 2.23 Zinc 0.62 Tin 0.36 Carbon 0.36 Titanium 0.28 Arsenic 0.26 Calcium 0.22 Manganese 0.18 Hydrogen 0.12 Phosphorus 0.10 Lead 0.09 Magnesium 0.05 Sodium 0.04 Zirconium 0.03 Barium 0.03 Fluorine 0.01 Copper 0.01 Bismuth P Yttrium P Antimony P Cerium P Lanthanum P P – Element calculated at less than 0.01% ND – Element not calculated

Distribution, Grain Size & Liberation

Sphalerite accounted for 91% of the total zinc in the tails, while the carbonate, smithsonite, and the oxide franklinite made up 3 to 4 % each (Table 4.8). Sphalerite grains in the tail were relatively large, with a P80 of 100 um (Figure 4.10). Smithsonite was finer with a P80 of 30 um and franklinite was less than 20 um. The liberation plot for the select zinc-containing minerals in Figure 3.11 shows moderate liberation for each, sphalerite, smithsonite, and franklinite, ranging from about 50 to 70%.

Table 4.8 Zinc distribution by mineral for the tail sample (wt. %) Zn mineral Dist. (%) Sphalerite 91.0 Smithsonite 4.3 Franklinite 3.4 Hemimorphite 0.8 Gahnite 0.5 Total 100.0

Figure 4.10 Mineral grain size distributions for franklinite, smithsonite, and sphalerite

Figure 4.11 Zinc mineral liberation in the tail sample)

Mineral Associations Sphalerite in the tail was mostly associated with quartz and pyrite and the residual cassiterite was associated mainly with quartz (Table 4.9). Table 4.9 Selected mineral associations for the tail sample.

Free Mineral Alunite Biotite FeMnO FeO Franklinite Hemimorphite K_Feldspar Muscovite Natrojarosite Plagioclase Plumbogummite Pyrite Quartz Siderite Smithsonite Sphalerite Sphalerite_Fe Surface Cassiterite 0.5 0.0 0.0 0.5 0.0 0.0 1.9 3.7 0.0 0.0 0.0 2.6 12.6 0.0 0.0 0.0 0.3 76.6

CuS 0.0 0.0 0.0 0.2 0.0 0.9 1.2 5.9 0.3 0.1 0.3 1.4 23.1 0.0 0.0 6.1 3.2 56.6

FeMnO 0.3 0.0 0.0 1.2 0.3 0.0 0.4 1.4 0.2 0.1 0.0 0.5 5.1 0.2 0.1 0.5 0.7 87.9

FeO 0.5 2.3 0.1 0.0 0.9 0.0 2.5 5.5 0.3 0.1 0.0 0.6 16.1 2.4 0.1 0.2 0.0 66.1

Franklinite 0.6 1.5 0.1 6.1 0.0 0.0 0.6 1.5 0.3 0.2 0.0 1.0 4.4 10.8 0.2 0.2 0.4 69.7

Gahnite 24.0 0.0 0.0 0.0 0.2 0.0 0.6 7.0 0.2 0.0 16.2 3.9 2.2 0.0 2.1 12.0 0.9 28.5

Hemimorphite 0.0 0.0 0.0 0.5 0.4 0.0 1.9 6.7 0.0 0.0 0.0 0.0 1.4 0.0 18.2 0.0 0.2 69.8

Magnetite_Ti 0.0 12.4 0.0 3.7 0.2 0.0 0.5 0.4 0.0 0.0 0.0 0.0 10.8 0.8 0.0 0.0 0.0 70.6

MnO 0.0 0.0 1.4 0.2 0.1 0.0 1.3 4.7 0.0 3.3 0.0 0.0 2.7 0.2 0.0 0.0 0.0 86.1

Natrojarosite 0.9 0.2 0.1 1.2 0.1 0.0 3.5 5.0 0.0 0.2 0.0 21.4 22.3 0.6 0.0 0.0 0.1 43.5

Pyrite 0.3 0.0 0.0 0.1 0.0 0.0 1.0 1.5 1.3 0.1 0.0 0.0 6.4 0.0 0.0 0.2 0.4 88.0

Smithsonite 0.2 1.7 0.4 3.0 1.0 6.5 0.6 1.7 0.0 0.0 0.0 0.0 0.3 10.1 0.0 0.0 0.1 73.1

Sphalerite 0.9 0.0 0.2 0.7 0.1 0.0 1.4 2.8 0.0 0.1 0.5 4.4 15.7 0.6 0.0 0.0 2.6 68.1

Sphalerite_Fe 0.6 0.0 0.4 0.4 0.4 0.0 1.9 4.3 0.3 0.0 0.2 10.7 14.5 2.2 0.0 4.6 0.0 58.5

4.1.3.3 Comparison of QEMSCAN and MLA Data Both MLA and QEMSCAN analysis identified quartz as the predominant minerals in the tailings sample followed by muscovite and feldspar. Differences arise on the amount of muscovite and feldspar which are higher according to QEMSCAN results; furthermore, QEMSCAN results show that feldspar and muscovite are well associated with each other and that feldspar also show a significant association with quartz.

Results on the semi quantitative elemental composition of the tailings sample are in agreement with oxygen and silicon being the main elements. Overall MLA numbers are higher than those from QEMSCAN results. MLA analysis was carried out on four different size fractions which provided more resolution of the minerals than QEMSCAN results; nonetheless, the two reports agreed with each other.

4.1.4 Chemical Analysis Two sets of ICP results on the chemical analysis were obtained, one from the sponsor’s side and the other from the research team’s side (tables 4.10 and 4.11 respectively).

Table 4.10 Chemical analysis of the tailings sample provided by the sponsor Element Concentration Concentration Unit Fe = 6.08 ± 0.12 % Zn = 0.89 ± 0.03 % Ca = 0.69 ± 0.04 % Al = 0.56 ± 0.01 % K = 0.24 ± 0.00 % As = 0.17 ± 0.01 % Mn = 0.13 ± 0.01 % Mg = 0.12 ± 0.01 % Pb = 0.11 ± 0.00 %

Cu = 297 ± 9.90 ppm Na = 131 ± 9.19 ppm Cd = 54.0 ± 2.83 ppm In = 52.0 ± 4.24 ppm Ti = 26.5 ± 3.54 ppm Ni = 17.5 ± 0.71 ppm Co = 13.0 ± 1.41 ppm

Table 4.10 Continued Element Concentration Concentration Unit Ag = 10.5 ± 0.71 ppm Cr = 7.50 ± 0.71 ppm Sn < 15 ppm Bi < 10 ppm Ga < 10 ppm Ge < 10 ppm Tl < 10 ppm V < 10 ppm Sb < 10 ppm W < 10 ppm Li < 5 ppm Mo < 5 ppm

Table 4.11 Chemical analysis of the tailings sample provided by CSM Element Concentration Concentration Unit Fe = 4.68 ± 1.0 % Al = 4.87 ± 1.07 % K = 1.83 ± 0.42 % Zn = 0.58 ± 0.13 % Ca = 0.52 ± 0.15 % Mg = 0.16 ± 0.04 % As = 0.13 ± 0.03 % Mn = 0.11 ± 0.02 % Li = 0.11 ± 0.01 % Na = 0.11 ± 0.01 % Ti = 0.10 ± 0.02 %

Pb = 905 ± 181 ppm P = 428 ± 89.6 ppm *Cu = 313 ppm Cr = 123 ± 24.4 ppm Sb = 103 ± 3.79 ppm V = 88.0 ± 17.8 ppm Ni = 69.0 ± 11.3 ppm Sn = 31.3 ± 3.06 ppm * Data generated from AAS analysis

Table 4.11 Continued Element Concentration Concentration Unit Cd = 24.0 ± 5.20 ppm Ga = 20.7 ± 5.77 ppm In = 18.3 ± 3.79 ppm Co = 17.0 ± 10.4 ppm Tl = 17.0 ± 7.81 ppm Zr = 14.7 ± 0.58 ppm Bi = 7.00 ± 7.00 ppm *Ag = 5.7 ± 0.58 ppm Ge < 10.0 ppm Mo < 10.0 ppm W < 10.0 ppm

Overall, most numbers agrees with each other when comparing the two sets of results. Aluminum, chromium, and titanium number are considerably lower on the sponsor’s side compared to the CSM data. Indium on the other hand is highly considerably higher on the sponsor’s side. An indium chemical analysis was conducted on the tailings sample at an independent lab (Hazen Research), and the indium content in the sample was determined to be 20.0 ppm which agreed with the CSM generated data.

4.2 Jarosite Sample

Upon receipt, the jarosite sample was dried overnight. The sample was homogenized by mixed using a Jones Splitter. Afterwards, the sample was split in 0.5 kg lots and was stored.

4.2.1 Particle Size Distribution The jarosite sample was very fine and its size distribution appeared narrow enough to decide for microtrac analysis rather than wet sieve. From one of the splits, a representative sample for the analysis, and the results are shown in figure 4.12 below. As shown in the image above, no particles in the sample was larger than 55 um, and the P80 was determined to be 7.18 um.

Figure 4.12 Particle size distribution of the jarosite sample via Microtrac size analysis

4.2.2 X-Ray Diffraction Analysis Table 4.12 Minerals identified by XRD for the jarosite sample Compound Name Chemical Formula Score Mineral Name Sodium Iron Sulfate NaFe (SO ) (OH) Natrojarosite 3 4 2 6 48 Hydroxide Potassium Hydronium Iron K (H O) Fe (SO ) (OH) Hydroniumjarosite 0.02 3 0.98 3 4 2 6 25 Sulfate Hydroxide Calcium Sulfate CaSO4 24 Copper Iron Sulfide CuFeS2 23 Chalcopyrite Lead Iron Sulfate Hydroxide PbFe6(SO4)4(OH)12 21 Plumbojarosite Silicon Oxide SiO2 20 Coesite Lead Zinc Iron Sulfate ZnFe Pb(SO ) (OH) Beaverite 2 4 2 6 17 Hydroxide Silver Aluminum Iron Sulfate AgFe Al (SO ) (OH) Argentojarosite 2.88 0.12 4 2 6 17 Hydroxide

Figure 4.13 shows the XRD generated results for the jarosite sample. The minerals identified are shown in table 4.12; the sample is shown to be comprised primarily of hydrates of sulfate. Natrojarosite score the highest, and there possibility of the hydronium and potassium jarosite being present. More complex phase minerals that showed up are beaverite, plumbojarosite, and argentojarosite.

Figure 4.13 XRD generated pattern for the jarosite sample

4.2.3 Mineralogical Analysis 4.2.3.1 QEMSCAN Mineralogy Data Modal Abundance Figure 4.14 shows image of jarosite after SEM scan. The sample is mainly comprised of hydronium jarosite, pyrite, franklinite and calcium sulfate as shown in table 4.13. There is some evidence of the occurrence of some iron oxides, other zinc minerals and, gangue minerals such as quartz, feldspar, and muscovite.

Figure 4.14 Graphic Illustration of jarosite sample

As shown in table 4.13, the jarosite sample is predominantly comprised hydronium jarosite followed by pyrite, franklinite, iron oxides, and calcium sulfate. The minerals of interest for indium beneficiation (sphalerite, iron-rich sphalerite, and franklinite) amount to 9.83 % of the sample.

Table 4.13 Mineral abundance in the jarosite sample Minerals Chemical Formula Mass % Sphalerite ZnS 0.75 Franklinite ZnFe2O4 9.06 High Fe Sphalerite (Zn,Fe)S 0.02 Secondary Zn minerals Zn4Si2O7(OH)2. H2O, Zn2(SiO4), 0.69 ZnCO3.FeCO3, ZnAlO4, …etc. Ag-sulphide Ag2S 0.25 Chalcopyrite CuFeS 0.01

Table 4.13 Continued Minerals Chemical Formula Mass % Pyrite FexSy, and FeS 14.47 Other sulphides Sulfides of Pb, Sb, Cu, Ag, and Zn 0.12 3+ Hydronium-Jarosite (H3O)Fe3 (SO4)2(OH)6 69.61 Ca-sulphate CaSO4 1.12 Other Sulfates BaSO4, KAl3(SO4)2(OH)6, 0.74 SrSO4,…etc. Fe-Oxide Fe3+OOH 2.08 Mn-Fe oxide Oxides of Mn and Fe 0.01

Ti-minerals TiO2, CaTiSiO5, FeTiO3,… etc. 0.09 Quartz SiO2 0.42 Feldspar (Na, K)AlSiO8 0.17 Muscovite KAl2(Si3Al)O10(OH,F)2 0.25 Mafic Minerals Silicates of Fe and Mg 0.10 Others Minerals with low pixels 0.07 Total 100.0

Elemental Abundance Oxygen, iron, and sulfur were the main elements in the jarosite sample. In this sample, the semi quantitative zinc content was determined to be 2.94 wt. %. Of the 2.94 % of zinc in the Jarosite sample, the majority is found in the franklinite mineral as shown in table 4.15. A notable observation here is that 94.6 % of total zinc was found in the minerals targeted for indium beneficiation.

Table 4.14 Elemental abundance in the jarosite sample Element Jarosite Mass % O 40.23 Fe 36.79 S 16.94 Zn 2.94 H 1.38 Ba 0.38 Ca 0.33 Si 0.32 Ag 0.18 Al 0.14 Mo 0.09 Ti 0.05

Table 4.14 Continued Element Jarosite Mass % C 0.04 Au 0.03 K 0.02 Sn 0.02 Pb 0.01 Mg 0.01 Na 0.01 P 0.01 Sr 0.01 Mn P F P Cu P As P B P Sb P P: Element below 0.01 wt. %

Table 4.15 Mineral distribution of zinc in the jarosite sample Zn Minerals Distribution (%) Franklinite 77.6 Sphalerite 16.6 Secondary Zn minerals 5.4 High Fe Sphalerite 0.4 Total 100

Grain Size Distribution and Liberation Figure 4.15 shows the grain size distribution of minerals assumed to carry the indium value. As shown in the figure, more than 80 % of grains of sphalerite, franklinite, and hydronium jarosite are between 20 and 30 um. Figure 4.16 shows the liberation of minerals in the jarosite sample. Most of minerals are > 50 % liberated except for the gangue minerals such as quartz, muscovite, and feldspar. These minerals are mainly middling rather liberated.

In-bearing Minerals Grain Size Distribution in Jarosite 100.0 90.0 80.0 70.0 60.0 Franklinite Hydronium jarosite 50.0 Sphalerite

40.0 Volume % Volume 30.0 20.0 10.0 0.0

Grain Size (um) Figure 4.15 Grain size distribution of In-bearing minerals in jarosite

Locking and Liberation in Jarosite 100.0 90.0 80.0 70.0 60.0 50.0

40.0 Volume % Volume 30.0 20.0 10.0 0.0

Degree of Liberation Locked Middling Liberated

Figure 4.16 Locking and liberation of minerals in jarosite

Minerals Association Figure 4.17 shows the minerals associations of zinc minerals in the jarosite sample. Zinc minerals are mostly associated with the hydronium jarosite and the sulfide minerals. Data shows no evidence of their association with gangue minerals.

Mineral Association of Zn Minerals in Jarosite 70.0

60.0

50.0

40.0

30.0 Volume % Volume

20.0

10.0

0.0

Associated Minerals

Sphalerite Franklinite High Fe Sphalerite Secondary Zn minerals

Figure 4.17 Mineral associations of zinc minerals in jarosite

4.2.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) The MLA false color image from the jarosite 200 X 400 mesh fraction is shown in Figure 4.18. A multi-phasic sample of mostly franklinite, gahnite and quartz is highlighted. Below in Figure 4.19, the circled particle in the back-scattered electron (BSE) corresponds to the particle highlighted in the MLA image above. The BSE image reveals that the particle is highly porous, with a core of mostly gahnite (Ghn) and a franklinite (Frk) “shell”. Other minerals are identified to exhibit the variation in gray level produced by each of the minerals. Barite (Ba), iron oxide (FeO), pyrite (Py).

Figure 4.18 Classified MLA image from the jarosite sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage

FeO Py

Qtz Ba

Frk

Ghn

Frk

Figure 4.19 BSE image from the jarosite sample 200 X 400 mesh fraction

The BSE image in Figure 4.20 shows how fine-grained the jarosite sample was, keeping in mind that over 95% of the sample reported to the -400 mesh fraction. An isolated particle of iron oxide is identified.

FeO

Figure 4.20 BSE from the jarosite sample -400 mesh fraction

Modal Analysis

Natrojarosite comprised 60% of the jarosite sample, followed in abundance by franklinite and iron oxide at 13%, each (Table 4.16). Barite, quartz, and pyrite were minor constituents at 2 to 3% each. It is interesting to note that total sphalerite was 5 to 6% in the +200 mesh fractions and about 0.5 to 2% in the -200 mesh fractions.

Table 4.16 Mineral content of the jarosite sample (wt. %) +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Natrojarosite NaFe3(SO4)2(OH)6 42.3 43.3 9.76 61.5 60.5 Franklinite (Zn,Mn,Fe)(Fe,Mn)2O4 6.81 27.0 48.7 12.5 13.2 FeO Fe2O3 1.54 3.40 12.8 13.2 13.0 Barite BaSO4 1.25 4.04 7.56 2.91 2.99 Quartz SiO2 25.4 8.08 8.08 2.55 2.78 Pyrite FeS2 0.12 0.26 1.69 2.35 2.30 Muscovite KAl2(AlSi3O10)(OH)2 2.43 1.52 1.55 0.73 0.76 Cassiterite SnO2 1.14 0.55 0.1 0.73 0.72 Pyroxene CaMgSi2O6 0.71 0.52 0.76 0.61 0.61 Gahnite ZnAl2O4 0.84 1.24 1.85 0.50 0.54 K_Feldspar KAlSi3O8 2.06 1.10 1.28 0.50 0.53 Sphalerite ZnS 2.64 2.52 1.18 0.47 0.52 Anglesite PbSO4 0.48 0.64 0.59 0.34 0.35 Siderite FeCO3 P P 0.16 0.20 0.19 Sphalerite_Fe Zn0.8Fe0.2S 2.95 2.45 1.05 0.12 0.18 Rutile TiO2 P 0.12 0.12 0.14 0.14 Spessartine Mn3Al2(SiO4)3 0.14 0.22 0.46 0.13 0.13 Zircon ZrSiO4 P 0.16 0.06 0.07 0.07 Biotite K(Mg,Fe)3(AlSi3O10)(OH)2 P 0.10 0.16 0.05 0.06 Smithsonite ZnCO3 P ND ND 0.05 0.05 Chlorite (Mg3,Fe2)Al(AlSi3)O10(OH)8 0.08 P 0.4 P 0.05 Albite NaAlSi3O8 0.77 0.16 0.25 P 0.05 Sulfur S 0.08 1.04 0.46 P P CuS Cu2S 0.19 P P P P Monazite (La,Ce)PO4 P P ND P P Chromite FeCr2O4 P ND P P P Grossular Ca3Al2Si3O12 P P 0.08 P P Kyanite Al2SiO5 1.93 0.39 0.17 P P Plagioclase (Na,Ca)(Al,Si)4O8 1.25 0.45 0.21 P P

Table 4.16 Continued +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Magnetite_Ti Fe(Fe,Ti)2O4 0.07 P P P P Corundum Al2O3 0.28 P P P P Hemimorphite Zn4Si2O7(OH)2. H2O 0.08 P 0.07 P P Calcite CaCO3 1.53 0.17 0.07 P P Arsenopyrite FeAsS ND ND P P P Gypsum CaSO4.2H2O 2.36 0.13 P ND P Titanite CaTiSiO5 P P P P P Scorodite FeAsO4. 2H2O P P P P P Crandallite CaAl3(PO4)(PO3OH)(OH)6 P P P P P Xenotime YPO4 0.15 ND P P P Celestine SrSO4 0.10 0.13 ND ND P Andradite Ca3Fe2(SiO4)3 P P P ND P Alunite KAl3(SO4)2(OH)6 P P P P P Topaz Al2SiO4(F,OH)2 0.13 ND P ND P FeMnO (Fe,Mn)OOH ND P P ND P Perovskite CaTiO ND ND P ND P MnO MnOOH P P P ND P Chalcopyrite CuFeS2 P ND P ND P Ankerite CaFe(CO3)2 P ND ND ND P Galena PbS P P P ND P Apatite Ca5(PO4)3F P ND P ND P Mass Distribution (%) 0.22 1.88 1.32 96.6 100 P – Mineral present, calculated at less than 0.01%, ND – mineral not encountered

The jarosite sample was 64% sulfate & phosphates, of which was mostly the sulfate natrojarosite, and 28% oxides/hydroxides. Silicates were 5% and sulfides were 3% with a trace of carbonates as shown in Table 4.17.

Table 4.17 Jarosite composition by mineral groupings (wt. %) Mineral Group Jarosite Sulfates, phosphates, others 63.9 Oxides/hydroxides 27.7 Silicates 5.13 Sulfides 3.04 Carbonates 0.26

MLA-calculated Elemental Content

The MLA-calculated bulk elemental analysis is shown in Table 4.18. The elemental composition was derived from the modal mineralogy and the assigned chemical formula as defined in Table 2. The zinc content of the jarosite was calculated at 1.9%.

Table 4.18 Jarosite MLA-calculated bulk elemental analysis (wt. %) Element Jarosite Oxygen 39.5 Iron 35.4 Sulfur 9.96 Manganese 4.19 Sodium 2.87 Zinc 1.9 Silicon 1.86 Barium 1.76 Hydrogen 0.76 Tin 0.57 Aluminum 0.42 Lead 0.24 Potassium 0.15 Calcium 0.13 Titanium 0.09 Magnesium 0.08 Zirconium 0.03 Copper 0.03

Table 4.18 Continued

Element Jarosite Carbon 0.03 Chromium 0.01 Cerium 0.01 Lanthanum 0.01 Arsenic 0.01 Phosphorus 0.01 Yttrium P Strontium P Fluorine P P – Element calculated at less than 0.01% ND – Element not calculated

Distribution, Grain Size & Liberation The zinc content was due primarily to the oxides franklinite and gahnite that accounted for 75% of the total zinc in the jarosite sample. Sphalerite contributed an additional 24% to the overall zinc balance.

Table 4.19 Zinc distribution by mineral for the jarosite sample (wt. %) Zn mineral Dist. (%) Franklinite 64.7 Sphalerite 23.5 Gahnite 10.0 Smithsonite 1.4 Hemimorphite 0.3 Total 100

The grain size distributions for the zinc minerals in Figure 4.21 indicate that they were similarly sized with P80’s between 15 to 20 um. The liberation by particle composition for the predominant zinc minerals in the jarosite sample are shown in Figure 4.22. Both franklinite and sphalerite were well liberated at more than 90% liberation, while the less abundant gahnite was more poorly liberated at around 70% liberation. Values cited are for particles greater than 95% in composition of their respective mineral.

Figure 4.21 Mineral grain size distributions for franklinite, gahnite, and sphalerite

Figure 4.22 Liberation for the zinc minerals in the jarosite sample

Mineral Associations The free surface values tabulated for the mineral associations in Table 4.20 show a high degree of liberation with many values over 90%. The zinc minerals franklinite and sphalerite have free surface values of over 90% while gahnite is around 80%. Since liberation is so high little can be said about the associations. Franklinite shows a small affinity for the major phase, natrojarosite. Sphalerite shows only appreciable associations with itself. Gahnite shows its greatest association with barite

Table 4.20 Mineral associations for selected phases in the jarosite sample

Free Mineral Barite FeO Franklinite Hemimorphite Muscovite Natrojarosite Quartz Siderite Smithsonite Spessartine Sphalerite Sphalerite_Fe Surface Cassiterite 0.0 0.0 0.0 0.0 0.0 1.1 0.0 0.0 0.0 0.0 0.0 0.0 97.9

CuS 0.0 0.0 0.1 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.2 10.3 88.8

FeMnO 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0

FeO 0.0 0.0 1.5 0.0 0.0 0.9 0.0 0.0 0.0 0.0 0.0 0.0 97.3

Franklinite 0.2 1.0 0.0 0.0 0.4 2.6 0.5 0.0 0.0 0.0 0.0 0.0 94.7

Gahnite 10.9 0.0 4.0 0.0 2.1 1.8 0.1 0.0 0.0 0.0 0.0 0.0 80.9

Hemimorphite 0.0 0.0 2.8 0.0 26.9 0.3 1.0 0.0 13.6 0.3 0.0 0.0 53.6

Magnetite_Ti 0.0 19.9 4.7 0.0 0.1 0.0 0.7 0.0 0.0 0.0 0.0 0.0 74.0

MnO 48.7 0.0 0.3 0.0 0.0 0.1 9.0 0.0 0.0 16.8 0.0 0.0 25.1

Natrojarosite 0.0 0.1 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 99.5

Pyrite 0.0 0.0 0.0 0.0 0.0 1.0 0.9 0.0 0.0 0.0 0.0 0.1 97.6

Smithsonite 0.0 0.0 4.3 4.9 0.0 0.0 0.0 31.7 0.0 0.0 0.0 0.0 59.1

Sphalerite 0.0 0.0 0.7 0.0 0.0 0.2 0.1 0.0 0.0 0.0 0.0 5.8 92.2

Sphalerite_Fe 0.0 0.0 0.1 0.0 0.0 1.0 0.2 0.0 0.0 0.0 12.9 0.0 79.6

4.2.3.3 Comparison of QEMSCAN and MLA Data For the jarosite sample the main minerals identified was natrojarosite and hydronium jarosite according to MLA and QEMSCAN respective data, the difference lying solely on software definitions for minerals. The abundance of pyrite and iron oxides were different in the sense that pyrite was determined to be 2.3 from MLA while it amounted to 14.5 from QEMSCAN data. Similarly the amount of iron oxides was determined to be 13.0 % from MLA while it amounted to 2.1 % from QEMSCAN results.

Both reports determined oxygen, iron, and sulfur to be the predominant elements in the sample. With the stronger resolution it used, MLA identified the presence of rare earth metals to a hundredth of a percent; comparatively, QEMSCAN captured their presence however to a lesser amount. Overall, the two reports generated data that agreed with each other for the most part.

4.2.4 Chemical Analysis Tables 4.21 and 4.22 show results of the chemical analysis generated by the sponsor and CSM respectively.

Table 4.21 Chemical analysis of the jarosite sample provided by the sponsor Element Concentration Concentration Unit Fe = 21.4 % Na = 2.18 % Pb = 1.97 % Zn = 1.55 % Al = 0.59 % K = 0.44 % Cu = 0.20 % H2O = 33.4 %

Co = 793 ppm Mn = 514 ppm Mg = 437 ppm In = 389 ppm Ti = 386 ppm Cr = 213 ppm Cd = 201 ppm Ag = 150 ppm

Table 4.21 Continued Element Concentration Concentration Unit Au < 100 ppm Mo < 50.0 ppm Ni = 19.0 ppm Ge < 10.0 ppm Hg < 10.0 ppm Sb < 10.0 ppm Tl < 10.0 ppm V < 10.0 ppm W < 10.0 ppm Ca = 5.01 ppm Li < 5.00 ppm Si = 1.36 ppm

Table 4.22 Chemical analysis of the jarosite sample provided by CSM Element Concentration Concentration Unit Fe = 18.7 ± 0.35 % Ca = 3.07 ± 0.21 % Na = 1.98 ± 0.05 % Pb = 1.54 ± 0.02 % Zn = 1.39 ± 0.03 % K = 0.31 ± 0.06 % Al = 0.27 ± 0.03 % Li = 0.20 ± 0.01 %

Mn = 937 ± 29.3 ppm Cu = 860 ± 99.4 ppm As = 700 ± 9.61 ppm In = 246 ± 3.06 ppm Cd = 168 ± 10.8 ppm Ni = 156 ± 2.08 ppm Sr = 146 ± 51.2 ppm Ba = 137 ± 76.9 ppm *Ag = 114 ± 1.00 ppm Cr = 111 ± 7.51 ppm Ge = 84.0 ± 42.7 ppm

Table 4.22 Continued

Element Concentration Concentration Unit V = 78.3 ± 4.04 ppm Bi = 69.7 ± 2.08 ppm Sn = 61.7 ± 30.9 ppm Ga = 61.3 ± 0.58 ppm Sb = 48.3 ± 19.4 ppm Tl = 35.3 ±0.58 ppm Mo = 33.3 ± 12.5 ppm Zr = 10.0 ± 0.00 ppm W < 10.0 ppm Ti < 10.0 ppm Co < 5.00 ppm Mg < 5.00 ppm P < 5.00 ppm * Data generated from AAS analysis

4.3 Ferrite Sample

Upon receipt, the ferrite sample was dried overnight. The sample was homogenized by mixed using a Jones Splitter. Afterwards, the sample was split in 1.0 kg lots and was stored.

4.3.1 Particle Size Distribution From one of the splits, a representative sample was taken for analysis. The ferrite sample had a widely spread size distribution which did not allow for a direct microtrac analysis. Therefore, a wet sieve analysis was conducted on the as received material; the -400 Tyler mesh fraction was analyzed on the microtrac, and the results were combined to generate a particle size distribution as the results are shown in figure 3.23 below. As shown in the figure, a fairly large fraction of particles in the sample are below 50 um while there are still instances of particles as large as 1600 um in size. The P80 in this case was determined to be 18.1 um while the P90 was calculated to be 80.4 um.

Figure 4.23 Cumulative particle size distribution of the ferrite sample via wet sieve

4.3.2 X-Ray Diffraction Analysis

Table 4.23 Minerals identified by XRD for the ferrite sample Compound Name Chemical Formula Score Mineral Name Cadmium Copper Gallium Cu Cd Ga O 0.5 0.5 2 4 43 Oxide Zinc Manganese Iron Oxide (Zn, Mn, Fe) (Fe, Mn)2O4 40 Franklinite Zinc Iron Oxide ZnFe2O4 40 Franklinite Cadmium Nickel Zinc Iron Zn Cd Fe Ni O Cd-Zn-Ni ferrite 0.2 0.3 2 0.5 4 32 Oxide Magnesium Oxide MgO 28 Periclase Magnesium Iron Oxide MgFe2O4 26 Magnesioferrite Iron Oxide Fe3O4 26 Magnetite Calcium Magnesium Manganese (Ca, V)0.01 (Mg0.03, Mn0.01)2 Ferriannite Aluminum Iron Silicon Titanium Ti0.74Fe2.1Al0.05Si0.01O4 26 Vanadium Oxide Manganese Iron Oxide MnFe2O4 25 Jacobsite Iron Silicon Oxide Fe7SiO10 16

Figure 4.24 shows the XRD pattern generated for the ferrite sample. As shown in table 4.23 above, the sample is mainly comprised of the mineral franklinite and the manganese rich franklinite. Other than franklinite, XRD minerals search identified a variety of spinel phases such as the copper cadmium gallium oxide, the ferrianite, the cadmium zinc nickel ferrite, magnesioferrite, and jacobsite. A silicate phase was also identified along with some lead selenite and its sulfate.

Figure 4.24 XRD pattern for the ferrite sample

4.3.3 Mineralogical Analysis 4.3.3.1 QEMSCAN Mineralogy Data Modal Abundance Figure 4.25 shows an illustration of the ferrite sample after SEM scan. The sample is mainly made up of franklinite in the aqua color which encloses a variety of other minerals including the gangue minerals. The graphical illustration suggests that franklinite is neither locked nor completely liberated while other minerals will mostly be locked.

Figure 4.25 Graphic illustration of the ferrite sample

Table 4.24 shows the mineral abundance in the ferrite sample; aside from the outstanding 83.09 % franklinite, there are iron oxides, sphalerite, smithsonite siderite and galena that assay above 1.0 wt. %.

Table 4.24 Minerals abundance in the ferrite sample Minerals Chemical Formula Mass % Sphalerite ZnS 5.83 high Fe Sphalerite (Zn,Fe)S 0.07 Smithsonite Siderite ZnCO3.FeCO3 2.60 Hemimorphite Zn4Si2O7(OH)2.(H2O) 0.33 Willemite Zn2SiO4 0.50 Franklinite ZnFe2O4 83.1 Franklinite (Mn) Zn0.6Mn0.8Fe1.6O4 0.19 Ag- sulfide Ag2S 0.06 Chalcopyrite CuFeS2 0.02 Galena PbS 1.41 Pyrite FexSy, and FeS 0.20 Other sulfides Sulfides of Pb, Sb, Cu, Ag, and Zn 0.01 Barite BaSO4 0.02 Ca- sulfate CaSO4 0.38 Mn-sulfate MnSO4.7H2O 0.07 Other sulfates Sulfates including barite, alunite, celestine,…etc. 0.02 Calcite CaCO3 0.57 2+ Ankerite Ca(Fe , Mg, Mn)) (CO3)2 0.01 Fe- oxides Fe3+OOH 2.72 Mn-oxide Variety of Manganese oxides 0.57 Ti-minerals TiO2, CaTiSiO5, FeTiO3,… etc. 0.02 Feldspar (Na, K)AlSiO8 0.08 Fe-Olivine (Fe, Mg)2SiO4 P Mafic Minerals Silicates of Fe and Mg 0.27 Muscovite KAl2(Si3Al)O10(OH,F)2 0.30 Quartz SiO2 0.63 Apatite Ca5(PO4)3F P Others Minerals with low pixels 0.04 Total 100.0 P: Mineral present below 0.01 wt. % Elemental Abundance In the ferrite sample, iron, zinc, and oxygen turned out to be the main elements as shown in table 4.25. Manganese and lead are also present at concentration greater than 1.0 wt. %. Of the 27.7 % zinc found in the sample, 81.3 % is found in franklinite (see table 4.26), and 95.7 of total zinc is found in minerals of interest for the beneficiation of indium namely, the sphalerite, franklinite, high iron sphalerite, and the manganese rich franklinite minerals.

Table 4.25 Elemental abundance in the ferrite sample Element Ferrite Mass % Fe 39.4 Zn 27.7 O 26.2 S 2.62 Mn 1.31 Pb 1.04 C 0.76 Si 0.59 Ca 0.19 Al 0.09 Ag 0.07 H 0.05 Au 0.02 K 0.02 Mg 0.02 Cu 0.01 Ba 0.01 Na 0.01 Ti 0.01 As P F P Sr P P P Sn P B P Mo P Sb P P: Element present below 0.01 wt. %.

Table 4.26 Mineral distribution of zinc in the ferrite sample Zn Minerals Distribution (%) Franklinite 81.3 Sphalerite 14.1 Smithsonite Siderite 2.54 Willemite 1.06 Hemimorphite 0.64 high Fe Sphalerite 0.15

Table 4.26 Continued Zn Minerals Distribution (%) Franklinite (Mn) 0.11 Others 0.04 Total 100

Grain Size Distribution Figure 4.26 shows the grain size distribution for zinc minerals in the ferrite sample.

According to these results, most of the minerals are fine in size with a P80 value between 50 and 60 um. Franklinite, which is the predominant mineral in the sample, had grains as large as 350 um according to these results.

Zn Minerals Grain Size Distribution 100.0

90.0

80.0 Franklinite

70.0 Franklinite (Mn) Hemimorphite 60.0 Smithsonite Siderite 50.0 Sphalerite

Volume % Volume 40.0 Willemite 30.0

20.0

10.0

0.0

Grain Size (um) Figure 4.26 Grain size distribution of zinc minerals in ferrite

Figure 4.27 shows the liberation of minerals in the ferrite sample. According to the data, zinc minerals such as sphalerite, and its iron rich phase, willemite, hemimorphite, and smithsonite are mostly locked or not entirely liberated. Franklinite on the other shows a lot of middling in its liberation which suggests that it encapsulates other minerals during the roasting process. Gangue minerals also follow the locked-middling trend that zinc minerals showed.

Locking and Liberation in Ferrite 90.0 80.0 70.0 60.0 Locked 50.0 Middling 40.0 Liberated

30.0 Volume % Volume 20.0 10.0 0.0

Degree of Liberation Figure 4.27 Locking and liberation of minerals in ferrite

Minerals Associations

Zn Minerals Associations in Ferrite 90.0 80.0 Sphalerite 70.0 high Fe Sphalerite Smithsonite 60.0 Siderite Hemimorphite 50.0 Willemite

40.0 Volume % Volume 30.0 20.0 10.0 0.0

Associated Minerals

Figure 4.28 Mineral associations of zinc minerals in the ferrite sample

Figure 4.28 shows the minerals association of zinc minerals in the ferrite sample. As seen in the figure, franklinite is mainly associated with the sphalerite minerals and the oxides of iron and manganese. Additionally, it is seen that all zinc minerals are directly associated with franklinite in this particular sample.

4.3.3.2 MLA Data (Report Prepared by G. Wyss from Montana Tech) The false color image from the ferrite sample shows that the major phase is franklinite (brown). Sphalerite is engulfed in franklinite in the highlighted particle in Figure 4.29.

Figure 4.29 Classified MLA image from the ferrite sample 200 X 400 mesh sieve fraction. Particle inset units are in pixels and concentration palette values are in surface area percentage

The BSE image reveals that sphalerite is concentrically encrusted by the zinc-iron oxide classified as franklinite in Figure 4.30. The “franklinite” obviously is compositionally zoned as seen by the variation in the gray level. The “salt & pepper” particles that were classified as franklinite appear to be fine-grained agglomerates of zinc-iron-manganese oxides.

MnO

Ghn

ZnS Frk Frk

Figure 4.30 BSE image from the ferrite sample 200 X 400 mesh fraction

Modal Analysis Franklinite was the most abundant phase in the ferrite sample at 88%. Manganese oxides were more prevalent in the ferrite than in the jarosite, and the somewhat “pure” manganese oxide (MnO) was 3.5% of the sample. The zinc-bearing minerals hemimorphite was at 0.85%, smithsonite was 0.48%, and total sphalerite was 0.60% (Table 4.27).

Table 4.27 Mineral content of the ferrite sample (wt. %) +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Franklinite (Zn,Mn,Fe)(Fe,Mn)2O4 47.1 87.9 86.0 92.8 87.6 MnO MnOOH 22.4 3.40 2.21 1.50 3.54 FeO Fe2O3 1.70 2.47 4.88 2.12 2.47 Quartz SiO2 7.60 2.57 2.94 0.69 1.82 Hemimorphite Zn4Si2O7(OH)2 . H2O 3.31 1.07 0.84 0.49 0.85 Calcite CaCO3 5.16 0.32 0.26 0.10 0.55 Smithsonite ZnCO3 4.39 0.36 0.13 0.10 0.48 Anglesite PbSO4 0.41 0.17 0.23 0.62 0.48 Sphalerite_Fe Zn0.8Fe0.2S 0.29 0.35 0.48 0.47 0.44 Gahnite ZnAl2O4 0.13 0.14 0.26 0.30 0.26 Muscovite KAl2(AlSi3O10)(OH)2 1.06 0.26 0.24 0.09 0.21 Siderite FeCO3 1.46 0.21 0.26 P 0.21 FeMnO (Fe,Mn)OOH 0.35 0.13 0.43 0.14 0.19 K_Feldspar KAlSi3O8 1.03 0.13 0.15 0.07 0.16 Sphalerite ZnS 0.43 0.15 0.19 0.12 0.16 Plagioclase (Na,Ca)(Al,Si)4O8 0.92 0.07 0.06 0.05 0.12 Pyroxene CaMgSi2O6 0.32 0.05 0.09 P 0.07 Albite NaAlSi3O8 0.58 P 0.07 P 0.06 Galena PbS P P P 0.07 0.05 CuS Cu2S 0.06 P 0.07 0.05 0.05 Natrojarosite NaFe3(SO4)2(OH)6 P P P 0.06 P Grossular Ca3Al2Si3O12 0.32 P P P P Barite BaSO4 0.12 P P P P Dolomite CaMg(CO3)2 0.21 P P P P Chlorite (Mg3,Fe2)Al(AlSi3)O10(OH)8 0.10 P P P P Magnetite_Ti Fe(Fe,Ti)2O4 0.10 P P P P Biotite K(Mg,Fe)3(AlSi3O10)(OH)2 P P P P P Rutile TiO2 P P P P P Ankerite CaFe(CO3)2 P P P P P

Table 4.27 Continued +100 100 X 200 200 X 400 -400 Mineral Formula mesh mesh mesh mesh Comp Ankerite CaFe(CO3)2 P P P P P Spessartine Mn3Al2(SiO4)3 P P P ND P Gypsum CaSO4 . 2H2O 0.07 P P ND P Selenium Se ND ND ND P P Pyrite FeS2 P P P ND P Chalcopyrite CuFeS2 P P P P P Andradite Ca3Fe2(SiO4)3 P P P ND P Cassiterite SnO2 P P P P P Scorodite FeAsO4 . 2H2O P P P ND P Topaz Al2SiO4(F,OH)2 P P ND ND P Crandallite CaAl3(PO4)(PO3OH)(OH)6 P P P ND P Apatite Ca5(PO4)3F P P P ND P Bismuth Bi P P P P P Chromite FeCr2O4 ND P P ND P Corundum Al2O3 P P P ND P REE_SrCO3 Sr(Ce,La)(CO3)2(OH) . H2O ND ND ND P P Titanite CaTiSiO5 P P P ND P Kyanite Al2SiO5 P ND ND ND P Sulfur S P ND ND ND P Celestine SrSO4 ND ND P ND P Zircon ZrSiO4 P P P ND P Alunite KAl3(SO4)2(OH)6 P P ND ND P Xenotime YPO4 P P ND ND P Monazite (La,Ce)PO4 P P ND ND P Plumbogummite PbAl3(PO4)2(OH)5 . H2O P ND ND ND P Perovskite CaTiO P ND ND ND P Mass Distribution (%) 7.8 17.4 11.9 62.9 100 P – Mineral present, calculated at less than 0.01%, ND – mineral not encountered

Oxides/hydroxides dominated the ferrite sample at 94% of the overall composition. Silicates were 3.4%, carbonates at 1.3% and sulfides at 0.7% (Table 4.28).

Table 4.28 Ferrite composition by mineral groupings (wt. %) Mineral Group Ferrite Oxides/hydroxides 94.1 Silicates 3.39 Carbonates 1.27 Sulfides 0.70 Sulfates, phosphates, others 0.58 Oxides 94.1

MLA-calculated Elemental Content The MLA-calculated zinc content was 9.3% as shown in Table 4.29. Manganese was also concentrated in the ferrite sample was about 30% of the calculated elemental content.

Table 4.29 Ferrite sample MLA-calculated bulk elemental analysis (wt. %). Element Ferrite Iron 29.9 Manganese 29.7 Oxygen 28.5 Zinc 9.32 Silicon 1.12 Lead 0.37 Sulfur 0.28 Calcium 0.26 Aluminum 0.18 Carbon 0.14 Hydrogen 0.05 Potassium 0.05 Copper 0.04 Barium 0.02 Magnesium 0.01 Sodium 0.01 Titanium 0.01

Distribution, Grain Size & Liberation Franklinite was primary contributor of both iron and zinc to the ferrite samples as shown by the elemental distributions for iron and zinc in Table 4.30 and Table 4.31, respectively. Collectively, hemimorphite, smithsonite, and sphalerite were responsible for only about 10% of the total zinc in the ferrite.

Table 4.30 Iron distribution by mineral for the ferrite sample (wt. %) Iron-bearing Mineral Dist. (%) Franklinite 93.4 FeO 5.8 Siderite 0.3 FeMnO 0.2 Sphalerite_Fe 0.2 Total 99.9

Table 4.31 Zinc distribution by mineral for the ferrite sample (wt. %) Zinc-bearing Mineral Dist. (%) Franklinite 87.7 Hemimorphite 4.9 Smithsonite 2.7 Sphalerite 3.7 Gahnite 1.0 Total 100

The grain size distribution P80’s for the iron-bearing minerals franklinite and iron oxide were similar at around 50 to 60 um as shown in Figure 4.31. The liberation plots in Figure 4.32 show franklinite at about 90% liberation and iron oxide at just above 40% liberation. The grain size distributions for the zinc minerals show a wide variation in the P80’s (Figure 4.33).

Sphalerite was the finest with a P80 of 40 µm and smithsonite was the coarsest at 200 µm. Franklinite was the only well liberated zinc mineral, while the others were poorly liberated at between 30 and 40% liberation (Figure 4.34).

Figure 4.31 Iron mineral grain size distribution

Figure 4.32 Iron mineral liberation

Figure 4.33 Zinc mineral grain size distributions

Figure 4.34 Zinc mineral liberation

Mineral Associations Franklinite was well liberated and had a free surface value of 92% (Table 4.32). Hemimorphite and sphalerite were found primarily with franklinite. Smithsonite was found mainly with franklinite, but also displayed associations with calcite.

Table 4.32 Selected mineral associations for the ferrite sample

Mineral Anglesite Calcite Chlorite FeO Franklinite Hemimorphite K_Feldspar MnO Muscovite Natrojarosite Plagioclase Pyroxene Quartz Smithsonite Sphalerite Sphalerite_Fe Free Surface

Cassiterite 0.0 0.0 0.0 1.2 96.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.0 0.0 0.0 0.7

CuS 0.3 0.1 0.0 0.0 27.6 3.6 0.0 1.1 0.1 0.0 0.0 0.1 1.5 0.6 4.3 4.7 55.5

FeMnO 0.1 0.0 0.0 0.9 25.2 3.0 0.1 13.7 0.2 0.1 0.0 0.0 2.7 0.1 0.0 0.1 51.6

FeO 0.1 0.1 0.0 0.0 42.6 0.1 0.0 0.2 0.2 0.1 0.0 0.0 0.9 0.0 0.2 0.6 54.1

Franklinite 0.6 0.1 0.0 1.6 0.0 1.0 0.1 0.7 0.2 0.0 0.0 0.0 1.8 0.3 0.1 0.5 92.2

Gahnite 7.2 0.1 0.0 0.0 34.7 1.3 0.0 0.1 3.0 0.0 0.0 0.0 0.5 0.5 0.0 0.0 52.2

Hemimorphite 0.2 0.6 0.0 0.1 37.1 0.0 0.3 4.2 1.3 0.0 0.0 0.1 3.5 4.5 0.2 0.1 46.3

Magnetite_Ti 0.0 0.0 7.8 0.9 8.2 0.2 9.2 0.0 5.4 0.0 7.5 5.4 5.4 0.0 0.0 0.0 44.6

MnO 0.8 0.1 0.0 0.2 16.0 3.2 0.0 0.0 0.2 0.1 0.0 0.0 1.6 0.1 0.0 0.0 75.6

Natrojarosite 0.6 0.0 0.0 1.0 17.8 0.0 0.0 1.0 0.1 0.0 0.0 0.0 3.4 0.0 0.0 0.2 74.3

Pyrite 2.3 0.0 0.4 4.6 23.9 0.0 0.0 0.1 1.8 7.4 0.0 0.0 3.7 0.0 0.0 14.8 37.7

Smithsonite 0.2 9.1 0.0 0.2 29.0 14.6 0.3 0.2 0.7 0.0 0.0 0.1 1.4 0.0 0.2 0.4 41.9

Sphalerite 0.3 0.0 0.0 1.7 32.2 1.2 0.1 0.1 0.1 0.0 0.0 0.0 2.2 0.5 0.0 7.1 52.2

Sphalerite_Fe 0.3 0.0 0.0 1.9 49.5 0.3 0.0 0.1 0.1 0.0 0.0 0.0 0.7 0.2 2.5 0.0 43.0

SEM Pics The SEM images in Figure 4.35 show the oxide coatings that formed around many of the sphalerite particles in the ferrite sample. The oxide coatings were mainly of iron and zinc oxides, but contained minor amounts of silicon, lead, and some sulfur.

Figure 4.35 Sphalerite coated by complex iron-zinc oxides containing silicates and lead sulfates

Also located in the ferrite sample was a small micron-sized grain of silver-copper sulfide in a particle of quartz (Figure 4.36).

Figure 4.36 Micron-sized silver-copper sulfide in quartz

4.3.3.3 Comparison of QEMSCAN and MLA Data In the case of the ferrite sample, both reports determined franklinite to be the predominant mineral; MLA determined the franklinite mineral to be the manganese rich phase

(Zn,Mn,Fe)(Fe, Mn)2O4 while QEMSCAN determined it to be ZnFe2O4 Notable differences occurred in the determination of the abundance of sphalerite and the oxides of iron and manganese. It is to be noted that ferrite sample was comprised of a variety of complex phases that supposedly formed during the roasting process as the SEM images revealed (figure 4.33 and 4.34).

Results on the elemental composition showed that iron and zinc were the two main elements in the sample. Because of the mineral’s definition in from MLA, manganese assay was determined to be 29.7 % while QEMSCAN determined it to be 1.31 %. In general the reports agreed on the elemental composition aside from the differences aforementioned.

4.3.4 Chemical Analysis Tables 4.33 and 4.34 show the results from the chemical analysis provided by the sponsor and CSM respectively.

Table 4.33 Chemical analysis of the ferrite sample provided by the sponsor Element Concentration Concentration Unit Fe = 29.8 % Zn = 22.2 % Pb = 5.03 % Cu = 1.55 % Mn = 1.27 % Si = 1.18 % Ca = 0.74 % Al = 0.67 % K = 0.24 % Co = 0.15 % Cd = 0.12 % In = 0.11 % H2O = 18.68 %

Table 4.33 Continued Element Concentration Concentration Unit Mg = 920 ppm Na = 424 ppm Ti = 394 ppm Ag = 240 ppm Cr = 135 ppm Au < 100 ppm Mo < 50.0 ppm Ni = 15.0 ppm Ge < 10.0 ppm Hg < 10.0 ppm Sb < 10.0 ppm Tl < 10.0 ppm V < 10.0 ppm W < 10.0 ppm Li < 5.00 ppm

Table 4.34 Chemical analysis of the ferrite sample provided by CSM Element Concentration Concentration Unit Fe = 25.2 ± 0.82 % Zn = 19.9 ± 0.75 % Pb = 4.11 ± 0.06 % Mn = 1.16 ± 0.02 % Ca = 0.68 ± 0.06 % Cu = 0.45 ± 0.07 % As = 0.36 ± 0.01 % Al = 0.35 ± 0.04 % Li = 0.21 ± 0.01 % Cd = 0.13 ± 0.004 %

In = 783 ± 31.1 ppm Sb = 632 ± 11.9 ppm Sn = 520 ± 14.4 ppm Ti = 451 ± 12.3 ppm Bi = 351 ± 18.1 ppm

Table 4.34 Continued Element Concentration Concentration Unit Ni = 224 ± 24.1 ppm Ga = 200 ± 9.61 ppm *Ag = 182 ± 1.53 ppm V = 72.3 ± 25.6 ppm Cr = 24.7 ± 4.51 ppm Tl = 18.3 ± 1.15 ppm K < 50.0 ppm P < 50.0 ppm Ge < 10.0 ppm Mg < 10.0 ppm Mo < 10.0 ppm W < 10.0 ppm Zr < 10.0 ppm Co < 5 ppm Sr < 5 ppm

As shown in the tables, iron and zinc are the main elements in the ferrite sample with an assay greater than 20 wt. %. Lead and manganese are the next most abundant element in the sample followed by silicon. Numbers generated by the sponsor are generally higher than those produced by the CSM team, especially for indium which is 1100 ppm from the sponsor while it was calculated to be 783 ppm from the CSM team.

It has been mentioned in the introduction and literature survey that indium is mostly associated with minerals such sphalerite; therefore, the presence of sphalerite was tracked in each of the three sample that were received. The tailings sample was determined to be comprised mainly of silicates, and contained sphalerite minerals to an abundance of 1.27 wt. % according to QEMSCAN data. The jarosite sample was mainly comprised of the jarosite mineral with the presence of franklinite (≈ 9.0 wt. %) and sphalerite (0.77 wt. %) according to QEMSCAN data. The ferrite sample was comprised mainly of the franklinite mineral that encapsulates other minerals such as sphalerite (5.9 wt. %) according to QEMSCAN data. Chemical analysis on these sample determined the indium content to be 18.3 ppm in the tailings sample, 246 ppm in the jarosite sample, and 783 ppm in the ferrite sample.

CHAPTER 5 RESULTS AND DISCUSSION

Chapter 5 details all results generated throughout the duration of the project. Information presented in this chapter includes results from physical separation (gravity, magnetic, and electrostatic) as well as leaching experiments.

5.1 Physical Separation

Section 5.1 details results from physical separation work namely gravity, magnetic, and electrostatic separation conducted on the tailings, jarosite, and ferrite samples. The section also includes a discussion of the observed results. Graphs presented in this section will often contain identifiers such as “H” and “L;” the reader is advised to comprehend them as a low setting and a high setting of either G force or electric field applied during experiments.

5.1.1 Gravity Separation 5.1.1.1 Float/Sink Gravity Separation A Tailings Sample Table 5.1 shows the weight distribution of sinks and floats as a function of the medium’s specific gravity. As the specific gravity of the medium is increased, the weight distribution of the sinks fraction is decreased. As mentioned earlier in chapter 3 and 4, one of the goals of these float/sink gravity separation experiments is the beneficiation of indium which is believed to be contained in sphalerite and franklinite which are heavy minerals. Eventually, in this case, the goal is to concentrate indium in the sinks fraction, and at the highest medium’s density, 2.75 wt. % of total sample is recovered.

Table 5.1 Weight distribution between the sinks and floats fractions of the tailings sample Medium Initial Feed Calculated Initial Sinks Floats Density (g/cm3) Weight (g) Feed Weight (g) Weight (g) Weight (g) 2.31 20.93 20.39 19.65 0.74 2.77 20.66 22.94 14.72 8.22 3.06 20.02 18.78 2.75 16.03

Figure 5.1 shows a grade vs. recovery curve for indium as a result of the float/sink experiments. As seen in the figure, the highest recovery of indium is achieved at a fairly low grade of (see table B-1 in appendix B). An increase in the medium’s density increased the grade further to 43 ppm, only the recovery significantly decreases to 45.1 wt. %. At this medium’s

93 density, less than 55 wt. % of iron, zinc, cadmium, and silver are also recovered in the sink fraction. On the other hand, only 3.2 and 19.3 wt. % of aluminum and sodium respectively are recovered in the sinks fraction.

Figure 5.1 Grade vs recovery curve for indium in the sinks fraction of the tailings sample

Results observed here fall short of the expectations. In reference to table 4.2, roughly 15- 20 wt. % of the sample was expected to be recovered in the sinks fraction, and in this case 14.6 % was recovered. Also in reference to table 4.4, at least 97.2 % of zinc should have been recovered in the sinks fraction, has sphalerite been totally liberated. The fact that only 54 % zinc was recovered in the sinks fraction suggests that sphalerite is poorly liberated at P80 of 105 um.

B Jarosite Sample Table 5.2 below shows the weight distribution of sinks and floats fractions in the jarosite sample as a function of the medium’s density; as the density is increased the weight distribution of the sink fraction decreased. In reference to table 4.13, and assuming 100% liberation of minerals, at least 18 wt. % of the sample is expected to report to the sinks fraction at the highest medium’s density as was the case.

Table 5.2 Weight distribution between the sinks and floats fractions of the jarosite sample Medium Initial Feed Calculated Initial Sinks Floats Density (g/cm3) Weight (g) Feed Weight (g) Weight (g) Weight (g) 2.25 20.09 19.03 19.03 0 2.5 20.08 17.92 14.62 3.30 2.79 20.01 18.51 12.87 5.64 3.08 20.15 18.25 3.29 14.96

Figure 5.2 Grade vs recovery curve for indium in the floats fraction of the jarosite sample

Figure 5.2 shows a grade recovery curve for indium as in the floats fraction. According to the figure, Indium was mostly recovered in the floats fraction, recovery and grade both increasing as the medium’s specific gravity was increased. The highest combination of grade and recovery of indium in the fraction was obtained at the highest medium’s density where 83.1 wt. % of indium was recovery at 304 ppm. In this particular case, the results suggest that indium is contained in light minerals rather than in the heavy sphalerite mineral.

C Ferrite Sample Table 5.3 below shows the weight distribution of sinks and floats in the ferrite sample as a function of the medium’s density; the calculated feed weights was higher as shown in the table due the medium’s adherence to the surface of the sample’s particle even after the washing stage. According to the results shown, the ferrite sample is mainly comprised of heavy minerals, such that less than 1.0 g of the sample reported to the floats fraction. These results agree with QEMSCAN observations that 99 % of the sample is comprised of heavy minerals (table 4.24).

Table 5.3 Weight distribution between the sinks and float fractions of the ferrite sample Medium Feed Calculated Initial Sinks Floats Density (g/cc) Weight (g) Feed Weight (g) Weight (g) Weight (g) 2.31 20.35 21.27 21.19 0.08 2.77 20.44 20.90 20.18 0.72 3.06 20.01 20.70 19.74 0.96

Figure 5.3 Grade vs recovery curve for indium in the sinks fraction of the ferrite sample

Figure 5.3 shows a grade vs. recovery curve for indium as a result of float/sink experiments on the ferrite sample; according the this figure, the highest recovery of indium in the sinks fraction is 100 % (see table B-3 in appendix B) which occurred at the medium’s density where a negligible amount of float fraction is recovered. The take away from these experiments is that increasing the medium’s density only redistributes indium among the products while it does not achieve upgrading worthwhile exploring.

5.1.1.2 Falcon Gravity Separation A Tailings Sample

Table 5.4 shows the weight distribution between the heavies and the lights fraction after gravity separation using the Falcon unit. In principle, the conditions required to have a cleaner heavies fraction are higher G force, lower pulp density, and higher water pressure; this can be seen by comparing experiment 1 and 5 for example where an increase in the water pressure resulted in a decrease of the weight distribution to the fraction containing heavy minerals. It should be noted however that overall the changes in weights distribution were not significantly higher so as to observe considerable significant changes in concentration ratio

Figure 5.4 shows grade recovery data for indium after experiments. As seen in the figure, high indium grade and recoveries were observed at low pulp densities. Low pulp densities allowed for a production of a cleaner fraction of heavy minerals thus rejecting much of the light minerals that do not contain indium.

Table 5.4 Weight distribution between the heavies ad lights fractions of the tailings sample Exp. # Initial Feed Calculated Initial Heavies Lights weight (g) Feed weight (g) Weight (g) Weight (g) 1 100.52 99.02 33.85 65.17 2 100.77 99.42 27.47 71.95 3 100.27 93.86 24.49 69.37 4 100.85 97.02 31.27 65.76 5 100.08 98.63 28.59 70.04 6 100.18 99.02 30.51 68.51 7 100.61 99.11 20.60 78.51 8 100.30 99.48 22.85 76.63

Figure 5.4 Grade vs. recovery of indium in the heavies fraction of the tailings sample

The highest recovery of indium in the heavy minerals fraction occurred at the lower limits of 2 parameters (10.0 % solids, and 5 psi water) and a 200 G force. In reference to table B- 4 in appendix B, it should be noted that the highest recovery of indium (75.0 %) occurred in the light minerals fraction at a grade of 36 ppm. These results agree with observations made from the float/sink experiments which suggest a low liberation of sphalerite mineral.

B Jarosite Sample Table 5.5 shows the weight distribution to the heavies and lights fractions of the jarosite sample. It can be seen here that the jarosite sample contains a large fraction of light minerals seeing that more than 80 % of the sample reported to the lights fraction. Zinc minerals are expected to be recovered in the heavy minerals fraction with the expectation to recover most of the indium present in the sample.

Figure 5.5 shows indium’s grade vs recovery data in the light minerals fraction of the jarosite sample. In this case, a lower pulp density and a higher water pressure yielded higher indium recovery to the lights fraction. A change in the centrifugal force did not result in

98 significant change in recovery as did the change in water pressure; therefore water pressure proved to be a high impact parameter in the case of gravity separation on the jarosite sample with the Falcon unit.

Table 5.5 Weight distribution between the heavies and lights fractions of the jarosite sample Exp. # Initial Feed Calculated Initial Heavies Lights weight (g) Feed weight (g) Weight (g) Weight (g)* 1 100.12 97.36 8.08 89.28 2 100.27 97.53 8.95 88.58 3 100.12 97.33 6.93 90.39 4 100.16 97.57 13.89 83.68 5 100.14 97.34 7.01 90.33 6 100.13 97.31 6.28 91.04 7 100.15 97.44 10.02 87.42 8 100.15 97.37 7.49 89.88 * Lights weight recalculated using Indium’s feed grade and assuming 3.0 % loss

Figure 5.5 Grade vs. recovery of indium in the heavy minerals fraction of the jarosite sample

The highest indium grade and recovery (249 ppm, 93.2 %) occurred at a high G force, low pulp density and high water pressure setting (table B-5). This observation confirms results from the float/sink experiments that indium is contained mainly in the lights minerals.

C Ferrite Sample Table 5.6 shows the weight distribution between the heavies and the lights fractions of the ferrite sample after the first set of experiments; all experiments yielded roughly a 15-85 distribution between the light and the heavy materials. In the case of the ferrite sample, the effect particle size vs particle density duality was considerable enough such that the coarse light materials reported to the heavy minerals fraction while the very fine heavy minerals reported in the light minerals fraction.

Table 5.6 First set of weight distributions between the heavies and lights fractions of the ferrite sample Exp. # Initial Feed Calculated Initial Heavies Lights weight (g) Feed weight (g) Weight (g) Weight (g) 1 100.14 95.69 78.90 16.80 2 100.30 96.56 79.92 16.64 3 100.56 96.59 85.25 11.34 4 100.45 96.26 83.22 13.04 5 100.40 93.82 82.23 11.59 6 100.30 96.80 79.51 17.29 7 100.21 96.93 90.21 6.72 8 100.33 96.58 82.19 14.40

Figure 5.6 shows indium’s grade vs recovery data in the heavy minerals fraction. According to the results, the highest indium grade in the fraction was achieved at the low setting of all three parameters; at this setting, less material reports to the lights fraction, while the coarse and light materials are still reporting to the heavy minerals fraction. The highest indium recovery (92.8%) was achieved a high limit of all there parameters; indium grade at this setting was 917 ppm)

With the aim of reducing the effect of the particle size/particle density duality, a second set of experiment was conducted. In this case, the sample was thoroughly mixed in a slurry before being fed onto a Tyler #7 mesh sieve on top of the entry point of the falcon unit. From

100 these experiments three different fractions were generated and their weight distribution is shown in table 5.7 below. As shown in the table, the sieve fraction was well below 15 % of the sample; this fraction was mainly comprised of coarse gangue minerals.

Table 5.7 Second set of weight distribution between the heavies and lights fractions of the ferrite sample Exp. # Initial Feed Calculated Initial Heavies Lights Sieves weight (g) Feed weight (g) Weight (g) Weight (g) Weight (g) 9 100.27 96.91 39.66 49.23 8.02 10 100.53 97.27 40.36 50.79 6.12 11 100.03 94.39 37.69 43.07 13.64 12 100.12 96.72 38.76 53.38 4.57

Figure 5.6 Grade vs recovery of indium in the heavy minerals fraction of the ferrite sample. Data illustrated here are from the first set of experiments

Also, in the new set of experiments, the water pressure was increased in order to increase the recovery of the lights fraction which contained less of the gangue minerals. As shown in the table, the experiments resulted in a close to 45-55 distribution between the heavy and the light

101 minerals fraction. As shown in figure 5.7 a higher water pressure increased indium’s grade and recovery to the light fraction. The highest indium grade and recovery (981 ppm, 59.0 %) was obtained at a low G force and high water pressure

Figure 5.7 Grade vs recovery of indium in the heavy minerals fraction of the ferrite sample. Data illustrated here are from the second set of experiments

In reference to table B-6 and B-7 appendix B, it can be seen from both set of experiments that the highest indium grade was 1065 ppm which only occurred with a 17.8 % recovery of indium. An attempt to increase recovery would result in a higher water consumption which most of the time is not desired.

5.1.2 Magnetic Separation 5.1.2.1 Tailing Sample Table 5.8 shows the weight distribution between the magnetic and non-magnetic fractions in the tailings sample. As shown in the table the tailings sample contained a large fraction of non-magnetic materials, and an increase in the magnetic field intensity did not increase the weight distribution to the magnetic fraction. Sphalerite is non-magnetic, so in this case, the goal

102 is to recover indium in the non-magnetic fraction, thus separating sphalerite from pyrite. It should be noted however that the presence of impurities such as iron in its lattice can render sphalerite magnetic; therefore, it is also expected that sphalerite will be present in the magnetic fraction.

Table 5.8 Weight distribution between the magnetic and non-magnetic fractions of the tailings sample Initial Feed Calculated Initial Mag Non Mag Exp. # Weight (g) Feed Weight (g) Weight (g) Weight (g) 1 40.13 38.13 4.40 33.74 2 40.54 39.17 7.15 32.02 3 40.36 38.98 6.23 32.75 4 40.22 38.46 6.33 32.13

Figure 5.8 Grade vs recovery of indium in the non-magnetic fraction of the tailings sample

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Figure 5.8 shows a grade vs recovery graph for indium in the non-magnetic fraction of the tailings sample. Overall, indium grade did not change considerably (variation between 14 and 17 ppm); however, recoveries did change as the magnetic field intensity was changed. The highest indium recovery of 82.3 % in the non-magnetic fraction occurred at the lowest filed intensity. Consequently in the case of the tailings sample, an increase in field intensity did not improve grade or recovery of indium in the non-magnetic fraction. In reference to table B-8 in appendix B, the highest indium grade (25 ppm) occurred in the magnetic fraction only at a recovery of 28.5 %.

5.1.2.2 Jarosite Sample Table 5.9 shows the weight distribution between the magnetic and non-magnetic fractions of the jarosite sample; as shown in the table an increase in the intensity of the field resulted in a general increase in the distribution of the magnetic fraction. However, the distribution was almost constantly in a 55-45 split between the non-magnetic and magnetic fractions

Table 5.9 Weight distribution between the magnetic and non-magnetic fractions of the jarosite sample Initial Feed Calculated Initial Mag Non Mag Exp. # Weight (g) Feed Weight (g) Weight (g) Weight (g) 1 40.25 33.62 13.90 19.72 2 40.23 32.39 10.24 22.15 3 40.15 30.02 13.11 16.91 4 40.28 31.28 17.74 13.55

Figure 5.9 shows an indium vs recovery curve for indium as a result of WHIMS experiments. Indium grades varied between 300 and 310 ppm (which is not much upgrading) with an increase in the strength of the applied magnetic field. Recoveries however were dependent on the magnetic field strength; the highest recovery of indium (71.6 %) occurred at the highest strength at a grade of 303 ppm. It should be noted however, that at this field strength, most paramagnetic material are also directed to the magnetic fraction. From the calculated 240 ppm indium in the feed, the enrichment ratio in this case is only 1.26.

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Figure 5.9 Grade vs recovery graph for indium in the magnetic fraction of the jarosite sample

5.1.2.3 Ferrite Sample Table 5.10 shows the weight distribution between magnetic and non-magnetic materials in the ferrite sample. Unlike the expected results, most of minerals reported in the non-magnetic fraction. Franklinite is dark brown in color whereas the magnetic fraction was mostly black, so it is assumed that the magnetic fraction is mainly comprised of the ferromagnetic mineral magnetite. Also data reported in the table shows that as the field intensity and the oscillation rate is increased, the magnetic fraction is also increased. The increase in oscillation rate yielded a cleaner fraction. Increasing the wash water rate only resulted in a decrease of the magnetic fraction because the effective residence time of the sample in the tube is decreased.

Figure 5.10 shows a grade vs recovery graph for indium in the non-magnetic fraction of the ferrite sample. According to these results, indium was recovered most entirely in the non- magnetic fraction. The highest indium grade and recovery (878 ppm, 99.97%) occurred at low field intensity, high oscillation, and low wash water rate. Also, the results suggested that franklinite in this case was not ferromagnetic. The presence of manganese and other metal in the

105 lattice of franklinite are potential reason for the paramagnetic behavior of franklinite in this particular case.

Table 5.10 Weight distribution between the magnetic and non-magnetic fractions of the ferrite sample Initial Feed Calculated Initial Mag Non Mag Exp. # Weight (g) Feed Weight (g) Weight (g) Weight (g) 1 40.02 36.81 0.09 36.72 2 40.02 37.79 0.18 37.60 3 40.03 37.31 0.08 37.23 4 40.01 37.64 0.21 37.43 5 40.07 36.99 0.15 36.84

Figure 5.10 Grade vs recovery for indium in the non-magnetic fraction of the ferrite sample

5.1.3 Electrostatic Separation 5.1.3.1 Tailings Sample Since indium reported in the light minerals fraction in both the float/sink and the Falcon gravity tests, the goal is now to recover indium in the non-conductive fraction with the silicates

106 minerals (see table C-1 for electrical properties of minerals in the tailings sample). This way, sphalerite can be separated from pyrite since both the pure and the iron rich sphalerite phase are non-conductive.

Table 5.11 shows the weight distribution between the conductive and non-conductive materials in the tailings sample. In principal, and increase in the electric field’s intensity at a low speed of the separation drum and a lower distance of the corona wire from the drum should result in high distribution of materials to the non-conductive fraction as was observed.

Table 5.11 Weight distribution between the conductive and non-conductive fractions of the tailings sample Exp. # Initial Feed Calculated Initial Non-conductive Conductive weight (g) Feed weight (g) Weight (g) Weight (g) 1 100.25 97.34 24.32 73.02 2 100.24 98.31 36.27 62.04 3 100.39 98.47 19.85 78.62 4 100.53 98.66 33.80 64.86 5 100.51 99.19 36.11 63.09 6 100.22 98.20 46.91 51.29 7 100.20 98.85 35.62 63.23 8 100.20 97.99 42.83 55.16

Figure 5.11 shows grade vs recovery data for indium in the fraction of the tailings sample. As shown in the figure, the highest indium grades and recovery occurred at the lower speed of the separation drum and the lower distance of the corona wire to the separation drum. However, the recoveries obtained were lower than 50%; in this case indium was recovered at 42.1 % and 31 ppm and this occurred at a high electric field strength.

Table B-11 in appendix B shows that the highest recovery of indium (71.1 %) was in the conductive fraction at a high separator drum speed, high electric field, and low distance from the corona wire to the separator drum. Indium grade at these settings was 42 ppm. Such results were observed because of the high speed of the separator drum which decrease the distribution of the non-conductive fraction thus concentrating indium in the conductive fraction. Based on the calculated feed grade, electrostatic separation did not achieve considerable enrichment of indium in the tailings sample.

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Figure 5.11 Grade vs recovery data for indium in the non-conductive fraction of the tailings sample

5.1.3.2 Ferrite Sample Table 5.12 shows the weight distribution between the conductive and non-conductive fractions of the ferrite sample. Franklinite is a conductive mineral (see table C-2), so the goal here is the removal of gangue minerals such as quartz since they are non-conductive. As shown in the table, most the sample was recovered in the conductive fraction as expected.

Figure 5.12 shows grade vs recovery data for indium in the conductive fraction. In this case the highest indium grade and recovery (964 ppm, 88.2 %) was obtained at a high speed of the separator drum roll speed. Nonetheless, the conductive fraction was diluted by the somewhat coarse particles of the gangue minerals which were thrown off the separator drum with a higher speed. A lower speed could have remedied to the problem albeit the limitation that 130 rpm was the lowest speed that could be applied on the separator drum.

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Table 5.12 Weight distribution between the conductive and non-conductive fractions of the ferrite sample Exp. # Initial Feed Calculated Initial Non-conductive Conductive weight (g) Feed weight (g) Weight (g) Weight (g) 1 100.56 98.58 16.10 82.48 2 100.36 97.95 14.29 83.65 3 100.72 98.60 11.87 86.73 4 100.48 96.78 11.42 85.37 5 100.44 97.99 16.79 81.20 6 100.49 97.46 18.56 78.90 7 100.55 97.41 16.44 80.97 8 100.71 97.56 17.62 79.94

Figure 5.12 Grade vs recovery data for indium in the conductive fraction of the ferrite sample

5.1.4. Conclusions on physical separation Experiments

Table 5.13 show a summary of all the physical separation work conducted for the purpose of this project. For the tailings sample, the indium grade was not upgraded past 60 ppm, and in all cases, the fraction containing most of indium was still associated with the silicate

109 minerals which were not desired for the leaching step. It was concluded that the zinc minerals’ low liberation was the primary reason for the low recoveries. Moreover, the head grade of indium in the tailings sample was very low to the extent that there is very little economic incentive for processing the sample. Consequently, efforts on the beneficiation of indium from the tailings sample were stopped, and the tailings sample was not considered for leaching experiments.

Unlike the expectations set for the jarosite sample based on QEMSCAN results, indium was not mostly recovered in the heavy minerals fraction which would contain most of the zinc minerals nor was it recovered in the non-magnetic fraction with the WHIMS experiments. Therefore, it was decided that the jarosite sample would be leached as received.

Table 5.13 Summary of physical separation work on all received samples In Calc. In In Feed Distribution Sample Wt. % Fraction* Analysis Content in Fraction (ppm) (ppm) (%) Sink/Float Testing Sink 14.7 18 43 45.1 Magnetic Separation Mag 18.3 16 28 28.5 Tailings Gravity Separation Heavies 27.7 36 54 41.6 Electrostatic Conductive 56.3 33 42 71.1

Sink/Float Testing Float 82.0 299 304 83.1 Jarosite Magnetic Separation Mag 43.7 302 309 44.7 Gravity Separation Lights 93.6 250 249 93.2

Sink/Float Testing Sink 100 992 992 100 Magnetic Separation Non mag 99.6 867 871 99.9 Ferrite Gravity Separation Lights 14.9 786 1065 20.2 Electrostatic Conductive 87.9 962 964 88.2 * Fraction considered to be the concentrate

In the case of the ferrite sample, higher expectations were set on the magnetic separation experiment which yielded opposite results. One hypothesis given here is that the presence of impurities in the franklinite mineral may have rendered the mineral less responsive a magnetic field. With electrostatic separation, the conductive fraction was diluted with large non-

110 conductive materials thus not achieving the desired separation. It was concluded that for the ferrite sample, it was necessary to remove the coarse gangue minerals before leaching. A separation based on gravity, magnetic susceptibility, and surface conductivity of the minerals was possible for all three sample. Unfortunately the enrichment ratio did not exceeds 1.5 for the most part.

5.2 Leaching

Section 5.2 presents data generated from the leaching step of the jarosite and the ferrite samples. A discussion is provided on the observed results from the investigation of each variable.

5.2.1 Jarosite Sample 5.2.1.1 Effect of Temperature Results from the investigation of the effect of temperature shows that the extraction of indium increases with an increase in time up to 6 hours except for 90 ° C as shown in figure 5.13 below. According to these results, there is an onset point in time at which indium extraction starts to decrease; this onset point occurs earlier with an increase in temperature as seen in the figure. Leaching at 80 °C however shows a different behavior; the decrease of indium extraction starts at 4 hours, and is rather small; moreover, the difference in indium extraction with the 70°C is relatively small across the time scale. Eventually after 8 hours of leaching, 47% of total indium is extracted at 80°C, and 1.0M H2SO4. The 90°C trend show an anomaly behavior from 1 to 2 hours; at 90°C the calculated leached fraction was lower at 2 and 4 hours of leaching in comparison to the 1 hour leach.

The dissolution of jarosite is described in equation 3.1 reiterated below. Thermodynamics data from HSC 5.0 shows that the reaction becomes more thermodynamically favorable with an increase in temperature. Nonetheless, it also shows that the reaction is exothermic which translates in lower yields as temperature in increased. The equilibrium is shifted to the left (acid production + precipitation). Investigation on acid consumption as a function of temperature showed that acid consumption was generally higher at higher temperature (see figure D.1 in appendix D). It can be concluded then that the equilibrium of this reaction is not the factor responsible for the behavior of indium extraction as a function of temperature, and that the behavior at 90°C arose from experimental error; more testing would have to be conducted to fully understand what is actually happening at that temperature.

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6 + → . + . + .

Figure 5.13 Effect of temperature on indium extraction during jarosite sample leaching

5.2.1.2 Effect of Initial Acid Concentration For the investigation of the effect of the initial acid concentration on indium extraction, 80°C was chosen because of the ease of handling of the water bath and the fairly constant increase of indium extraction with time. The solid concentration and agitation were kept constant. According to the results shown in figure 5.14, the extraction of indium is a strong function of initial acid concentration. There is an approximate 20% marginal increase in indium extraction as the initial acid concentration is increased from 1M to 2M, and 2M to 3M; indium extraction plateaus with time at 3M and 4M acid concentration.

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Figure 5.14 Effect of initial acid concentration on indium extraction during jarosite sample leaching

Figure 5.15 shows the evolution of pigmentation of the sample as acid concentration is increased at 1 and 2 hours of leaching. The jarosite mineral is yellow in color, and it is visible that the residue goes to a red color suggesting the dissolution of most of the jarosite mineral. Sample dissolution approaches a constant 74% at 3M and 4M acid concentration after 4 hours of leaching.

Figure 5.15 Sample color evolution with increase in initial acid concentration

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5.2.1.3 Effect of Pulp density Results from the study of the effect of pulp density shows a drastic decrease (≈20%) in indium extraction when the solid concentration is increased from 15 to 20 % wt./vol. as shown in figure 5.16 below. There is no significant changes in indium extraction when the solid concentration is further increased to 25 % suggesting that the solid concentration can be increased to 25% for the same level of indium extraction. It was showed that acid consumption decreased as more solids were introduced in the system (see figure D.3 in appendix D).

Figure 5.16 Effect of pulp density on indium extraction during jarosite sample leaching

5.2.2 Ferrite Sample Table 5.14 below shows a materials balance for the feed materials for the leaching of the ferrite sample.

Table 5.14 Ferrite sample sieve fraction analysis Products Wt. Metal Content % Distribution % ppm In % Ca % Si* % Al In Ca Si Al + 10 mesh 2.93 45 9.39 15.9 1.62 0.16 38.5 9.40 12.5 -10 mesh 2.47 871 0.45 4.63 0.34 99.8 61.5 90.6 87.5 * Semi quantitative XRF values

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5.2.2.1 Effect of Temperature Results from the study of the effect of temperature showed a slow decrease in indium extraction from 1 to 2 hours of leaching at all three temperatures as shown in figure 5.17. In the range of 2 to 6 hours of leaching, indium extraction rapidly increases until it start decreasing again after 6 hours. Unlike the case of the jarosite sample leaching, 80°C proved to be the ideal temperature for leaching, for a further increase to 90 °C only resulted in an overall decrease in indium extraction.

The dissolution of ferrite is described in equation 3.2 below. Thermodynamics data from HSC 5.0 shows that the reaction becomes less thermodynamically favorable with an increase in temperature. It also showed that the reaction is exothermic, thus acid consumption would decrease if temperature is increased.

� � � + → + + .

Figure 5.17 Effect of temperature on indium extraction during ferrite sample leaching

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Investigation on acid consumption showed a general increase with an increase in temperature unlike what thermodynamics predicted (see figure D.4 in appendix D). Consequently, thermodynamics alone cannot be used to explain the behavior of indium extraction as a function of temperature. The abnormal behavior observed could be resulted from errors occurred during the experiments.

5.2.2.2 Effect of Initial Acid Concentration Results from the investigation of the effect of initial acid concentration shows that indium extraction steadily increased with an increase in the initial acid concentration as shown in figure 5.18 below. According to these results, indium extraction is a strong function of the acid concentration. After 1 hour of leaching, indium extraction increased from 28% at 1M to 71 % at

4M H2SO4. The highest indium extraction (90%) occurred after 4 hours of leaching at 4M sulfuric acid concentration.

Figure 5.18 Effect of Initial acid concentration on indium extraction during ferrite sample leaching

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Acid consumption as a function of initial acid concentration showed that approximately 80 % is consumed at 2M (see figure D.5 in appendix D) after 4 hours of leaching. At the highest indium extraction, 70% of the 4M acid was consumed.

5.2.2.3 Effect of Pulp Density Figure 5.19 below shows results from the investigation of the effect of pulp density on the extraction of indium. According to these results, close to 65% of indium is extracted at 15 %wt. /vol. solids; however, this extraction is significantly decreased when solids concentration is increased to 20 % wt. /vol. From 20 to 25 % wt. /vol. solids, indium extraction is fairly constant at 52% until it drastically decreases to 37 % when the solid concentration is further increased to 30% wt. /vol.

According to observations made, acid consumption significantly increased with an increase in the concentration of solids in the system (see figure D.6 in appendix D). From 25 to 30 % wt. /vol. solids, acid consumption stays slightly constant until a maximum 72.5 % of total acid is consumed at 30 % wt. /vol. solids.

Figure 5.19 Effect of pulp density on indium extraction during ferrite sample leaching

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5.2.3 Leached Solutions from leaching of the Jarosite and Ferrite Samples

Table 5.15 below shows impurities present in the leach solution for both the jarosite and the ferrite samples; these results occurred at parameters which yielded the highest recovery extraction of indium. In both cases, iron is the main impurity with a ratio to indium of >700 in the jarosite sample case and >300 in the ferrite sample case. Other major impurities in the jarosite sample leaching are sodium, zinc, and aluminum. In the case of the ferrite sample leaching, other major impurities include zinc and manganese.

Table 5.15 Summary of impurities in leachate at parameters yielding the highest indium recovery

Jarosite (3M H2SO4, 4 hrs., 20 % Ferrite (4M H2SO4, 4 hrs., 20 % sol., 80°C) sol., 80°C) Element Element/Indium Element/Indium Content Content Ratio Ratio Fe g/L 24.7 741.5 34.9 312.3 Zn g/L 1.6 47.5 26.7 238.5 In ppm 33.3 1.0 111.9 1.0 Cd ppm 24.4 0.7 174.7 1.6 Na ppm 2533 76.1 22.0 0.2 K ppm 237 7.1 - - Ga ppm - - 28 0.3 Cu ppm 252 7.6 714 6.4 Al ppm 482 14.5 475 4.2 Ca ppm 144 4.3 559 5.0 Mn ppm 79.7 2.4 1087 9.7 As ppm 90.6 2.7 531 4.7 Mg ppm 53.6 1.6 98.8 0.9 Ag ppm 0.371 0.0 16.7 0.1 Ti ppm 48.0 1.4 43.3 0.4

With the high ratio of iron to indium, applying solvent extraction (SX) directly to recover indium would likely result in a high iron distribution to organic phase; it would then be necessary to effectively separate indium from iron. A potential route is to carry out a selective precipitation stage through which the Fe/In ratio is significantly reduced. Possible reagents to be used are

Na2S, NaOH, and NH4OH. Using HSC Chemistry, thermodynamics shows that using Na2S has a higher thermodynamic drive for selectively separating indium from zinc and iron; precipitation with the hydroxide phases shows potential to co-precipitate all three metals.

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5.2.4 Revisiting Magnetic Separation During the filtering of residues from the leaching of the jarosite and the ferrite materials, it was observed that particles adhered to the magnetic stirrer; this suggested that it may be desirable to remove them prior to the leaching step. It was then decided to revisit magnetic separation of on the jarosite and ferrite materials. The goal was to have a better idea on the potential for separation before leaching. To that purpose, a two stage wet high intensity magnetic separation (WHIMS) tests were conducted on each sample. The matrix used was a standard window screen that was cut and bundled in a canister in the WHIMS unit.

The ferrite sample was made only this time the ferrite sample was sieved into 3 size fractions (+10, -10+48, -48 mesh-Tyler); the -48 mesh fraction was used as the feed to the WHIMS for further indium grade improvement. From the results shown in table 5.16 below, as much as 10 % aluminum, 13% silicon, and nearly all calcium were removed; furthermore, the important observation is that approximatively 98 % of all indium reported to the – 48 mesh size fraction. The calculated head grades were 854 ppm, 0.39 wt. %, 4.95 wt. %, and 0.68 wt. % for indium, calcium, silicon, and aluminum respectively.

Table 5.16 Ferrite sample sieve fractions analysis Products Wt. % Metal Grade % Distribution PPM In % Ca % Si* % Al In Ca Si Al + 10 mesh 2.93 45 9.39 15.9 1.62 0.20 70.8 9.41 6.95 -10+48 mesh 2.47 507 4.61 9.14 1.04 1.51 29.2 4.54 3.76 -48 mesh 94.60 888 0.00 4.51 0.64 98.3 0.00 86.1 89.3 * Semi quantitative XRF results

Table 5.17 Summary of magnetic separation experiments In Calc. Feed In Recovery in Sample Wt. % Fraction* In Grade (ppm) grade (ppm) Fraction (%) Jarosite Non mag 86.5 247 242 85.0 Ferrite Non Mag 98.3 859 869 99.4

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Table 5.17 above shows the best outcome in 3 experiments. In the case of jarosite magnetic separation, a total of 34 wt. % zinc was removed to the magnetic fraction with a low magnetic field on both stages. Nonetheless, no significant indium upgrading was observed. The results lead to the conclusion that indium is mostly present in the matrix of jarosite itself, thus it cannot be upgraded via physical separation since jarosite is the predominant mineral in the sample.

In regard to the ferrite sample, we observed no additional improvement on indium content beyond physical separation via sizing. Magnetite and zinc iron oxide having a very close extraction range, it remained difficult to separate the two minerals. The conclusion from this work is that it is best to sieve the sample to remove as much silica and the other gangue minerals to reduce their content in the pregnant leach solution after leaching.

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CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS

Chapter 6 lists major conclusions drawn from the project, and it provides recommendations for future work

6.1 Conclusions

Three sample were provided to the research team for this project (tailings, jarosite, and ferrite) for the beneficiation and recovery of indium therein.

Characterization of the tailings sample showed that it was mainly comprised of silicate minerals such as quartz, muscovite, and feldspar. Particle size distribution of the sample pout the

P80 at 105.9 um, and the liberation data showed that zinc minerals were mostly locked. Chemical analysis of the tailings sample determined the indium content to be 18.3 ppm; the sample was rich in iron, aluminum, and zinc content was 0.58 wt. %. Though analyzed analytically, semi quantitative results showed that the sample was very high in silicon.

Neither physical separation method applied on the tailings yielded appreciable upgrading of indium. For the most part, the low liberation of zinc minerals that were believed to contain indium was the main cause. Also, the head grade in the sample was very small (<20 ppm) and had little economic interest; consequently, no additional work was conducted on the sample.

Characterization of the jarosite sample showed that it was mainly comprised of sulfate minerals, though there was evidence of a noticeable amount of franklinite and pyrite. Particle size distribution of the sample determined the P80 to be 7.18 um which is very fine in size, and liberation data showed that zinc mineral were fairly liberated and that they were mostly associated with the predominant jarosite mineral. Chemical analysis on the sample determined the indium content of the jarosite sample to be 246 ppm, and the predominant elements were oxygen, iron, and sulfur. The content of zinc in the sample was determined to be 1.38 wt. %.

Contrary to the assumptions made that indium would be present in the sphalerite mineral the jarosite sample, physical separation work concluded that indium was mainly present in the matric of the jarosite mineral which was predominant in the sample. In this case the jarosite sample was to be leached as received; however, iron would still be the main impurities in the leach solution.

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Characterization work on the ferrite sample showed that it was mainly comprised of zinc ferrite AKA franklinite. Particle size distribution conducted showed that the P80 was 18.1 um and the P90 was 80.4 um. Franklinite was determined to be mostly liberated though it encapsulated various secondary zinc minerals as well as com0plex silicates phases. Chemical analysis showed that indium was present at 783 ppm and that the zinc content was 19.9 wt. %.

Physical separation testing on the ferrite sample became challenging because the response obtained were not in agreement with the expected results. Franklinite which is normally a ferromagnetic mineral responded neither to a low nor a high intensity magnetic separation. It was determined however, that the best route to take was to screen (nominal screen size 297 um) the sample in order to remove most of the gangue minerals thus reducing the contamination of the leach solution.

As mentioned earlier, the first goal of the present project was the identification of secondary resources for the extraction of indium. Based on the characterization, chemical analysis as well as physical separation work, it was determined that ferrite and jarosite materials were worth exploiting further, the ferrite sample more so than the jarosite sample.

Indium was successfully dissolved using a sulfuric acid leach for the jarosite sample. It was determined that higher indium extraction was achieved at lower temperature, higher initial acid concentration, and lower pulp density. In addition, it was determined that during leaching, acid consumption increased with higher temperatures, higher initial acid concentration, and lower pulp density. The highest indium extraction from the jarosite sample was achieved at 3M

H2SO4, 4 hours, 20 % sol., and 80°C, and the main contaminant in the leach solution were iron, zinc, sodium, and aluminum.

Indium was successfully put in solution using a sulfuric acid leach for the ferrite sample. It was determined that higher indium extractions were obtained at 80°C with higher initial acid concentration and lower pulp density. It was also determined that during the leaching of the ferrite sample, acid consumption increased with higher temperatures, higher initial acid concentrations, and higher pulp density. The highest indium extraction achieved was obtained at

4M H2SO4, 4 hours, 20 % sol., and 80°C.

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6.2 Recommendations and Future Work

6.2.1 Recommendations This section provides recommendations for the continuity of the project.

1. Confirm acid consumption data by taking into account the potential iron hydrolysis. Use of an inhibitor is advised. 2. Conduction a ferrous content analysis in order to better explain the observations made in the leaching step.

3. Investigate a reductive leaching for the leaching of the ferrite sample.

4. For the ferrite sample the Zn/In ratio is high enough to consider the production of an intermediate zinc product in order to offset the operation cost per gram of indium produced.

5. A kinetic study on the leaching of the jarosite and the ferrite sample is necessary to understand the behavior of the leaching between 2 and 6 hours of leaching, and gain a better grasp of the effect of each parameters.

6. The iron content in the leach solution was still very high and acid consumption is such that the leaching step is not economic for both the jarosite and the ferrite sample. A potential process to use for the reduction of the Fe/In ratio is Investigate a magnetizing roast process followed by a magnetic separation in order to separate out iron leaving a non-magnetic product possibly enriched in indium and perhaps more suitable for a low acid consuming leaching process, thus reducing the complexity of the purification step.

6.2.2 Considerations for the Recovery of Indium from the Leach Solution Koleini and coworkers investigated the recovery of indium from leach solution with a low content of indium (Koleini et al. 2010). A sample with a feed assay of 145 ppm was leached using Na2S of he reducing agent. The pregnant leach solution (PLS) was sent to an indium precipitation stage to separate it from iron and zinc. The precipitate was passed to another stage of reductive leaching with Na2S; the following PLS was sent to a solvent extraction and stripping stage, then onto a final precipitation stage with Cottrell powder (ZnO). Based on the authors’ claim, the overall recovery of indium was 64.2 %.

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Figure 6.1 shows the first alternative process route to be considered in reference to the work aforementioned. This example fits the case of the jarosite sample that has a feed assaying 246 ppm. After determining leaching conditions yielding the best kinetics for the jarosite sample, the next step is to determine the best conditions for the recovery of indium from the PLS. Since indium is present at a low concentration in the PLS in the case of the jarosite sample, this route provide footprints for its separation from zinc and iron. Impurities will differ from those that were present in the investigators solution, therefore the need to also investigation on the best reagent to use for the precipitation stage.

Precipitation

Figure 6.1 Process route 1 considered for the recovery of indium from the leach solution in reference to (Koleini et al. 2010)

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More recently, Li and co-authors investigated the possibility of reducing the length of the purification step similar to the one described in Koleini et al.’s work (Li et al. 2015). Their work consisted of a direct solvent extraction of indium as shown in figure 5.21 below. The PLS coming from a reductive leaching circuit was sent to a countercurrent multistage solvent extraction circuit with 3 extraction stages and 4 stripping stages with a 60 % recycling of the strip solution. The aqueous to organic ratio was set at 6:1 and 1:6 for the extraction and the stripping stage respectively. One crucial step in the process was the copper cementation where most copper is removed, but also ferric ions are reduced to ferrous which is not extracted together with trivalent indium. The leach solution entered the SX circuit at 128 ppm, and exited at 738 ppm with a 96.1 % extraction.

Precipitation

Figure 6.2 Process route 2 considered for the recovery of indium from the leach solution in reference to (Li et al. 2015)

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Figure 6.2 shows the second alternative process route for the recovery of indium from the leach solution. This example is more suited for the case of the ferrite sample leaching that resulted in a PLS assaying 111 ppm indium. Additional work is still need for the determination of conditions yielding the best kinetics. In this case the copper precipitation stage would serve the main purpose of converting the ferrous iron to ferric since the Cu/In ratio is relatively lower compared to the Fe/In ratio in the PLS. Future work would include finding the best condition for solvent extraction of indium so as to maximize the overall recovery from that particular circuit. In the case of the ferrite sample, a precipitation stage with zinc oxide is actually beneficial in the sense that the solution exiting that circuit would be enriched in zinc which is already high; this solution can be used for the production of a salable intermediate zinc product in order to offset some of the operating costs.

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Yao, Jinhuan, Xuanhai Li, Liuping Pan, and Jiamei Mo. 2012. “Enhancing Physicochemical Properties and Indium Leachability of Indium-Bearing Zinc Ferrite Mechanically Activated Using Tumbling Mill.” Metallurgical and Materials Transactions B 43 (3): 449–59. doi:10.1007/s11663-012-9641-7. Yoshito, Kudo. 2000. “Separation and Concentration Method for Recovering Gallium and Indium from Solutions by Jarosite Precipitation.” Europe Union. Zhang, Yanjuan, Xuanhai Li, Liuping Pan, Xinyuan Liang, and Xueping Li. 2010. “Studies on the Kinetics of Zinc and Indium Extraction from Indium-Bearing Zinc Ferrite.” Hydrometallurgy 100 (3-4). Elsevier B.V.: 172–76. doi:10.1016/j.hydromet.2009.10.015. Zhang, Yanjuan, Xuanhai Li, Liuping Pan, Yansong Wei, and Xinyuan Liang. 2010. “Effect of Mechanical Activation on the Kinetics of Extracting Indium from Indium-Bearing Zinc Ferrite.” Hydrometallurgy 102 (1-4). Elsevier B.V.: 95–100. doi:10.1016/j.hydromet.2010.02.003.

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APPENDIX A PHYSICAL PROPERTIES OF MINERALS IDENTIFIED BY XRD IN THE RECEIVED SAMPLES

Table A-1 Physical properties of minerals in the tailings sample Chemical Formula Mineral Name Specific Gravity Magnetism

SiO2 Quartz 2.7 NM

Cu0.25Cd0.75Ga2O4 ND ND

Zn0.1Cd0.4Fe2Ni0.5O4 Cd-Zn-Ni ferrite ND ND ZnO Zincite 5.56 NM

Zn0.98Fe2.02O4 Franklinite 5.14 F

Pb(Al, Cu)3(SO4)2(OH)6 Osarizawaite ND ND

Zn0.2Mn0.8Fe2O4 Jacobsite, zincian 4.75 M (weak)

KAl3Si3O11 Muscovite 2.8-3.0 NM

(Cd0.04Fe0.24Zn0.72)S Sphalerite, ferroan 4.05 P (varies with composition)

Table A-2 Physical properties of minerals in the jarosite sample Chemical Formula Mineral Name Specific Gravity Magnetism

NaFe3(SO4)2(OH)6 Natrojarosite 2.9-3.3 ND

K0.02(H3O)0.98Fe3(SO4)2(OH)6 Hydroniumjarosite 2.9-3.6 ND

CaSO4 2.3 NM

CuFeS2 Chalcopyrite 5.09 M upon heating

PbFe6(SO4)4(OH)12 Plumbojarosite 3.6-3.67 ND

SiO2 Coesite 2.7 NM

ZnFe2Pb(SO4)2(OH)6 Beaverite 4.36 ND

AgFe2.88Al0.12(SO4)2(OH)6 Argentojarosite 3.66 ND

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Table A-3 Physical properties of minerals in the ferrite sample Chemical Formula Mineral Name Specific Gravity Magnetism Cu0.5Cd0.5Ga2O4 ND ND (Zn, Mn, Fe) (Fe, Mn)2O4 Mn rich Franklinite 5.05-5.22 P (varies with composition) ZnFe2O4 Franklinite 5.14 F Zn0.2Cd0.3Fe2Ni0.5O4 Cd-Zn-Ni ferrite ND ND MgO Periclase 3.78 NM MgFe2O4 Magnesioferrite 4.65 NM Fe3O4 Magnetite 5.15 F (Ca, V)0.01 (Mg0.03, Mn0.01)2Ti0.74Fe2.1Al0.05Si0.01O4 Ferriannite 2.7 NM MnFe2O4 Jacobsite 4.75 M (weak) Fe7SiO10 ND ND

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APPENDIX B PHYSICAL SEPARATION COMPLETEMENTAL DATA

Table B-1 Summary table of float/sink gravity separation experimental results for the tailings sample Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment Exp. # Grade (ppm) sink (ppm) Float (ppm) sink (%) Float (%) in sink in float 1 19 19 31 94.20 5.80 0.98 1.59 2 16 11 25 44.07 55.93 0.69 1.56 3 14 43 9 45.05 54.95 3.08 0.64

Table B-2 Summary table of float/sink gravity separation experimental results on the jarosite sample Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment Exp. # grade (ppm) sink (ppm) Float (ppm) sink (%) Float (%) in sink in float 1 265 265 0 100 0 1 0 2 217 256 44 96.27 3.73 1.18 0.2 3 256 296 163 80.58 19.42 1.16 0.64 4 300 281 304 16.91 83.09 0.94 1.01

Table B-3 Summary table of float/sink gravity separation experimental results on the ferrite sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) sink (ppm) Float (ppm) sink (%) float (%) in sink in float 1 992 992 0 100 0 1 0 2 873 897 199 99.21 0.79 1.03 0.23 3 788 823 63 99.63 0.37 1.04 0.08

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Table B-4 Summary table of Falcon gravity separation experimental results for the tailings sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) heavies (ppm) lights (ppm) heavies (%) lights (%) in Heavies in Lights 1 33 38 31 38.90 61.10 1.14 0.93 2 36 54 29 41.55 58.45 1.50 0.81 3 32 40 29 36.96 63.04 1.24 0.90 4 31 36 29 37.12 62.88 1.15 0.93 5 36 48 31 38.73 61.27 1.34 0.86 6 35 48 29 42.43 57.57 1.38 0.83 7 28 41 25 30.08 69.92 1.45 0.88 8 37 41 36 25.35 74.65 1.10 0.97

Table B-5 Summary table of Falcon gravity separation experimental results for the jarosite sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) heavies (ppm) lights (ppm) heavies (%) lights (%) in Heavies in Lights 1 250 271 248 8.98 91.02 1.08 0.99 2 248 253 248 9.36 90.64 1.02 1 3 247 285 244 8.23 91.77 1.16 0.99 4 250 273 246 15.56 84.44 1.09 0.98 5 250 272 248 7.85 92.15 1.09 0.99 6 250 264 249 6.81 93.19 1.06 1 7 247 272 244 11.34 88.66 1.1 0.99 8 248 276 246 8.55 91.45 1.11 0.99

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Table B-6 Summary table of Falcon gravity separation experimental results for the ferrite sample (Set # 1) Exp. # In Calc. feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment Grade (ppm) heavies (ppm) lights (ppm) heavies (%) lights (%) in heavies in lights 1 956 951 981 82.00 18.00 0.99 1.03 2 921 903 1009 81.12 18.88 0.98 1.10 3 893 873 1047 86.25 13.75 0.98 1.17 4 889 866 1039 84.18 15.82 0.97 1.17 5 817 792 992 84.99 15.01 0.97 1.21 6 910 887 1017 80.05 19.95 0.97 1.12 7 920 917 955 92.80 7.20 1.00 1.04 8 894 864 1065 82.24 17.76 0.97 1.19

Table B-7 Summary table of Falcon gravity separation experimental results for the ferrite sample (Set # 2) Exp. # Calc. In In grade In In In In In In In In feed in grade in grade recovery recovery recovery enrichment enrichment enrichment grade heavies lights in sieve in heavies in lights in sieve in heavies in lights in sieve (ppm) (ppm) (ppm) (ppm) (%) (%) (%) 9 889 833 973 651 38.35 55.59 6.06 0.94 1.09 0.78 10 894 894 944 476 41.5 55.15 3.35 1 1.06 0.53 11 881 830 980 709 37.62 50.75 11.63 0.94 1.11 0.85 12 918 855 981 722 37.32 58.97 3.72 0.93 1.07 0.84

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Table B-8 Summary table of magnetic separation experimental results for the tailings sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) Mag (ppm) Non-Mag (ppm) Mag (%) Non-Mag (%) in Mag in Non-Mag 1 18 28 17 17.67 82.33 1.53 0.93 2 16 25 14 28.51 71.49 1.56 0.87 3 18 28 16 24.98 75.02 1.56 0.89 4 19 28 17 24.50 75.50 1.49 0.90

Table B-9 Summary table of magnetic separation experimental results for the jarosite sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) Mag (ppm) Non-Mag (ppm) Mag (%) Non-Mag (%) in Mag in Non-Mag 1 298 302 295 41.91 58.09 1.01 0.99 2 297 307 293 32.64 67.36 1.03 0.99 3 302 309 296 44.73 55.27 1.02 0.98 4 240 303 157 71.65 28.35 1.26 0.65

Table B-10 Summary table of magnetic separation experimental results for the ferrite sample Exp. # Calc. In feed In grade in In grade in In recovery in In recovery in In enrichment In enrichment grade (ppm) Mag (ppm) Non-Mag (ppm) Mag (%) Non-Mag (%) in Mag in Non-Mag 1 851 427 852 0.12 99.88 0.50 1.00 2 867 114 871 0.06 99.94 0.13 1.00 3 843 255 844 0.06 99.94 0.30 1.00 4 878 40 883 0.03 99.97 0.05 1.01 5 867 11 871 0.01 99.99 0.01 1.00

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Table B-11 Summary table of electrostatic separation experimental results for the tailings sample Exp. # Calc. In feed In grade in In grade in C In recovery in In recovery in In enrichment In enrichment grade (ppm) NC (ppm) (ppm) NC (%) C (%) in NC in C 1 31 27 32 21.94 78.06 0.88 1.04 2 34 25 39 27.26 72.74 0.74 1.15 3 26 25 26 19.53 80.47 0.97 1.01 4 22 23 21 36.34 63.66 1.06 0.97 5 30 31 30 37.16 62.84 1.02 0.99 6 35 31 39 42.10 57.90 0.88 1.11 7 31 21 36 24.73 75.27 0.69 1.18 8 33 22 42 28.91 71.09 0.66 1.26

Table B-12 Summary table of electrostatic separation experimental results for the ferrite sample Exp. # Calc. In feed In grade in In grade in C In recovery in In recovery in In enrichment In enrichment grade (ppm) NC (ppm) (ppm) NC (%) C (%) in NC in C 1 870 948 855 17.79 82.21 1.09 0.98 2 886 931 879 15.32 84.68 1.05 0.99 3 962 944 964 11.82 88.18 0.98 1.00 4 851 944 839 13.08 86.92 1.11 0.99 5 864 929 850 18.43 81.57 1.08 0.98 6 897 893 898 18.96 81.04 1.00 1.00 7 851 908 839 18.02 81.98 1.07 0.99 8 859 880 854 18.51 81.49 1.02 0.99

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APPENDIX C ELECTRICAL PROPERTIES OF MINERALS IDENTIFIED BY QEMSCAN

Table C-1 Electrical properties of mineral in the tailings sample Minerals Chemical Formula Conductivity Comment Sphalerite ZnS NC depends on impurities High Fe Sphalerite (Zn,Fe)S NC depends on impurities Franklinite ZnFe2O4 C Secondary Zn minerals Willemite, hemimorphite, smithsonite - Mix of NC and C minerals siderite,…etc. * Ag-sulfide Ag2S C Sulfides are usually conductors Arsenopyrite FeAsS C Chalcopyrite CuFeS2 C Galena PbS C Pyrite* FeS C Pyrrhotite FexSy C

Alunite KAl3(SO4)2(OH)6 NC Sulfate are nonconductive

Barite+Celestine BaSO4 NC Other sulfates Sulfates with low pixels NC sulfates are nonconductive generally Calcite CaCO3 NC

Cassiterite SnO2 C Fe-oxides* Fe3+OOH NC Vary with temperature Mn-oxides Variety of Manganese oxides C* Could be

Ti-minerals TiO2, CaTiSiO5, FeTiO3,… etc. C

Quartz SiO2 NC Triboelectric charging may be used

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Table C-1 Continued Minerals Chemical Formula Conductivity Comment

Feldspar (Na, K)AlSiO8 14.72 NC

Muscovite KAl2(Si3Al)O10(OH,F)2 30.01 NC Mafic Minerals Silicates of Fe and Mg 2.361 NC 3+ Epidote* Ca2(Fe , Al)3(SiO4)3(OH) 0.015 NC Others Minerals with low pixels 0.054 NC

Table C-2 Electrical properties of minerals in the ferrite sample Minerals Chemical Formula Conductivity Comment Sphalerite ZnS NC Varies with composition high Fe Sphalerite (Zn,Fe)S NC Varies with composition

Smithsonite ZnCO3 NC Varies with composition

Siderite FeCO3 NC Varies with composition

Hemimorphite Zn4Si2O7(OH)2.(H2O) NC

Willemite Zn2SiO4 NC

Franklinite ZnFe2O4 C

Franklinite (Mn) Zn0.6Mn0.8Fe1.6O4 C

Ag- sulfide Ag2S C Sulfides are usually conductors

Chalcopyrite CuFeS2 C Galena PbS C Pyrite* FeS C Pyrrhotite FexSy C Other sulfides Sulfides of Pb, Sb, Cu, Ag, and Zn - Mix of NC and C minerals

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Table C-2 Continued

Minerals Chemical Formula Conductivity Comment

Barite BaSO4 NC

Ca- sulfate CaSO4 NC

Mn-sulfate MnSO4.7H2O NC Sulfates including barite, alunite, Other sulfates NC sulfates are nonconductive generally celestine,…etc.

Calcite CaCO3 NC 2+ Ankerite Ca(Fe , Mg, Mn)) (CO3)2 NC Fe- oxides Fe3+OOH NC Vary with temperature Mn-oxide Variety of Manganese oxides C

Ti-minerals TiO2, CaTiSiO5, FeTiO3,… etc. C

Feldspar (Na, K)AlSiO8 NC Mafic Minerals Silicates of Fe and Mg NC

Muscovite KAl2(Si3Al)O10(OH,F)2 NC

Quartz SiO2 NC Triboelectric charging may be used

Apatite Ca5(PO4)3F NC Others Minerals with low pixels NC

Electrical properties for the mineral in all three samples were extracted from Telford and coworkers work (Telford, Geldart, and Sheriff 1990)

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APPENDIX D ACID CONSUMPTION FROM LEACHING OF THE JAROSITE ANS FERRITE SAMPLES

Figure D-1 Effect of temperature on acid consumption during jarosite sample leaching

Figure D-2 Effect of Initial acid concentration on acid consumption during jarosite sample leaching

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Figure D-3 Effect of pulp density on acid consumption during jarosite sample leaching

Figure D-4 Effect of temperature on acid consumption during ferrite sample leaching

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Figure D-5 Effect of Initial acid concentration on acid consumption during ferrite sample leaching

Figure D-6 Effect of pulp density on acid consumption during ferrite sample leaching

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