Applied Science, Faculty of
Materials Engineering, Department of
DSpace
UBCV
Heise, Connor William Anthony
Master of Applied Science - MASc
University of British Columbia
Existing literature has failed to provide a substantive explanation for the variability in mineral electrochemistry or methods for its mitigation. The majority of research data has limited use beyond the mineral sampled for experimentation. Even if it did, the conclusions may not translate to different methods or mineral origins. The data itself is not to blame for this challenge, but rather the reporting on how this data was collected. The experimental methods and descriptions of materials are not consistently or appropriately reported. This work sought to understand how different mineral electrodes can affect electrochemical results. Three distinct chalcopyrite origins were used in open circuit potential (OCP), galvanostatic, and potentiostatic experiments. I observed the effects of crevice corrosion, mineral origin and composition, sample preparation, solution stirring, and experimental method. Masking the interface between the resin and mineral surface of the electrodes resulted in upwards of 100 mV potential difference under galvanostatic conditions. As expected, the origin and composition of a mineral affect observed data. Different mineral origins can result in upwards of 242 mV potential difference under 1 μA galvanostatic conditions in stagnant 2 g/L HâSOâ at 21°C. Additionally, variation within the same origin can result in approximately 247 mV difference. The effects of electrolyte solution stirring were considerable as well. For example, OCP and galvanostatic potentials can change on the order of 45 mV when stirring and/or nitrogen bubbling. The enclosed data led to the proposal of methods for reducing variability in mineral electrochemistry and structuring reporting guidelines. Mineral electrochemists need to agree on a standard for experimental preparation and reporting to ensure future research can make use of historical data and build upon it.
EXPLORING VARIABILITY IN MINERAL ELECTROCHEMISTRY USING CHALCOPYRITE AS AN EXAMPLE by Connor William Anthony Heise B.A.Sc, The University of British Columbia, 2019 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Materials Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2025 © Connor William Anthony Heise, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Exploring Variability In Mineral Electrochemistry Using Chalcopyrite As An Example submitted by Connor William Anthony Heise in partial fulfilment of the requirements for the degree of Master of Applied Science in Materials Engineering Examining Committee: Edouard Asselin, Professor, Materials Engineering, UBC Supervisor David Dixon, Professor, Materials Engineering, UBC Supervisory Committee Member Wenying Liu, Associate Professor, Materials Engineering, UBC Supervisory Committee Member iii Abstract Existing literature has failed to provide a substantive explanation for the variability in mineral electrochemistry or methods for its mitigation. The majority of research data has limited use beyond the mineral sampled for experimentation. Even if it did, the conclusions may not translate to different methods or mineral origins. The data itself is not to blame for this challenge, but rather the reporting on how this data was collected. The experimental methods and descriptions of materials are not consistently or appropriately reported. This work sought to understand how different mineral electrodes can affect electrochemical results. Three distinct chalcopyrite origins were used in open circuit potential (OCP), galvanostatic, and potentiostatic experiments. I observed the effects of crevice corrosion, mineral origin and composition, sample preparation, solution stirring, and experimental method. Masking the interface between the resin and mineral surface of the electrodes resulted in upwards of 100 mV potential difference under galvanostatic conditions. As expected, the origin and composition of a mineral affect observed data. Different mineral origins can result in upwards of 242 mV potential difference under 1 μA galvanostatic conditions in stagnant 2 g/L H2SO4 at 21°C. Additionally, variation within the same origin can result in approximately 247 mV difference. The effects of electrolyte solution stirring were considerable as well. For example, OCP and galvanostatic potentials can change on the order of 45 mV when stirring and/or nitrogen bubbling. The enclosed data led to the proposal of methods for reducing variability in mineral electrochemistry and structuring reporting guidelines. Mineral electrochemists need to agree on a standard for experimental preparation and reporting to ensure future research can make use of historical data and build upon it. iv Lay Summary Mineral electrochemistry is used to study how quickly minerals dissolve so that we can design appropriate metal extraction processes. Existing literature does not provide a clear explanation for why variability exists in mineral electrochemistry or provide ways of reducing it. Insufficient reporting on experimental conditions and methods makes generating broader conclusions and precise comparisons to other mineral research difficult. Through experimental observation, I saw the effects of crevice corrosion (an artifact of sample preparation and mounting), mineral origin and composition, sample preparation, solution stirring, and experimental method. From this, I propose methods for reducing variability in mineral electrochemistry. I also propose guidelines for reporting to ensure adoption of those methods. v Preface The primary investigator and author of this and a listed manuscript to be published was Connor William Anthony Heise, who was responsible for conducting all research, preparing and analyzing the results, and writing the manuscripts. Dr. Edouard Asselin supervised the work and provided guidance and editorial input with further guidance provided by both Dr. David Dixon and Dr. ZiHe (Ryan) Ren. No generative artificial intelligence (GenAI) was used in any aspect of this work. Some of the work presented throughout all chapters of this thesis has resulted, or will result, in publication in journal papers. The following is a list of such publications: Literature review findings on chalcopyrite passivation published in: â¢ New Perspective on the Depassivation Mechanism of Chalcopyrite by Ethylene Thiourea o Ren, ZiHe and Chao, Chihwei and Krishnamoorthy, Prashanth and Heise, Connor and Sabzehei, Kiana and Asselin, Edouard and Dixon, David G. and Mora, Nelson, New Perspective on the Depassivation Mechanism of Chalcopyrite by Ethylene Thiourea. Available at SSRN: https://ssrn.com/abstract=4161827 or http://dx.doi.org/10.2139/ssrn.4161827 Experimental results and discussion expected to be published in: â¢ Exploring Variability in Mineral Electrochemistry Using Chalcopyrite As An Example o Heise, Connor and Asselin, Edouard and Dixon, David and Ren, ZiHe, Exploring Variability in Mineral Electrochemistry Using Chalcopyrite as an Example. Available at: TBD vi Table of Contents Abstract ........................................................................................................................................................ iii Lay Summary ................................................................................................................................................ iv Preface .......................................................................................................................................................... v Table of Contents ......................................................................................................................................... vi List of Tables ................................................................................................................................................ ix List of Figures ..............................................................................................................................................xiii Acknowledgements .................................................................................................................................... xxv Dedication ................................................................................................................................................. xxvi Chapter 1: Introduction ........................................................................................................................ 1 1.1 Problem Definition ............................................................................................................................ 1 1.2 Objectives of this Investigation ......................................................................................................... 6 1.3 Why Chalcopyrite? ............................................................................................................................ 6 Chapter 2: Literature Review ................................................................................................................ 7 2.1 Copper: Itâs Need and How to Source ............................................................................................... 7 2.2 Chalcopyrite Thermodynamics in Oxidative Leaching....................................................................... 8 2.3 Chalcopyrite Passivation .................................................................................................................. 16 2.3.1 Elemental Sulfur Theory ................................................................................................... 16 2.3.2 Metal Deficient Polysulfide Theory ................................................................................... 18 2.3.3 Jarosite Theory .................................................................................................................. 20 2.3.4 Mixed Compound Theory ................................................................................................. 21 2.3.5 Intrinsically Passive Theory ............................................................................................... 21 2.3.6 General Conclusion on Chalcopyrite Passivation .............................................................. 25 2.4 Mineral Variability in Literature ...................................................................................................... 27 2.5 Final Thoughts on Literature Review ............................................................................................... 35 Chapter 3: Experimental and Instrumental ........................................................................................ 36 3.1 Electrode Materials ......................................................................................................................... 37 3.1.1 X-ray Powder Diffraction (XRD) of Chalcopyrite Origins ................................................... 38 3.1.2 Energy-dispersive X-ray Spectroscopy (EDS) of Chalcopyrite Massive Electrodes ........... 40 3.1.2.1 Selection of EDS Quantification Method .......................................................... 40 3.1.2.2 EDS Characterization Data ................................................................................ 42 3.1.3 Optical, SE, and BSE Imagery with EDS Mapping of Chalcopyrite Massive Electrodes .... 44 vii 3.1.4 Inductively Coupled Plasma â Optical Emission Spectroscopy (ICP-OES) of Chalcopyrite Origins .......................................................................................................................................... 54 3.1.5 Comparison of Characterization Methods ........................................................................ 56 3.1.6 Conclusions on Reporting Mineral Characterization ........................................................ 59 3.2 Mineral Massive Electrode .............................................................................................................. 60 3.2.1 Massive Electrode Construction ....................................................................................... 60 3.2.2 Massive Electrode Preparation for Experimentation ....................................................... 63 3.3 Solution Preparation........................................................................................................................ 64 3.4 Electrochemical Cell ........................................................................................................................ 65 3.5 Electrochemical Techniques ............................................................................................................ 67 3.5.1 Open Circuit Potential (OCP) ............................................................................................ 67 3.5.2 Galvanostatic Polarization ................................................................................................ 67 3.5.3 Potentiostatic Polarization ................................................................................................ 67 Chapter 4: Investigation of the Variability in Mineral Electrochemistry ............................................ 68 4.1 Introduction to Variability in Mineral Electrochemistry.................................................................. 68 4.2 Open Circuit Potential ..................................................................................................................... 68 4.3 Effects of Resin-Mineral Interface ................................................................................................... 73 4.3.1 Massive Electrode Construction ....................................................................................... 73 4.3.2 Masking Effectiveness on a Massive Electrode ................................................................ 77 4.3.3 Open Circuit Potential on Masked Massive Electrodes .................................................... 81 4.3.4 Galvanostatic Polarization on Masked Massive Electrodes.............................................. 83 4.3.4.1 Anodic Polarization Curves from Galvanostatic Polarization ........................... 89 4.4 Effects of Mineral Origin .................................................................................................................. 93 4.4.1 Open Circuit Potential ....................................................................................................... 93 4.4.2 Galvanostatic Polarization ................................................................................................ 95 4.5 Effects of Solution Agitation .......................................................................................................... 101 4.5.1 Effects of Solution Stirring .............................................................................................. 102 4.5.1.1 Open Circuit Potential .................................................................................... 103 4.5.1.2 Galvanostatic Polarization .............................................................................. 104 4.5.2 Effects of Solution Sparging ............................................................................................ 105 4.5.2.1 Galvanostatic Polarization .............................................................................. 106 4.6 Mineral Massive Electrode Lifespan .............................................................................................. 108 viii 4.6.1 Effects of Cracks in Massive Electrodes .......................................................................... 109 4.6.1.1 Open Circuit Potential .................................................................................... 110 4.6.1.2 Galvanostatic Polarization .............................................................................. 112 4.6.2 Effects of Mineral Thickness in Mineral Massive Electrodes .......................................... 113 4.6.3 Effects of Connection Wire in Mineral Massive Electrodes ............................................ 114 4.6.3.1 Galvanostatic Polarization .............................................................................. 115 Chapter 5: Conclusions and Recommendations ............................................................................... 117 5.1 Conclusions and Recommendations on Reporting........................................................................ 117 5.2 Data Summary and Conclusions .................................................................................................... 118 5.3 Recommended Techniques for Reproducible Data in Mineral Electrochemistry ......................... 120 5.3.1 Mineral Massive Electrode Construction ........................................................................ 120 5.3.1.1 Mineral Selection and Preparation ................................................................. 120 5.3.1.2 Wire Preparation ............................................................................................ 123 5.3.1.3 Resin Preparation ........................................................................................... 125 5.3.2 Masking ........................................................................................................................... 127 5.3.3 Luggin Capillary ............................................................................................................... 129 5.3.4 Summary of Techniques for Reproducible Data in Mineral Electrochemistry ............... 130 5.4 Recommendations for Further Investigation ................................................................................ 130 5.4.1 Graduate Studies Welcome Package .............................................................................. 140 References ................................................................................................................................................ 141 ix List of Tables Table 1: ASTM, ISO, and NACE standards for non-mineral corrosion electrochemistry that could impact mineral electrochemistry .............................................................................................................................. 5 Table 2: Range of reported Open Circuit Potential data from a range of work utilizing different solutions, concentrations, and origin of chalcopyrite ore. The average measured OCP was 511 mV SHE with a standard deviation of 40 mV. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings ............................................................................................ 30 Table 3: Range of reported Passivation Potential data from a range of work utilizing difference solutions, concentrations, and origin of chalcopyrite ore. The average measured PP was 709 mV SHE with a standard deviation of 64 mV. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings ............................................................................................ 31 Table 4: Range of reported Passivation Current data from a range of work utilizing difference solutions, concentrations, and origin of chalcopyrite ore. The average measured ipass was 7.6e-4 A/cm2 with a standard deviation of 1.2e-3 A/cm2. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings ............................................................................................ 32 Table 5: Quantitative XRD analysis through Match!3 software of the chalcopyrite Origins A, B, and C (all values in wt%) used to produce massive electrodes for this work. A Rigaku MultiFlex XRD unit was used with Cu-Kα (1.5418740Ã ) detector and graphite monochromator over a 2θ of 20 - 100 degrees and a sampling width of 0.01 degrees at 2 degrees/min. The X-ray generator was set to 30 kV and 30 mA. .... 39 Table 6: Comparison of EDS characterization methods P/B ZAF and Phi(Rho, Z) performed on chalcopyrite Origins A, B, and C to determine total Cu, Fe, and S weight percent. Values are presented as an average of multiple massive electrodes (origin â number of observed massive electrodes): Origin A - 1, Origin B - 3, Origin C â 3. ......................................................................................................................... 41 Table 7: Comparison of EDS and XRD characterizations performed on chalcopyrite Origins A, B, and C to determine total CuFeS2 weight percent. Values for EDS are presented as an average of multiple massive electrodes (origin â number of observed massive electrodes): Origin A - 1, Origin B - 3, Origin C â 3. ..... 41 Table 8: Quantitative EDS analysis by Phi(Rho, Z) quantification of chalcopyrite Origins A, B, and C. All values are in weight percent averaged from multiple electrodes (origin â number of observed massive electrodes): Origin A - 2, Origin B - 8, Origin C â 7. An FEI Quanta 650 Zeiss SEM with a Bruker XFlash® 6-30 detector with energy resolution of 45eV at Cu-Kα was used to acquire the data from 1 μm diamond polished massive electrodes. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01% ignored as within experimental error............... 42 Table 9: Quantitative EDS analysis by Phi(Rho, Z) of seven chalcopyrite massive electrodes from chalcopyrite Origins A, B, and C. An FEI Quanta 650 Zeiss SEM with a Bruker XFlash® 6-30 detector with energy resolution of 45eV at Cu-Kα was used to acquire the data from 1 μm diamond polished massive electrodes. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01% ignored as within experimental error. ............................................... 43 x Table 10: Quantitative EDS analysis by Phi(Rho, Z) of seven chalcopyrite massive electrodes from chalcopyrite Origins A, B, and C. Values calculated based on the assumption all Cu present forms CuFeS2 and the amounts of Fe and S are calculated based on the Cu amount from the ideal mass ratio for CuFeS2 of Cu (34.63%) â Fe (30.43%) â S (34.94%) until the amounts of Fe and S are fully used. Remaining Fe and/or S are assumed to be inclusions. ............................................................................... 43 Table 11: Surface areas of the seven chalcopyrite massive electrodes used for experimentation approximated by pixel processor ImageJ and taking the average of four measurements with error based on two-sided t-distribution 95% CI. ............................................................................................................ 46 Table 12: Aqua regia digested ICP-OES characterization of chalcopyrite Origins A, B, and C from the same powder samples used for XRD. Raw data was provided by Kemetco Resources in mg/kg and was converted to weight percent for comparison to XRD and EDS. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01 wt% ignored as within experimental error. *Oxygen content is not able to be identified due to the nature of the method using plasma flames for identification. **There was not sufficient dilution capable of providing confident sulfur content data. .................................................................................................................................... 55 Table 13: Elemental compositions in wt% of chalcopyrite Origins A, B, and C comparing EDS and ICP-OES. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01 wt% ignored as within experimental error. *ICP-OES Oxygen content is not able to be identified due to the nature of the method using plasma flames for identification. **There was not sufficient dilution capable of providing confident sulfur content data for ICP-OES. .................... 56 Table 14: Characterization of chalcopyrite Origins A, B, and C based on XRD, EDS, and ICP-OES comparing the weight percent of Cu, Fe, and S. Total CuFeS2 versus other content is shown. *XRD assumes all chalcopyrite follows the ideal weight ratio Cu (34.6%) â Fe (30.4%) â S (34.9%) which was used to calculate Cu, Fe, and S quantities based on CuFeS2 amount. **ICP-OES was unable to produce reliable S content due to insufficient dilution, in lieu of this, S content was calculated based on Cu and Fe content and CuFeS2 ideal weight ratio. .................................................................................................................... 57 Table 15: Characterization of chalcopyrite Origins A, B, and C based on XRD, EDS, and ICP-OES weight percent averaged together from Table 14. ................................................................................................. 57 Table 16: Comparison of XRD, EDS, and ICP-OES characterizations performed on chalcopyrite Origins A, B, and C to determine total weight ratio of Cu â Fe â S. *Values for XRD calculated from Table 5 assuming all chalcopyrite in the three origins follow the ideal weight ratio for CuFeS2 of Cu (34.6%) â Fe (30.4%) â S (34.9%). **ICP-OES was unable to produce reliable S content due to insufficient dilution, in lieu of this, S content was calculated based on Cu and Fe content and CuFeS2 ideal weight ratio. .......... 59 Table 17: Characterization of Cu â Fe â S weight ratio in chalcopyrite Origin A, B, and C based on XRD, EDS, and ICP-OES values averaged together and compared to the ideal Cu â Fe â S weight ratio ............ 59 Table 18: Copper connection wires from Figure 32 with gauges determined by measurement and calculated resistance based on Equation 31 where ÏCu = 1.682*10-8 Ω m @ 21°C and L = 6 in. = 0.1524 m (see section 5.3.1.2 Wire Preparation) ....................................................................................................... 61 xi Table 19: OCP data for seven CuFeS2 massive electrodes (characterization data in Table 5 - Table 17 and Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper between experiments. Averages presented with two-sided t-distribution 95% confidence interval. ......................................................................................................... 70 Table 20: OCP data for three CuFeS2 origins and seven massive electrodes (characterization data in Table 5 - Table 17 and Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Literature data averaged from Table 2. Averages presented with two-sided t-distribution 95% confidence interval (Origin â number of experiments: A â 7, B â 13, C â 6, Literature â 19). ..................................................................................................................... 70 Table 21: Images of two chalcopyrite massive electrodes via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Origin B â B1 polarized for 1 h, Origin A â A1 for 2 h. âMaskedâ shows polarized electrodes with mask on (SAMasked = 0.442 cm2), center column after mask removed with acetone. These compare to the same electrodes polarized without a mask (SAA1 = 1.012 cm2; SAB1 = 1.294 cm2). .............................. 78 Table 22: Differences of 2.26, 22.62, and 226.24 μA/cm2 galvanostatic polarization (GAL) data for three CuFeS2 origins from Figure 63 and Figure 64 at various exposure times. Negative values represent first listed origin having the lower potential. ..................................................................................................... 97 Table 23: Differences of 2.26 and 22.62 μA/cm2 galvanostatic polarization (GAL) data for three CuFeS2 origins from Figure 65 and Figure 66 at various exposure times. Negative values represent first listed origin having the lower potential. .............................................................................................................. 99 Table 24: Peripheral tip speed calculations for various industry standard magnetic stir bars and commonly reported rpm [Peripheral Tip Speed = (rpm / 60 s) * circumference of stirring path = (rpm / 60 s) * 2 * Ï * (stir bar length in meters)] ..................................................................................................... 103 Table 25: Differences in OCP data from Figure 70 between stagnant and stirred conditions at three exposure times and average rate of separation ....................................................................................... 104 Table 26: Differences in galvanostatic polarization data from Figure 71 between stagnant and stirred conditions at five exposure times and average rate of separation .......................................................... 105 Table 27: Differences in galvanostatic polarization data from Figure 72 between stagnant and stirred conditions at five exposure times and average rate of separation .......................................................... 107 Table 28: Experimental lifespan for 7 CuFeS2 massive electrodes from 3 origins (characterization data: Table 5 - Table 17, Figure 18 â Figure 31). All experiments were performed in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Massive electrode C2 used stirring and/or N2 sparging for some experiments while masked. CuFeS2 purity from Table 10 and Table 11 shows masked and unmasked surface areas. Galvanostatic (GAL) and potentiostatic (POT) polarization show minimum and maximum applied currents and potentials, respectively. ................................................................. 109 Table 29: OCP data for CuFeS2 electrodes from Figure 74 and Figure 75 comparing first three experiments (Origin A â A1 Test 1, 2, and 3 are 147, 148, and 149, respectively) ................................... 112 xii Table 30: Reproduction of Table 18 from section 3.2.1 Massive Electrode Construction â Copper connection wires from Figure 85 with gauges determined by measurement and calculated resistance based on Equation 31 where ÏCu = 1.682*10-8 Ω m @ 21°C and L = 6 in. = 0.1524 m .............................. 123 Table 31: Dimensions and surface areas for non-electrically connected rods in carbon and plastic....... 134 Table 32: Images of chalcopyrite Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 100 μA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. SAMasked = 0.442 cm2. Non-electrically connected rod placed in contact in center of massive electrode for duration of experimentation. Reference Table 31 for rods used. ........................ 134 Table 33: Images of chalcopyrite Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. SAMasked = 0.442 cm2. Non-electrically connected rod placed in contact in center of massive electrode for duration of experimentation. Reference Table 31 for rods used. ...................................... 135 Table 34: Images of two chalcopyrite massive electrodes (top and bottom Origin A: SAA = 3.011 â 6.481 cm2 and middle Origin B: SAB = 3.137 â 6.679 cm2) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Non-electrically connected rod placed 5 mm over center of massive electrode for duration of experimentation. Reference Table 31 for rods used. ...................................................... 137 Table 35: Images of two chalcopyrite massive electrodes (1st and 4th Origin A: SAA = 0.816 â 2.623 cm2 ; 2nd, 3rd, and 5th Origin A: SAA = 3.011 â 6.481 cm2) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Non-electrically connected rod placed 2 mm in front of and centered on massive electrode whose surface is facing counter electrode for duration of experimentation. Reference Table 31 for rods used. ............................................................................................................................. 139 xiii List of Figures Figure 1: Copper production versus ore grade reproduced here from graph originally produced by Raw Materials Group, Stockholm (Bowker & Chambers, 2017; The World Bank Group, 2006) .......................... 7 Figure 2: Copy of "Pourbaix diagram for the CuFeS2-H2O system at 25°C (Garrels and Christ 1965)" (Córdoba et al., 2008) ................................................................................................................................. 11 Figure 3: Copy of âThe system CuâFeâSâOâH (in part) at 25°C and 1 atmosphere total pressure. Total dissolved sulfur = 10-1 m. (Courtesy R. Natarajan and R. Garrels.)â (Garrels, 1960) .................................. 12 Figure 4: Copy of âThe system CuâFeâSâOâH (in part) at 25°C and 1 atmosphere total pressure. Total dissolved sulfur = 10-4 m. (Courtesy R. Natarajan and R. Garrels.)â (Garrels, 1960) .................................. 13 Figure 5: Copy of âThe Eh-pH Diagram for the Cu-Fe-S-H2O System.â (Peters, 1976) ................................ 14 Figure 6: Copy of âEh-pH Diagram for Chalcopyrite Decomposition Without H2S as a reactant, and Without FeS2 as a Product (After Majima4).â (Peters, 1976). âMajima4â was not found referenced in Peters (1976). Two Majima works were referenced but neither were the 4th reference; however, it is most likely based on findings from an unpublished manuscript, their 2nd reference: âH. Majima and E. Peters, Electrochemical Mechanisms for the Decomposition of Metal Sulphides, Unpublished manuscript, 1969, 24 pages.â ..................................................................................................................... 15 Figure 7: Copy of âThe effect of applied potential on capacitance of the chalcopyrite-solution interface: (a) Mott-Schottky plot showing n-type depletion behavior between 0.3 and 0.6 V (v. SCE), and the inversion region at potentials >0.7 (v. SCE); (b) the current-voltage plot, showing accumulation, depletion and inversion regions. Data from (Ghahremaninezhad et al., 2010) for chalcopyrite at 0.5 M H2SO4 and 25°Câ (Crundwell, 2015) ............................................................................................................ 23 Figure 8: Copy of "The current voltage curve for the ideal n-type semiconductor-solution interface, showing the accumulation, depletion and inversion regions" (Crundwell, 2015) ..................................... 23 Figure 9: Copy of "Current density and capacitance vs applied potential for freshly polished chalcopyrite plotted as (b) log(i) and 1/C2 and (c) i and Câ (Ren et al., 2022a) ............................................................... 24 Figure 10: Copy of chalcopyrite âone-electronâ model showing various redox potentialsâ energy level on same scale (Crundwell, 2015) ..................................................................................................................... 24 Figure 11: (Top) âHypothetical anodic polarization curves showing active-passive (curve a) and pseudopassive (curve b) behavior. Epp = passivation potential, Ecorr = open circuit (corrosion) potential, icc = critical current, ipassive = passive current.â Reproduced from (Debernardi & Carlesi, 2013; Viramontes et al., 2007) (Bottom Left) Defining Epp and icc for both active-passive and active-pseudopassive curves (Bottom Right) Defining Etranspassive and ipassive for both active-passive and active-pseudopassive curves .. 28 Figure 12: Copy of "Graphical representation of reported rest potential ranges of metal sulfides vs. SHE" (Tanne & Schippers, 2021) .......................................................................................................................... 29 Figure 13: Reproduction of "Anodic polarization curves for CuFeS2 from 6 different locations in 1M H2SO4, 30mV/min, 20 °C" (Warren et al., 1982) with addition of red lines denoting data variation ......... 33 xiv Figure 14: Graphical representation of reported (Left) weight percent range of chalcopyrite to inclusions (Right) weight ratio range of Cu-Fe-S in chalcopyrite ................................................................................. 34 Figure 15: Three different chalcopyrite massive electrodes showing various inclusions that appear visually different despite coming from the same sample origin (chalcopyrite Origin B from Chapter 3: Experimental and Instrumental) ................................................................................................................. 34 Figure 16: Quantitative XRD raw data spectra analyzed by Match!3 software for characterization of chalcopyrite Origins A, B, and C used to produce massive electrodes for this work. A Rigaku MultiFlex XRD unit was used with a Cu-Kα (1.5418740Ã ) detector and graphite monochromator over a 2θ of 20 - 100 degrees and a sampling width of 0.01 degrees at 2 degrees/min. The X-ray generator was set to 30 kV and 30 mA. ............................................................................................................................................. 39 Figure 17: Chalcopyrite massive electrode Origin A â A1 polished to 1200 grit with carbide paper imaged via the native camera sensor and application on an iPhone 8 running iOS 14.4 all in the same location under different conditions. (Left) shows the scale of Origin A â A1 in ambient sunlight from window right of electrode (Center) focuses on Origin A â A1 in overhead white light with focus on mineral in massive electrode (Right) focuses on Origin A â A1 slightly more head-on in same lighting as center image and AFTER undergoing hydrometallurgical experimentation ........................................................................... 44 Figure 18: Chalcopyrite massive electrode Origin A â A1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 6x magnification (Right) SE polished to 1 μm diamond polish at 6x magnification ............................................................................................................ 47 Figure 19: Chalcopyrite massive electrode Origin A â A1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 47 Figure 20: Chalcopyrite massive electrode Origin B â B1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 8x magnification (Right) SE polished to 1 μm diamond polish at 8x magnification ............................................................................................................ 48 Figure 21: Chalcopyrite massive electrode Origin B â B1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 48 Figure 22: Chalcopyrite massive electrode Origin B â B2 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification ............................................................................................................ 49 xv Figure 23: Chalcopyrite massive electrode Origin B â B2 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 49 Figure 24: Chalcopyrite massive electrode Origin B â B3 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 60x magnification (Right) SE polished to 1 μm diamond polish at 60x magnification .......................................................................................................... 50 Figure 25: Chalcopyrite massive electrode Origin B â B3 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 50 Figure 26: Chalcopyrite massive electrode Origin B â B4 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification ............................................................................................................ 51 Figure 27: Chalcopyrite massive electrode Origin B â B4 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 51 Figure 28: Chalcopyrite massive electrode Origin C â C1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification ............................................................................................................ 52 Figure 29: Chalcopyrite massive electrode Origin C â C1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 52 Figure 30: Chalcopyrite massive electrode Origin C â C2 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification ............................................................................................................ 53 Figure 31: Chalcopyrite massive electrode Origin C â C2 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location ....................................................................................... 53 xvi Figure 32: Four easily accessible wires and considered for massive electrode construction. (Left - Red) Iron wire of small gauge. Avoid using if possible. (Left - Blue) Copper wire of sufficient gauge to transfer current with negligible resistance (Left - White) Copper wire with ideal gauge with many strands to make contact with large area of mineral surface, also has green shielding (Left - Yellow) Copper wire with too large a gauge and too low strand count to make good contact to mineral surface, ensure affixing media has sufficient coverage and contact (Right) Wire scale shown next to ball point pen. Wire only required reaching a short distance to reduce resistance. ......................................................................................... 61 Figure 33: Example of massive electrode construction. (Left to Right) Raw chalcopyrite ore, small piece removed, sanded to approximate rectangular prism with centimeter scale, copper wire attached by silver paste in epoxy mold, copper wire attached by copper tape and embedded in epoxy (either silver paste or copper tape used, not both) ......................................................................................................... 62 Figure 34: Examples of chalcopyrite massive electrodes polished to 1200 grit and ready for experimentation. (Left) Resin placed in vacuum to remove entrained air bubbles before pouring over mineral. Copper wire attached with silver paste (Center) Resin placed in vacuum to remove entrained air bubbles before pouring over mineral. Copper wire attached with copper tape (Right) Resin not placed in vacuum resulting in entrained air bubbles. Copper wire attached with copper tape. Centimeter ruler placed in image for scale............................................................................................................................. 63 Figure 35: (Left) Bic Mark-it ultra-fine point permanent marker in Deep Sea Blue (Center Left) Chalcopyrite massive electrode with 0.442 cm2 circle drawn on it by permanent marker (Center Right) Sally Hansen Insta-Dry Hail Cherry Red nail polish used as mask material (Right) Chalcopyrite mineral electrode with 0.442 cm2 circle drawn in permanent marker and masked with nail polish. A centimeter ruler is measuring the diameter of the circleâs inner edge at 0.75 cm ....................................................... 64 Figure 36: Chalcopyrite massive electrodes with nail polish masks. (Left) Nail polish attempting to mask the resin-mineral interface while preserving as much of the exposed mineral surface as possible. The nail polish can be seen to produce a distinct line at the resin-mineral interface suggesting it was not filled in and potentially not fully isolating it from electrolyte and current. (Center) Nail polish successfully masking the resin-mineral interface following the drawn circle (Right) Nail polish successfully masking the resin-mineral interface following the drawn circle. It is back-light to prove nail polish extends outwards covering everything at least 2 mm past the resin-mineral interface ......................................... 64 Figure 37: Schematic of electrochemical cell experimental setup used in all experiments conducted in this work. The magnetic stir bar was only present for experiments where stirring was expressly stated. When used, the same magnetic stir bar was placed to ensure clean spinning and to be near the massive electrode, not necessarily between CE and WE. Luggin capillary intentionally placed so it did not cover the mineral and to have WE and RE in-line with counter electrode. ......................................................... 66 Figure 38: Images of an experiment showing the electrochemical cell experimental setup used in all experiments. The magnetic stir bar was only present for experiments where stirring was expressly stated. When used, the same magnetic stir bar was used and placed to ensure clean spinning and to be near the massive electrode. Luggin capillary intentionally placed so it did not cover the mineral and have WE and RE in-line with counter electrode. ................................................................................................. 66 xvii Figure 39: THIS DATA SHOULD NOT BE USED WITH CONFIDENCE. OCP data on massive chalcopyrite electrodes from two uncharacterized Origin A (α, β) samples in 100 mL of stirred (600 and 1200 rpm) and not stirred 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper without a Luggin capillary or resin-mineral interface masking. Surface area: Origin A-α = 1.430 cm2, Origin A-β = 0.816 cm2. ............. 69 Figure 40: OCP data for seven CuFeS2 massive electrodes (characterization data: Table 5 - Table 17, Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed = 0.442 cm2. Each line is an average of multiple experiments with two-sided t-distribution 95% CI error bars (electrode â number of experiments): A1 â 7, B1 â 3, B2 â 3, B3 â 3, B4 â 4, C1 â 3, C2 â 3. ........................................................... 71 Figure 41: OCP data for three CuFeS2 origins (characterization data: Table 5 - Table 17) in stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Each line is averaged from multiple electrodes each with a minimum of three experiments with two-sided t-distribution 95% CI error bars (origin â number of electrodes): Origin A - 1, Origin B - 4, Origin C â 2. ................................................................................................................................................................. 71 Figure 42: Box and whisker diagram of OCP data for three CuFeS2 origins (characterization data in Table 5 â Table 17) in stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Each plot is from multiple electrodes each with a minimum of three experiments (origin â # of massive electrodes): Origin A â 1, Origin B â 4, Origin C â 2. Number of data points used to calculate average, max, min, median, Q2, Q3 (origin - # of data points): Origin A â 7, Origin B â 13, Origin C â 6, Literature â 19 (Literature data from Table 2). âXâ represents average, bar separating colors represents median. Color difference for easier data distinction: orange > median, blue < median. Outliers are shown as points. ......................... 72 Figure 43: OM images at 5x magnification of a chalcopyrite massive electrode polished to 1200 grit showing the crevice between chalcopyrite and the resin it is embedded in (Top) resin shrinkage during curing, inability of resin to flow into crevice [brightness: +20%, contrast: -40%] (Bottom) resin shrinkage during curing, micro-bubbles entrapped in resin during curing producing voids [brightness: +20%, contrast: -25%] ............................................................................................................................................ 74 Figure 44: Basic schematic of crevice corrosion occurring in a massive electrode between the mineral and the resin ............................................................................................................................................... 75 Figure 45: SE images of two different chalcopyrite massive electrodes resin-mineral interfaces (Top) polished to 1 μm diamond polish at 800x magnification showing a crevice up to 6 μm wide (Center) polished to 1200 grit on carbide paper at 800x magnification showing a crevice approximately 1 μm wide (Bottom) different location on same sample as Center image at 750x magnification showing a crevice <1 μm ............................................................................................................................................................... 76 Figure 46: 5 experimentation steps for chalcopyrite Origin B â B1 massive electrode via native camera sensor and application on an iPhone 8 running iOS 14.4 (Left) Step 1: pre-experimentation â polished to 1200 grit with carbide paper (Left Center) Step 2: pre-experimentation â mask boundary marked at surface area = 0.442 cm2 (Center) Step 3: pre-experimentation â nail polish mask applied up to marked area (Right Center) Step 4: post-experimentation â galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Right) Step 5: post-experimentation â nail polish mask removed with acetone .. 77 xviii Figure 47: 5 experimentation steps for chalcopyrite Origin B â B2 massive electrode via native camera sensor and application on an iPhone 8 running iOS 14.4 (Left) Step 1: pre-experimentation â polished to 1200 grit with carbide paper (Left Center) Step 2: pre-experimentation â mask boundary marked at surface area = 0.442 cm2 (Center) Step 3: pre-experimentation â nail polish mask applied up to marked area (Right Center) Step 4: post-experimentation â galvanostatic polarization for 2 h at 100 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Right) Step 5: post-experimentation â nail polish mask removed with acetone .................................................................................................................................................................... 77 Figure 48: OM images of chalcopyrite Origin B â B1 massive electrode after galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Left) 5x magnification [brightness:+30%] (Right) 50x magnification [brightness:+40%]................................................................ 79 Figure 49: OM images of chalcopyrite Origin B â B2 massive electrode after galvanostatic polarization for 2 h at 100 μA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Left) 5x magnification [brightness:+40%] (Right) 20x magnification [brightness:+20%]................................................................ 79 Figure 50: SEM images of chalcopyrite Origin B â B1 massive electrode after galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Top Left) SE at 18x magnification of mask boundary (Top Right) BSE at 18x magnification of mask boundary (Center Left) SE at 60x magnification of mask boundary from middle of Top Left (Center Right) BSE at 60x magnification of mask boundary from middle of Top Right (Bottom Left) SE at 60x magnification of masked area from upper right of Top Left (Bottom Right) BSE at 60x magnification of masked area from upper right of Top Right ............................................................................................................................................................ 80 Figure 51: OCP data for CuFeS2 massive electrode Origin B â B1 (characterization data: Table 5 â Table 17, Figure 20 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.294 cm2. Line âOCP â CuFeS2 â B1 â Maskedâ has resin-mineral interface masking and is average of three experiments. Line âOCP â CuFeS2 â B1â has no resin-mineral interface masking and is average of two experiments: âTest 1â, âTest 4â. Error bars are two-sided t-distribution 95% CI. ................................................................................................................. 81 Figure 52: NON-MASKED DATA SHOULD NOT BE USED WITH CONFIDENCE. OCP data for CuFeS2 massive electrode Origin B â B1 (characterization data: Table 5 â Table 17, Figure 20 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.294 â 3.569 cm2. âOCP â CuFeS2 â B1 â Maskedâ has resin-mineral interface masking and is average of three experiments. âOCP â CuFeS2 â B1â has no resin-mineral interface masking and is average of four experiments: âTest 1â, Test 2â, âTest 3â, and âTest 4â. Error bars are two-sided t-distribution 95% CI. ..................................................................................................................................... 82 xix Figure 53: Galvanostatic polarization (GAL) applied at 0.5 μA (masked) and 1 μA (unmasked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. Both lines represent average of three experiments with two-sided t-distribution 95% CI error bars. ........................................................................................ 84 Figure 54: Chalcopyrite massive electrode hand sawed to extract mineral from resin. Resin maintains enough bonds to the chalcopyrite surface resulting in fracturing of the mineral surface from bulk when separation is attempted. ............................................................................................................................. 86 Figure 55: Galvanostatic polarization (GAL) applied at 0.1, 0.3, and 0.5 μA (masked) and 1 μA (masked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. All lines represent average of three experiments with two-sided t-distribution 95% CI error bars. ................................................................... 87 Figure 56: Galvanostatic polarization (GAL) applied at 0.1, 0.5, 1, 10, and 100 μA (masked) and 1, 10, and 100 μA (unmasked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. Masked lines represent average of three experiments, unmasked lines represent average of four experiments, except 0.99â0.33 μA/cm2 represents three. All lines with two-sided t-distribution 95% CI error bars. ............ 88 Figure 57: Isolated display of data from Figure 56 for GAL applied at 100 μA for CuFeS2 massive electrode Origin A â A1 masked (SA = 0.442 cm2) and unmasked (SA = 1.012 â 3.024 cm2). All lines with two-sided t-distribution 95% CI error bars. ................................................................................................................. 88 Figure 58: Galvanostatic polarization (GAL) data at 10 min, 1 hour, and 2 hours for 0.1, 0.3, 0.5, 1, 10, and 100 μA and 1 mA for step-wise building of anodic polarization curves. Data for CuFeS2 massive electrodes Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2, unmasked = 1.012 â 3.024 cm2. Masked data represent average of three experiments, except 10 and 100 μA average of four. Unmasked data represent average of four experiments, except 1 μA represents three. All data with two-sided t-distribution 95% CI error bars. ................................................................ 89 Figure 59: Galvanostatic polarization (GAL) data at 1 hour for 0.1, 0.3, 0.5, 1, 3, 5, and 10 μA for step-wise building of anodic polarization curves. Potentiostatic polarization (POT) data at 1 hour; E based on average potential value produced from GAL at 1 hour. Data for CuFeS2 massive electrodes Origin B â B3 (characterization data in Table 5 â Table 17, Figure 24 â Figure 25) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2. Data represent average of three experiments. All data with two-sided t-distribution 95% CI error bars. ....................................... 91 Figure 60: Comparison of three exposure times for CuFeS2 masked electrode galvanostatic polarization (GAL) data from Figure 58 overlaid on 1 hour step-wise potentiodynamic (swPOTD) polarization in 2 g/L H2SO4 at 25°C reproduced from Figure 4a in Viramontes et al. (2007). ..................................................... 92 xx Figure 61: Reproduction of Figure 42 from 4.2 Open Circuit Potential showing a box and whisker diagram of OCP data for three CuFeS2 origins compared to literature with the addition of three red lines. Solid red: average OCP of Origin A, B, and C (from 7 massive electrodes and 26 experiments in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper). Dotted red: two-sided t-distribution 95% CI error bars (491.9 ± 9.7 mV SHE). ................................................................................. 94 Figure 62: Reproduction of Figure 41 from 4.2 Open Circuit Potential showing OCP data for three CuFeS2 origins with addition of the three originsâ average (7 massive electrodes, 26 experiments in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper). All data with two-sided t-distribution 95% CI error bars. .................................................................................................................... 95 Figure 63: Galvanostatic polarization (GAL) applied at 1 μA data for three CuFeS2 originsâ massive electrodes with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Origin characterization data: Table 5 - Table 17, Figure 17 â Figure 31. Surface area with mask = 0.442 cm2. All lines are average of multiple experiments with two-sided t-distribution 95% CI error bars (origin â number of electrodes â number of experiments): A â 1 â 3, B â 3 â 10, C â 2 â 6. ............................................................................................................................................. 96 Figure 64: Galvanostatic polarization (GAL) applied at 10 and 100 μA data for three CuFeS2 originsâ massive electrodes with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Origin characterization data: Table 5 - Table 17, Figure 17 â Figure 31. Surface area with mask = 0.442 cm2. All lines are average of multiple experiments with two-sided t-distribution 95% CI error bars. (Origin â number of electrodes â number of experiments): 22.62 μA/cm2 = A â 1 â 3, B â 3 â 10, C â 1 â 3 | 226.24 μA/cm2 = A â 1 â 3, B â 1 â 2. ....................................... 97 Figure 65: Galvanostatic polarization (GAL) applied at 1 μA data for three CuFeS2 Origin B massive electrodes (characterization data: Table 5 - Table 17, Figure 20 â Figure 25) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. All data represent average of three experiments, except B2 average of four. All data with two-sided t-distribution 95% CI error bars. ................................................................................ 98 Figure 66: Galvanostatic polarization (GAL) applied at 10 and 100 μA data for three CuFeS2 Origin B massive electrodes (characterization data: Table 5 - Table 17, Figure 20 â Figure 25) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. All data represent average of three experiments, except B1 @ 226.24 μA/cm2 average of two and B2 average of four. All data with two-sided t-distribution 95% CI error bars. ................................................................................................................................................... 98 xxi Figure 67: Galvanostatic polarization (GAL) data at 1 hour for 0.1, 0.3, 0.5, 1, 10, and 100 μA and 1 mA for step-wise building of anodic polarization curves from CuFeS2 massive electrodes Origin A â A1 and Origin B â B1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2; A1 unmasked = 1. 012 â 3.024 cm2; B1 unmasked = 1.294 â 3.569 cm2. Masked data represent average of three experiments, except 10 and 100 μA average of four and B1 at 1 mA average of two. A1 unmasked data represent average of four experiments, except 1 μA represents three. B1 unmasked represent average of three experiments, except 100 μA is one. All data with two-sided t-distribution 95% CI error bars. ............................................................................................................................................................ 99 Figure 68: Comparison of two originsâ three CuFeS2 masked massive electrodesâ galvanostatic polarization (GAL) data using the compilation method from Figure 58 overlaid on 1 hour step-wise potentiodynamic (swPOTD) polarization in 2 g/L H2SO4 at 25°C reproduced from Figure 4a in (Viramontes et al., 2007). ......................................................................................................................... 100 Figure 69: Comparison of two originsâ three CuFeS2 masked massive electrodesâ galvanostatic polarization (GAL) data using the compilation method from Figure 58 overlaid on a reproduction of âAnodic polarization curves for CuFeS2 from 6 different locations in 1 M H2SO4, 30 mV/min, 25°Câ (Warren et al., 1982). ................................................................................................................................ 101 Figure 70: OCP data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. ..................................... 104 Figure 71: Galvanostatic polarization (GAL) applied at 1 μA data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. ...................................................................................................... 105 Figure 72: Galvanostatic polarization (GAL) applied at 1 μA data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution sparged with nitrogen at 10 mL/min. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. ..................................... 106 Figure 73: Chalcopyrite massive electrode Origin B â B4 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) Optical imagery of sample masked to surface area = 0.442 cm2 (Right) SE polished to 1 μm diamond polish at 7x magnification .......................................................................................................... 110 Figure 74: OCP data for CuFeS2 massive electrodes (characterization data: Table 5 - Table 17, Figure 18 â Figure 19, Figure 28 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. (Left) Origin C â C1 and C2 with data for first experiments run on these electrodes (Right) Origin A â A1 with data for first masked OCP experiments .............................. 111 xxii Figure 75: OCP data for CuFeS2 Origin B (characterization data: Table 5 - Table 17, Figure 20 â Figure 27) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. These are the first experiments run on these electrodes. (Top Left) Origin B â B1 crack free (Top Right) Origin B â B2 crack free (Bottom Left) Origin B â B3 crack free (Bottom Right) Origin B â B4 with cracks present in both expsosed and masked surfaces ............................................................................ 111 Figure 76: Galvanostatic polarization (GAL) applied at 0.1, 1, 10, and 100 μA data for CuFeS2 Origin B â B4 massive electrode (characterization data: Table 5 - Table 17, Figure 26 â Figure 27) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Cracks are present in both expsosed and masked surfaces. ......... 113 Figure 77: Galvanostatic polarization (GAL) data for CuFeS2 Origin B â B4 from Figure 76 overlaid on Figure 65 and Figure 66 from section 4.4.2 Galvanostatic Polarization ................................................... 113 Figure 78: Galvanostatic polarization (GAL) applied at 0.5 and 100 μA and 1 mA data for CuFeS2 Origin B â B1 massive electrode (characterization data: Table 5 - Table 17, Figure 20 â Figure 21) with and without resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2; without = 1.294 â 3.569 cm2. Final mineral thickness 0.9 mm. ..................................................................................................................................... 114 Figure 79: Galvanostatic polarization (GAL) applied at 0.1, 0.3, 0.5, 1, 5, 10, and 100 μA and 1 mA data for CuFeS2 Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Lines with two-sided t-distribution 95% CI error bars represent average of three experiments. Connection wire suspected of cyclic strain resulting in fractured strands, increasing resistance. ............................................................................... 115 Figure 80: CuFeS2 Origin A â A1 massive electrode in solution showing connection wire bend to allow proper exposed surface orientation. (Left) Test 142 (Right) Test 195 showing reinforcement and inert shielding added to bend location ............................................................................................................. 116 Figure 81: Reproduction of Figure 33 from 3.2.1 Massive Electrode Construction â Example of massive electrode construction. (Left, Center Left, Center) 5.3.1.1 Mineral Selection and Preparation (Center Right) 5.3.1.2 Wire Preparation (Right) 5.3.1.3 Resin Preparation ........................................................... 120 Figure 82: Chalcopyrite from raw ore to prepared for electrode (Left) raw ore, section cut with diamond saw rock cutter, smaller section cut with diamond saw rock cutter, hand polished to 1200 grit with carbide paper (Right) raw ore, section fractured off while hand sawing, hand polished to 1200 grit with carbide paper ............................................................................................................................................ 121 Figure 83: CuFeS2 polished to 1200 grit with carbide paper. (Left) two roughly shaped pieces: left - two regions of large inclusions, right - region of large inclusions and an exposed crack (Center) Origin B â B1 exhibiting isolable cracks resulting from experimentation (Right) Origin B â B4 exhibiting cracks through entire sample that cannot be polished out or masked ............................................................................. 122 Figure 84: Chalcopyrite Origin A â A1 max diameter of 0.75 cm restricting masking to 0.442 cm2 ......... 122 xxiii Figure 85: Reproduction of Figure 32 from 3.2.1 Massive Electrode Construction â Four easily accessible wires considered for massive electrode construction. (Left - Red) multi-strand iron wire with too small gauge and strand count, but good single-strand gauge; avoid using if possible (Left - Blue) multi-strand copper wire with good gauge, single-strand gauge, and strand count â 19 AWG 12/30 (Left - White) multi-strand copper wire with ideal gauge, single-strand gauge, and strand count â 18 AWG 41/34 (Left - Yellow) multi-strand copper wire with good gauge, large single-strand gauge, and low strand count â 14 AWG 7/22 (Right) Wire scale shown next to ball point pen, approximately 6 in. = 0.1524 m. based on minimum distance to potentiostat connection ........................................................................................ 124 Figure 86: (Left Two) Enson EN-06B8 silvery epoxy and it securing a copper wire to a CuFeS2 mineral shown before resin application (Right Two) ¼â copper tape and it securing a copper wire to a CuFeS2 mineral shown after resin application ...................................................................................................... 125 Figure 87: Single use wooden stirring sticks. The small is good for low volume resin stirring. Use anything similar to the right side of large when stirring medium volumes of resin. Large volumes may require specialized mechanically assisted stirring. ................................................................................................ 126 Figure 88: Mineral massive electrode (Top Three) with entrained air bubbles in resin resulting from lack of proper de-gassing (Bottom Left) with entrained air bubbles resulting from no de-gassing (Bottom Right) with properly de-gassed resin ........................................................................................................ 126 Figure 89: (Left) 3 sizes of resin molds (Center) Section removed on blue molds to allow connection wire to exit 90° to the exposure surface to allow for better positioning in experimental setup (Right) Cured resin encasing mineral with connection wire attached with copper tape exiting 90° to the exposure surface ....................................................................................................................................................... 127 Figure 90: Chalcopyrite Origin B - B1 massive electrode: (Top Left) Step 1 â polished with 1200 grit carbide paper (Top Center) Step 2 â mask boundary marked at SA = 0.442 cm2 (Top Right) Step 3 â nail polish mask applied at least 2 mm past resin-mineral interface (Bottom Left) Step 4 â galvanostatic exposure at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Bottom Right) Step 5 â mask removed with paper towel soaked in acetone ........................................................................................................................... 128 Figure 91: (Left & Center) Luggin capillary with un-usable opaque glass frit (Right) Luggin capillary with brand new glass frit ................................................................................................................................... 129 Figure 92: Ideal Luggin capillary placement near experimental surface of mineral massive electrode .. 130 Figure 93: Galvanostatic polarization (GAL) applied at 1 mA (WE unmasked, no Luggin capillary) for 360 s to an Origin A CuFeS2 massive electrode (characterization data in Table 5 â Table 17) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area = 3.011 â 6.481 cm2. (Left) polished pre-exposure (Center) electrochemical cell with RE close to resin-mineral interface (Right) post-exposure showing visually different passivation near RE placement .............................................. 132 xxiv Figure 94: Galvanostatic polarization (GAL) applied at 1 mA (WE unmasked, no Luggin capillary) for 360 s to an Origin A CuFeS2 massive electrode (characterization data in Table 5 â Table 17) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area = 3.011 â 6.481 cm2. (Left) Luggin capillary distance from WE surface (Center) RE placed directly over WE surface (Right) post-exposure showing visually different passivation near RE placement ....................................................... 133 Figure 95: Images of an experiment showing electrochemical cell experimental setup. Luggin capillary intentionally placed to not cover mineral and have WE and RE in-line with CE. The non-electrically connected rods were weighed down (Bottom Center) Version 1 = 102.64 g (Bottom Right) Version 2 = 104.00 g â reduced rod holder overhang, made rod switching simpler ................................................... 133 Figure 96: Diagram of theorized interaction between non-electrically connected conductive and non-conductive rods contacting WE surface when polarized. A competing theory is the first state shown remains with the passivated area increasing with time, but not moving under the contact area of the rod. ............................................................................................................................................................ 135 Figure 97: Galvanostatic polarization (GAL) applied at 1, 10, and 100 μA and 1 mA data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18, Figure 19) masked in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Non-electrically connected rods from Table 31 placed in contact with WE surface. All lines represent average of four experiments except 2.26 μA/cm2 â Plastic HDPE represents three. All lines with two-sided t-distribution 95% CI error bars. .............................................................. 136 Figure 98: Images of an experiment showing electrochemical cell experimental setup. Reference electrode (without Luggin capillary) intentionally placed to not cover mineral and have working and reference electrode in-line with counter electrode. Non-electrically connected rod suspended at 5 mm above, with bottom surface parallel to, WE surface. ............................................................................... 137 Figure 99: Images of an experiment showing electrochemical cell experimental setup. Reference electrode (without Luggin capillary) intentionally placed to not cover mineral and have working and reference electrode in-line with counter electrode. (Top Three) Non-electrically connected rod suspended at 2 mm in front of and parallel to WE surface in line with CE (Bottom Left) Non-electrically connected rod suspended at 2 mm in front of and parallel to WE surface in line with CE (Bottom Right) Non-electrically connected rod placed halfway between first rod and CE, approximately 1.5 cm space on either side ................................................................................................................................................. 138 Figure 100: Diagram of theorized interaction between non-electrically connected conductive and non-conductive rods near WE surface when polarized. A competing theory is the first state shown remains with the passivated area increasing with time, but not moving under the shielded area of the rod. ..... 139 xxv Acknowledgements I would like to extend my deepest gratitude to the following people who have played distinguished roles throughout the execution and completion of this research:  Dr. Edouard Asselin for his continued guidance and insight paired with his eternal patience throughout this entire journey, as well as trusting me and making it possible for the journey to happen in the first place  Dr. David Dixon for jumping in to help make sense of things that were not self-evident and to help confirm ongoing theories  Dr. ZiHe (Ryan) Ren for being a helping hand and providing everything I needed to get off the ground to start my research and help make sense of things that may have been otherwise misinterpreted along the way  Jetti Resources for having the trust in me to complete this research and provide the funding necessary to make it possible as they revolutionize the copper extraction industry  Kemetco Research for donating their time and expertise to perform characterization at a momentâs notice  Heli Eunike for running a wonderful microscopy laboratory and always finding a way in her busy schedule to make sure I was able to get access to what has to be the most popular SEM in Canada whenever I needed too  My colleague and laboratory mate Hossein Zargarnezhad, Ph.D. for his continual support in answering any and all of my questions whenever I had them with a smile and encouragement, and somehow always finding the part I needed  My parents and sister for being ever loving, supportive, and positively critical of my work habits, ensuring I not only succeeded, but did so with honor and humility  My Lord and Savior, Jesus Christ, for building my character along the way and blessing me with this opportunity and countless provisions xxvi Dedication To every aspiring and actuating researcher: The road is long and hard. But enjoy it, knowing that the pursuit of knowledge for the betterment of us all is worth the sacrifices. I only hope that this provides a framework to build our future successes from. Now go improve the world! 1 Chapter 1: Introduction 1.1 Problem Definition Copper (Cu) is a highly desired material across many disciplines and industries due to its wide range of uses, including electronics, industrial and construction applications, art installations, and various commodities. It played a defining role in the Bronze Age and continues to be vital as the world electrifies its economy. The increased demand for Cu, driven by economic growth and electrification, has put a strain on current supply chains for the materials required to make this possible, presenting new challenges that require unique solutions. Factors such as increased ore complexity, decreasing ore grades, and the desire to reprocess waste streams (e.g. waste rock and tailings) have resulted in renewed funding for an old problem: how do we recover Cu from chalcopyrite (CuFeS2) using hydrometallurgical methods, such as heap leaching, instead of concentrating the mineral and smelting it? While all steps in a hydrometallurgical process are vital to its success, leaching is arguably the most important, as it allows for all further processes to occur, not only to an appreciable amount, but in some cases, to occur at all. Leaching is widely defined as a dissolution process through which soluble minerals are removed by a solvent, or lixiviant, from a solid material into an aqueous solution (Gupta, 2003; Tasker et al., 2003). There are many variations of leaching processes, each with its own advantages and drawbacks, tailored for specific locations and operations. In terms of chalcopyrite leaching, heap leaching in conjunction with bioleaching has garnered much commercial interest for nearly five decades to determine the correct conditions and mechanisms required when utilizing sulfuric acid (Debernardi & Carlesi, 2013; Tasker et al., 2003). Sulfuric acid leaching is done with an oxidant, typically ferric, which needs to be regenerated by oxygen. The following equations describe the leaching reactions that are generally agreed upon to take place (Dutrizac, 1989; Faris et al., 2017; A. Ghahremaninezhad et al., 2012; Hirato et al., 1987; Li et al., 2013; Linge, 1976, 1977; Munoz et al., 1979; Nicol, 2022; Olvera et al., 2014; Pan et al., 2012; Peters, 1976): Anodic oxidation of chalcopyrite:  â  +  +  +  [Equation 1] Cathodic reduction of ferric to ferrous:  +  â  [Equation 2] Oxygen regeneration of ferric from ferrous:  +  +  â  +  [Equation 3] Overall reaction on mineral surface:  +  â  +  +  [Equation 4] 2 When the leaching reaction occurs in the presence of sulfuric acid, Equation 1 through Equation 4 become the following (Faris et al., 2017; Ghahremaninezhad et al., 2012; Nazari et al., 2011, 2012): Redox reaction of chalcopyrite with ferric in the presence of sulfuric acid:  +   â  +  +  [Equation 5] Oxygen regeneration of ferric from ferrous in the presence of sulfuric acid:  +  +  â   +  [Equation 6] Overall leach reaction when in the presence of sulfuric acid:  + +  â  +  + +  [Equation 7] When performing this leaching in the presence of microorganisms (i.e. bioleaching) the ferric can be regenerated directly at a faster rate than by oxygen while also being able to oxidize the generated elemental sulfur, regenerating sulfuric acid (Debernardi & Carlesi, 2013): Regeneration of ferric by microorganisms in the presence of sulfuric acid:  +  +   +  [Equation 8] Sulfate from elemental sulfur by microorganisms in the presence of sulfuric acid:  + .  +   +  [Equation 9] The old problem that needs to be addressed pertains to the interaction between elemental sulfur and chalcopyrite during the leaching process. Is the inability to effectively recover Cu from CuFeS2 solely caused by the elemental sulfur hindering the reaction surface? Are there other interactions resulting from intermediate reactions beyond those shown in Equation 1 through Equation 7? Is the generation of surface-obstructing reaction products playing a major role in inhibiting leaching, or does chalcopyrite have intrinsic passivity that leads to slow reaction rates? Pyrometallurgy, which involves concentration and smelting, has long dominated the metallurgical extractive industry for base metals. Its high operating temperatures accelerate chemical reaction rates, making potentially unspontaneous reactions spontaneous while also separating the desired metal(s) from undesired impurities (U.S. Congress, 1988). The proven techniques and resulting products have kept pyrometallurgical processes as the default extractive technique. However, due to growing environmental concerns related to off-gases, high energy demands during concentration, and decreasing ore quality, other methods must be employed to meet the demand for metallurgical materials, particularly copper. Hydrometallurgy has increasingly filled the production gap left by pyrometallurgical methods. Some notable advantages being its ability to effectively extract from low-grade ores, including waste tailings, and have good environmental control while supporting a range of economies of scale tailored to specific operational needs (U.S. Congress, 1988). However, hydrometallurgy cannot compete directly with pyrometallurgical methods, i.e. it is not well adapted to copper concentrate processing (Dreisinger, 2006). The advantage of hydrometallurgical methods for copper processing 3 relies on the ability to process low grade ores. Indeed, the lower the ore grade, the more expensive it is to make a concentrate and the more uneconomical the smelting process becomes. There is consensus across literature that the majority of copper production is now from ores with approximately 0.2 â 1% copper, most averaging 0.6% (Greenwood & Earnshaw, 1997; Haldar, 2018; Han et al., 2018; Watling, 2013, 2014). CuFeS2 is the most prevalent copper-bearing mineral, accounting for upwards of 70% of copper deposits while only containing 34.5% copper in its purest form (Córdoba et al., 2008; Haldar, 2017). It is also one of the most prevalent copper-containing minerals in mining tailings (Falagán et al., 2017; Han et al., 2018). Current and past research has focused on revealing why chalcopyrite is recalcitrant to hydrometallurgical leaching methods. The majority point towards CuFeS2 passivation as the root cause (Watling, 2013). Despite this, there are few breakthroughs resulting in significant improvements in copper extraction. The two main challenges continuing to restrain hydrometallurgy from sweeping the industry are profitability and the passivation of chalcopyrite (Debernardi & Carlesi, 2013). At the time of publishing, the only commercially adopted, high-yield process in sulfuric acid is from Jetti Resources in partnership with the University of British Columbia. Together, they determined and successfully use proprietary catalytic technology in bioleaching to recover economic copper extraction. Existing public literature covers a wide range of information and techniques. However, before taking any paper at face value for its assertions, it is important to understand the lack of continuity, cohesiveness, and overall agreement throughout the existing literature. This results from competing theories and non-reproducible results, both between recent and older highly citied work. This became evident quite quickly during literature review as some papers make broad claims or even attempt to disprove other papers despite using substantially dissimilar solutions, methods, and experimental conditions. While sulfuric acid is the standard lixiviant used in hydrometallurgy, the addition of various salts or changes in acid concentration can affect the electrochemistry (for example simply through solution Fe speciation) and make comparisons complicated. This holds true for comparing similar processes as well as trying to understand how different processes would affect the same mineral. For example, one work focuses on understanding the active-passive behavior of a mineral and another on how it will fare in galvanic leaching, but extrapolation of one work to another is not possible when the conditions are different. Some works use nitrate or ferric chloride solutions while others use ferric sulfate (Kimball et al, 2010; Li et al., 2013; Linge, 1976; Majima et al., 1985; Qian et al., 2014; Velásquez-Yévenes et al., 2010; Watling, 2013). These are completely different, particularly as regards iron complexation. While they state differences in reaction kinetics, they may, for example, not make it clear which species resulted in dissolution as more than one species was present that is capable of such dissolution. They may go on to present ambivalent results or even use different solutions to confirm their results. In cases where the solutions are comparable, they use different ferric/ferrous concentrations or completely different intended leaching methods, heap leaching versus pressure leaching versus in-situ leaching for example. Furthermore, all are reporting at a wide range of ore compositions and temperatures, even comparing stagnant versus mixed solutions (Córdoba et al., 2008; Debernardi & Carlesi, 2013; Dutrizac, 1989; Ghahremaninezhad et al., 2012; Han et al., 2018; Hirato et al., 1987; Kaplun et al., 2011; Khoshkhoo et al., 2017; Khoshkhoo et al., 2014; Kimball et al., 2010; Koleini et al., 2011; Li et al., 2013; Li et al., 2017; Lin et al., 2012; Liu et al., 2018; Majima et al., 1985; Olvera et al., 2014; Qian et al., 2014; S. F. Wu et al., 2015; Yue & Asselin, 2014). The same treatment gets applied to open circuit potential (OCP) and passivation 4 potential (PP). This makes it impossible to translate how a mineral would behave in varying solutions or conditions as no standard exists for comparison (Tanne & Schippers, 2021). The lack of reproducibility has become synonymous with mineral electrochemistry through characterization in published work (Barton & Hiskey, 2022b; Li et al., 2013; Viramontes et al., 2007; Warren et al., 1982). The present work seeks to provide a way to reconcile differences, improve reproducibility, and lay a framework for more consistent research. Not all research can use the same solution pH or the same background ions because not all research focuses on the same intended application. However, most research utilizes large (approximately 0.5 â 3 cm2 in surface area), a.k.a. âmassiveâ, mineral electrodes. Most papers do not completely explain the physical methods used to produce their sample electrodes or provide details for the specific sample, many only stating the sample appeared visually free from inclusions or contained a qualitative amount (Debernardi & Carlesi, 2013; Dutrizac, 1989; Ghahremaninezhad et al., 2015; Hong-xu et al., 2006; Khabibullinet al., 2009; Khoshkhoo et al., 2014; Liu et al., 2017; Majima et al., 1985; Mikhlin et al., 2016; Nicol, 2022; M. Nicol et al., 2017; Parker et al., 2003; Tanne & Schippers, 2021; Warren et al., 1982; Wu et al., 2015). To establish a set of standards for reproducible data, we must return to the fundamentals of electrochemical methods. Multiple organizations have been founded for this direct purpose. ASTM International (founded as the American Society for Testing and Materials), American National Standards Institute (ANSI), International Organization for Standardization (ISO), and NACE International (founded as the National Association of Corrosion Engineers) are all internationally recognized and respected for this work. They even recognize the National Information Standards Organization (NISO), accredited by ANSI, to ensure documentation through all their organizations is standardized. There is great effort into ensuring this is accomplished in non-mineral electrochemical experimentation. Unfortunately, this level of care has not extended to mineral electrochemistry. While standards exist laying out general terminology definitions and conventions for corrosion electrochemistry (Table 1) (ASTM Standard G3-14, 2019; ISO 8044:2020, 2020; NACE/ASTM Standard G193-22, 2022) that have been colloquially adapted and adopted within mineral electrochemistry, there is no explicit mention of mineral electrochemistry or mineral corrosion. The existence of these organizations and the international acceptance of their work highlighting how electrochemical methods are set up provide the foundation for standardization. ASTM International alone has over 200 standards dedicated to non-mineral electrochemistry, many of which would be of great interest for mineral electrochemistry (Table 1) (ASTM Standard G102-23, 2023; ASTM Standard G111-21a, 2021; ASTM Standard G150-18, 2018; ASTM Standard G5-14, 2021; ASTM Standard G78-20, 2020), including some that could have had impact on this research (Table 1) (ASTM Standard D6208-07, 2020; ASTM Standard G1-03, 2017; ASTM Standard G46-21, 2021; ASTM Standard G59-97, 2020; ASTM Standard G71-81, 2019; ASTM Standard G82-98, 2021; NACE TM0169/G31-21, 2021). In similar fashion, ISO has a wealth of standards for non-mineral electrochemistry that would be of interest for mineral electrochemistry and this research (Table 1) (ISO 11463:2020, 2020; ISO 11845:2020, 2020; ISO 17474:2012, 2022; ISO 17475:2005, 2019; ISO 17864:2005, 2005; ISO 8407:2021, 2021). 5 Table 1: ASTM, ISO, and NACE standards for non-mineral corrosion electrochemistry that could impact mineral electrochemistry General Terminology Definitions and Conventions for Corrosion Electrochemistry ASTM Standard G3-14 Standard Practice for Conventions Applicable to Electrochemical Measurements in Corrosion Testing ISO 8044:2020, 2020 Corrosion of metals and alloys â Vocabulary NACE/ASTM Standard G193-22, 2022 Standard Terminology and Acronyms Relating to Corrosion Standards for Non-Minerals that Require a Mineral Electrochemistry Version ASTM Standard G102-23, 2023 Standard Practice for Calculation of Corrosion Rates and Related Information from Electrochemical Measurements ASTM Standard G111-21a, 2021 Standard Guide for Corrosion Tests in High Temperature or High Pressure Environment, or Both ASTM Standard G150-18, 2018 Standard Test Method for Electrochemical Critical Pitting Temperature Testing of Stainless Steels and Related Alloys ASTM Standard G5-14, 2021 Standard Reference Test Method for Making Potentiodynamic Anodic Polarization Measurements ASTM Standard G78-20, 2020 Standard Guide for Crevice Corrosion Testing of Iron-Base and Nickel-Base Stainless Alloys in Seawater and Other Chloride-Containing Aqueous Environments Standards for Non-Minerals that would Impact this Work if Existed in a Mineral Electrochemistry Version ASTM Standard D6208-07, 2020 Standard Test Method for Repassivation Potential of Aluminum and Its Alloys by Galvanostatic Measurement ASTM Standard G1-03, 2017 Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens ASTM Standard G46-21, 2021 Standard Guide for Examination and Evaluation of Pitting Corrosion ASTM Standard G59-97, 2020 Standard Test Method for Conducting Potentiodynamic Polarization Resistance Measurements ASTM Standard G71-81, 2019 Standard Guide for Conducting and Evaluating Galvanic Corrosion Tests in Electrolytes ASTM Standard G82-98, 2021 Standard Guide for Development and Use of a Galvanic Series for Predicting Galvanic Corrosion Performance NACE TM0169/G31-21, 2021 Standard Guide for Laboratory Immersion Corrosion Testing of Metals ISO 11463:2020, 2020 Corrosion of metals and alloys â Guidelines for the evaluation of pitting corrosion ISO 11845:2020, 2020 Corrosion of metals and alloys â General principles for corrosion testing ISO 17474:2012, 2022 Corrosion of metals and alloys â Conventions applicable to electrochemical measurements in corrosion testing ISO 17475:2005, 2019 Corrosion of metals and alloys â Electrochemical test methods â Guidelines for conducting potentiostatic and potentiodynamic polarization measurements ISO 17864:2005, 2005 Corrosion of metals and alloys â Determination of the critical pitting temperature under potentiostatic control ISO 8407:2021, 2021 Corrosion of metals and alloys â Removal of corrosion products from corrosion test specimens 6 This knowledge of reproducibility is not limited to standards organizations, there is extensive literature addressing reproducibility efforts within non-mineral electrochemical experimentation. Referenced here are a small fraction of the work spanning 27 years documenting pitting reproducibility research in non-mineral electrochemistry (Eghbali et al., 2011; Frangini & De Cristofaro, 2003; Lillard, 2001; Ovarfort, 1988; Stockert et al., 1985). This shows the wealth of shared knowledge surrounding a singular issue within non-mineral electrochemistry. Unfortunately, all of these methods defined through standards and literature are not directly applicable to mineral electrochemistry due to minerals being fundamentally different than non-minerals. Even if they were, the proof has most certainty not been documented, especially not through well established and internationally recognized organizations. I was unable to find any resources laying out ways to combat controllable error across mineral electrochemical experimentation at the time of publishing. While there may be industry standard laboratory practices, they get communicated verbally, not written down and proven. Acquiring reproducible data plagues mineral electrochemistry. As a result, I seek to show the importance of experimental methods by observing their effects and documenting them. 1.2 Objectives of this Investigation With the known difficulty of acquiring reproducible data in mineral electrochemistry, there are gaps in collective knowledge and, consequentially, an inability to infer actionable information. Therefore, I seek to quantify the variability in results and provide an improved general structure for reporting to allow for future comparisons, and hopefully, process design. 1.3 Why Chalcopyrite? There are many mineralogical forms containing copper. Due to it being a chalcophile, the majority of Cu is found as sulfides (Habashi, 1997); however, large amounts are also found as oxides or carbonates. Common examples of such minerals are: azurite (Cu3(CO3)2(OH)2), malachite (Cu2CO3(OH)2), bornite (Cu5FeS4), covellite (CuS), chalcocite (Cu2S), tetrahedrite ((Cu,Fe)12Sb4S13), cuprite (Cu2O), enargite (Cu3AsS4), and chalcopyrite (CuFeS2). I studied chalcopyrite in this thesis because it has the following features: a) It is considered the most important Cu source due to its prevalence i. Accounts for upwards of 70% of copper deposits while containing 34.5% copper in its purest form (Córdoba et al., 2008; Haldar, 2017) ii. It is one of the most prevalent copper containing minerals present in mining tailings as it is notoriously difficult to separate the copper using traditional mining techniques (Debernardi & Carlesi, 2013; Falagán et al., 2017) b) CuFeS2 leaching is electrochemical (Peters, 1976) c) It is the subject of most electrochemical studies because it passivates d) There is limited existing literature presenting variability information for CuFeS2 electrochemistry 7 Chapter 2: Literature Review 2.1 Copper: Itâs Need and How to Source There is no brevity of conversation regarding the shortage of minerals required to produce the future. Global population is growing faster now than any other time in history and, in parallel, mineral consumption is growing faster than the population as more consumers enter the market and global living standards increase (Kesler, 2007). Precious metals demand is expected to increase steadily in the next few decades as a result of growing pressure for electrification, digitalization, and infrastructure. By 2050, copper demand is expected to increase by between 275 â 350% and exceed current copper reserves as early as 2036 (Elshkaki et al., 2016). Unsurprisingly, this increased demand has brought with it increased push back. From the Paris Agreements and G20 Summits to political elections and daily social media trends, conservation has become the focus of many global discussions and subsequently increased the rate of technological innovations. The convergence of discussion and innovation has refocused the lens through which many are viewing the future, further driving exponential change in social, political, environmental, and economic spheres (Keenan et al., 2019; Mporas et al., 2020). In contradiction, the general population demands the resources now, but rebukes the existing methods to provide them. The preferential extraction of minerals from the highest ores grades has led to precipitously decreasing average ore grades and the need to process exponentially more ore for equivalent production. With demand at a historical high and ore grades a historical low, extraction scale is increasing at nearly the inverse rate of ore grade decline, shown in Figure 1 for copper. While this balance makes sense, as ore grade approaches average resource grade, the associated economic and environmental impacts, particularly in energy and water consumption paired with greenhouse gas emissions, will act as barriers to industry expansion (Northey et al., 2014). The amount of copper production has remained relatively unchanged in the same time ore production has increased over twentyfold; resulting in the copper to ore production ratio dropping at a faster rate than ore grade. Figure 1: Copper production versus ore grade reproduced here from graph originally produced by Raw Materials Group, Stockholm (Bowker & Chambers, 2017; The World Bank Group, 2006) 8 This can be partially explained by the stable forms minerals usually present themselves. Copper is a chalcophile element, meaning it has an affinity for sulfide phases. As a result, the majority is being found as sulfides; however, large amounts are also found as oxides or carbonates. This introduces the challenge of having to deal with sulfur alongside typical extraction challenges. Chalcopyrite (CuFeS2) contains 35.0% by weight sulfur, that is 0.5% more than copper, in its purest form (Córdoba et al., 2008; Haldar, 2017). This results in large ore volumes boasting small copper concentrations, and contributes significantly to global mining operations producing upwards of 25 billion tonnes in solid waste a year, of which nearly 7 billion is mine tailings, the by-product of the production of mineral resources, the rejected and historically unrecoverable (Lu et al., 2018; Mporas et al., 2020). Therefore, CuFeS2 is one of the most prevalent copper containing minerals present in mining tailings due to its slowed dissolution kinetics resulting from passivation using traditional mining techniques (Debernardi & Carlesi, 2013; Falagán et al., 2017). Much of the research being conducted on copper is dedicated to discovering why chalcopyrite is recalcitrant to these methods. Research running parallel to this is novel methods to extract higher yields from both new and old copper depositories, whether through traditional mining or alternative sources such as mine tailings. One of the main factors drawing attention to reprocessing tailings is its reduced capital investment compared to conventional extraction which requires drilling, blasting, and haulage. Moreover, processing techniques that were formerly considered inefficient and uneconomic have been developed into profitable, efficient technologies, namely hydrometallurgy. These processes result in less environmental footprint and consume less energy than traditional methods (Ndlovu et al., 2017). Reprocessing will support sustainable mining, mitigating unfavorable public opinions and supporting environmental conservation (Mateus & Martins, 2019). In order to identify the process methods best equipped to produce high copper extraction from chalcopyrite, chalcopyrite and the techniques for its evaluation must be better understood. 2.2 Chalcopyrite Thermodynamics in Oxidative Leaching The chalcopyrite-water (CuFeS2 â H2O) Pourbaix (Eh-pH) diagram allows for understanding the chemical interactions that can take place by presenting the species present at a given pH and potential under specific conditions (temperature, pressure, and concentration/activity). While it shows where compounds are stable and regions of no corrosion is possible, it does not show kinetics, but rather a static picture of processes, ignoring metastable states/species. There have not been many published for this system, with a commonly cited Eh-pH diagram being shown in Figure 2. However, this diagram does not reference CuFeS2 directly. Rather it presents CuFeS and Cu3FeS4 species having a stable point across nearly the entire pH scale 0 â 14, unless there was unintentional omission of the subscript â2â from sulfur in CuFeS. Figure 2 is reference by Córdoba et al. (2008) as a recreation of the diagram presented in Garrels & Christ (1965) which is further a reproduction from Garrels (1960) that credits an unpublished manuscript from Harvard University in 1957 â 1958 from R. Natarajan and R. Garrels (I was not able to locate or acquire this manuscript). Córdoba et al. (2008) presents the diagram as âCuFeS2âH2O system at 25°Câ which is technically correct assuming the unintentional omission; however, Natarajan and Garrels (unpublished 1957 â 1958) and subsequently Garrels (1960) and Garrels & Christ (1965) present two diagrams and label them as âThe system CuâFeâSâOâH (in part) at 25°C and 1 atmosphere total pressure. Total dissolved sulfur = 10-1 m.â and ââ¦Total dissolved sulfur = 10-4 m.â They are presented in Figure 3 and Figure 4, respectively. It is therefore unclear which diagram is being referenced by Córdoba et al. (2008) as neither figure contains the H2S â HS- or HSO4- â SO42- lines. In contrast, Gaudin (1974) references the diagram 9 with ââ¦Total dissolved sulfur = 10-4 mâ with no additions or removals while truncating the diagram to be pH 2 â 8 and Eh = -0.8 â 1.0 volts. The distinction, and therefore clarity, of what the diagram represents is vital as the interactions experienced changes with conditions, such as when H2S is not present as a reactant and FeS2 is not present as a product, shown in Figure 6 from Peters (1976). Peters (1976) also presents the only other widely available and referenced (Daehn & Allanore, 2020; Karcz et al., 2017; Schlesinger et al., 2011) Eh-pH diagram for the Cu â Fe â S â H2O system, presented in Figure 5, where the activity of all components is 0.1 M except for Cu2+ at 0.01 M. Chapter 7 from Garrels & Christ (1965) presents directions on how to construct Eh-pH diagrams. Peters & Majima (1968) reference Garrels & Christ (1965) as exemplar when constructing their Eh-pH diagram for FeS2 â H2O at 25°C in the acid region. This suggests Peters (1976) used the same methods when constructing Figure 5, while knowing of the existence of Figure 3 and Figure 4, but added focus for sulfate production from sulfide minerals during anodic polarization. The following Nernst equations guide the construction of these diagrams. Most general reaction:  +  â " +# + $ [Equation 10] % = % â ()$* $+ + +"+,# = % + .()$* +"+,#+ + [Equation 11] Horizontal lines: " + $ â  [Equation 12] %./.0 = % + .()$* +"+  [Equation 13] Vertical lines:  +  â " +# [Equation 14] 12 = +"+,#+ + [Equation 15] Slanted lines:  +  â " +# + $ [Equation 16] %./.0 = % + .()$* +"+  â #$ â.()* 4 [Equation 17] 10 where: E° = Standard electrode potential R = Universal gas constant (8.314 J/molK) T = Absolute temperature (K) n = Number of electrons per mole â± = Faradayâs constant (96,485 C/mol) 6 = Activity Keq = Equilibrium constant Two example equations from the CuFeS2 â H2O system are as follows (Peters, 1976):  â  +  +  +  [Equation 1] %./.0 = %|,, + .() *  +,+, [Equation 18]  +  â  [Equation 2] %./.0 = %,|, +.() * +, +, = % + .()* +,+, [Equation 19] These equations represent the upper left of the diagram, where sulfur will separate from copper and iron, but copper and iron will not separate in the presence of elemental sulfur (S°) formation. This leads into the theoretical nature of decomposition pathways present on the diagram. Some may proceed âover geological timescalesâ or will become spontaneous at high pressures, however they are âknown not to occur in the laboratoryâ (e.g. H2S consumed as reactant or FeS2 formation) (Daehn & Allanore, 2020). The goal of hydrometallurgy seeking to acquire copper in aqueous form is further hindered by chalcopyriteâs large stable region spanning approximately pH 0 â 14 and Eh = -0.8 â 0.3 V depending on conditions when observed (Figure 3 â Figure 6). Further, this region is surrounded by Cu â S species. Therefore, there appears no direct path to Cu° or Cu2+ without sulfur bonding. This paired with copperâs nobility to iron leads to chalcopyriteâs recalcitrance to copper dissolution. It has been recognized within industry and research and has resulted in the formation of many theories attempting to describe the reaction kinetics and determine a way to improve them. 11 Figure 2: Copy of "Pourbaix diagram for the CuFeS2-H2O system at 25°C (Garrels and Christ 1965)" (Córdoba et al., 2008) 12 Figure 3: Copy of âThe system CuâFeâSâOâH (in part) at 25°C and 1 atmosphere total pressure. Total dissolved sulfur = 10-1 m. (Courtesy R. Natarajan and R. Garrels.)â (Garrels, 1960) 13 Figure 4: Copy of âThe system CuâFeâSâOâH (in part) at 25°C and 1 atmosphere total pressure. Total dissolved sulfur = 10-4 m. (Courtesy R. Natarajan and R. Garrels.)â (Garrels, 1960) 14 Figure 5: Copy of âThe Eh-pH Diagram for the Cu-Fe-S-H2O System.â (Peters, 1976) 15 Figure 6: Copy of âEh-pH Diagram for Chalcopyrite Decomposition Without H2S as a reactant, and Without FeS2 as a Product (After Majima4).â (Peters, 1976). âMajima4â was not found referenced in Peters (1976). Two Majima works were referenced but neither were the 4th reference; however, it is most likely based on findings from an unpublished manuscript, their 2nd reference: âH. Majima and E. Peters, Electrochemical Mechanisms for the Decomposition of Metal Sulphides, Unpublished manuscript, 1969, 24 pages.â 16 2.3 Chalcopyrite Passivation The thermodynamics of polarizing chalcopyrite present multiple avenues to acquire either Cu° or Cu2+. These can be identified in the Pourbaix diagrams in Figure 3 â Figure 6. Depending on activities, across approximately pH 0 and Eh < -0.1 V through pH 20 and Eh < -0.8 V, Cu° is stable as well as across approximately pH 4 and Eh = 0.3 V through pH 15 and -0.7 V < Eh < -0.4 V. Cu2+ presents as stable in the upper left from approximately pH 0 â 7 and 0.1 V < Eh < 1.2 V. While thermodynamics determines if a process is possible, the viability, and ultimately, the success of hydrometallurgical processes rely on kinetics. Therefore, despite the thermodynamic favorability of extracting copper from chalcopyrite, it is notorious for being recalcitrant to hydrometallurgical methods due to a passivation that occurs while undergoing processing, reducing the kinetics to practically null. There are many theories seeking to demystify the passivation process which have led to many research papers being published on the topic; however, there has not been unanimity on the root cause. Although, it is mostly agreed upon that the passivation results from a layer, or layers, forming over the mineral surface, but the composition of detriment is up for debate. Suggested compositions are: intrinsic passivity, elemental sulfur (S0), disulfide (S22-), polysulfide/metal-deficient sulfide (Sn2-), iron hydroxy-oxide/iron oxyhydroxides, jarosites, or some combination thereof (Debernardi & Carlesi, 2013; Hackl et al., 1995; Li et al., 2013). Whichever composition, the possible effects of this formed layer have been narrowed down to the following (Debernardi & Carlesi, 2013; Hackl et al., 1995; Li et al., 2013) (references listed by no means an exhaustive list; rather these works effectively collated existing literature discussing these topics): â¢ Slows the rate of transfer of attacking oxidant species or ions from the bulk electrolyte to the chalcopyrite reaction surface â¢ Slows the rate of transfer of electrons and product ions and species from the reacting surface to the bulk electrolyte â¢ Slows the rate of electron transfer to the oxidant in the bulk electrolyte â¢ Allows the transfer of ions from the electrolyte to the surface, or, vice versa â¢ Entirely coats the surface and prevents the attacking oxidants from contacting the active chalcopyrite surface These effects have been determined through investigation of the passivating layer during the ferric leaching of chalcopyrite utilizing surface studies and electrochemical methods. The sections following will detail suggested compositions of the layer(s) and comment on their validity for being the passivating constituents. 2.3.1 Elemental Sulfur Theory While undergoing leaching in ferric sulfate and ferric chloride acid solutions, chalcopyrite particles have been observed to acquire a layer, or layers, of elemental sulfur (Dutrizac, 1989; Munoz et al., 1979; Nazari & Asselin, 2009; Nazari et al., 2012). The following reaction (Equation 4) is believed to take place and accounts for elemental sulfur generation (Dutrizac, 1989; Ghahremaninezhad et al., 2012; Hirato et al., 1987; Li et al., 2013; Munoz et al., 1979; Nicol, 2022; Olvera et al., 2014; Pan et al., 2012; Peters, 1976):  +  â  +  +  [Equation 4] This reaction assumes complete production of elemental sulfur from the sulfide ion being oxidized during leaching; however, a small percentage, approximately 6% on average, âreports as SO4â (Dutrizac, 1989). 17 Therefore, free S0 is produced just under twice as fast as copper, with respect to molar ratio, and is suspected of coating the remaining chalcopyrite. This is a reasonable assumption as elemental sulfur is effectively inert in leaching systems with ferric ions so long as temperature is kept below sulfurâs melting point and, as a result, tends to remain suspended in leach solution and even adheres to vessel walls (Dutrizac, 1989). This elemental sulfur layer generation is charged with being the root cause for reduced reaction kinetics as the electron transfer through the sulfur layer is considered the rate limiting step (Munoz et al., 1979). However, the coating has been shown not to be homogeneous, growing in cycles of peeling and formation leaving discontinuities, forming a porous structure (Córdoba et al., 2009; Debernardi & Carlesi, 2013; Majima et al., 1985; Nazari & Asselin, 2009). Yet the porosity does not appear to be macroscopic, rather having a granular texture that does not readily allow solution through to the surface (Dutrizac, 1989). The growth and peeling cycling can potentially be described by sulfur allotropy, two forms of which being orthorhombic rings (S8) and polymeric chains (S-S), the former being the dominant and more stable solid allotrope. The latterâs instability and insolubility in solvents results in its ability to be oxidized, potentially by sulfur-oxidizing microorganisms or purely by its own instability, allowing for solubility of the sulfur layer (Debernardi & Carlesi, 2013; Nazari & Asselin, 2009). While sulfur allotropy being the root cause of peeling is currently a conjecture, peeling has been observed as two-dimensional aggregate flakes present in leach solution. The dense sulfur layer that formed appeared to be slowing the leaching rate until it peeled off, leaving a roughened surface which could not be completely encapsulated by elemental sulfur, allowing increased, linear kinetics (Hirato et al., 1987; Majima et al., 1985). The slowed, parabolic-like leaching rate occurred for the first approximately 100 hours of leaching and then was linear for the remaining of the leach (Hirato et al., 1987). Homogeneity of sulfur layer formation can also be effected by the growth mechanisms, which is largely a function of particle surface morphology and leaching solution (sulfate versus chloride) (Debernardi & Carlesi, 2013). However, particle size can also affect layer homogeneity. Chalcopyrite particles (approximately 1 cm2) with polished surfaces that were extensively pitted were observed to have both large and small sulfur globules in discrete sites, which could lead to kinetic models matching that of linear (steady state), parabolic (ion diffusion limited), or accelerating (increasing leaching rate with time, e.g. protection layer failure) (Dutrizac, 1989; Faraji et al., 2022; Khanna, 2005). However, this was not the case for chalcopyrite particles sub 37 μm as they were completely enveloped in elemental sulfur. This occurred in both granular and globular fashion, in which smaller sulfur coated particles would agglomerate and not form rough leached surfaces, potentially accounting for non-linear/parabolic leaching kinetics being observed (Dutrizac, 1989). Particle size, pH, temperature, concentration, redox potential/pulp density, oxygen presence, and catalyst amount and type affect the quantity and density of elemental sulfur detected (Debernardi & Carlesi, 2013; Dutrizac, 1989; Hirato et al., 1987; Li et al., 2013; Munoz et al., 1979). Elemental sulfur as a passivating layer has been contested. While it is generally agreed that S° is found in the majority of leaching scenarios, many have concluded it does not actually take part in the passivation and is merely present as a spectator product that exists as a film on chalcopyrite species (Córdoba et al., 2009; Hirato et al., 1987; Pan et al., 2012; Parker et al., 2003). Therefore, the dense sulfur layer cannot act as the limiting leaching step resulting in parabolic kinetics, this being supported by no observed effect to rate when the elemental sulfur film is removed (Linge, 1976). This is further disproved by a sulfur layer pore diffusion model not being able to produce dissolution rates within a reasonable range of experimental values. Instead, the 18 chalcopyrite lattice is proposed to cause this as the oxidation process occurs in slow steps within the lattice, providing a possible explanation for a fast initial reaction that slows (Linge, 1976). 2.3.2 Metal Deficient Polysulfide Theory With no convincing evidence for passivation through the elemental sulfur theory, an explanation for observed kinetics remains necessary. Solid-state diffusion into and out of the chalcopyrite lattice may instead be responsible for the slow kinetics (Linge, 1976, 1977; Munoz et al., 1979). While the metal deficient polysulfide theory is fundamentally different, it follows the same theoretical reaction (Equation 4) as the elemental sulfur theory:  +  â  +  +  [Equation 4] However, it identifies that the chalcopyrite lattice has a metal deficient surface at the start of the reaction. Conservation of energy leads chalcopyrite to react in one of two ways, requiring accounting for an experimentally found 6+ charge resulting from three cations ejected for every three electrons consumed by the oxidant (Linge, 1976). The first speculated path suggests lattice expulsion of an un-oxidized sulfide ion to maintain neutrality of charge. The reaction is expressed in Equation 20, where an electron hole is represented by â and 9 is the extent of reaction (Linge, 1976).  + : â : â  : :;:  <:+ : + : + =: > [Equation 20] The second speculated path suggests that in an acid solution, the three cation vacancies are filled by three protons, leaving the sulfide sub-lattice undisturbed and satisfying charge neutrality, expressed in Equation 21 (Linge, 1976).  + : â : â  : :;: :  + : + : [Equation 21] These two reactions result in a chalcopyrite phase that is either metal-deficient (e.g. Cu3Fe2S6) as in Equation 20, or proton-stabilized (e.g. Cu3Fe2H3S8) as in Equation 21. In either case, the solid-state diffusion of cations results in a transformation that can be kinetically modelled, revealing chalcopyrite transformation to a new phase occurs at a different rate to that of its reverse. Due to chalcopyrite starting out metal deficient, in order to supply enough metal ions to balance the reaction, the phase transformation reaction would need to repeatedly occur; this favors Equation 21. Also in Equation 21, the cations in the crystal lattice are hydrated quickly and this oxidation does not occur within the sulfide sub-lattice, which, when considering Equation 4, may explain faster initial reaction kinetics in comparison to the reaction after a time (Linge, 1976). Linge (1976) seems to stand alone in documenting this specific path of reactions, being referenced by others and not explicitly refuted (Debernardi & Carlesi, 2013; Hackl et al., 1995). Linge (1977) continues the rate calculations for solid-state diffusion and concludes it to be âthe best interpretation for the parabolic dissolution kinetics of chalcopyrite.â However, this reaction does not consider the next steps for the metal-deficient chalcopyrite in solution and how its leaching becomes observably passivated rather than merely kinetically slowed. The processing conditions, namely potential, must be considered. At low anodic potentials the non-stoichiometric chalcopyrite, expressed as ?@A BCDA EBâFB GFB HE by (Linge, 1976), ?@A BCDA IHE by (Hackl et al., 1995), and ?@A BCDA IHE J by (Warren et al., 1982), exists as an 19 intermediate product which forms a passive, semi-conductive polysulfide layer when mixed with sulfur. This initial passivating film and intermediate is expressed in Equation 22 (Warren et al., 1982).  â  : K : + : + K + L + : + K [Equation 22] This formula is agreed upon by Hackl et al. (1995), excluding the elemental sulfur, stating it as the fastest step in the overall reaction and follows M â« 9, 9 + M â 1, which may be a result of their experiments being run at elevated temperature. This then decomposes and gives way to a second intermediate polysulfide in the 700 â 750 mV range and is expressed in Equation 23 (Warren et al., 1982).  : K L â  â L$ â 0 +  â K +  â K +  â K [Equation 23] The first intermediate is postulated to be bornite (Cu5FeS4) whilst the second to be covellite (CuS); however, the second could be a non-stoichiometric covellite which undergoes dissolution at low potentials following Equation 24 (Warren et al., 1982). This general process is also agreed upon by (Hackl et al., 1995), determining that Equation 23 and Equation 24 are consecutively slower than Equation 22. $ â 0 â  +  +  [Equation 24] These two polysulfide layers are suggested to provide sufficient passivation to account for the slowed kinetics at low potentials and are seen to occur at higher potentials (>700 mV) as well, except that the first polysulfide gets produced negligibly in comparison to the quantity of oxidized chalcopyrite to Cu2+ and Fe3+. Therefore, the process better follows Equation 4 and Equation 25 wherein the moles of reacting chalcopyrite can vary in each reaction (Warren et al., 1982).  + R â  +  +   + S + T [Equation 25] Operating at high anodic potentials results in increased current, giving rise to an altered dissolution of the non-stoichiometric covellite seen at lower potentials, expressed in Equation 30 (Warren et al., 1982). $ â 0 +  â  +   +  +  + T [Equation 26] Regardless of the potential level, the passivating polysulfide layer appears to be composed of ?@HU V > 2 resulting from solid-state diffusion, V remains unknown (Hackl et al., 1995). The general process of forming two intermediate sulfides with the first peeling away and giving rise to the second at certain potential levels appears to be consistent across research (Ghahremaninezhad et al., 2010; Hackl et al., 1995; Parker et al., 2003; Warren et al., 1982). However, at higher potentials, the polysulfideâs passivity decreases to a point where it is no longer considered a passive layer and a ferric sulfate phase gives rise to jarosite nucleation (Ghahremaninezhad et al., 2010; Parker et al., 2003). While potential has proven to give rise to specific reaction progression, it is should not be the only process condition considered. Temperature has shown to have an effect on passivation layer composition. During bioleaching at 6°C, elemental sulfur (S0) and polysulfide (Sn2-) were detected along with monosulfide (S2-), disulfide (S22-), and sulfate (SO42-). S0 and Sn2- being the main components of a passivating layer in conjunction with jarosite (as SO42-). The jarosite content reduced by 25.8% to 20.9% during leaching whilst the polysulfide increased by 11% to 21.4%. The polysulfide was therefore identified as most plausible substance resulting in 20 passivation (Peng et al., 2019). When observing sample surfaces from 6 and 28°C, no jarosite precipitation was observed at the lower temperature compared to 20.3% of total mass being jarosite at 28°C (Peng et al., 2019). 2.3.3 Jarosite Theory The metal deficient polysulfide theory is well supported by experimental evidence; however, it cannot go unnoticed that in many experiments supporting this theory, jarosites have been observed. Their presence in solution and composing a portion of the passivating layer result in the conclusion that they may have a role in the passivation of chalcopyrite, albeit under specific conditions (Peng et al., 2019). Jarosites commonly occur as products in sulfate-rich and acidic (pH < 3.0) environments resulting from sulfide mineral oxidation (Cogram, 2018). Their chemical composition generally contains iron (Fe3+) and sulfur (S6+) with a cation (YUZ) such as potassium (K+), hydronium (H30+), or lead (Pb2+) to take the following form: [$ S [Equation 27] The jarosite can experience elemental substitution in which the Fe3+ can be replaced by aluminum (Al3+), chromium (Cr3+), gallium (Ga3+), vanadium (V3+), or copper (Cu2+) and sulfur (S6+) can be replaced by arsenic (As5+) or phosphorus (P5+) (Cogram, 2018). In the pH range of 2 â 2.5 at room temperature, iron hydrolysis can occur, allowing for precipitate formation and increase acidity, following Equation 28. Iron hydroxides (CDGB) and goethite (CD\G) have been found to be precursors to jarosite formation; therefore, the products of Equation 28 in the presence of cations allows jarosite formation following Equation 29 (Debernardi & Carlesi, 2013).  + â  â + [Equation 28]   + 1,^,^ ,  +  â 1,^,^ ,  S â +S [Equation 29] A second method leading to Equation 29 jarosite precipitation has been suggested, resulting from intermediate thiosulfate reacting with ferric ions present on or near the mineral surface, producing iron sulfate, which was found to be present on sample surfaces (Parker et al., 2003). Regardless of the method resulting in iron sulfate presence, jarosite formation rate is dependent on temperature and acidity (Ghahremaninezhad et al., 2010). As temperature increases, particularly above 60°C, jarosite formation increases, which can greatly increase rate of further crystallization as existing jarosite crystals can act as nuclei for further precipitation (Debernardi & Carlesi, 2013; Ghahremaninezhad et al., 2010). Moving from 6 to 28°C proved to be enough to present increased jarosite precipitation (Peng et al., 2019). In comparison, increased acidity reduces jarosite formation, notably pH levels below 1.5 (Debernardi & Carlesi, 2013; Ghahremaninezhad et al., 2010; Li et al., 2013). Suitable conditions for jarosite formation appear at higher potentials, approximately 750 mV vs. MSE (Ghahremaninezhad et al., 2010), also reported as 450 mV vs. Ag/AgCl (Córdoba et al., 2008) and 1340 mV vs. SHE (Li et al., 2013), and it occurs rapidly when reached (Córdoba et al., 2008). The precipitation of jarosite has led many to believe it is a contributing factor in reducing the interaction of oxidant/bacteria with the surface of chalcopyrite by forming a passivating layer, typically in conjunction with elemental sulfur and/or polysulfides (Córdoba et al., 2008; Debernardi & Carlesi, 2013; Ghahremaninezhad et al., 2010; Li et al., 2013; Parker et al., 2003; Wu et al., 2015). However, some research has determined that jarosites do not play a large role, or even any role, in the passivation processes (Lin et al., 2012; Pan et al., 2012; Wu et al., 2015). 21 2.3.4 Mixed Compound Theory The theories covered up to this point suggest one compound resulting in the passivation of chalcopyrite. However, it was briefly mentioned when discussing the jarosite theory that jarosite precipitation was typically found to form a passivating layer in conjunction with elemental sulfur and/or polysulfides. This was supported by a more recent study done by Zhang et al. (2019) when analyzing the surface of chalcopyrite mineral samples that underwent bioleaching. Insoluble precipitates of elemental sulfur and potassium jarosite were discovered and credited with decreasing the copper leaching rate. The study was seeking to determine the effects of the nonionic surfactant Triton X-100 (t-octyl phenoxy polyethoxy ethanol) had when used in the bioleaching of chalcopyrite in acidic ferric sulfate media. When this surfactant was used, analysis of the mineral surface suggested the removal of both elemental sulfur and jarosite species, effectively de-passivating the chalcopyrite and enhancing the bioleaching (Zhang et al., 2019). This is not the only research that discovered multiple constituents in passivating layers. Elemental sulfur is the most cited as present in reactions, followed by polysulfides and jarosites, in its various forms, and are typically observed in pairs as the presence of one typically leads to the formation of another (Córdoba et al., 2008, 2009; Debernardi & Carlesi, 2013; Ghahremaninezhad et al., 2010; Hackl et al., 1995; Li et al., 2013; Lin et al., 2012; Pan et al., 2012; Parker et al., 2003; Peng et al., 2019; Warren et al., 1982; Wu et al., 2015). Much of the research done on chalcopyrite passivation tends to focus on one constituent causing the leaching rate reductions. This is concluded even after stating the presence of multiple constituents, postulating theories that dismiss them as contributing factors despite the constituents stated are typically the defining component of at least one of the other leading theories. While the competing theories supply supporting information for their conclusions, they lack the ability to completely account for leach rate reduction. The mixed compound theory suggests that the information mismatch is a result of all present compounds playing a role, no matter how minor, and allows for account of all rate reductions, leading to each compound having a âpassivation strengthâ. This takes basis from passive layers that are grown on metals or alloys, with few exceptions, behave as an insulating or semiconducting material (Di Quarto & Santamaria, 2003). It has been suggested that the passivation strengths are ranked as ?@_CDEH` > ?@_HAA > Ha > bcdefghD (i.e. polysulfides > orthorhombic sulfur rings > jarosite and similar species) (Lin et al., 2012; Wu et al., 2015). 2.3.5 Intrinsically Passive Theory The general consensus regarding chalcopyrite passivation purports that passivation occurs due to the formation of a layer on the surface of chalcopyrite which results in decreased access to the surface for leaching, producing reduced reaction kinetics. Corrosion science has determined multiple methods concluding in passivation, a common method being layer formation. However, layer formation is not always the result of foreign materials building up on a surface; it can often be intrinsic passivation. Intrinsic passivity arises from a materialâs ability to produce a stable oxide film on its surface that results in the suspension of further corrosion activity. This method occurs for aluminum, chromium, and titanium; however, for chalcopyrite, it may have to do more with its conduction/valance bands. It has been suggested that chalcopyrite is an n-type semiconductor, which only passes a significant amount of current under cathodic potential application (Crundwell, 2015). The specific potential that is passed can also affect the characteristics of the semiconductor-solution interface, and four regions are present for chalcopyrite, largely based on its Mott-Schottky plot (Figure 7). Potentials below 0.2 V vs. SCE (0.441 V vs. SHE) are the 22 cathodic region and result in accumulation; whereas potentials between 0.3 â 0.6 V vs. SCE (0.541 â 0.841 V vs. SHE) are consistent with depletion as they are anodic for n-type semiconductors. This depletion is consistent with bulk material being semiconducting and not due to a semi-conductive passive film building on the surface. At potentials between 0.6 - 0.7 V vs. SCE (0.841 â 0.941 V vs. SHE), there is a significant drop in charge carrier density, which is again consistent with n-type semiconductors based on the rate of drop. This region may also suggest the growth of the CuS film that is widely supported by the other leading passivation theories (Crundwell, 2015). At the final potential region, above 0.7 V vs. SCE (0.941 V vs. SHE), inversion occurs, in which the valance band accumulates mobile holes resulting in a build-up of capacitance. This leads to a current increase, overcoming the depletion region by supplying required electrons for significant dissolution rates (Crundwell, 2015). Chalcopyriteâs Mott-Schottky plot (Figure 7) can be compared with an ideal n-type semiconductor plot (Figure 8) showing that the four potential regions, and therefore the accumulation, inversion, and depletion regions, are consistent (Crundwell, 2015). This suggests chalcopyrite is in fact an n-type semiconductor. Following the assumption that chalcopyrite is a semiconductor, its band gap becomes relevant in demystifying the increase in leaching rates when the redox potential is decreased (Crundwell, 2015). In order for there to be electron transfer between the semiconducting surface and the solution oxidant, the oxidant energy level and conduction/valence bands must coincide. This is due to electron transfer occurring adiabatically (without the gain or loss of energy). Therefore, if the redox couple has an equivalent energy level within the band gap, electron transfer is not expected at high rates (Crundwell, 2015). The energy level of various redox potentials can be seen in Figure 10 where Fe is associated with the conduction band and Cu with the valence band. This theory is supported by a slightly more recent work, however there are a few distinctions made. The common theory assumes, correctly, that when equilibrium is reached by an n-type semiconductor in aqueous electrolyte, their bands bend up to form a depletion zone resulting from the fact âmost semiconductors have their conduction band edge above the H2/H+ couple and their valence band edge below the OH-/O2 coupleâ (Ren et al., 2022a). This is not the case for fresh chalcopyrite that is immersed in acidic ferric sulfate lixiviant as it âremains in the accumulation state as long as the solutionâs redox potential is below 0.52 Vâ vs. Ag/AgCl (0.742 V vs. SHE) (Ren et al., 2022a). This aligns with the ferric/ferrous redox couple voltage, which is generally from 0.32 â 0.5 V vs. Ag/AgCl (0.542 â 0.722 V vs. SHE). Therefore, this suggests that chalcopyrite is in fact still in the accumulation zone and not the depletion zone as previously suggested, providing an explanation for the slow dissolution rate when fresh chalcopyrite interacts with acidic ferric sulfate lixiviant, which is the most commonly used (Figure 9) (Ren et al., 2022a). 23 Figure 7: Copy of âThe effect of applied potential on capacitance of the chalcopyrite-solution interface: (a) Mott-Schottky plot showing n-type depletion behavior between 0.3 and 0.6 V (v. SCE), and the inversion region at potentials >0.7 (v. SCE); (b) the current-voltage plot, showing accumulation, depletion and inversion regions. Data from (Ghahremaninezhad et al., 2010) for chalcopyrite at 0.5 M H2SO4 and 25°Câ (Crundwell, 2015) Figure 8: Copy of "The current voltage curve for the ideal n-type semiconductor-solution interface, showing the accumulation, depletion and inversion regions" (Crundwell, 2015) 24 Figure 9: Copy of "Current density and capacitance vs applied potential for freshly polished chalcopyrite plotted as (b) log(i) and 1/C2 and (c) i and Câ (Ren et al., 2022a) Figure 10: Copy of chalcopyrite âone-electronâ model showing various redox potentialsâ energy level on same scale (Crundwell, 2015) 25 The intrinsic passivity theory rests on the fact that chalcopyrite is truly an n-type semiconductor, which has been widely supported with the majority of reports stating natural chalcopyrite is (Barton & Hiskey, 2022b), and as a result states (Crundwell, 2015): 1) âthe passive region is a result of the slow supply of holes to the surface (characteristic of n-type material under anodic bias)â 2) âonset of the active region is because of the Fermi level approaching the valence bandâ 3) ârapid dissolution occurs at the point at which the Fermi level overlaps with the valence band edge, resulting in the accumulation of surface holesâ This strict assertion of n-type semiconductor intrinsic passivation discounts any layer that forms on the surface of chalcopyrite from being passivating. In order for this to hold validity, chalcopyrite would need to present a photo-effect across the entirety of the anodic potential range, which it appears to do. Passivating films would only be able to exhibit the photo-effect in the passive region, therefore providing a secondary support of the intrinsic passivity theory (Crundwell, 2015; Crundwell et al., 2015). However, newer information may present a way for both intrinsic passivation and a passivation layer to be true simultaneously. Holding true to the classification of chalcopyrite as a n-type semiconductor, there is sufficient evidence to support that a copper-rich, covellite-like layer is formed on the surface as the âpassivating layerâ and acts as a p-type semiconductor (Ren et al., 2022a). The formation of a p-type on the surface of an n-type semiconductor results in a depletion region, which decreases capacitance and increases impedance. This would result in the mineral transitioning from a resistor to a diode as leaching progresses, becoming very similar to stable oxide films on metal, acting as an insulator to electrochemical reactions (Ren et al., 2022a). With charge transfer resistance being inversely proportional to the rate of charge transfer, the bulk chalcopyrite is more favorable to electrochemical oxidation to the surface product than the inverse and suggests the p-n junction capacitance plays the dominant role in overall effective capacitance, being more prominent in the early stages of reaction resulting in the p-type layerâs depletion and ultimately hindering the mineral surfaceâs electrochemical reaction platform (Ren et al., 2022a). These conclusions set up intrinsic passivity as a leading cause in chalcopyriteâs recalcitrance to dissolution. 2.3.6 General Conclusion on Chalcopyrite Passivation Understanding chalcopyrite passivation is vital to copper recovery and may also provide valuable insight for other hydrometallurgical processes. General consensus leans towards the formation of a passivating layer on the chalcopyrite surface; however, that is where general consensus ceases. Layer composition has been stated to consist of one constituent, a combination of two or more constituents, and even multiple constituents in which only some of them affect passivity. One of the most documented constituents is elemental sulfur, but it has been largely discredited as responsible. While S0 surface build up has been confirmed by many studies (Dutrizac, 1989; Munoz et al., 1979; Nazari & Asselin, 2009; Nazari et al., 2012), its porous structure allows for transport of ions to and from the surface (Córdoba et al., 2009; Debernardi & Carlesi, 2013; Hirato et al., 1987; Li et al., 2013; Linge, 1976; Majima et al., 1985; Nazari & Asselin, 2009; Pan et al., 2012; Parker et al., 2003). On the other hand, jarosites and related species have been quite well accepted as playing a large role (Córdoba et al., 2008, 2009; Debernardi & Carlesi, 2013; Ghahremaninezhad et al., 2010; Li et al., 2013; Pan et al., 2012; Parker et al., 2003; Peng et al., 2019; Wu et al., 2015). Polysulfides have also been proven to be present by many 26 studies, although they appear to be largely affected by potential level to the extent that they decrease in passivating strength at higher potentials (Ghahremaninezhad et al., 2010; Hackl et al., 1995; Parker et al., 2003; Warren et al., 1982). They also appear to be a result of solid-state diffusion, which suggests the layer is formed from the original sample and not a result of foreign material building up on the surface (Hackl et al., 1995; Linge, 1976, 1977). While layer formation is the general consensus, there are other theories aiming to demystify chalcopyrite passivation, a leading one being intrinsic passivity. Some research has suggested an active-passive transition due to the formation of an oxide layer typical of metals as defined by corrosion science. However, an oxide layer has not been widely observed and any type of passivating layer formation has not been shown to fully account for the observed kinetics. The intrinsic passivity theory proposed for chalcopyrite suggests that chalcopyriteâs n-type semiconducting properties are responsible for the observed passivation (Crundwell, 2015). In many disciplines, semiconducting properties form the basis for understanding observed occurrences and therefore depend on band gaps. Due to this, specific leaching conditions must be met in order to counter the passivating nature and allow large current flows (Crundwell, 2015). Much of the research done on chalcopyrite passivation concludes, even after stating the presence of multiple constituents, that only one constituent is affecting the leaching rate. These dismissals are counter to other research conclusions as the dismissed contributing factor is typically the defining component of at least one of the other leading theories. While the competing theories supply supporting information for their conclusions, they lack the ability to completely account for leach rate reduction. The mixed compound theory suggests that the information mismatch is a result of all present compounds playing a role, no matter how minor, and allows for account of all rate reductions, leading to each compound having a âpassivation strengthâ. This takes basis from passive layers that are grown on metals or alloys that, with few exceptions, behave as an insulating or semiconducting material (Di Quarto & Santamaria, 2003). It has been suggested that the passivation strengths are ranked as ?@_CDEH` > ?@_HAA > Ha > bcdefghD (i.e. polysulfides > orthorhombic sulfur rings > jarosite and similar species) (Lin et al., 2012; Wu et al., 2015). This is further contested by the strict perspective intrinsic passivation theory, suggesting layer passivation is not even the correct mechanism to describe chalcopyrite passivation. This is concluded based on layer passivation not being able to explain the photo-effect that occurs on chalcopyrite over the entire range of the anodic potential range (Crundwell, 2015). However, if looking at all theories combined, a more evolved perspective would suggest both can be true. The formation of a p-type layer on top of the n-type semiconductor chalcopyrite resulting in diode characteristics through which the p-type layer depletes until it becomes insulating to electrochemical reactions (Ren et al., 2022a). In order for any progress to be made, experimental control and advanced monitoring techniques will need to be utilized. Experiments are all done under different conditions and material composition making it difficult to compare results and have external sources corroborate otherâs results. There are many proposed mechanisms and sample properties identified that are purported to affect solution and sample behavior, but they are not understood well enough to provided coherent discussion on the role they may or may not play. Therefore, experimentation on specific questions will allow for result clarity and observation of the mechanisms occurring at the molecular or atomic scale will help displace competing theories (Debernardi & Carlesi, 2013; Li et al., 2013). 27 Passivation origin is of great importance in understanding the root cause of recalcitrance; however, understanding also the conditions which result in the passivation are of equal consequence. There are many variable parameters: pH, temperature, pulp density, oxygen presence, among many others, that work in unison to produce leaching conditions which lead to the passivation (Córdoba et al., 2009). This information, when combined with ongoing passivation origin research, will result in the demystification of chalcopyrite passivation and allow for improved process design. 2.4 Mineral Variability in Literature Observation of published literature quickly presents a wide array of data. It is to be noted, however, that fundamental electrochemical information, most notably open circuit potential (OCP), passivation potential (PP), and passive current density (ipassive), are not present in all papers. These data points are important to the base thermodynamics and kinetics of the mineral specimen and for the intended hydrometallurgical application. The open circuit potential is the rest potential established between solution and working electrode â it is the potential at which leaching occurs. The passivation potential is the potential at which there is a loss of electrochemical reactivity. If we look at a schematic example of an anodic polarization curve in Figure 11, we can see an active-passive transition shown by curve a and pseudo-passive behavior by curve b. Following curve a, as potential increases, current follows until reaching a critical current (icc) at the passivation potential (EPP), at which point the current sharply drops to a passive current (ipassive). In the event the potential is raised beyond the passivation region, there exists a transition from passivity to transpassivity (Etranspassive). Following curve b, while it starts identical to curve a, there is no point in time where current decreases with increasing potential, providing rather ambiguous regions in which icc, EPP, and Etranspassive occur. Chalcopyrite typically follows a curve more represented by curve b than curve a and therefore, in terms of hydrometallurgical processing, the passive/pseudo-passive region in which chalcopyrite sits results in its recalcitrance to leaching and the basis for the majority of research. For the case of curve a and active-passive behavior, there is general consensus that icc and EPP reside at the point where the current is no longer increasing with increasing potential and may even start decreasing with increasing potential (Nicol et al., 2017; Viramontes-Gamboa et al., 2010; Viramontes et al., 2007; Warren et al., 1982). Unfortunately, there has not been a definitive definition stating where icc and EPP reside in the case of curve b, the active/pseudo-passive state (Ghahremaninezhad et al., 2010; Ghahremaninezhad et al., 2015; Viramontes et al., 2007). For the purposes of this work, I will assume the EPP is defined as the following (Figure 11): â¢ Active/passive EPP: corresponding potential value to the current value at the first instance of non-increasing current when potential increases with respect to the previous current value â¢ Active/pseudo-passive EPP: corresponding potential value at the intersection of the Tafel-slope from the active region and tangent line from the first linear increase of current with increasing potential after the Tafel region These definitions therefore define the value of icc as the current value corresponding to the potential value at EPP. This leads to the need to also define ipassive as it may present itself clearly as in curve a with the clear active/passive transition, or not be a very relevant value to consider as is the case in curve b with the active/pseudo-passive behavior. Therefore, for the purposes of this work, I will assume that ipassive is defined as the following (Figure 11): 28 â¢ Active/passive ipassive: current value at the first instance of non-decreasing current when potential increases with respect to the previous current value assuming icc has already been reached o Etranspassive: corresponding potential value at the intersection of icorr and the tangent line from the first linear increase of current with increasing potential assuming Epp has already been reached â¢ Active/pseudo-passive ipassive: Non-relevant value as there is no explicit change in current that would allow for discrete identification of an important current value, it would more appropriately be defined by a range of values from icc to itranspassive, which is best defined by the corresponding current value to Etranspassive o Etranspassive: corresponding potential value to the current value at the intersection of the tangent line from the pseudo-passive region starting at Epp & icc and tangent line from the first linear increase of current with a slope less than that of the pseudo-passive region with increasing potential after Epp Figure 11: (Top) âHypothetical anodic polarization curves showing active-passive (curve a) and pseudopassive (curve b) behavior. Epp = passivation potential, Ecorr = open circuit (corrosion) potential, icc = critical current, ipassive = passive current.â Reproduced from (Debernardi & Carlesi, 2013; Viramontes et al., 2007) (Bottom Left) Defining Epp and icc for both active-passive and active-pseudopassive curves (Bottom Right) Defining Etranspassive and ipassive for both active-passive and active-pseudopassive curves 29 Tanne & Schippers (2021) have recently reported on the variability of chalcopyrite electrochemistry while investigating microbial and galvanically leached chalcopyrite. Their OCP results for a range of metal sulfides from reported data can be observed in Figure 12. This showed that chalcopyrite and pyrite are quite noble compared to other minerals used in common processes, making them more difficult to leach while having a 145 and 150 mV range in OCP, respectively. However, the chalcopyrite range was shown to be even wider as Tanne & Schippers (2021) data produced an OCP as low as 285 mV vs. SHE and as high as 640 mV vs. SHE. Pyrite remained the most noble with minor overlap from chalcopyrite in the 541 â 551 mV vs. SHE range. In contrast, chalcopyrite had complete overlap with covellite, which was entirely within the lower half of chalcopyrite OCP range from 420 â 499 mV vs. SHE. Chalcopyrite also had a small overlap with chalcocite in the 406 â 440 mV vs. SHE range. This information suggests that the potential needed to run an extraction process varies greatly based on the composition and grade of the ore. The resulting consequences of this is small changes in potential can result in large changes in processes costs as well as play a large role in the extent of possible extraction. Table 2, Table 3, and Table 4 show data I compiled through literature review for OCP, PP, and ipassive respectively. There is not extensive reporting of this data for minerals. Through observation of eleven papers, there is quite a large range of OCP data, with some reported values being both higher and lower than the range reported by Tanne & Schippers (2021). This follows for the passivation potential as well, however this data is much less reported on. Figure 12: Copy of "Graphical representation of reported rest potential ranges of metal sulfides vs. SHE" (Tanne & Schippers, 2021) 30 Table 2: Range of reported Open Circuit Potential data from a range of work utilizing different solutions, concentrations, and origin of chalcopyrite ore. The average measured OCP was 511 mV SHE with a standard deviation of 40 mV. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings Study Authors Background Electrolyte Temp Solution Agitation Reference Electrode OCP CuFeS2 Origin Electrode Type °C rpm mV mV SHE Crundwell et al. (2015) 0.3 M H2SO4 30 Electrode Spinning 1500 3M KCl Ag/AgCl 281 491 Messina, South Africa Rotating Massive 20 310 520 20 352 562 Warren et al. (1982) 1 M H2SO4 25 ----- SCE ----- 450 â 550 â¢ Transvaal, South Africa â¢ Mt. Isa, Australia â¢ Mt. Lyall, Australia â¢ Kennecott â Chino, New Mexico â¢ Craigmont, British Columbia â¢ Sudbury, Ontario Massive Tanne & Schippers (2021) 1 M H2SO4 20 ----- 3M NaCl Ag/AgCl ----- 640 Bag Grund Mine â Harz Mountains, Germany Massive ----- 285 Noranda Mines â Quebec, Canada Jyothi et al. (1989) 0.9 K inoculated 4.4 g/L FeSO4·7H2O adjusted to pH 2.0-2.3 ----- ----- SCE 310 551 ----- Massive 0.9 K uninoculated 4.4 g/L FeSO4·7H2O adjusted to pH 2.0-2.3 ----- 165 406 Chmielewski & Kaleta (2011) 0.5 M H2SO4 deoxygenated with argon 25 ----- KCl sat. Ag/AgCl (Eh=+197mV) 330 527 Lubin-Glogow Copper Basin, SW Poland Massive Mehta & Murr (1983) 1 M HClO4 25 1002 (16.7 s-1) SCE ----- 530 Transvaal, South Africa Massive 1 M H2SO4 20 ----- 520 Ghahremaninez-had et al. (2015) 0.5 M H2SO4 25 ----- MSE sat. K2SO4 -70 550 Creighton Mine â Sudbury, Ontario, Canada Massive 0.5 M H2SO4, 5ppm Ag+ ----- 30 650 Wu et al. (2015) 3.0 g/L (NH4)2SO4, 0.1 g/L KCL, 0.5 g/L MgSO4·7H20, 0.5 g/L K2HPO4, 0.1 g/L Ca(NO3)2 50 ----- sat. Ag/AgCl ----- 475 Daye, Hubei Province, China Massive Viramontes-Gamboa et al. (2010) 30 g/L H2SO4 Oxygen purged and nitrogen sparged 23, 50 & 80 ----- KCl sat. SCE 270* â 338* 511 - 579 Chihuahua, Mexico Massive Saavedra et al. (2018) 0 K microbial culture, 1 g/L KCL, 0.2 g/L MgSO4·7H20, 2.6 g/L (NH4)H2PO4 adjusted to pH 1.8 with 10 N H2SO4 30 ----- K2SO4 sat. SSE (0.640 V/NHE) ----- 445 Charcas, San Luis Potosi, Mexico Massive Liu et al. (2017) 0.2 mol/L H2SO4 25 ----- SCE 225 467 Mt Lyell, Australia Massive 31 Table 3: Range of reported Passivation Potential data from a range of work utilizing difference solutions, concentrations, and origin of chalcopyrite ore. The average measured PP was 709 mV SHE with a standard deviation of 64 mV. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings Study Authors Background Electrolyte Methods Temp Solution Agitation Reference Electrode PP CuFeS2 Origin Electrode Type °C rpm mV mV SHE Warren et al. (1982) 1 M H2SO4 (98 g/L) Potentiodynamic Polarization 25 ----- SCE ----- 600* Transvaal, South Africa Massive 550* Mt. Isa, Australia 733* Mt. Lyall, Australia 734* Kennecott â Chino, New Mexico 730* Craigmont, British Columbia 750* Sudbury, Ontario Viramontes-Gamboa et al. (2006) 30 g/L H2SO4 Oxygen purged and nitrogen sparged & 5g Fe & KMnO4 at values to maintain temp and potential Leaching Potentiostatic Anodic Polarization 80 Maximum magnetic agitation KCl sat. SCE 510 751 Concentrate 10 g/L H2SO4 Oxygen purged and nitrogen sparged Potentiostatic Anodic Polarization 490 731 Sta. Eulalia, Mexico Massive 10 g/L H2SO4 Oxygen purged and nitrogen sparged 550 791 Chihuahua, Mexico Massive 50 g/L H2SO4 Oxygen purged and nitrogen sparged 490 731 Viramontes et al. (2007) 2 - 100 g/L H2SO4 Potentiostatic 25-80 Maximum magnetic agitation SCE 440-515 681 - 756 Chihuahua, Mexico Massive Viramontes-Gamboa et al. (2010) 30 g/L H2SO4 Oxygen purged and nitrogen sparged Steady-state sampled-current Voltammetry 23, 50 & 80 ----- KCl sat. SCE 440-510 681 - 751 â¢ Chihuahua, Mexico â¢ Santa Eulalia, Mexico â¢ Temagami, Canada Massive Kametani & Aoki (1985) 1 M H2SO4 (98 g/L) & 0.1 M total Fe (1.4 g/L) & KMnO4 at values to maintain temp and potential Suspended oxidation, Potentiostatic 90 Agitation for suspension SCE (215mV over SHE) 450 665 Kosaka Mine, Dowa Mining Co. Ltd., Japan Copper concentrate 32 Table 4: Range of reported Passivation Current data from a range of work utilizing difference solutions, concentrations, and origin of chalcopyrite ore. The average measured ipass was 7.6e-4 A/cm2 with a standard deviation of 1.2e-3 A/cm2. *Data value extracted from workâs graphical data as value was not reported explicitly within the workâs writings Study authors Background electrolyte Methods Temp Solution Agitation Reference Electrode Passive Current CuFeS2 Origin Electrode Type °C rpm μA/cm2 A/cm2 Warren et al. (1982) 1 M H2SO4 (98 g/L) Potentiodynamic Polarization 25 ----- SCE ----- 1.5e-5* Transvaal, South Africa Massive ----- 5.6e-6* Mt. Isa, Australia ----- 2.1e-4* Mt. Lyall, Australia ----- 1.3e-3* Kennecott â Chino, New Mexico ----- 6.9e-5* Craigmont, British Columbia ----- 1.1e-4* Sudbury, Ontario Viramontes-Gamboa et al. (2006) 10 g/L H2SO4 Oxygen purged and nitrogen sparged Potentiostatic Anodic Polarization 80 Maximum magnetic agitation KCl sat. SCE 13* 1.3e-5 Sta. Eulalia, Mexico Massive 10 g/L H2SO4 Oxygen purged and nitrogen sparged 81* 8.1e-5 Chihuahua, Mexico Massive 50 g/L H2SO4 Oxygen purged and nitrogen sparged 1900* 1.9e-3 Viramontes et al. (2007) 2 - 100 g/L H2SO4 Potentiostatic 25-80 Maximum magnetic agitation SCE 20* - 4000* 2e-5 â 4e-3 Chihuahua, Mexico Massive Viramontes-Gamboa et al. (2010) 30 g/L H2SO4 Oxygen purged and nitrogen sparged Open Circuit/Steady-state sampled-current Voltammetry 23, 50 & 80 ----- KCl sat. SCE 2*-2100* 2e-6 â 2.1e-3 â¢ Chihuahua, Mexico â¢ Santa Eulalia, Mexico â¢ Temagami, Canada Massive 33 The variability in OCP and PP data leads to another major issue with reported experimental data, the lack of reproducibility. This results from the nature of the mineral specimen, such as inclusions and actual copper content. The compositional difference between two particular chalcopyrite mineral samples can be substantial, with one being almost pure and the other containing up to twenty-three inclusions. Furthermore, the preparation of the mineral can also affect the results, namely surface preparation and the extent of polishing (Li et al., 2013; Viramontes et al., 2007). Warren et al. (1982) produced quite famous anodic polarization curves working with six different sources of natural chalcopyrite, reproduced in Figure 13. The curves varied by up to 2 orders of magnitude in current density and approximately 110 mV in potential difference, referencing the presence of impurities as the suggested reason of lack of agreement (Warren et al., 1982). While this sheds light on why reproducibility is difficult, it also provides an explanation for why operating potentials need to vary based on the mineral being used. Figure 13: Reproduction of "Anodic polarization curves for CuFeS2 from 6 different locations in 1M H2SO4, 30mV/min, 20 °C" (Warren et al., 1982) with addition of red lines denoting data variation Based on studies such as Warren et al. (1982), the presence of impurities has long been held as the general reason for poor reproducibility across studies. Indeed, literature review revealed the wide range of differences chalcopyrite mineral origin can have. There can be up to 32% inclusions in a particular ore sample with a plethora of potential inclusions. Such inclusions have been shown to include: Ag, Al, Al2O3, As, Au, Ba, Be, Bi, bornite (Cu5FeS4), Ca, CaO, calcite (CaCO3), Cd, Co, covellite (CuS), Cr, feldspar ([Ca,K,Na]AlSi3O8), galena (PbS), gypsum (CaSO4·2(H2O)), K, Li, Mg, mica (XY2â3Z4O10[OH,F]2 where X = 34 [Ba,Ca,Cs,K,Na,(H3O),(NH4)]; Y = [Al,Cr,Fe2+,Li,Mg,Mn,V,Zn]; Z = [Al,Be,Fe3+,Si,Ti]), Mn, Mo, molybdenite (MoS2), Na, Ni, Pb, pyrite (FeS2), pyrrhotite (Fe1-xS), quartz (SiO2), Sb, Si, silica (SiO2), siderite (Fe2+CO3), sphalerite ([Fe,Zn]S), Sr, Tl, Zn, V, Talc (Mg3Si4O10(OH)2) and chlorites ([Mg,Fe]3[Si,Al]4O10(OH)2· [Mg,Fe]3(OH)6), amorphous phases, and gangue (Crundwell et al., 2015; Dutrizac, 1989; Ghahremaninezhad et al., 2015; Hirato et al., 1987; Jyothi et al., 1989; Khoshkhoo et al., 2014; Linge, 1976; Munoz et al., 1979; Qian et al., 2014; Tanne & Schippers, 2021; Tevfik & Aras, 2013; Velásquez-Yévenes et al., 2010; Viramontes-Gamboa et al., 2010; Viramontes et al., 2007; Wu et al., 2015). The molar ratio of copper to iron to sulfur present in the chalcopyrite also varies. In its purest form, chalcopyrite (CuFeS2) contains 34.5% Cu, 30.5% Fe, and 35.0% S (Haldar, 2017). Literature has reported weight ratio ranges as: 20.7 â 35.8% Cu, 22.6 â 30.9% Fe, and 30.8 â 35.4% S (Crundwell et al., 2015; Dutrizac, 1989; Ghahremaninezhad et al., 2015; Hirato et al., 1987; Khoshkhoo et al., 2014; Linge, 1976; Munoz et al., 1979; Qian et al., 2014; Tanne & Schippers, 2021; Tevfik & Aras, 2013; Velásquez-Yévenes et al., 2010; Viramontes-Gamboa et al., 2010; Viramontes et al., 2007; Wu et al., 2015). This is shown graphically in Figure 14. While literature has now well documented that different origin chalcopyrite can vary greatly, there has been little to no documentation of variance within a single origin. Figure 15 shows three chalcopyrite massive electrodes with various inclusions that appear visually different from one another despite the fact they all came from the same origin. Figure 14: Graphical representation of reported (Left) weight percent range of chalcopyrite to inclusions (Right) weight ratio range of Cu-Fe-S in chalcopyrite Figure 15: Three different chalcopyrite massive electrodes showing various inclusions that appear visually different despite coming from the same sample origin (chalcopyrite Origin B from Chapter 3: Experimental and Instrumental) 35 It can be further noted that the lack of experimental reproducibility and exceedingly wide range of reported OCP, PP, and ipassive data can be a result of different electrode types and their inherent qualities, ranging from mineral porosity, crack sizing, and density to the specific blend of inclusions and their distribution within a given sample. The two most popular electrodes utilized are carbon paste and massive electrodes. Carbon paste electrodes typically contain graphite, chalcopyrite, and silicon oil pulverized and combined together, resulting in small quantities of chalcopyrite being exposed in particle form (Lázaro et al., 1995). Massive electrodes are far more popular as they are more easily produced and only contain a pure ore sample that is embedded in resin and then polished, typically to 1200 grit. It produces an approximate 2-dimensional surface, which is more ideal for observation of passivity, which tends to be of most interest when researching chalcopyrite. However, the interface between the resin and ore sample can produce a 3-dimensional surface, greatly affecting the results. It may also be noted that whichever electrode type is used, the rotation of the electrode and/or stirring of the solution it is in can greatly affect experiment results as it can increase mass transport (Banks et al., 1999). Literature has made it quite clear variability exists in mineral electrochemistry, especially the variable electrochemical response of chalcopyrite (Barton & Hiskey, 2022b; Li et al., 2013; Viramontes et al., 2007; Warren et al., 1982). And it is not new information that the electrode itself and the conditions surrounding it can affect the experimental results. However, these ideas have never been collated, existing only in part across multiple papers and decades. The results of experimentation typically suggest mineral composition variation as the root of all issues and calling it solved without providing steps to mitigate it. Few if any experiments have been conducted specifically to discover the sources of variability and seek success rates in mitigation methods. This work seeks to do just that. 2.5 Final Thoughts on Literature Review Chalcopyrite has become the source of much research and investigation with regards to its passivation and resulting recalcitrance to hydrometallurgical methods of extraction. While there is quite a large number of existing papers on the subject, there is a surprisingly large lack of agreement. This revolves around reported values of open circuit potential and passivation polarization as well as identification of the root causes of passivation. While a vast majority of this work was completed before the release of Barton & Hiskey (2022b), which was released around the same time as Ren et al. (2022a) and Ren et al. (2022b), it is clear that this work is in deep agreement when they stated âmost leaching experiments on chalcopyrite are performed on samples whose actual minerology is essentially unknownâ and âthere are a huge number of sometimes-interacting variables that are poorly measured or completely ignored in most studies of chalcopyrite leachingâ. In order for any true progress to be made, more effort needs to be placed on reporting methods and understanding what material is being worked with so that reproducing data that other papers have reported is possible. This would allow for clearer comparisons with regards to experimental methods and their resulting effects and data produced. At this point, there is a staggeringly large amount of assumed information that removes the possibility for confident comparisons and the ability to make a claim about the specific behaviors of chalcopyrite. 36 Chapter 3: Experimental and Instrumental It is no secret that the materials used for experimentation have a large impact on results. Thus, putting dissimilar materials under the same experimental conditions can produce different results. This is clear in homogeneous material cases, such as experimenting with pure iron (Fe) versus pure copper (Cu). They are fundamentally different materials giving them different properties and reactivity. It is common knowledge that doping homogeneous materials will change their material properties and reactivity. Pure iron doped with carbon increases its strength and toughness becoming steel. And doping steel with chromium increases its corrosion resistance, producing stainless steel. Any changes in the weight percent of carbon or chromium result in a different classification or grade of steel. This renders them completely different materials when performing experiments and understanding the results. There is a gap in how homogeneous and non-homogeneous materials are treated in this manner. There exists a prevalent assumption that any mineral is equivalent to any other mineral generally classified in the same way. In other words, if two separate researchers state they used chalcopyrite, their results are generally considered comparable. Most papers do not completely explain the physical methods used to produce their sample electrodes or provide details for the specific sample, many only stating the sample appeared visually free from inclusions (Debernardi & Carlesi, 2013; Dutrizac, 1989; Ghahremaninezhad et al., 2015; Hong-xu et al., 2006; Khabibullin et al., 2009; Khoshkhoo et al., 2014; Liu et al., 2017; Majima et al., 1985; Mikhlin et al., 2016; Nicol, 2022; Nicol et al., 2017; Parker et al., 2003; Tanne & Schippers, 2021; Warren et al., 1982; Wu et al., 2015). This is further confirmed by the recent work from Barton & Hiskey (2022a) stating: In more than 75% of the articles reviewed for this study, the sample mineralogy was either not analyzed or failed to match the chemical analysis to within 5% of the reported Cu. Potentially catalyzing trace elements and electrical characteristics were not analyzed in any of the articles reviewed. There should be no difference in the specificity used in how we report on homogeneous materials and native non-homogeneous materials, such as minerals. A pure chalcopyrite sample has different strength and reactivity than a chalcopyrite sample with inclusions, i.e. non-pure chalcopyrite. Just as a small change in weight percent of carbon or chromium can greatly affect the type of steel created and its material properties, so can a small change in weight percent or type of inclusions in minerals. To understand the results from electrochemical experimentation on homogeneous materials, it is common practice to observe the composition of the experimental samples. The same treatment needs to be extended for understanding data acquired in mineral electrochemistry. When this work started in 2019, there was little to no recognition of the importance of mineralogy across electrochemical research publishing. There is now a slow growing understanding of its importance as a few published articles post 2019 state there needs to be a standard for comparison (Barton & Hiskey, 2022a, 2022b; Tanne & Schippers, 2021). I completely agree and hope this work contributes to laying the groundwork for standardization. This chapter provides methods to characterize the mineral(s) used to have context for all observed data. 37 3.1 Electrode Materials There are many compelling reasons in section 1.3 Why Chalcopyrite? explaining chalcopyriteâs selection for this research. With those in mind, it is clear chalcopyrite makes a strong exemplar mineral for the major problems plaguing electrochemical mineral research. Observed variability and lack of reproducibility are typically explained away as the nature of experimenting with minerals. To test this hypothesis and clarify what may be causing the differences, I used three natural chalcopyrite origins for electrode fabrication. The provenance of Origin A and B are unknown, but Origin C is from the Conception del Oro Mine in Zacatecas, Mexico. While it is unfortunate that two of the origins do not have a traceable provenance, this is a common occurrence throughout published work (Burdick & Ellis, 1917; Ghahremaninezhad et al., 2015; Hong-xu et al., 2006; Jyothi et al., 1989; Kimball et al., 2010; Lázaro et al., 1995; Linge, 1976; Nazari et al., 2011, 2012; Olvera et al. 2016; Ren et al., 2022a; Ren et al., 2022b; Stott et al. 2003; Viramontes-Gamboa et al., 2006; Viramontes et al., 2007; Von Oertzen et al., 2006). When a company is releasing work on their specific mineral source, traceability is simple as they gather the sample â assuming they want to publicize the origin of the sample, which is not always the case. In contrast, most public literature results from a third-party mineral acquisition. Each mineral may have passed through many hands before arriving at the research lab. So even if there was information attached, it is rarely reliable enough to make judgments about composition. Despite the fact that most works that stated visual inspection for chalcopyrite purity only stated mineral provenance as further characterization, this workâs lack of provenance information is not nearly as important as it may seem. Unless a company is funding research for the use of that specific mineral, the traceability of a mineral's source has little importance. While a traceable source can assist in orienting expectations, it does not remove the need for detailed characterization of the material. When a work presents the mineral provenance it presumes, intentionally or otherwise, that the public record of the source is sufficient information to understand content and composition. However, mineral content and composition is highly guarded information by mines and their subsidiaries as knowledge of the source results in their ability to leverage it for their economic success. Even if such information were easily accessible, it is not sufficient to only characterize the bulk composition. If experimenting with massive electrodes, the characterization of the exposed surface is more representative of the results. Comparing this composition to that of the bulk allows for data extrapolation and making broader statements about the mineral. It is important to characterize the sample using as many methods as available. Today's technology is capable of providing low-error data, but no method is perfect. Each comes with a set of unique limitations that need to be considered. Using multiple methods allows for confirmation of results and accounts for any inherent error associated with any particular characterization method. To varying degrees, material characterization is as much an art as it is a science depending on the methods used. Mathematical approximations and educated reasoning from experienced technicians result in all characterization data obtained. This work required the characterization of three mineral origins (A, B, C) and the seventeen massive electrodes produced from them, seven of which (A1, B1, B2, B3, B4, C1, C2) were selected for experimentation based on visual, optical microscopy (OM), and scanning electron microscopy inspection 38 of the resin, resin-mineral interface, and mineral surface continuity (i.e. lack of cracks on exposed surface). X-ray Powder Diffraction (XRD) and Energy-dispersive X-ray Spectroscopy (EDS) were compared with a trace element assay conducted via Inductively Coupled Plasma â Optical Emission Spectroscopy (ICP-OES). Optical imagery (photography with iPhone 8) was used when appropriate, but preference was given to Secondary Electron Detection (SE) and Backscattered Electron Detection (BSE) that were available through the Scanning Electron Microscope (SEM) used for EDS. These methods were selected based on ease of access, their ability to provide the desired information, and due to their common use throughout literature and standard laboratory practice. 3.1.1 X-ray Powder Diffraction (XRD) of Chalcopyrite Origins The XRD raw data were acquired from hand-ground mortar and pestle powder samples. The powder samples contained sections of multiple ore pieces from the same origin. This included the mineral surrounding the chalcopyrite volume used to produce the mineral massive electrodes examined in EDS. A comprehensive characterization of the mineral origin was acquired, allowing for comparison to the origin and massive electrode characterizations from EDS and ICP-OES. Due to the non-destructive nature of XRD, it was performed before ICP-OES, a destructive method, and alongside EDS, a non-destructive method. A Rigaku MultiFlex XRD unit was used with a Cu-Kα (1.5418740Ã ) detector and graphite monochromator over a 2θ range of 20 - 100 degrees and a sampling width of 0.01 degrees at 2 degrees/min. The X-ray generator was set to 30 kV and 30 mA. The data were processed through Match!3 software (version 3.8.0.137 selected based on availability) in which a Rietveld Refinement quantitative phase analysis was performed to approximate the spectra and acquire higher confidence identifications. Table 5 summarizes the characterization results and Figure 16 shows the raw XRD spectra. Selection of the 2θ range resulted from initial experimentation. 2θ outside of 20 â 100 degrees acquired large amounts of background noise and drift that resulted in unusable data. Following this choice, to increase the effectiveness of the Rietveld Refinement, all data were processed with background noise reduced by Match!3 software. The main goal of XRD characterization was to confirm that Origins A, B, and C were at least 70% by weight chalcopyrite. This value was selected based on literature review where 68.4% by weight was the lowest reported chalcopyrite purity discovered when using massive electrodes (see Figure 14). Given the available spectra library in Match!3, the lack of origin information, and a converged Rietveld Refinement, the achieved Bragg R-Factor and Reduced Chi-Squared (Ï2) are sufficient as a first characterization. This data allowed for informed EDS and ICP-OES characterization and confidence in claiming that chalcopyrite is the main mineral in each origin. 39 Table 5: Quantitative XRD analysis through Match!3 software of the chalcopyrite Origins A, B, and C (all values in wt%) used to produce massive electrodes for this work. A Rigaku MultiFlex XRD unit was used with Cu-Kα (1.5418740Ã ) detector and graphite monochromator over a 2θ of 20 - 100 degrees and a sampling width of 0.01 degrees at 2 degrees/min. The X-ray generator was set to 30 kV and 30 mA. Mineral Ideal Formula Weight Percent Origin A Origin B Origin C Chalcopyrite CuFeS2 87 96 92 Sphalerite ZnS 10 --- 4 Quartz SiO2 3 2 1 Iron Silicide FeSi --- 1 --- Anatase TiO2 --- <1 --- Perovskite CaTiO3 --- <1 --- Periclase MgO --- --- 3 Rietveld Refinement Converged Converged Converged Final Weighted Average Bragg R-Factor 33.7% 44.9% 36.4% Final Reduced Ï2 2.4 5.2 5.6 Figure 16: Quantitative XRD raw data spectra analyzed by Match!3 software for characterization of chalcopyrite Origins A, B, and C used to produce massive electrodes for this work. A Rigaku MultiFlex XRD unit was used with a Cu-Kα (1.5418740Ã ) detector and graphite monochromator over a 2θ of 20 - 100 degrees and a sampling width of 0.01 degrees at 2 degrees/min. The X-ray generator was set to 30 kV and 30 mA. 40 3.1.2 Energy-dispersive X-ray Spectroscopy (EDS) of Chalcopyrite Massive Electrodes Seventeen chalcopyrite massive electrodes were constructed for characterization: two from Origin A, eight from Origin B, and seven from Origin C (refer to section 3.2.1 Massive Electrode Construction for the construction method). The ideal case would have the same number of massive electrodes for each origin. Unfortunately, there was not enough Origin A to produce an equal number of electrodes. Therefore, electrodes were produced based on their requirement for experimentation. After construction, all electrodes were coated in a thin layer of carbon by an Edwards 306 Evaporator to improve conductivity and avoid charge build up in the SEM chamber. This removed the ability to determine if carbon (C) was present in any of the electrodes. Massive electrodes rely on an exposed surface for reactions to occur. Thus, the exposed surface has the largest effect on experimental results. Understanding this surface will provide context for interpreting any data produced from it. EDS is capable of non-destructive observation of this surface for characterization. Each massive electrode was observed at areas and points taken from multiple sections on the electrode. This method was selected to capture the most data possible while working within the limited area the SEM can observe at a given time. The detector required a 10 mm working distance from the surface of the electrode. The average of all values obtained produced the characterization for each electrode. The average of all electrode values from a given origin produced the characterization of that origin. It was this origin value that was used for comparison to XRD and ICP-OES. Seven of the seventeen electrodes were selected for experimentation and given names according to their origin (A1, B1, B2, B3, B4, C1, and C2). Each was characterized and compared to their respective origins. The EDS raw data were obtained in an FEI Quanta 650 Zeiss Scanning Electrode Microscope (SEM) equipped with a backscatter detector and a full EDS analysis system with a large area detector. A Bruker XFlash® 6-30 detector with an energy resolution of 45eV at Cu-Kα was used to obtain all data which was processed through the quantification method Phi(Rho, Z). Before presenting the characterization data, there is an important observation to discuss. It provides context for a previous statement I made: âMathematical approximations and educated reasoning from experienced technicians result in all characterization data obtainedâ (from section 3.1 Electrode Materials). Analysis of data acquired from an EDS quantification method provided unexpected results. And there was no logical way to reconcile the values while conforming to reality. The choice of a quantification method must be intentional as the error may not always be as obvious. 3.1.2.1 Selection of EDS Quantification Method There were five quantification methods available in the SEM software: P/B ZAF, Phi(Rho, Z), P/B film, Clif-Lorimer, and Zeta Factor Method. P/B film and Clif-Lorimer are ideal for thin-film observations and Zeta Factor Method is an improvement on Clif-Lorimer. Thus, they do not apply to my massive electrode application, leaving P/B ZAF and Phi(Rho, Z). The University of British Columbia Materials Engineering Department - Electron Microscopy Laboratoryâs standard quantification method is P/B ZAF. However, analysis of the data output by this method stated unrealistic sulfur content for my samples. Table 6 compares the data from both methods for Origin A, B, and C. Values are presented in weight percent as 41 an average of multiple massive electrodes (chalcopyrite origin â number of observed massive electrodes): Origin A - 1, Origin B - 3, Origin C â 3. Table 6: Comparison of EDS characterization methods P/B ZAF and Phi(Rho, Z) performed on chalcopyrite Origins A, B, and C to determine total Cu, Fe, and S weight percent. Values are presented as an average of multiple massive electrodes (origin â number of observed massive electrodes): Origin A - 1, Origin B - 3, Origin C â 3. Method Element Weight Percent Origin A Origin B Origin C P/B-ZAF Phi(Rho, Z) P/B-ZAF Phi(Rho, Z) P/B-ZAF Phi(Rho, Z) EDS Cu 17 34 14 26 16 27 Fe 20 31 20 26 22 27 S 62 34 34 26 38 27 Phi(Rho, Z) quantified Origin A sulfur content to be 34 wt%, whereas P/B ZAF quantified it to be 62 wt%, a 28 wt% difference. P/B ZAF also produced sulfur values greater than Phi(Rho, Z) by 8 and 11 wt% for Origin B and C, respectively. Any justification for the sulfur content identified by P/B ZAF reduced the amount of possible Cu that could exist, quantifying Cu below Phi(Rho, Z) by 17, 12, and 11 wt% for Origin A, B, and C, respectively. This reduction in Cu quantification reduces the possible CuFeS2 purity. Assuming all origins follow the ideal chalcopyrite weight ratio of Cu (34.63%) â Fe (30.43%) â S (34.94%)1, the resulting values disagree with the results from XRD. This is shown in Table 7 where Phi(Rho, Z) quantified at least 76% by mass CuFeS2 and P/B ZAF quantified at most 49% by mass. XRD quantification stated at least 87 wt% CuFeS2 (Table 5), suggesting Phi(Rho, Z) is a more correct quantification method. Table 7: Comparison of EDS and XRD characterizations performed on chalcopyrite Origins A, B, and C to determine total CuFeS2 weight percent. Values for EDS are presented as an average of multiple massive electrodes (origin â number of observed massive electrodes): Origin A - 1, Origin B - 3, Origin C â 3. Method Mineral Weight Percent Origin A Origin B Origin C P/B-ZAF Phi(Rho, Z) P/B-ZAF Phi(Rho, Z) P/B-ZAF Phi(Rho, Z) EDS CuFeS2 49 99 40 76 48 78 Other 51 1 60 24 52 22 XRD CuFeS2 87 96 92 Other 13 4 8 Without taking into account the XRD data, Table 7 data may lead to the conclusion that Phi(Rho, Z) overestimates CuFeS2 content while P/B ZAF underestimates. In the event that Phi(Rho, Z) does overestimate, a known small overestimate that conforms to physical reality is preferable to the drastic underestimation of P/B ZAF that does not. However, the values obtained agree with XRD data trends and only presented Origin A above XRD values. This proves the importance of using more than one characterization method. Observation of more massive electrodes will move the values closer to their true value. There is, therefore, no reason to assume overestimation is occurring. 1 Calculation based on MWCu = 63.546 g/mol, MWFe = 55.845 g/mol, MWS = 32.065 g/mol, and MWCuFeS2 = 183.521 g/mol. A popular composition is Cu (34.5%) â Fe (30.5%) â S (35.0%) (Haldar, 2017). This is incorrect based on calculations using the molecular weights above, which are widely accepted and reported. 42 All data acquired suggests Phi(Rho, Z) is providing the more correct quantification of the data and as such I will move forward with this method for any reported EDS data. With this choice I can then accept the methodâs data asserting that all origins contain a majority of CuFeS2 and are above the minimum reported chalcopyrite purity of 68.4 wt% (see Figure 14 - left). 3.1.2.2 EDS Characterization Data Based on the results from the previous section, I have determined to characterize data with the Phi(Rho, Z) quantification method. The quantified EDS results in weight percent are summarized in Table 8. Values are an average of multiple massive electrodes (chalcopyrite origin â number of observed massive electrodes): Origin A - 2, Origin B - 8, Origin C â 7. More electrodes were produced for observation post the selection of the characterization method Phi(Rho, Z). This allowed for a more accurate characterization of the origins. Table 8: Quantitative EDS analysis by Phi(Rho, Z) quantification of chalcopyrite Origins A, B, and C. All values are in weight percent averaged from multiple electrodes (origin â number of observed massive electrodes): Origin A - 2, Origin B - 8, Origin C â 7. An FEI Quanta 650 Zeiss SEM with a Bruker XFlash® 6-30 detector with energy resolution of 45eV at Cu-Kα was used to acquire the data from 1 μm diamond polished massive electrodes. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01% ignored as within experimental error. Element Symbol EDS - Weight Percent Origin A Origin B Origin C Silver Ag Trace <1 Trace Aluminum Al Trace <1 Trace Arsenic As Trace Trace Trace Bismuth Bi Trace Trace Trace Calcium Ca 2 4 4 Chlorine Cl ----- Trace ----- Cobalt Co Trace Trace Trace Copper Cu 33 29 30 Iron Fe 31 28 29 Potassium K ----- Trace ----- Magnesium Mg Trace Trace <1 Manganese Mn <1 <1 <1 Molybdenum Mo ----- ----- Trace Oxygen O <1 5% 5 Lead Pb <1 Trace <1 Sulfur S 32 29 29 Silicon Si Trace 3 3 Tellurium Te Trace Trace ----- Titanium Ti ----- Trace Trace Zinc Zn Trace 1 <1 It is not sufficient to characterize a massive electrode by using the characterization of its mineral origin. That specific massive electrode needs to be observed. This is important as the composition of the massive electrode can vary greatly from the bulk mineral it was produced from; potentially behaving differently when subject to the same experimental conditions. Characterization of both the origin and the specific samples used for experimentation allows for the extrapolation of data from the sample to 43 the origin. Table 9 summarizes the Phi(Rho, Z) EDS characterizations for all chalcopyrite massive electrodes used to produce the data in Chapter 4: Investigation of the Variability in Mineral Electrochemistry. Their purities and the calculated weight ratios of Cu â Fe â S are shown in Table 10. Table 9: Quantitative EDS analysis by Phi(Rho, Z) of seven chalcopyrite massive electrodes from chalcopyrite Origins A, B, and C. An FEI Quanta 650 Zeiss SEM with a Bruker XFlash® 6-30 detector with energy resolution of 45eV at Cu-Kα was used to acquire the data from 1 μm diamond polished massive electrodes. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01% ignored as within experimental error. Element Symbol EDS - Weight Percent Origin A Origin B Origin C A1 B1 B2 B3 B4 C1 C2 Silver Ag Trace Trace ----- 1 ----- ----- Trace Aluminum Al ----- 2 3 Trace Trace Trace 3 Arsenic As Trace ----- ----- ----- ----- ----- ----- Bismuth Bi Trace Trace Trace ----- ----- ----- Trace Calcium Ca ----- 7 6 1 4 7 5 Chlorine Cl ----- Trace ----- ----- ----- ----- <1 Cobalt Co Trace ----- ----- ----- ----- ----- ----- Copper Cu 34 25 24 34 31 25 26 Iron Fe 31 26 25 32 28 26 26 Potassium K ----- Trace ----- ----- ----- ----- <1 Magnesium Mg ----- ----- ----- ----- Trace Trace <1 Manganese Mn ----- Trace Trace Trace Trace Trace Trace Molybdenum Mo ----- ----- ----- ----- <1 ----- ----- Oxygen O <1 11 13 Trace 5 9 9 Lead Pb Trace Trace Trace ----- ----- ----- Trace Sulfur S 34 24 24 32 31 25 25 Silicon Si Trace 5 5 Trace 2 5 5 Tellurium Te Trace Trace ----- ----- ----- ----- <1 Titanium Ti ----- ----- Trace Trace ----- ----- ----- Zinc Zn Trace ----- <1 Trace Trace 2 Trace Table 10: Quantitative EDS analysis by Phi(Rho, Z) of seven chalcopyrite massive electrodes from chalcopyrite Origins A, B, and C. Values calculated based on the assumption all Cu present forms CuFeS2 and the amounts of Fe and S are calculated based on the Cu amount from the ideal mass ratio for CuFeS2 of Cu (34.63%) â Fe (30.43%) â S (34.94%) until the amounts of Fe and S are fully used. Remaining Fe and/or S are assumed to be inclusions. Element / Mineral Symbol EDS - Weight Percent Origin A Origin B Origin C A1 B1 B2 B3 B4 C1 C2 Copper Cu 34.7 34.8 34.8 35.2 34.6 34.8 35.5 Iron Fe 30.5 30.6 30.6 31.0 30.4 30.6 31.2 Sulfur S 34.7 34.6 34.6 33.8 34.9 34.7 33.4 Chalcopyrite CuFeS2 99 71 68 95 89 73 75 Other Other 1 29 32 5 11 27 25 44 3.1.3 Optical, SE, and BSE Imagery with EDS Mapping of Chalcopyrite Massive Electrodes By definition, characterization requires observation. Full characterization cannot be considered complete without optical observation. This is typically the first step in characterization. It has the lowest barrier to entry in both equipment requirements and operator skills. It is also the native method used when considering material for experimentation. Observation with the naked eye leads to the assumption it is the desired mineral. Optical microscopy (OM) with a skilled technician is a more effective way of confirming the initial selection of material. I show imagery as the third characterization method here for a few reasons. When using it in isolation, it can mislead characterization as the naked eye is not capable of such minute detail. It is also very difficult to produce data such as the percentage of inclusions. However, the images can be compared to the values produced by both XRD and EDS characterization for confirmation. They can also be compared to SEM imagery through SE and BSE. I collected such images at the same time as EDS characterization. Optical imagery is vital to characterization and must always be used when other methods are employed as it can provide confirmation or display errors. As stated before, using optical imagery in isolation can mislead characterization. Take observation of my chalcopyrite massive electrode Origin A â A1 as an example. The first logical step in characterization is observation with the naked eye. The native camera sensor through the native camera application on an iPhone 8 running iOS 14.4 will act as the proxy for the naked eye. Three separate images of the chalcopyrite massive electrode Origin A â A1 polished to 1200 grit with carbide paper is shown in Figure 17. The left image was taken with the intent to show the scale of Origin A â A1. The center image provides a better-focused image of the mineral in the massive electrode. And the right image appears similar to the center image. Figure 17: Chalcopyrite massive electrode Origin A â A1 polished to 1200 grit with carbide paper imaged via the native camera sensor and application on an iPhone 8 running iOS 14.4 all in the same location under different conditions. (Left) shows the scale of Origin A â A1 in ambient sunlight from window right of electrode (Center) focuses on Origin A â A1 in overhead white light with focus on mineral in massive electrode (Right) focuses on Origin A â A1 slightly more head-on in same lighting as center image and AFTER undergoing hydrometallurgical experimentation Looking at each of the three images in Figure 17 in isolation provides different visual information. This can result in different conclusions about the composition of the massive electrode. Starting with the left 45 image, it appears that the massive electrode might not actually be chalcopyrite. It is possibly pyrite or a similar grey-appearing mineral. Chalcopyrite's âcolor is typically brass to golden-yellow, often tarnished, with greenish-black streak and sub-metallic lusterâ (Haldar, 2017). All of these are not visible in this image. By changing the source light from ambient sunlight from the nearest window to an overhead white lightbulb and ensuring focus on the mineral in the massive electrode, the center image is captured. This image exhibits the characteristic golden-yellow, brass-like color expected of chalcopyrite. It appears to have very little to no inclusions with any color differences/dark spots resulting from various crystal structure orientations being visible due to the 1200 grit polish. Moving to the right image, it appears similar to the center image, yet it exhibits much more grain structure and appears a bit paler. This is an effect of a few factors. The paler coloration can be the effect of the light source and the angle in relation to the camera sensor/naked eye. The massive electrode is more perpendicular to the camera sensor in comparison to the center image. It is angled so that it reflects the overhead source light more into the sensor. This could potentially be overblowing the sensor and reducing color separation, oversaturating the yellow color. This particular angle allows for more observation of the existing grain and crystal structure and orientations present in the massive electrode due to its 1200 grit polish. Another factor is that it has undergone some sort of hydrometallurgical experimentation. This last fact may or may not be known to any given observer and would change the species present on the surface. All this analysis may seem like an over-analysis of the physical observation of a massive electrode sample. One could simply turn the sample or change the lighting or polish to a higher or lower grit and re-image. This would remove any questionable observations when combined with a report on the conditions used. This is mostly true. Unfortunately, there exist many published work that simply state the sample they used appeared visually free from inclusions (Debernardi & Carlesi, 2013; Dutrizac, 1989; Ghahremaninezhad et al., 2015; Khabibullin et al., 2009; Khoshkhoo et al., 2014; Liu et al., 2017; Majima et al., 1985; Mikhlin et al., 2016; Nicol et al., 2017; Parker et al., 2003; Tanne & Schippers, 2021; Warren et al., 1982; Wu et al., 2015). It is impossible to determine what went into this visual observation, what resulted in the assertion, and what led them to believe they had confidence in that assertion. There is a very real chance that the sample was observed by someone other than the person who constructed it. It could have also been an old sample that was recovered from a drawer after being experimented on five years ago, had the dust wiped off with a cloth, and looked at in low lighting. The history of the sample and its current state are unknown as they are unreported. Thus, it is important to ensure whatever methods or conditions that are used to capture an image or physical observation are reported. Especially when that image or physical observation is used to determine the characterization of a mineral. This is the main reason this section was not presented first when characterizing the minerals used for experimentation. Optical imagery rarely provides the whole story about the characterization of a mineral. It should be an ancillary method used to confirm results, not state them. It is blatantly clear that any mineral used for experimentation was first physically observed before performing any other experiments. It is the simple requirement for considering a mineral for experimentation. Issuing the statement that a sample appeared free from inclusion suggests a decision was made; that it required characterization to confirm the mineral was as expected. Having chosen a mineral sample, one can then start the process of characterization. Using optical methods post other methods allows for reduced bias 46 in findings. Once the characterization data has been gathered, it can be compared to the physical mineral. Judgment can then be made on how well or not the data agrees with what is being observed. This section is purposefully placed before characterization through ICP-OES and after XRD and EDS. Up to this section all methods used are typically within the budget and skills of most researchers. While the use of ICP-OES is accepted in industry as a reliable method for characterization, it is a destructive method. And it is not always accessible given the cost of equipment and the skills required for operating it and preparing the samples. Regardless, each method chosen for characterization must have a specific intent. Either it provides comparable data to other methods selected or it collects information no other method is able to. I used optical, SE, and BSE imagery to confirm the results acquired from XRD and EDS with ICP-OES providing further confirmation. Using this mindset, the image clusters in Figure 18 through Figure 31 present the seven chalcopyrite massive electrodes used in experimentation for Chapter 4: Investigation of the Variability in Mineral Electrochemistry. The captions for each image cluster describe the conditions under which each image was collected. Methods used were optical imagery (native camera sensor through native camera application on an iPhone 8 running iOS 14.4), SE, BSE, and EDS mapping. Each image was compared to the chalcopyrite origin data acquired from XRD in Table 5 and EDS in Table 8. They were also compared to the EDS data for specific chalcopyrite massive electrodes in Table 9 and Table 10. The images were helpful in identifying the error in EDS quantification method P/B ZAF. The samples do not suggest extremely high sulfur contents nor extremely low chalcopyrite contents based on color and observable inclusions. They also provided high confidence that the data for each massive electrode and origin from XRD and EDS were well within reasonable expectations. The EDS mapping images were limited in scope due to the method's operational requirements. A close working distance of 10 mm from the material surface was required within the SEM chamber to achieve high data accuracy. This resulted in a small area being available to map. Multiple sections were observed on each electrode surface. One of these sections was selected as a representation of the sample as a whole to reduce image quantity. To provide scale for Figure 18 through Figure 31, the exposed surface areas of the seven chalcopyrite massive electrodes are presented in Table 11. Since all electrodes were hand-constructed, they are not of perfect regular shape. This made it difficult to physically measure the surface area accurately. A pixel processor called ImageJ was used in place. ImageJ approximates the area of an object based on the pixel count in a selected area. A centimeter ruler was placed in the image of every electrode that was used to define the number of pixels in a centimeter. Using this ratio, the number of pixels in a selected area was counted. It then reported the area in square centimeters. Four separate measurements were averaged to decrease user error in selecting the material surface boundary. Table 11: Surface areas of the seven chalcopyrite massive electrodes used for experimentation approximated by pixel processor ImageJ and taking the average of four measurements with error based on two-sided t-distribution 95% CI. Exposed Surface Area Origin A Origin B Origin C Masked A1 B1 B2 B3 B4 C1 C2 All Electrodes cm2 1.012 1.294 1.395 1.090 1.781 1.207 1.082 0.442 95% CI 0.009 0.009 0.002 0.005 0.008 0.004 0.002 0 47 Figure 18: Chalcopyrite massive electrode Origin A â A1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 6x magnification (Right) SE polished to 1 μm diamond polish at 6x magnification Figure 19: Chalcopyrite massive electrode Origin A â A1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 48 Figure 20: Chalcopyrite massive electrode Origin B â B1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 8x magnification (Right) SE polished to 1 μm diamond polish at 8x magnification Figure 21: Chalcopyrite massive electrode Origin B â B1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 49 Figure 22: Chalcopyrite massive electrode Origin B â B2 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification Figure 23: Chalcopyrite massive electrode Origin B â B2 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 50 Figure 24: Chalcopyrite massive electrode Origin B â B3 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 60x magnification (Right) SE polished to 1 μm diamond polish at 60x magnification Figure 25: Chalcopyrite massive electrode Origin B â B3 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 51 Figure 26: Chalcopyrite massive electrode Origin B â B4 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification Figure 27: Chalcopyrite massive electrode Origin B â B4 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 52 Figure 28: Chalcopyrite massive electrode Origin C â C1 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification Figure 29: Chalcopyrite massive electrode Origin C â C1 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 53 Figure 30: Chalcopyrite massive electrode Origin C â C2 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) BSE polished to 1 μm diamond polish at 7x magnification (Right) SE polished to 1 μm diamond polish at 7x magnification Figure 31: Chalcopyrite massive electrode Origin C â C2 EDS mapping (Top Left) BSE location of EDS mapping polished to 1 μm diamond polish (Top Right) EDS map showing all identified elements together (Bottom Left) EDS mapping showing Cu location (Bottom Center) EDS mapping showing Fe location (Bottom Right) EDS mapping showing S location 54 3.1.4 Inductively Coupled Plasma â Optical Emission Spectroscopy (ICP-OES) of Chalcopyrite Origins A 34-element chemical assay was performed on the chalcopyrite mineral origins through ICP-OES to provide a more detailed characterization. It is more sensitive to lower element compositions than both XRD and EDS. The ICP-OES samples were collected from the same hand-ground mortar and pestle powders produced for XRD. This allows for a more direct comparison of mineral origin characterization to that of XRD and EDS. Due to the nature of ICP-OES being destructive, this method was performed last. This ensured all other data could be gathered before consuming the mineral samples. Kemetco Research, a third-party research company, performed the ICP-OES. They were selected based on their access to the required equipment and skilled technicians to operate it. A third party was also selected to ensure that no bias was introduced based on expectations from XRD and EDS. The mineral samples were aqua regia digested (nitrohydrochloric acid â 3:1 mixture hydrochloric acid to nitric acid) to various dilutions based on standards the machine was trained on. Due to the nature of the method using plasma flames for identification, the oxygen content was not identifiable. There was also not confident sulfur content data. This was unexpected given this method is commonly used to acquire this exact data. Kemetco Research reported multiple attempts at various dilutions, but was ultimately unable to acquire sufficient dilution for confident data at their machineâs current calibration in the time-frame required for this workâs completion. ICP-OES characterization data for chalcopyrite Origin A, B, and C are summarized in Table 12 in mg/kg, which was converted into weight percent. For table clarity, values between 1 and 0.1 wt% were labeled as â<1â, values between 0.1 and 0.01 wt% were labeled as âTraceâ and values less than 0.01 wt% were ignored as they were within experimental error. Table 13 summarizes the comparison of EDS and ICP-OES characterizations by elemental composition in wt%. Elements that were not identified within either method were removed to simplify the table. EDS and ICP-OES have high agreement in elements that exist in each origin and wt% of their composition. This provides high confidence in both methods' ability to characterize these chalcopyrite origins. It also provides high confidence in being able to use EDS as the single characterization method for each individual massive electrode. In the event that ICP-OES did not provide satisfactory results, one of two things would need to occur. Either ICP-OES would need to be re-tested to ensure correct dilutions were made, or another method would need to be selected to determine if XRD and EDS or ICP-OES were providing errored results. However, it is not probable that both XRD and EDS would be incorrect. Most likely the error would still be occurring in ICP-OES. 55 Table 12: Aqua regia digested ICP-OES characterization of chalcopyrite Origins A, B, and C from the same powder samples used for XRD. Raw data was provided by Kemetco Resources in mg/kg and was converted to weight percent for comparison to XRD and EDS. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01 wt% ignored as within experimental error. *Oxygen content is not able to be identified due to the nature of the method using plasma flames for identification. **There was not sufficient dilution capable of providing confident sulfur content data. Element Symbol Dilution Level Origin A Origin B Origin C mg/kg mg/kg wt% mg/kg wt% mg/kg wt% Silver Ag 10 198 Trace 196 Trace 113 Trace Aluminum Al 20 285 Trace 682 Trace 2959 <1 Arsenic As 40 727 Trace 734 Trace 354 Trace Boron B 100 <100 Trace 177 Trace <100 Trace Barium Ba 4 <4 ----- <4 ----- <4 ----- Beryllium Be 4 <4 ----- <4 ----- <4 ----- Bismuth Bi 40 530 Trace 364 Trace <100 Trace Calcium Ca 20 6489 <1 5638 <1 18554 2 Cadmium Cd 4 103 Trace 38 ----- 95 ----- Cobalt Co 10 1173 <1 1139 <1 618 Trace Chromium Cr 10 <10 ----- <10 ----- 18 ----- Copper Cu 20 310542 31 288406 29 247576 25 Iron Fe 20 270070 27 253731 25 221520 22 Potassium K 100 <100 Trace <100 Trace <100 Trace Lithium Li 20 <20 ----- <20 ----- <20 ----- Magnesium Mg 20 103 Trace 851 Trace 1927 <1 Manganese Mn 4 113 Trace 104 Trace 432 Trace Molybdenum Mo 20 <20. ----- <20 ----- <20 ----- Sodium Na 100 <100 Trace <100 Trace <100 Trace Nickel Ni 10 113 Trace 100 Trace 48 ----- Oxygen* O -----* -----* -----* -----* -----* -----* -----* Phosphorus P 100 <100 Trace <100 Trace <100 Trace Lead Pb 40 915 Trace 396 Trace <110 Trace Sulfur** S 100** 82807** 8** 81777** 8** 74989** 7** Antimony Sb 40 <40 ----- <40 ----- <40 ----- Selenium Se 40 <40 ----- <40 ----- <40 ----- Silicon Si 40 2750 <1 1858 <1 5142 <1 Tin Sn 40 <40 ----- <40 ----- <40 ----- Strontium Sr 4 <4 ----- 4 ----- 7 ----- Titanium Ti 20 <20 ----- 132 Trace 375 Trace Thallium Tl 40 <40 ----- <40 ----- <40 ----- Uranium U 100 <100 Trace <100 Trace <100 Trace Vanadium V 20 <20 ----- <20 ----- <20 ----- Zinc Zn 10 11757 1 4298 <1 12371 1 56 Table 13: Elemental compositions in wt% of chalcopyrite Origins A, B, and C comparing EDS and ICP-OES. Values between 1 and 0.1 wt% labeled as â<1â, values between 0.1 and 0.01 wt% labeled as âTraceâ and values less than 0.01 wt% ignored as within experimental error. *ICP-OES Oxygen content is not able to be identified due to the nature of the method using plasma flames for identification. **There was not sufficient dilution capable of providing confident sulfur content data for ICP-OES. Element Symbol Weight Percent Origin A Origin B Origin C EDS ICP-OES EDS ICP-OES EDS ICP-OES Silver Ag Trace Trace <1 Trace Trace Trace Aluminum Al Trace Trace <1 Trace Trace <1 Arsenic As Trace Trace Trace Trace Trace Trace Boron B ----- Trace ----- Trace ----- Trace Bismuth Bi Trace Trace Trace Trace Trace Trace Calcium Ca 2 <1 4 <1 4 2 Cadmium Cd ----- Trace ----- ----- ----- ----- Chlorine Cl ----- ----- Trace ----- ----- ----- Cobalt Co Trace <1 Trace <1 Trace Trace Copper Cu 33 31 29 29 30 25 Iron Fe 31 27 28 25 29 22 Potassium K ----- Trace Trace Trace ----- Trace Magnesium Mg Trace Trace Trace Trace <1 <1 Manganese Mn <1 Trace <1 Trace <1 Trace Molybdenum Mo ----- ----- ----- ----- Trace ----- Sodium Na ----- Trace ----- Trace ----- Trace Nickel Ni ----- Trace ----- Trace ----- ----- Oxygen* O <1 -----* 5 -----* 5 -----* Phosphorus P ----- Trace ----- Trace ----- Trace Lead Pb <1 Trace Trace Trace <1 Trace Sulfur** S 32 8** 29 8** 29 7** Silicon Si Trace <1 3 <1 3 <1 Tellurium Te Trace ----- Trace ----- ----- ----- Titanium Ti ----- ----- Trace Trace Trace Trace Uranium U ----- Trace ----- Trace ----- Trace Zinc Zn Trace 1 1 <1 <1 1 3.1.5 Comparison of Characterization Methods XRD, EDS, Optical/SE/BSE imagery, and ICP-OES together provide a well-rounded characterization of both the chalcopyrite mineral origins and the individual mineral massive electrodes. This data presents the importance of using multiple characterization methods. XRD provided an understanding of values observed in EDS and Optical/SE/BSE imagery. This allowed for the selection of a more appropriate quantification method in Phi(Rho, Z), whose results were further confirmed by ICP-OES. In isolation, each method merely provides an unconfident approximation, but any two methods in combination provide a sufficiently confident characterization. For example, the sulfur content of my three origins would be left unknown if ICP-OES was used in isolation (typically ICP-OES would be able to provide this data). But by obtaining EDS characterization the S content can be reported. And since EDS has strong 57 agreement with ICP-OES in Cu and Fe content, the S content provided by EDS can be accepted as a confident characterization. All three together fill in any gaps and provide the strongest confidence characterization. XRD and ICP-OES can only characterize mineral origins, leaving the massive electrode compositions unknown. While EDS can provide both electrode and origin compositions, it does so by observing electrodes. Therefore, it is not sufficient for high-confidence origin characterization. When combined with either XRD or ICP-OES, it can be a confident characterization method. And when compared to both, it can provide a high-confidence characterization. It is nearly impossible to produce an absolute value for composition given that each method observes a small sample of an entire mineral origin. However, statistics allows for this method of sampling, especially given the low errors each method produces. Table 14 summarizes the purity of chalcopyrite Origins A, B, and C by characterization method. Table 15 provides an unweighted average of all methods for weight percent of Cu, Fe, and S compared to inclusion elements. Table 13 provides a good understanding of the inclusion elements and their respective weight percent. The data from Table 15 alone is not sufficient at producing a well-rounded enough characterization if not provided alongside Table 13. The inclusion composition will affect the reactivity of the mineral. Table 14: Characterization of chalcopyrite Origins A, B, and C based on XRD, EDS, and ICP-OES comparing the weight percent of Cu, Fe, and S. Total CuFeS2 versus other content is shown. *XRD assumes all chalcopyrite follows the ideal weight ratio Cu (34.6%) â Fe (30.4%) â S (34.9%) which was used to calculate Cu, Fe, and S quantities based on CuFeS2 amount. **ICP-OES was unable to produce reliable S content due to insufficient dilution, in lieu of this, S content was calculated based on Cu and Fe content and CuFeS2 ideal weight ratio. Element / Mineral Weight Percent Origin A Origin B Origin C XRD* EDS ICP-OES XRD* EDS ICP-OES XRD* EDS ICP-OES Cu 30 33 31 33 29 29 32 30 25 Fe 27 29 27 29 25 25 28 26 22 S 30 32 31** 34 28 29** 32 29 25** CuFeS2 87 95 89 96 83 83 92 85 71 Other 13 5 11 4 17 17 8 15 29 Table 15: Characterization of chalcopyrite Origins A, B, and C based on XRD, EDS, and ICP-OES weight percent averaged together from Table 14. Element / Mineral Weight Percent Origin A Origin B Origin C Cu 31 30 29 Fe 28 27 25 S 31 30 29 CuFeS2 90 87 83 Other 10 13 17 The inclusions present across Origins A, B, and C with the highest weight percent are calcium (Ca), cobalt (Co), manganese (Mn), oxygen (O), silicon (Si), and zinc (Zn). All these elements are less noble than copper. This suggests chalcopyrite origins with more inclusions will be more reactive. As an explanation, 58 take two origins with the exact same element inclusions and total inclusion percentage. These are expected to react identically. But if one had a higher percentage of less noble elements, that origin would be expected to be more reactive. Comparing these elements to the XRD data from Table 5 further suggests that inclusion elements are likely to exist as oxides. Given oxides are generally reactive in such environments and all these inclusions are less noble than copper, there is the expectation that high-inclusion chalcopyrite is more reactive than pure chalcopyrite. This may be countered when there is a higher presence of more noble elements such as silver (Ag), which could increase copperâs reactivity (Córdoba et al., 2008; Crundwell, 2015; Ghahremaninezhad et al., 2012; Hackl et al., 1995; Li et al., 2013; Miller et al., 1981; Nazari et al., 2011, 2012; Nikoloski et al., 2017; Olvera et al., 2014, 2016; Price & Warren, 1986; Tapera & Nikoloski, 2019; Tapera et al., 2018; Watling, 2013). Based on the characterization data, I expect Origin A to be the noblest because it has the lowest amount of inclusions (Table 15), which are similar in composition to Origin B and C, making total inclusion content the larger variable (Table 13). Determining the expectation of nobility between Origin B and C is not as straightforward. Starting with the inclusion percentage, Origin B is 4 wt% purer (Table 15). And the weight percentage of Ca, the most reactive high-weight percent inclusion, in both Origin B and C is approximately equal (Table 13). Thus, Origin C has a higher weight percentage of less noble elements. This would seem to present Origin B as nobler. However, Origin B may have more Ag (Table 13). This may seem inconsequential given the small amount that is present. But if any given sample contains more silver, given its higher nobility than copper, it could result in higher copper reactivity. Table 9 shows Origin B samples contain the most silver and Origin B â B3 contains the most at 1 wt% while also containing the lowest Ca by at least 4 wt% compared to Origin C samples. Therefore, Origin B may in fact be nobler on average, but there exist cases where Origin C samples may react nobler. This exercise of ranking the origins of a mineral is here to illustrate that just because one mineral may have fewer inclusions does not provide enough information to understand how it may react. The composition and percent composition provide a deeper understanding. And when they are combined, a more complete picture can be formed and allow for more clear comparison of experimental results. Taking a deeper look into the values in Table 14 shows a high level of agreement across all characterization methods. The largest disparity is 7 wt% between XRD and ICP-OES of Origin C â Cu and S. However, in some cases, two methods show the same value. Origin B showed the most agreement with EDS and ICP-OES presenting the same value for Cu and Fe presence. Origin A had XRD and ICP-OES agree on Fe presence and had only a 1 wt% disparity in Cu presence. Unfortunately, ICP-OES could not provide a third opinion of S content. But calculating the expected value based on ideal weight ratio of Cu (34.6%) â Fe (30.4%) â S (34.9%) presented strong agreement from both XRD and EDS for Origin A. Origin B ICP-OES calculations presented a 1 wt% variance with EDS and 5 wt% with XRD. Origin C ICP-OES showed higher variances for XRD and EDS at 7 wt% and 4 wt%, respectively. Using the Cu, Fe, and S content and inclusion percentage summarized in Table 14 and Table 15, I can determine the weight ratio of Cu â Fe â S in each origin. The comparison of values calculated from XRD, EDS, and ICP-OES are shown in Table 16 and averaged in Table 17 to compare against the ideal weight ratio. This value can provide another perspective to characterizing reactivity and understanding 59 experimental results. However, this data cannot be observed in isolation, just like inclusion percentage or inclusion composition, but it can provide more clarity to the observed phenomena. Table 16: Comparison of XRD, EDS, and ICP-OES characterizations performed on chalcopyrite Origins A, B, and C to determine total weight ratio of Cu â Fe â S. *Values for XRD calculated from Table 5 assuming all chalcopyrite in the three origins follow the ideal weight ratio for CuFeS2 of Cu (34.6%) â Fe (30.4%) â S (34.9%). **ICP-OES was unable to produce reliable S content due to insufficient dilution, in lieu of this, S content was calculated based on Cu and Fe content and CuFeS2 ideal weight ratio. Element Weight Ratio Origin A Origin B Origin C XRD* EDS ICP-OES XRD* EDS ICP-OES XRD* EDS ICP-OES Cu 34.6 35.1 34.7 34.6 35.0 34.6 34.6 35.2 34.6 Fe 30.4 30.9 30.2 30.4 30.8 30.4 30.4 30.9 30.4 S 34.9 34.0 35.0** 34.9 34.2 34.9** 34.9 33.9 34.9** Table 17: Characterization of Cu â Fe â S weight ratio in chalcopyrite Origin A, B, and C based on XRD, EDS, and ICP-OES values averaged together and compared to the ideal Cu â Fe â S weight ratio Element Weight Ratio Origin A Origin B Origin C Ideal Cu 34.8 34.8 34.8 34.6 Fe 30.5 30.5 30.6 30.4 S 34.7 34.7 34.6 34.9 3.1.6 Conclusions on Reporting Mineral Characterization Whenever reporting on characterization data, it is important to provide all information possible and confirm the results using multiple methods. This will allow for a more clear understanding of the mineral that was used, which will allow for more accurate comparisons. It is nearly impossible to obtain two minerals with the exact same composition, but understanding their differences can provide the explanation for observed phenomena. This chapter provides much of the thought surrounding the choices made during characterization. This was necessary to show the importance of using multiple methods and provide understanding for why I chose the methods I did. This elaboration is not always necessary to provide. If a work were to characterize using the same methods as done here (XRD, EDS, Optical/SE/BSE Imagery, and ICP-OES) the following information should be the minimum required: â¢ XRD o Description of how the sample was obtained and prepared for experimentation o Name the equipment model, settings, and software used to interpret raw data o Raw data spectra (Figure 16) o Table of data summary (Table 5) 60 â¢ EDS o Description of how the samples were obtained, constructed, and prepared for experimentation o Name the equipment model, settings, and quantification method used to interpret raw data o Table of data summary for each sample used (Table 9)  Table of data summary for sample origin if using multiple samples from same origin (Table 8)  Table of data summary to remove readerâs need to calculate purity (Table 10) o Images from EDS mapping data to determine mineral element composition/locations (e.g. Figure 18 and Figure 19) â¢ Optical/SE/BSE Imagery o Photographs of samples that approximate what the naked eye would see (e.g. Figure 18 - Left) o Images of sample from SE and BSE showing as much surface area as possible to compare to photographs of sample (e.g. Figure 18 â Center & Right) o Table of data summary for each sampleâs surface area (Table 11) â¢ ICP-OES o Description of how samples were obtained and prepared for experimentation o Name of equipment model and/or name of 3rd party who completed the measurements o The digestion used for dilution o Table of data summary for dilution levels and obtained values (Table 12) â¢ Optional reporting to ease understanding of data o Comparison tables of data summary from all methods used (Table 13 and Table 14)  Easier for quick comparison for reader than observing the data table from each method and having to go back and forth o Any data that can be calculated from other data presented (Table 16)  Depending on the importance of such data to the experimental results 3.2 Mineral Massive Electrode I chose to use massive electrodes for my working electrode. They are the most commonly used electrode type when studying mineral electrode passivity based on literature review and allow for consistent mineral electrode production. Also, the most cited chalcopyrite anodic polarization curves were measured on massive electrodes (Warren et al., 1982) and will be compared to in this work. More importantly, massive electrodes do not introduce any foreign substances (such as carbon paste) that could alter experimental results. The massive electrodes were constructed by hand by the same researcher who performed all characterization and experiments. 3.2.1 Massive Electrode Construction Starting with a rock (approximately 5 â 8 inch diameter) of raw chalcopyrite ore, a section was removed through impact. This continued until small enough pieces remained that could fit in a 3 inch diamond 61 saw rock cutter to be cut close to the final dimensions. It was then hand-sanded to an approximate rectangular prism. Two larger parallel sides were approximately 1 â 3 cm2 with a thickness of approximately 3.5 â 6 mm. Thicknesses were kept slightly larger than desired final thickness allowing for sanding to final dimension once embedded in epoxy. All edges were hand-sanded up to 1200 grit with carbide paper, keeping the exposed surface area constant with repeated polishing between experiments. Edge sanding has further benefit as it reduces the chance of edge current effects from poor epoxy adhesion to the mineral. Poor adhesion would allow electrolyte to penetrate along the edge and current to bypass the bulk of the electrode. A copper wire was affixed by silver paste (Enson EN-06B8, surface resistivity â¤20 mΩ/square/mil) or copper tape (resistance through adhesive = 3 â 5 mΩ/square) to one of the two approximately 1 â 3 cm2 surfaces. It was made as short as possible to reduce resistance, being only long enough to reach from the electrode to the potentiostat connection a few inches away. Examples of the wires used and approximate scale of wire length are shown in Figure 32. The white wire was used until stock was depleted and was replaced with the blue wire. The white copper wire was preferred for its gauge and strand count. The gauge is able to pass both 1 μA and 1 mA with sufficiently low resistance to have a negligible effect on results (Table 18). The strand count allows for a good physical interaction between the back of the polished mineral surface and the wire strands. The yellow copper wire was used only when white and blue wire were depleted, although it has too few strands and too large a diameter to make the most effective bond with the mineral surface, relying on the copper tape to ensure connection. Silver paste was used to affix the copper wire to Origin A electrodes and copper tape for Origin B and C electrodes. Examples of each step are shown in Figure 33. Figure 32: Four easily accessible wires and considered for massive electrode construction. (Left - Red) Iron wire of small gauge. Avoid using if possible. (Left - Blue) Copper wire of sufficient gauge to transfer current with negligible resistance (Left - White) Copper wire with ideal gauge with many strands to make contact with large area of mineral surface, also has green shielding (Left - Yellow) Copper wire with too large a gauge and too low strand count to make good contact to mineral surface, ensure affixing media has sufficient coverage and contact (Right) Wire scale shown next to ball point pen. Wire only required reaching a short distance to reduce resistance. Table 18: Copper connection wires from Figure 32 with gauges determined by measurement and calculated resistance based on Equation 31 where ÏCu = 1.682*10-8 Ω m @ 21°C and L = 6 in. = 0.1524 m (see section 5.3.1.2 Wire Preparation) Massive Electrode Connection Wire Strand Size AWG Strands Effective Cable Size Effective AWG Resistance Color Ã mm Single Strand # mm2 Ã mm Multi-Strand mΩ A1 blue 0.27 29.5 12 0.687 0.935 19 AWG 12/30 3.7 B1, B2, B4 yellow 0.63 22.2 7 2.182 1.667 14 AWG 7/22 1.2 B3, C2 white 0.16 34 41 0.824 1.024 18 AWG 41/34 3.1 C1 green 0.16 34 41 0.824 1.024 18 AWG 41/34 3.1 62 Figure 33: Example of massive electrode construction. (Left to Right) Raw chalcopyrite ore, small piece removed, sanded to approximate rectangular prism with centimeter scale, copper wire attached by silver paste in epoxy mold, copper wire attached by copper tape and embedded in epoxy (either silver paste or copper tape used, not both) The polished mineral with wire affixed was then fully covered in System Three Cold Cureâ¢ two part epoxy (available at: https://www.systemthree.com/products/cold-cure-cold-weather-epoxy) and allowed to cure for at least 24 hours in a fume hood. This resin was selected based on availability, cure time, and its stability in highly acidic media. The resin-embedded chalcopyrite was hand-sanded with 80 grit carbide sand paper until the free surface was nearly exposed. Hand-sanding continued with 240 grit carbide paper until the free surface was exposed, and was then hand-sanded up to 1200 grit. While sanding, care was taken to ensure the thickness of the mineral was constant and not less than 3 mm, but no larger than 5 mm. In use, the electrode is polished to 1200 grit between each experiment, so this thickness allows for multiple experiments to be performed. There is a balance here between extending the electrode life while minimizing any electrode resistance from mineral thickness. Since the thickness decreases after each experiment, no sample was used with a thickness less than 1 mm (see section 4.6.2 Effects of Mineral Thickness in Mineral Massive Electrodes), allowing the first and last experiment run on the sample to be within a few millimeters of each other. This thickness range also reduces the potential for stress cracking. Chalcopyrite is a relatively brittle mineral and when large currents are passed through it, the material can fracture due to the induced stresses. All other surfaces remain embedded within the resin. The exposed surface was then hand-polished to 1200 grit with carbide paper. At this point, the massive electrode was ready to prepare for EDS characterization where it was diamond polished to 1 μm and coated in carbon. After characterization it was polished to 1200 grit with carbide paper and was ready for experimentation. Examples of experimentation ready chalcopyrite massive electrodes are shown in Figure 34. The right image shows an electrode with speckled resin. This is a result of air bubbles being trapped in the resin when mixing, which were not able to escape during curing. A vacuum chamber should be used to remove any entrained air bubbles before pouring over the mineral (see section 5.3.1.3 Resin Preparation). The left and center images show electrodes whose resin was placed in a vacuum for a few minutes prior to pouring. The entrained air bubbles can result in a path to the sides or back of the mineral through the resin, no longer isolating it from the electrolyte and current. 63 Figure 34: Examples of chalcopyrite massive electrodes polished to 1200 grit and ready for experimentation. (Left) Resin placed in vacuum to remove entrained air bubbles before pouring over mineral. Copper wire attached with silver paste (Center) Resin placed in vacuum to remove entrained air bubbles before pouring over mineral. Copper wire attached with copper tape (Right) Resin not placed in vacuum resulting in entrained air bubbles. Copper wire attached with copper tape. Centimeter ruler placed in image for scale. 3.2.2 Massive Electrode Preparation for Experimentation Each experiment was started by hand polishing the exposed face of a chalcopyrite massive electrode to 1200 grit with carbide paper. It was then sonicated for 1 minute in de-ionized (DI) water to remove any oils and debris. It was dried with gently forced air provided by a fume hood for at least 5 minutes at ambient room temperature (21°C). The exposed surface was then marked with a permanent marker (Bic Mark-it ultra-fine point permanent marker in Deep Sea Blue chosen for visibility and inertness) designating a 0.442 cm2 circle (Figure 35). This circular area was selected for a few reasons; the first being it ensured the surface area remained constant between experiments. Circles are simple to draw and a template could be used to draw the same size consistently. This allowed for using the most surface area on smaller electrodes while not producing areas of current concentration. The area within the circle remained exposed during experimentation. The area outside the circleâs boundary was covered in a single, thick layer of nail polish. This included covering the resin holding the mineral electrode to at least 2 mm from the resin-mineral interface (Figure 36). This was done to isolate the resin-mineral interface from electrolyte and current. Pairing the nail polish mask with the circular area within the mineral boundary proved effective at isolation (Figure 36). Nail polish was selected as the mask material due to its availability, ease of application, and inertness in acidic environments. The nail polish used was Sally Hansen Insta-Dri in Hail Cherry red (Item code 359) to ensure clear visibility of what was covered and what was not (Figure 35). It is advertised as fast-drying nail polish, drying a thin layer in 60 seconds. Given the thickness of the nail polish applied and to ensure the lowest permeability, the nail polish was allowed to dry for at least 5 minutes under gently forced air provided by a fume hood at ambient room temperature (21°C). The massive electrode was kept at ambient room temperature at all times as this was the temperature used for all experimentation. It also ensured the electrode never experienced thermal shock, which can result in micro-fracturing. After experimentation was completed, the electrode was given a DI wash. Then acetone and a paper towel were used to remove the nail polish and marker completely. The process was then repeated when starting a new experiment. For experiments excluding the nail polish mask, all steps were performed in order skipping the application and removal of the permanent marker circle and nail polish mask. 64 Figure 35: (Left) Bic Mark-it ultra-fine point permanent marker in Deep Sea Blue (Center Left) Chalcopyrite massive electrode with 0.442 cm2 circle drawn on it by permanent marker (Center Right) Sally Hansen Insta-Dry Hail Cherry Red nail polish used as mask material (Right) Chalcopyrite mineral electrode with 0.442 cm2 circle drawn in permanent marker and masked with nail polish. A centimeter ruler is measuring the diameter of the circleâs inner edge at 0.75 cm Figure 36: Chalcopyrite massive electrodes with nail polish masks. (Left) Nail polish attempting to mask the resin-mineral interface while preserving as much of the exposed mineral surface as possible. The nail polish can be seen to produce a distinct line at the resin-mineral interface suggesting it was not filled in and potentially not fully isolating it from electrolyte and current. (Center) Nail polish successfully masking the resin-mineral interface following the drawn circle (Right) Nail polish successfully masking the resin-mineral interface following the drawn circle. It is back-light to prove nail polish extends outwards covering everything at least 2 mm past the resin-mineral interface 3.3 Solution Preparation Sulfuric acid (H2SO4) solutions were used for all experimentation. Sulfuric acid is commonly used in published literature (and in industrial practice) when leaching chalcopyrite electrodes. There are many other solutions that can be and are used, such as hydrochloric acid. However, sulfuric acid provided the widest comparability to existing literature and industrial practice. The experimental solution was prepared by dissolving ACS reagent grade 96% sulfuric acid (VWR Chemicals BDH3072-2.5LG, Lot: 2018041797) in DI water to a concentration of 2 g/L (pH â 1.69). The dilutions were done in 1 and 2 L volumetric flasks. To ensure they obtained the 2 g/L ± 0.005 g H2SO4, the appropriate grams of sulfuric acid were weighed on a scale (2 g for 1 L and 4 g for 2 L). To minimize any error between experiments, every experiment used 100 mL of solution. 65 3.4 Electrochemical Cell The experimental apparatus was a traditional three-electrode cell connected to an AMETEK® VersaSTAT4 Potentiostat Galvanostat with data accessed through VersaStudio software. The cell included the following: â¢ Working Electrode (WE) â chalcopyrite massive electrode â¢ Counter Electrode (CE) â solid Ã6.5 mm graphite rod 8 cm long of which 4.5 cm were submerged in solution â¢ Reference Electrode (RE) â 4 M Potassium Chloride saturated Ag/AgCl RE submerged in a Luggin capillary filled with 10 mL (±5% per VWR glassware) 2 g/L sulfuric acid solution â¢ Vessel â 150 mL VWR glassware beaker filled with 100 mL (±5% per VWR glassware beaker) of 2 g/L sulfuric acid solution The solution remained unstirred and un-sparged throughout all experiments except for those determining the effect of stirring and sparging. The stirring was performed with a 12.7 mm long, 8 mm diameter Fisherbrandâ¢ Octagon Spinbarâ¢ magnetic stirring bar (catalog #14-513-58) with a rotations per minute (rpm) controller accurate to 1 rpm. Sparging with nitrogen (â¥ 99.995% from Linde Inc. (Canada)) at 10 mL/min (± 5% per Dwyer Omega flow meter) was performed through a glass frit sparger placed as close to the working electrode as possible without being in the line-of-sight of the working electrode to the counter electrode or stir bar. Both stirring and sparging were performed for 10 min prior to polarization and continued through polarization. Working electrode was only placed in solution immediately prior to polarization. The Luggin capillary was filled with 10 mL (± 5% per VWR glassware) of the sulfuric acid solution to ensure that the reference electrode was completely submerged in solution with no entrained air bubbles. The Luggin capillary's porous glass frit also prevented any contamination of the reference electrode. A new glass frit was installed prior to my experimental program and was used for all experimentation. A schematic of the experimental setup is shown in Figure 37 and images of an experiment in Figure 38. 66 Figure 37: Schematic of electrochemical cell experimental setup used in all experiments conducted in this work. The magnetic stir bar was only present for experiments where stirring was expressly stated. When used, the same magnetic stir bar was placed to ensure clean spinning and to be near the massive electrode, not necessarily between CE and WE. Luggin capillary intentionally placed so it did not cover the mineral and to have WE and RE in-line with counter electrode. Figure 38: Images of an experiment showing the electrochemical cell experimental setup used in all experiments. The magnetic stir bar was only present for experiments where stirring was expressly stated. When used, the same magnetic stir bar was used and placed to ensure clean spinning and to be near the massive electrode. Luggin capillary intentionally placed so it did not cover the mineral and have WE and RE in-line with counter electrode. 67 3.5 Electrochemical Techniques Three electrochemical techniques were used to acquire all data presented in this work. The primary methods were Open Circuit Potential (OCP) and galvanostatic polarization. Potentiostatic polarization was used for comparison to galvanostatic polarization data and to make comparisons to other work. 3.5.1 Open Circuit Potential (OCP) Open Circuit Potential, also known as rest potential, allows for the electrochemical system to reach steady state without applied current or voltage. This was done in a stagnant environment unless explicitly stated. OCP was performed for 12 min on the Ag/AgCl reference electrode before every set of experiments. The primary reference was compared to a secondary Ag/AgCl reference electrode that was only used for checking if the primary reference electrode produced drifting values. If the primary electrode produced drifting values, OCP was run for an additional 12 min to allow sufficient time for steady state to be reached. If equilibrium could not be reached in this time, the 4 M potassium chloride (KCl) reference electrode fill solution was replaced. OCP was performed on every chalcopyrite massive electrode. This method also allowed for simple experimentation to troubleshoot if a sample appeared to behave unexpectedly (e.g. very high or low OCP, or noise). If the sample produced noisy data, a second OCP experiment was run with fresh solution and a polished sample. If three consecutive experiments produced noisy data, the sample was removed from further experimentation. Most OCP experiments were run for 12 min, but some were run for 1 or 2 hours. 3.5.2 Galvanostatic Polarization Most experiments were conducted under galvanostatic polarization, which is constant current application to a working electrode with the resulting potential being measured. The applied current ranged from 1 μm to 1 mA. This method is commonly used in literature to observe passivating electrodes. Galvanostatic polarization was used under stagnant conditions unless stirring or sparging was explicitly stated. Most experiments were run for 1 hour. 3.5.3 Potentiostatic Polarization Some experiments were conducted under potentiostatic polarization, which is constant voltage application to a working electrode with the resulting current being measured. The applied voltage ranged from 270 â 690 mV. These values were selected based on data acquired from galvanostatic polarization for direct comparison. Potentiostatic polarization is also commonly used to observe passivating electrodes in literature. This method was exclusively used under stagnant conditions and experiments ran for 1 hour. 68 Chapter 4: Investigation of the Variability in Mineral Electrochemistry 4.1 Introduction to Variability in Mineral Electrochemistry Research has handled mineral electrochemistry similarly to non-mineral electrochemistry, such as that performed on steel. The standard laboratory practices typically used and some of the ANSI, ASTM, ISO, and NACE standards are partially adopted. However, these methods are not directly applicable. The apparatus used and the assumptions made do not account for the nature of minerals. Every mineral sample is distinctly unique, potentially porous and/or brittle, and every sampleâs exposed surface changes, in both chemistry and mineral phase compositions, when polished for a fresh surface. Furthermore, the sample composition cannot be engineered as mineral samples are discovered, not created. The idea that âyou get what you getâ has long been used to describe away the variability seen throughout mineral electrochemistry. However, there are many parameters that can be controlled and variability greatly minimized if carefully managed. While the mineral is responsible for the inherent variability, the parameters and methods used in preparing, performing, and analyzing data are responsible for exacerbating that variability and skewing results and/or analyses. 4.2 Open Circuit Potential Before any other information is reported, the Open Circuit Potential (OCP), also known as rest potential, should be reported. OCP measurements should allow for the electrochemical system to reach steady state without applied current or voltage. OCP describes the starting potential for many experiments. It also helps to put into context the values obtained from different samples or experiments for accurate comparison. In non-mineral electrochemistry, the OCP is typically held for a range of time to ensure a stable value before the intended experimental method, such as potentiostatic polarization, is executed at a set value above the OCP. This has become practice as it allows the electrochemical cell to reach a steady state that is repeatable and provides the foundation for consecutive experiments to be comparable. This also allows for comparisons to show the effect of various experimental conditions (e.g. pH, stirring rate, electrolyte composition, temperature). Unfortunately, mineral electrochemistry is not always able to be performed in the same way. In the case of the mineral chalcopyrite, the steady state is normally not attained in experimentally-practical timeframes. Rather, it undergoes passivation under OCP, resulting in an increasing potential over several hours. Three examples of this are shown in Figure 39 for two chalcopyrite Origin A (α, β) massive electrodes. OCP was run in 100 mL of 2 g/L H2SO4 at 21°C with the massive electrode polished to 1200 grit with carbide paper. Origin A-α was run for 7.5 hours stirred at 600 rpm and 9 hours unstirred. Origin A-β was run for 1 hour stirred at 1200 rpm. The first 12 min of the experiments are shown inset. 69 Figure 39: THIS DATA SHOULD NOT BE USED WITH CONFIDENCE. OCP data on massive chalcopyrite electrodes from two uncharacterized Origin A (α, β) samples in 100 mL of stirred (600 and 1200 rpm) and not stirred 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper without a Luggin capillary or resin-mineral interface masking. Surface area: Origin A-α = 1.430 cm2, Origin A-β = 0.816 cm2. At first glance, this information may seem reliable and actionable as the data was acquired from massive electrodes produced from a chalcopyrite origin that has been broadly characterized in Table 5 through Table 17 in Chapter 3: and both stirred and unstirred data is presented. However, there are a few issues with the reliability of this data. First, there is no surface characterization data on these specific massive electrodes. Therefore, it is not known how these electrodes represent their origin and this restricts comparison to other data. No Luggin capillary was used to shield the reference electrode from potential contamination, which is typically standard laboratory practice. More importantly, there is only one test under each condition, so these experiments may in fact be outliers. Further, there is no masking on the resin-mineral interface, which will have a significant impact on results (as displayed in section 4.3 Effects of Resin-Mineral Interface). For these reasons, no specific data points (potential values, slope calculations, stirring effects, etc.) should be used with any confidence from these data sets. However, a piece of usable data from these three experiments is the positive slope of the curves. The three data sets agree that chalcopyrite passivates under OCP. This produces a potential that continues to rise without ever reaching and holding a voltage long enough to classify it as steady-state within 7.5 hours (potentially even 9 hours). A common standard for equilibrium steady-state is when âthe electrode potential stabilized with a change of no more than 1 mV in 10 minâ (Olvera et al., 2014). The inset graph in Figure 39 presents the 12 min region under which all further OCP experimentation was conducted as it shows the initial values along with the upward drift of data without over-passivating the massive electrode, extending its experimental life (see section 4.6 Mineral Massive Electrode Lifespan). Due to this continuous increase in potential, the first potential recorded will be selected as the reportable OCP value for this workâs CuFeS2 massive electrodes. In order to ensure the first recorded value is reliable and not a result of equipment noise, the first recorded value is compared to the average of the first 10 seconds of data (1 data point collected per second) in Table 19. 70 Table 19: OCP data for seven CuFeS2 massive electrodes (characterization data in Table 5 - Table 17 and Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper between experiments. Averages presented with two-sided t-distribution 95% confidence interval. CuFeS2 Electrode Data Captured (1 data/sec) mV vs. SHE OCP Average 95% CI A1 1st Second 506.3 486.4 483.6 477.2 474.1 499.6 486.1 487.6 10.7 10 sec Average 506.3 486.4 484.0 477.2 474.1 499.6 486.2 487.7 10.7 B1 1st Second 494.4 490.7 491.0 492.0 5.1 10 sec Average 494.8 491.0 491.3 492.4 5.2 B2 1st Second 496.2 491.0 491.0 492.7 7.5 10 sec Average 496.2 491.3 491.3 492.9 7.1 B3 1st Second 494.4 475.6 476.0 482.0 26.6 10 sec Average 494.5 476.0 476.2 482.3 26.4 B4 1st Second 538.2 514.0 507.5 511.2 517.7 22.1 10 sec Average 538.5 514.4 507.8 511.7 518.1 22.1 C1 1st Second 495.6 486.4 481.5 487.8 17.8 10 sec Average 495.9 486.7 482.0 488.2 17.6 C2 1st Second 484.5 475.0 483.0 480.9 12.7 10 sec Average 484.8 475.3 483.1 481.1 12.5 The largest difference between a first data point and an average of the first ten is 0.5 mV (B4 experiment 4, C1 experiment 3). The largest difference between the average of multiple first data points and first ten is 0.4 mV (B1, B4, and C1). Both differences are within reported error (two-sided t-distribution 95% confidence interval). The largest errors are Origin B â B3 and B4 at 26.6 and 22.1 mV, respectively. If the first OCP value of 538.2 mV is excluded as an outlier from Origin B â B4 average, the average is 510.9 mV and error = 8.0 mV. Origin B â B3 has the only error greater than 18 mV and four of the seven electrodes have an error lower than 11 mV. This shows that reproducible data is not only possible in OCP mineral electrochemistry, but can have an error as low as 5 mV (Origin B â B1) across three separate experiments. Table 2 literature data ranges ± 40 mV on the average reported. Therefore, I have confidence in selecting the first recorded potential (average of at least 3 experiments) as the reportable OCP for my massive electrodes and mineral origins. See Table 20 and Figure 40 â Figure 42. Table 20: OCP data for three CuFeS2 origins and seven massive electrodes (characterization data in Table 5 - Table 17 and Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Literature data averaged from Table 2. Averages presented with two-sided t-distribution 95% confidence interval (Origin â number of experiments: A â 7, B â 13, C â 6, Literature â 19). CuFeS2 Electrode mV vs. SHE A1 B1 B2 B3 B4 C1 C2 OCP 488 492 493 482 511 488 481 95% CI 11 5 7 27 8 18 13 Origin A Origin B Origin C Literature OCP 488 498 484 511 95% CI 11 10 7 40 71 Figure 40: OCP data for seven CuFeS2 massive electrodes (characterization data: Table 5 - Table 17, Figure 17 â Figure 31) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed = 0.442 cm2. Each line is an average of multiple experiments with two-sided t-distribution 95% CI error bars (electrode â number of experiments): A1 â 7, B1 â 3, B2 â 3, B3 â 3, B4 â 4, C1 â 3, C2 â 3. Figure 41: OCP data for three CuFeS2 origins (characterization data: Table 5 - Table 17) in stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Each line is averaged from multiple electrodes each with a minimum of three experiments with two-sided t-distribution 95% CI error bars (origin â number of electrodes): Origin A - 1, Origin B - 4, Origin C â 2. 72 In order to have context for the observed OCP data, I compiled data from literature (Table 2 in 2.4 Mineral Variability in Literature) for comparison and plotted against my three origins in Figure 42. There cannot be direct comparison to any particular literature data as they were obtained under varying conditions (pH, solution, stirred/unstirred, temperature). However, my data agrees with the general consensus of where CuFeS2 OCP rests. It is of note that all but three experiments in my data (B4: 538.2 mV, 514.0 mV, 511.2 mV) fall below the median (520.0 mV) and mean (511.0 mV) of the compiled literature data. There are no obvious patterns within the collected literature data that would explain why I observed this. Compared to my conditions, literature data used increased temperatures and electrolyte concentrations with and without agitation and still produced higher values. The remaining difference is my masking of the working massive electrode resin-mineral interface. Figure 42: Box and whisker diagram of OCP data for three CuFeS2 origins (characterization data in Table 5 â Table 17) in stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Each plot is from multiple electrodes each with a minimum of three experiments (origin â # of massive electrodes): Origin A â 1, Origin B â 4, Origin C â 2. Number of data points used to calculate average, max, min, median, Q2, Q3 (origin - # of data points): Origin A â 7, Origin B â 13, Origin C â 6, Literature â 19 (Literature data from Table 2). âXâ represents average, bar separating colors represents median. Color difference for easier data distinction: orange > median, blue < median. Outliers are shown as points. 73 4.3 Effects of Resin-Mineral Interface All electrode types have their shortcomings. For mineral massive electrodes it is the resin-mineral interface. Unfortunately, this interface is unavoidable as it is fundamental to the construction of the electrode. Once understood, methods can be used to mitigate its effects. 4.3.1 Massive Electrode Construction Massive electrodes are produced through taking a prospective electrode material and removing a small portion from the parent material; typically through impact. An example of the process is shown in Figure 33 (reproduced below from section 3.2.1 Massive Electrode Construction). It is then sanded with carbide paper to a desired size and shape, typically a rectangular prism to allow an equivalent exposed surface area when polishing between experiments, with the largest face being 1 â 3 cm2 and the thickness being 3 â 5 mm. This sanded prism then has a wire, typically copper, attached to one of the large faces, typically through silver paste/epoxy or copper tape. The material prism with secured wire is placed in a mold and epoxy resin is poured over it until encapsulated. After the resin cures, the face of the electrode material that does not have the wire on it is sanded with carbide paper until it is exposed and is then typically polished up to 1200 grit with carbide paper. If the particular experiment requires a smoother surface or microscopy methods will be performed on the sample, up to 1 μm diamond polish is used. Figure 33: Example of massive electrode construction. (Left to Right) Raw chalcopyrite ore, small piece removed, sanded to approximate rectangular prism with centimeter scale, copper wire attached by silver paste in epoxy mold, copper wire attached by copper tape and embedded in epoxy (either silver paste or copper tape used, not both) The massive electrode production method results in encapsulating the electrode material in resin with the goal of producing a 2-dimensional surface for experimentation. Due to the nature of mechanical interfaces, there exists an area in which the electrode material and resin are mated together. This area is prone to not providing a complete interface, producing a 3-dimensional surface. This can result from a few potential sources: â¢ micro-bubbles entrapped in the resin during resin curing producing voids â¢ resin shrinkage during curing â¢ an inability of the resin to flow into all crevices of the electrode material during curing â¢ chip-out of the electrode material or resin at their interface during sanding/polishing â¢ dissolution of the electrode material at the resin-material interface during experimentation 74 Figure 43 shows examples of this interface on a chalcopyrite massive electrode that has been polished to 1200 grit. Regardless of how it was produced, 3-dimensional surfaces are the downfall to the usage of massive electrodes as crevice corrosion can occur at the resin-electrode interface. Crevices result in an increase in acid and salt concentration, which results in a micro-corrosion cell which produces more acid and in turn increases corrosion rate. This produces corrosion product that reduces fresh flow to the area, allowing corrosion to progress quickly and occur similarly to pitting corrosion (basic schematic in Figure 44). This would affect the observed potential induced from galvanostatic polarization as you would no longer be measuring the rate of mineral particle dissolution of the bulk material, but rather inside the crevice. Figure 43: OM images at 5x magnification of a chalcopyrite massive electrode polished to 1200 grit showing the crevice between chalcopyrite and the resin it is embedded in (Top) resin shrinkage during curing, inability of resin to flow into crevice [brightness: +20%, contrast: -40%] (Bottom) resin shrinkage during curing, micro-bubbles entrapped in resin during curing producing voids [brightness: +20%, contrast: -25%] 75 Figure 44: Basic schematic of crevice corrosion occurring in a massive electrode between the mineral and the resin While crevice corrosion may be a relatively common place corrosion method with agreement on where it is observed, the underlying processes leading to its occurrence have been under research for decades. The nuances of its occurrences rely on a plethora of factors, ranging from pH and temperature to passive film construction and grain boundaries (Alvarez & Galvele, 2010). Nearly all of the research has been focused on metallic structures, namely alloys of aluminum, copper, and stainless steel. With this research has come a range of ASTM International standards guiding the methods to accurately observe corrosion, crevice or otherwise. In this same time, mineral electrochemistry has continued to grow in industrial importance, but research and, as a result, research standards have been decidedly absent. At time of writing, I was unable to find any ASTM International, ANSI, ISO, or NACE International standards guiding experimental methods of mineral electrodes for corrosion determination or otherwise. This does not come at too much surprise as determination of any data from mineral electrodes has proven difficult to provide consistent, repeatable data (Li et al., 2013; Viramontes et al., 2007; Warren et al., 1982). While this was touched on in previous chapters, it bears repeating as this has informed the lack of cohesive information being reported and the inability to reproduce data from existing work. In order to gain any actionable information from mineral electrochemistry, standard experimental methods are required, especially in regards to corrosion identification. In order to make any claims on crevice corrosion in mineral electrochemistry, extrapolation of general themes from research done on metallic structures must be made. One of those important themes is pitting corrosion, which has many similarities to crevice corrosion and can even lead to crevice corrosion (Alvarez & Galvele, 2010; Kelly & Lee, 2018). This is important as the interface between the mineral and resin can range from being a clear crevice to being very tight and prone to pitting corrosion until it increases in size so as to resemble a crevice and allow for increased kinetics at the resin-mineral interface. Figure 45 shows a range of observable resin-mineral interfaces via SEM on two different chalcopyrite massive electrodes. When compared to Figure 43 observing a crevice through optical microscopy, the scale of the observable crevice can range from micrometers to millimeters wide and up to centimeters long depending on preparation. 76 Figure 45: SE images of two different chalcopyrite massive electrodes resin-mineral interfaces (Top) polished to 1 μm diamond polish at 800x magnification showing a crevice up to 6 μm wide (Center) polished to 1200 grit on carbide paper at 800x magnification showing a crevice approximately 1 μm wide (Bottom) different location on same sample as Center image at 750x magnification showing a crevice <1 μm 77 4.3.2 Masking Effectiveness on a Massive Electrode The two options available for eliminating the resin-mineral interface are either removing the resin or masking the interface. The former would result in having to find a new method of affixing the mineral so that it can be experimented on while being completely submerged in solution but isolated on all but one side. The latter is a simple process that can use an otherwise insulated electrode that is easy to produce. Masking requires a material that can non-permanently bind to the mineral and resin and have a low enough viscosity to fill the interface region all while being chemically and electrically inert to the system. An added benefit would be to have a quick application process. Traditional nail polish does this quite well. Other similar lacquers can work, but are typically more expensive and less simple to work with. Traditional nail polish is widely available and comes in a quick drying version which allows for minimized wait times prior to experimentation. It can also be easily removed using a paper towel and acetone. For best practices on mask application, see section 5.3.2 Masking. The masking effectiveness has been confirmed through visual inspection as well as through OM and SEM imaging. The area exposed to experimentation can be clearly seen by visual inspection on two different massive electrodes in Figure 46 and Figure 47. It appears much darker, even grey in color, compared to the typical golden color of chalcopyrite and darkens the appearance of inclusions. These are two examples of what was seen on every massive electrode experimented with a mask. The amount of coloration change was directly correlated with both the potential/current passed through the electrode and time it was exposed. The higher the potential or longer the time exposed, the darker it appeared. See Table 21 images comparing masked versus unmasked electrodes under galvanostatic polarization. Figure 46: 5 experimentation steps for chalcopyrite Origin B â B1 massive electrode via native camera sensor and application on an iPhone 8 running iOS 14.4 (Left) Step 1: pre-experimentation â polished to 1200 grit with carbide paper (Left Center) Step 2: pre-experimentation â mask boundary marked at surface area = 0.442 cm2 (Center) Step 3: pre-experimentation â nail polish mask applied up to marked area (Right Center) Step 4: post-experimentation â galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Right) Step 5: post-experimentation â nail polish mask removed with acetone Figure 47: 5 experimentation steps for chalcopyrite Origin B â B2 massive electrode via native camera sensor and application on an iPhone 8 running iOS 14.4 (Left) Step 1: pre-experimentation â polished to 1200 grit with carbide paper (Left Center) Step 2: pre-experimentation â mask boundary marked at surface area = 0.442 cm2 (Center) Step 3: pre-experimentation â nail polish mask applied up to marked area (Right Center) Step 4: post-experimentation â galvanostatic polarization for 2 h at 100 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Right) Step 5: post-experimentation â nail polish mask removed with acetone 78 Table 21: Images of two chalcopyrite massive electrodes via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Origin B â B1 polarized for 1 h, Origin A â A1 for 2 h. âMaskedâ shows polarized electrodes with mask on (SAMasked = 0.442 cm2), center column after mask removed with acetone. These compare to the same electrodes polarized without a mask (SAA1 = 1.012 cm2; SAB1 = 1.294 cm2). Galvanostatic Polarization Exposure Time Masked Mask Removed No Masking 1 μA 1 h 2 h 10 μA 1 h 2 h 100 μA 1 h 2 h 1 mA 1 h 2 h 79 Visual inspection provides strong indication that the mask is effective at isolating the covered area from conditions experienced by the exposed area. To ensure this isolation boundary ends as abruptly as Figure 46 and Figure 47 suggest, the boundaries of those two electrodes were observed via OM in Figure 48 and Figure 49, respectively. OM provides confirmation of visual inspection that even at 50x magnification, the masked area remains isolated from conditions experienced by the exposed area. While surface coloration change is strong evidence for an effective mask, it is not clear how exposure affects surface structure. If there is micro-cracking or pitting that is not clearly visible when there is no coloration change, the mask may not be as effective at isolation as the color boundary suggests. SEM can provide conclusive determination. Figure 48: OM images of chalcopyrite Origin B â B1 massive electrode after galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Left) 5x magnification [brightness:+30%] (Right) 50x magnification [brightness:+40%] Figure 49: OM images of chalcopyrite Origin B â B2 massive electrode after galvanostatic polarization for 2 h at 100 μA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Left) 5x magnification [brightness:+40%] (Right) 20x magnification [brightness:+20%] Figure 50 shows SE and BSE images that confirm the mask acts as a sufficient barrier to conditions experienced by the exposed surface during experimentation. The exposed surface displays pitting and micro-cracks not present under the mask. While the masked surface displays areas that appear similar to pitting, they are voids present in the mineral prior to experimentation (see Figure 43 and Figure 45). 80 Pitting and voids can be differentiated by the count per area and size. The exposed surface has significantly more pit-like areas present and they are smaller on average. The micro-cracks end abruptly, not feathering out past the mask boundary. This proves the mask has sufficiently low viscosity to flow into voids and non-permanently bind to the mineral surface to isolate up to the boundary of coverage. Figure 50: SEM images of chalcopyrite Origin B â B1 massive electrode after galvanostatic polarization for 1 h at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C. Surface polished to 1200 grit prior to experimentation, no polishing post experimentation after nail polish mask removed with acetone (Top Left) SE at 18x magnification of mask boundary (Top Right) BSE at 18x magnification of mask boundary (Center Left) SE at 60x magnification of mask boundary from middle of Top Left (Center Right) BSE at 60x magnification of mask boundary from middle of Top Right (Bottom Left) SE at 60x magnification of masked area from upper right of Top Left (Bottom Right) BSE at 60x magnification of masked area from upper right of Top Right 81 4.3.3 Open Circuit Potential on Masked Massive Electrodes Previous sections show that the presence of the resin-mineral interface theoretically affects experimental results. The remaining question is: how much does this interface affect actual measurement? Previous research (Burdick & Ellis, 1917; Córdoba et al., 2008; Debernardi & Carlesi, 2013; Dutrizac, 1989; Ghahremaninezhad et al., 2012; Ghahremaninezhad et al., 2015; Han et al., 2018; Hirato et al., 1987; Hong-xu et al., 2006; Jyothi et al., 1989; Kaplun et al., 2011; Khabibullin et al., 2009; Khoshkhoo et al., 2017, 2014; Kimball et al., 2010; Koleini et al., 2011; Lázaro et al., 1995; Li et al., 2013; Yubiao Li et al., 2017; Lin et al., 2012; Linge, 1976; Liu et al., 2017, 2018; Majima et al., 1985; Mikhlin et al., 2016; Nazari et al., 2011, 2012; Nicol, 2022; Nicol et al., 2017; Olvera et al., 2014, 2016; Parker et al., 2003; Qian et al., 2014; Ren et al., 2022a; Stott et al., 2003; Tanne & Schippers, 2021; Velásquez-Yévenes et al., 2010; Viramontes-Gamboa et al., 2006; Viramontes et al., 2007; Von Oertzen et al., 2006; Warren et al., 1982; Watling, 2013; Wu et al., 2015; Yue & Asselin, 2014) and standard laboratory practice have taken its effect as negligible by nature of omission. However, it may be amplified by the nature of the experimental setup. Standard laboratory practice places the reference electrode, whether in a Luggin capillary or not, at the edge of the massive electrode and as close to the mineral as possible. This results in the reference electrode being closer to the resin-mineral interface than any other location. Therefore, the measured potentials are expected to be lower than if the interface did not exist; 3-dimensional surfaces require less activation energy than 2-dimensional surfaces. The most simple and proven effective method of removing the resin-mineral interface from the solution is masking it. To determine if an observable potential difference exists, OCP was run on the same chalcopyrite massive electrode masked and unmasked. Figure 51 shows the experimental results. Figure 51: OCP data for CuFeS2 massive electrode Origin B â B1 (characterization data: Table 5 â Table 17, Figure 20 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.294 cm2. Line âOCP â CuFeS2 â B1 â Maskedâ has resin-mineral interface masking and is average of three experiments. Line âOCP â CuFeS2 â B1â has no resin-mineral interface masking and is average of two experiments: âTest 1â, âTest 4â. Error bars are two-sided t-distribution 95% CI. 82 The masked electrode produced an OCP of 492 mV with a two-sided t-distribution 95% CI range of ± 5 mV. The unmasked electrode produced an OCP of 472 mV, 20 mV less than the masked, with a significantly larger error range. This error range is significantly larger than expected due to the lack of experiments that produced stable data. The two experiments âOCP â CuFeS2 â B1 â Test 1â and âOCP â CuFeS2 â B1 â Test 4â that were able to produce stable data are 31 mV apart. The three OCP measurements for the masked condition were taken in succession and then the four measurements for the unmasked. The masked measurements were taken first as theory suggests that the electrode will be less affected by the masked experiment, leaving it closer to its original, pre-experimented condition. This allowed for a more confident comparison to the unmasked, traditional electrode condition. The first unmasked condition experiment produced clean data. Unfortunately, the next two experiments produced noisy, unusable data and during the fourth, the potentiostat produced an error and stopped the experiment short at 396 sec (720 sec expected). Figure 52 displays the noisy data from âTest 2â and âTest 3â and how they affect the average and error calculations compared to Figure 51. The data displayed in Figure 52 should not be used for specific value analysis as there is clearly uncontrolled interference with the data. However, it does bring into question whether there was residual nail polish mask in âOCP â CuFeS2 â B1 â Test 1â as the masked surface area is 0.442 cm2 and unmasked is 1.294 cm2, leading to the expectation of a lower expected potential for the unmasked condition. âOCP â CuFeS2 â B1 â Test 4â provides the closest to expected results while the noisy data moves the OCP value lower, consistent with an even larger exposed area. The unmasked top surface is measured to be 1.294 cm2, but with the edges of the massive electrode being exposed in the resin-mineral interface, the surface area could be as much as 3.569 cm2. While I cannot completely rule out the possibility of active dissolution causing the noisy data, two experiments exist that produced the expected clean lines. Figure 52: NON-MASKED DATA SHOULD NOT BE USED WITH CONFIDENCE. OCP data for CuFeS2 massive electrode Origin B â B1 (characterization data: Table 5 â Table 17, Figure 20 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.294 â 3.569 cm2. âOCP â CuFeS2 â B1 â Maskedâ has resin-mineral interface masking and is average of three experiments. âOCP â CuFeS2 â B1â has no resin-mineral interface masking and is average of four experiments: âTest 1â, Test 2â, âTest 3â, and âTest 4â. Error bars are two-sided t-distribution 95% CI. 83 While the existence of noisy data from the unmasked experiments is easy to explain away as a symptom of working with minerals, it is more than that. While there were experiments that produced noisy, unusable data with masked electrodes, there was almost always a reasoned explanation as to why they occurred (see section 4.6 Mineral Massive Electrode Lifespan). At the time of running the experiments, the experimental field notes suggested that the only explanation was the sanding in-between experiments was not deep enough to get below the passivated edges. In response, I polished deeper than was required for the masked condition (approximately twice as long to remove the coloration change, see Figure 46 - Figure 49 and Table 21 for examples of starting and experimented surface coloration). When the following experiment also produced noisy data, I polished even deeper, seeing no other issues with the electrode or setup. This finally produced stable data, but then the potentiostat malfunctioned. The potentiostat did not display an error code for why it stopped the experiment, but it was a similar stopping experienced when an unexpected load is detected, which I assume was a short through the electrode. Polishing depth was able to get below mineral previously exposed to solution, but there is no way to confirm polishing is successful without destruction of the sample for SEM inspection. The experiences while running this line of experiments feel endemic to the current and historical expectations of mineral electrochemistry: you may get one good test, and if you do, it is difficult to produce a repeat experiment. As further confirmation of this idea, the first experiment in the unmasked condition provided data that was just within the lower range of the 95% CI of the masked condition. This confirms two theories. First, masking the resin-mineral interface of the electrode keeps the mineral close to its original, pre-experimental condition when properly polished, also proved by the range of the 95% CI of the masked condition. Second, it is possible to produce a single set of clean experimental data (with two important caveats) from a properly constructed massive electrode without a mask (i.e. very small to negligible resin-mineral interface). However, caveat one is there is a low probability that the data is reproducible from the same electrode due to unknown depth of solution penetration. Caveat two is that it is nearly impossible to confirm that the first data set was not an outlier as continued experimentation cannot confidently confirm or deny the quality of the data. This results from further experimentation requiring electrode polishing, which changes the condition of the resin-mineral interface. This data has shown the importance of masking the resin-mineral interface on massive electrodes when observing OCP. However, it is difficult to state the generalization that masking results in an increased observed potential as the error observed in unmasked data is large. A better conclusion is masking allows for reproducibility and improved confidence, even when only a few experiments exist. 4.3.4 Galvanostatic Polarization on Masked Massive Electrodes Based on the previous sectionâs results, masking the resin-mineral interface has a measurable effect on experimental results. OCP data concluded the effects are reproducibility and improved confidence. It also suggested the possibility of measurements having a higher potential than unmasked massive electrodes due to more accurate data collection. However, most mineral electrochemical cells are operated under polarization in an attempt to extract a specific mineral, not left to approach rest potentials. This leaves the question: how much does this interface affect polarization measurements? 84 The effects of the 3-dimensional surface can be shown through experimental polarization data. It suggests the crevice corrosion in the resin-mineral interface has a significant effect on the results. Figure 53 shows data for galvanostatic polarization with an applied current density of approximately 1 μA/cm2 on a chalcopyrite massive electrode. The black line likely indicates passivation of the 1.012 cm2 surface, assumed 2-dimensional, with resin-mineral interface exposed. The red line represents data from the same chalcopyrite massive electrode covered with a nail polish mask to a surface area of 0.442 cm2. This ensures the entire resin-mineral interface is effectively removed from participation in the experiment (see 4.3.2 Masking Effectiveness on a Massive Electrode). Figure 53: Galvanostatic polarization (GAL) applied at 0.5 μA (masked) and 1 μA (unmasked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. Both lines represent average of three experiments with two-sided t-distribution 95% CI error bars. The black and red lines appear to be converging on the same potential, but they take very different paths to it. The unmasked electrode line slope denotes three regions that are mirrored closely by changes in error size and are indicative of the differences between the masked and unmasked data. The three regions are approximately 0 â 36 min, 36 â 60 min, and 60 min and beyond. This is contrasted by only two distinct regions for the masked electrode, approximately 0 â 24 min and 24 min and beyond. In the first 3 min, any variation is well within a 95% CI, reaching a maximum difference of 2.4 mV with maximum errors of 7.7 mV unmasked and 13.0 mV masked, as shown in the subset. This suggests that the unmasked electrodeâs 2-dimensional surface mineral dissolution plays the dominant role until crevice corrosion starts to outpace it. By 36 min, the potential required to keep approximately 1 μA/cm2 passing through the masked and unmasked electrodes reaches a maximum difference of 100.4 mV. This large difference in potentials most likely results from crevice corrosion sustaining its outpacing of mineral dissolution. This is significant as most chalcopyrite electrochemistry is performed at approximately 1 μA/cm2, and typically within the first 10 minutes of immersion, which is shown here to result in measurement differences of up to 34 mV. 85 Due to the nature of crevice corrosion, the size of the crevice plays a larger role in the dissolution rate than the material. Therefore, it should be expected that reproducibility is possible since the crevice size should be reasonably consistent between multiple consecutive experiments on the same massive electrode. Based on the investigation in section 4.3.1 Massive Electrode Construction and that the unmasked massive electrodes used for experimentation were constructed using the recommended techniques laid out in section 5.3 Recommended Techniques for Reproducible Data in Mineral Electrochemistry (excluding masking) it can be reasonably stated that the crevice volume will be within the range of up to approximately 6 μm wide (larger when poorly constructed), 5 mm deep (max being thickness of mineral), and up to a few centimeters long (max being perimeter of mineral). As long as the solution does not completely penetrate the resin-mineral interface and short to the wire attached to the back of the mineral, the massive electrode can be used for further experimentation. Unfortunately, crevice penetration depth for a given experiment remains unknown. The extent of solution penetration is currently difficult to prove as checking would involve dismantling the massive electrode. Extraction of the mineral from the resin was attempted, but resulted in damaging the mineral surfaces of interest. Figure 54 shows mechanical extraction resulting in fracturing of the mineral where it is well bonded to the resin. Other methods were considered, such as soaking the electrode for extended periods of time (hours to days) in a liquid solvent to soften the resin. Solvents capable of softening or dissolving resin, especially polar organic solvents such as acetone, or vinegar and alcohol can affect the surface of the chalcopyrite. This was a reason why DI water sonication was used promptly post acetone removal of the nail polish mask between experiments. Another option was heating; however the System Three Cold Cureâ¢ two part epoxy heat deflection temperature is 127°F/52.8°C. Sustained heating of the chalcopyrite to heat the resin to the proper temperature can result in expansion fracturing due to its brittle nature. There is similarly no way to physically confirm that there was minimal crevice size variation between experiments. Carbon deposition is required to observe chalcopyrite via SEM, which would need to be polished off prior to experimentation, changing the size of the resin-mineral interface. SEM was chosen as a result of being the only microscopy method I had access to that could produce required resolution. However, due to the high reproducibility of the electrochemical measurements, it is reasonable to assume that any variations in size or depth of penetration are small enough to consider negligible until the crevice becomes large enough that mineral dissolution outpaces crevice corrosion. This transition from crevice corrosion to mineral dissolution dominance will result in increased variability observed between experiments. 86 Figure 54: Chalcopyrite massive electrode hand sawed to extract mineral from resin. Resin maintains enough bonds to the chalcopyrite surface resulting in fracturing of the mineral surface from bulk when separation is attempted. Transition from crevice corrosion to mineral dissolution can be seen from approximately 36 â 60 min. This region for the unmasked electrode has increased slope matched with increased error, approximately 18.9 â 74.2 mV, while the masked has reduced slope and decreased error, approximately 20.7 â 30.0 mV. This provides further confidence that mineral dissolution is increasingly outpacing crevice corrosion for the unmasked sample. The first 24 min of the masked line are known to be representative of the initial mineral dissolution, which cannot occur in the unmasked until the crevice corrosion rate is slowed enough to allow mineral dissolution dominance. The transition from initial mineral dissolution to a quasi-steady rate of mineral dissolution, identified as chalcopyriteâs transpassive region, displays the largest errors for the masked electrode, rising in the first 24 min to a max of 40.6 mV then decreasing. This elevated variability is seen in both masking conditions during mineral dissolution transitions. A small portion results from the unique fresh surface of a mineral massive electrode (see section 4.4 Effects of Mineral Origin â Figure 13, Figure 63, Figure 65) as the transition rate will vary slightly based on composition. The unmasked electrode will be more affected by this as its dominating dissolution method is changing. The reduction in variability after this time region supports this claim. The unmasked line displays the same slope trend as the masked line once mineral dissolution is dominant. It is delayed by about 45 min and with less initial slope. This less steep slope may result from a lower current density produced by a larger exposed surface area from the remaining unpassivated crevice of the unmasked condition. Since there is currently no proven method for measuring crevice volume and exposed mineral area in the crevice for each experiment, an expected range is required. Crevice volume was stated previously to be within the range of up to approximately 6 μm wide, 5 mm (max depth being thickness of mineral), and max length being perimeter of mineral. The multiplication of the latter two would provide the maximum range of variability of the exposed mineral area, the minimum being the top exposed surface, assumed 2-dimensional. This would make the unmasked exposed area range from 1.012 â 3.024 cm2 and current density range to be 0.99 â 0.33 μA/cm2 for galvanic polarization at 1 μA. Based on this, it is more appropriate to present unmasked data as representing a current density range and compare it to masked data at the maximum and minimum of said range, as shown in Figure 55. 87 Figure 55: Galvanostatic polarization (GAL) applied at 0.1, 0.3, and 0.5 μA (masked) and 1 μA (masked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. All lines represent average of three experiments with two-sided t-distribution 95% CI error bars. Comparing masked data at the limits of the range of current densities for the unmasked electrode confirms that the crevice results in a change of exposed surface area, reducing the effective current density. The dissolution is clearly dominated by the fresh surface initially, which is overtaken by the crevice and, as the crevice fills with corrosion product, it closes itself off from fresh solution, as diagramed in Figure 44. Based on this, the exposed area decreases towards its minimum until all that remains exposed is the top surface, increasing the current density in the process. If taking data before approximately 36 min, the data reflects the largest exposed surface area while data after 60 min reflects the minimum. The surface area between 36 and 60 min is ever changing and becomes increasingly less dependent on exposed crevice surface area and more on the mineral composition of the top surface. The error (95% CI) increased to its maximum for the unmasked in this region as a result of the varying rate of change in crevice size between experiments and the mineral dissolution rate based on composition of the top exposed surface. The final region from approximately 60 min and beyond shows convergence of the unmasked with the masked line. Mineral dissolution is dominant but slowing in both masking conditions as they pass through their transpassive regions, approaching their repassivation, or protection, potential asymptotically. This results in decreased observed error as this value is inherent to the bulk material and less dependent on the initial exposed surface. From this definition and observing the data in Figure 56 showing a range of current densities for both masked and unmasked conditions for the same electrode, the repassivation potential for CuFeS2 Origin A - A1 massive electrode is approximately 895 mV. It is expected, and displayed in Figure 56, that as the applied current density increases, the difference between the masked and unmasked conditions will decrease as the transition away from crevice dominated dissolution occurs more quickly, occurring in the first minute at 100 μA/cm2 (Figure 57). 88 The 1 μA/cm2 experiments (Figure 55) show separation in the 515 â 700 mV range and slowly converge while increasing in value. The 100 μA/cm2 data (Figure 57) show separation in the 680 â 920 mV range and drifts downwards to a stable value of approximately 895 mV. This suggests crevice corrosion plays a larger role in mineral dissolution below approximately 700 mV while bulk mineral dissolution starts to overtake the rate of crevice corrosion, becoming dominant above approximately 800 mV. The rate at which mineral dissolution matches that of crevice corrosion is then sped up by increased currents. Figure 56: Galvanostatic polarization (GAL) applied at 0.1, 0.5, 1, 10, and 100 μA (masked) and 1, 10, and 100 μA (unmasked) data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2, without = 1.012 â 3.024 cm2. Masked lines represent average of three experiments, unmasked lines represent average of four experiments, except 0.99â0.33 μA/cm2 represents three. All lines with two-sided t-distribution 95% CI error bars. Figure 57: Isolated display of data from Figure 56 for GAL applied at 100 μA for CuFeS2 massive electrode Origin A â A1 masked (SA = 0.442 cm2) and unmasked (SA = 1.012 â 3.024 cm2). All lines with two-sided t-distribution 95% CI error bars. 89 4.3.4.1 Anodic Polarization Curves from Galvanostatic Polarization The data from Figure 56 can be used to start building anodic polarization curves for masked and unmasked conditions. However, a decision needs to be made for which length of time is selected for data compilation. Based on the above analysis of Figure 55 â Figure 57, three times appear to be significant. The first is 10 min since most chalcopyrite electrochemistry is performed in the first 10 min after submersion. The second is 1 hour as it was identified as the region mineral dissolution was dominant in both masked and unmasked experiments and allows for better comparison to existing work. The third is 2 hours based on that being the edge of data collected and that the data for masked and unmasked at various induced currents converged on the same potentials by this time. A comparison of anodic polarization curves built step-wise from galvanostatic polarization data at these three times is shown in Figure 58 for masked and unmasked conditions. There is strong agreement between the three times and both masking conditions above current density 10-4.65 A/cm2. This current appears to be a pivot point for the data of the graph. Below 10-4.65 A/cm2 the observed potential increases with longer exposure while above the potential decreases, though not as significantly. This trend is roughly followed by the unmasked when compared to masked data. The unmasked condition appears to over approximate the potential between 10-5.65 and 10-4.65 A/cm2 and under approximate the potential below 10-5.65 A/cm2. If exposed long enough, the potential at all induced currents would asymptotically approach the same potential; so selecting a time to stop the experiment should be based on the intent of data usage. Exposing to 2 hours and collecting that data does not provide actionable data when trying to understand the first 10 min, and vice versa. If trying to understand general data, then expose for as long as reasonable and produce the range of data as shown in Figure 58. If comparing to specific data, more finesse may be required to ensure appropriate comparisons. Figure 58: Galvanostatic polarization (GAL) data at 10 min, 1 hour, and 2 hours for 0.1, 0.3, 0.5, 1, 10, and 100 μA and 1 mA for step-wise building of anodic polarization curves. Data for CuFeS2 massive electrodes Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2, unmasked = 1.012 â 3.024 cm2. Masked data represent average of three experiments, except 10 and 100 μA average of four. Unmasked data represent average of four experiments, except 1 μA represents three. All data with two-sided t-distribution 95% CI error bars. 90 At time of writing, Viramontes et al. (2007) was the only work I found that used some form of static polarization to build anodic polarization curves. However, there are important differences that must be stated before attempting comparison to Figure 58. The first is I use masking on my massive electrodes while they did not. While I did obtain unmasked data to compare to masking, I do not trust the unmasked data as a true representation of massive mineral electrode polarization, as discussed above. The second is they used potentiostatic polarization (set potentials to measure current) while I used galvanostatic polarization (set currents to measure potential). When performing multiple experiments on the same massive electrode, the rate of passivation is changed by the mineral polishing; polishing always produces a new surface composition. The resistance can also be changed by the reduction in thickness from polishing and removal of certain compositions. There are even semi-conductor considerations that can result in a change in resistance (Ren et al., 2022a). When comparing the average of multiple experiments of both potentiostatic and galvanostatic polarization on the same electrode in succession, the changes in resistance should be comparable and produce the same effects on both results. A comparison of this is shown in Figure 59. This work does not have sufficient data to make specific conclusions on why the differences are observed, but the resistance term is the only changing variable. Viramontes et al. (2007) performed measurements on resistance through impedance spectroscopy and found âRsolution + Rchalcopyrite were 5.1 Ω at 25°C and 2 g/L of H2SO4â and any applied correction by Equation 30 for resistance proved within experimental error based on observation of their provided graphical data. %;4K.i = %44 â (0i$ + (;4K.i [Equation 30] Figure 59 data suggest that potentiostatic polarization produces larger variability than galvanostatic polarization, especially at higher currents and potentials. It also suggests applying a changing current effects chalcopyrite passivation differently than a constant current. For a multitude of reasons, industry typically performs recovery at constant current. Therefore, galvanostatic polarization data may provide more actionable insight into massive electrode electrochemistry than potentiostatic, potentiodynamic, or galvanodynamic polarization. The data also suggest that galvanostatic and potentiostatic data present two different depictions of reproducibility due to resistance. However, the trends they present are comparable. They agree that chalcopyrite moves from active dissolution to passivation quickly and enters a transpassive region. 91 Figure 59: Galvanostatic polarization (GAL) data at 1 hour for 0.1, 0.3, 0.5, 1, 3, 5, and 10 μA for step-wise building of anodic polarization curves. Potentiostatic polarization (POT) data at 1 hour; E based on average potential value produced from GAL at 1 hour. Data for CuFeS2 massive electrodes Origin B â B3 (characterization data in Table 5 â Table 17, Figure 24 â Figure 25) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2. Data represent average of three experiments. All data with two-sided t-distribution 95% CI error bars. A third important difference is in Viramontes et al. (2007) the massive electrode is only polished once at the beginning of the experiment and not after each potentiostatic hold, also remaining in the same electrolyte solution. Their experimental method is therefore step-wise approximating potentiodynamic polarization through 1 hour holds at specific potentials (increments of 20 mV from Ecorr + 30 mV < E < 400 mV and 600 mV < E â¤ Etraspassive and increments of 10 mV from 400 mV < E < 600 mV). I will refer to their method as step-wise potentiodynamic (swPOTD) polarization. This method provides data resolution by allowing uniform time at each potential that cannot be captured in the rate of potential sweeping in potentiodynamic polarization. Their method assumes that recovery methods sweep through a range of potentials, low to high, and that an extended residence time at a given potential is representative of a mineralâs exposure, allowing for increased passivation at each step. But as mentioned previously, leaching typically occurs at a set current (1 â 10 μA/cm2) and typically for approximately 10 min, only experiencing a limited range of potentials that immediately interact with a fresh mineral surface, not a polarized and therefore passivated mineral surface. This means their method does not remove the history of passivation from the potentials the electrode was previously exposed to. That history is âbaked inâ to future measurements in this method and therefore cannot provide accurate data representing a polished, fresh electrode under the same potentiostatic conditions. A pre-passivated mineral is not representative of the fresh mineral present in a new leaching operation. Therefore, my method is more conservative in nature, but it is also more representative. Two more notable differences are the experiments were âconducted under maximum magnetic agitation in 700 mL electrochemical cellâ (Viramontes et al., 2007) and the massive electrode was polished to 600 grit carbide paper. See section 4.5.1 Effects of Solution Stirring for understanding data 92 acquisition under stirring versus no stirring as this work was performed in stagnant conditions. This work polished to 1200 grit carbide paper, rather than 600 grit. This can affect the reactiveness of the initial surface, lower grits being more reactive as they provide more initiation sites for corrosive behavior. With all of these differences stated, I can make an informed comparison in Figure 60 of masked electrode data from Figure 58 overlaid on a reproduced Figure 4a from Viramontes et al. (2007). Figure 60: Comparison of three exposure times for CuFeS2 masked electrode galvanostatic polarization (GAL) data from Figure 58 overlaid on 1 hour step-wise potentiodynamic (swPOTD) polarization in 2 g/L H2SO4 at 25°C reproduced from Figure 4a in Viramontes et al. (2007). The 10 min galvanostatic polarization data below 1.13 μA/cm2 presents slopes similar to the active regions of swPOTD, but are shifted left by approximately 10 μA/cm2 and down approximately 100 mV. Above 22.60 μA/cm2 the data provides similar conclusions as both 1 and 2 hour data. Since the 2 hour data is not captured below 2.26 μA/cm2, it also provides similar conclusions as the 1 hour data. Therefore, the galvanostatic polarization potentials at 1 hour provide the most comparable data to the 25°C data from Viramontes et al. (2007), especially as both collected data after 1 hour of exposure. Between 20 and 200 μA/cm2 galvanostatic data compares well with the slope of swPOTD data, being approximately 30 mV separated. The data also follows the trends seen in Figure 55 â Figure 57 where unmasked data presents a lower value than masked. Above 200 μA/cm2 the slopes differ as the galvanostatic potential raises approximately 75 mV to 2260 μA/cm2 while swPOTD at 25°C raised by < 1 mV. Only elevated temperatures under swPOTD polarization see a positive slope at higher current densities, 80°C showing the most similarity. Below 20 μA/cm2 there is significant separation between galvanostatic and swPOTD, where galvanostatic does not show the active to passive transition, appearing to move from active dissolution to passivation quickly and enters a transpassive region. This trend is also seen in Figure 59; however, it shows it for both galvanostatic and potentiostatic. The data separation is made greater as Viramontes et al. (2007) does not present a current density lower than 8.00 μA/cm2 while galvanostatic polarization was performed as low as 0.23 μA/cm2. This separation is best explained by the âbaked inâ history that results from not polishing between data observations. 93 4.4 Effects of Mineral Origin Variability, the lack of reproducibility, and novel results in mineral electrochemistry have long been described away by the idea that âyou get what you get.â Itâs an easy concept to accept as everyone who has interacted with minerals has never found two to be exactly the same. This simple conclusion allows variability to be the defining feature of minerals and becomes the default answer to all questions otherwise unanswered and the root cause for the lack of reproducibility and novel results. The previous section has made it clear that variability does not define reproducibility as it is possible to reduce variability through masking massive electrodes. The previous section also displays a new perspective on anodic polarization curves, which have previously been built almost exclusively from single experiment dynamic polarization. The data for both of these reduces the reach of the variability claim. However, while this data provides new insights, it still leaves open the possibility to conclude that using a different chalcopyrite origin is still a major contributing factor for presented results. If this is true, by how much does mineral origin contribute to variability, the lack of reproducibility, and/or novel results? A small, but vital distinction needs to be repeated from 3.1 Electrode Materials regarding mineral origin. The actual location of origin for the mineral matters little to none unless research is being conducted for processes using that exact mineral source. It is more important that a characterization of the bulk mineral source be conducted alongside characterization of the specific samples being used to perform experimentation (i.e. the surface of a massive electrode). The composition and quantities thereof are what result in data variation, not where it was acquired from. Naming minerals by their location of acquisition assists in tracking the information through a publication, but it does not give license to someone using the same mineral source not to perform independent investigation. The lack of reproducibility for a single massive electrode was largely covered throughout 4.3 Effects of Resin-Mineral Interface with experimental data in 4.3.3 Open Circuit Potential on Masked Massive Electrodes and 4.3.4 Galvanostatic Polarization on Masked Massive Electrodes. In short, reproducibility is possible and presented; however, variability is still present resulting from a fresh surface for each experiment. For galvanostatic polarization, the higher the applied current density the more reproducible the data becomes, making variability a smaller factor. The following sections seek to provide numerical expectations for how a mineral origin may affect a massive electrodeâs experimental data. 4.4.1 Open Circuit Potential While reviewing literature for OCP values to present in Table 2 from 2.4 Mineral Variability in Literature, it became clear there was no experimentally validated and accepted value for chalcopyrite OCP. Mineral variability, process difference, and agreement on when to consider an OCP measurement stable appear to be the restricting factors. Tanne & Schippers (2021) reported a 145 mV range (406 â 551 mV vs. SHE) in literature then produced data making the range 355 mV (285 â 640 mV vs. SHE). The present work determined literature presents a 365 mV range (285 â 650 mV SHE), although I consider the lower limit value to be an outlier and consider literature to agree on a 244 mV range (406 â 650 mV vs. SHE). This is shown in Figure 61 in comparison to data produced by this workâs 26 OCP experiments presenting a 64.1 mV range (474.1 â 538.2 mV vs. SHE) across three chalcopyrite origins and seven massive electrodes of purity â¥ 68% (Table 9, Table 10 from 3.1.2.2 EDS Characterization Data). Figure 62 shows average OCP data for the three origins (A, B, C) from Figure 41 in 4.2 Open Circuit Potential with the addition of their 94 average. This provides the range of expected CuFeS2 OCP to be 491.9 ± 9.7 mV (482.2 â 501.6 mV) for origin purity â¥ 83% (Table 13 and Table 15 from 3.1.4 Inductively Coupled Plasma â Optical Emission Spectroscopy (ICP-OES) of Chalcopyrite Origins and 3.1.5 Comparison of Characterization Methods, respectively). Therefore, mineral origin purity â¥ 83% can have an approximately 20 mV effect on CuFeS2 OCP. While this value may be useful in particle applications (e.g. leaching), this value is difficult to make practical use of when experimenting with massive electrodes. A more useful metric would be for individual massive electrodes of different origins. A mineral massive electrode from a different origin with purity â¥ 68% can have an approximately 64 mV effect on CuFeS2 OCP. The lower the purity, the higher the probability mineral origin will effect OCP measurement. However, this does not exclude high purity samples from larger errors as shown by electrode Origin A â A1 at 99% purity (Table 9, Table 10 from 3.1.2.2 EDS Characterization Data) with an approximately 22 mV range. This can occur when the impurities are not consistently spread throughout the electrode, but appear in pockets that get exposed from polishing for one or more experiments. This is also a leading reason behind the variability seen within a particular origin, paired with the fact that any particular massive electrode only samples a small portion of the origin. Table 20 in 4.2 Open Circuit Potential shows all originsâ average OCP with two-sided t-distribution 95% CI showing approximate ranges: Origin A â 22 mV, Origin B â 20 mV, Origin C â 14 mV. Figure 61: Reproduction of Figure 42 from 4.2 Open Circuit Potential showing a box and whisker diagram of OCP data for three CuFeS2 origins compared to literature with the addition of three red lines. Solid red: average OCP of Origin A, B, and C (from 7 massive electrodes and 26 experiments in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper). Dotted red: two-sided t-distribution 95% CI error bars (491.9 ± 9.7 mV SHE). 95 Figure 62: Reproduction of Figure 41 from 4.2 Open Circuit Potential showing OCP data for three CuFeS2 origins with addition of the three originsâ average (7 massive electrodes, 26 experiments in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper). All data with two-sided t-distribution 95% CI error bars. 4.4.2 Galvanostatic Polarization Mineral origin has been experimentally accepted as the main source for variability in mineral electrochemistry since Warren et al. (1982). Figure 13 (reproduced from section 2.4 Mineral Variability in Literature) is a reproduction of their figure showing six different chalcopyrite originsâ anodic polarization curves presenting approximately 110 mV (approximately 510 â 620 mV vs. SHE) difference in observed potential. They stated the following conclusions from this figure (Warren et al., 1982): Anodic polarization curves for various sources of natural mineral show significant differences, particularly in the value of the passive current which may vary by up to two orders of magnitude. These differences may arise due to slight differences in stoichiometry, but are more likely due to the presence of impurities. At high potentials all samples showed similar behavior. Mineral origin variability is confirmed in the present work across three chalcopyrite origins under galvanostatic polarization in Figure 63 and Table 22. The observed potential in the first second of exposure ranges approximately 43 mV (approximately 465 â 508 mV vs. SHE), growing to approximately 242 mV (approximately 560 â 802 mV vs. SHE) at 1 h. Between Warren et al. (1982) and this work chalcopyrite origin has been shown to result in a nearly 155 mV (approximately 465 â 620 mV vs. SHE) range in observed potential at a current density of 2.26 μA/cm2 (10-5.65 A/cm2) at first exposure. While I observed half the quantity of origins as Warren et al. (1982), my data presented over 2.5 times reduction in origin potential variability at first exposure. The present work agrees with the above statement from Warren et al. (1982) regarding variability source; however, I do not agree with its blanket use as cover for everything in mineral electrochemistry. Warren et al. (1982) did not perform multiple experiments for each electrode and did not use resin-mineral interface masking. While this work remains pivotal to mineral electrochemistry, it does not produce a complete picture. The data 96 remains suggestive of variability and potential trends, but actual data values may be outliers. Therefore, mineral origin of purity â¥ 83% can result in 2.26 μA/cm2 polarization data to range approximately 43 mV at first exposure and approximately 242 mV after an hour. Figure 13: Reproduction of "Anodic polarization curves for CuFeS2 from 6 different locations in 1M H2SO4, 30mV/min, 20 °C" (Warren et al., 1982) with addition of red lines denoting data variation Figure 63: Galvanostatic polarization (GAL) applied at 1 μA data for three CuFeS2 originsâ massive electrodes with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Origin characterization data: Table 5 - Table 17, Figure 17 â Figure 31. Surface area with mask = 0.442 cm2. All lines are average of multiple experiments with two-sided t-distribution 95% CI error bars (origin â number of electrodes â number of experiments): A â 1 â 3, B â 3 â 10, C â 2 â 6. 97 Table 22: Differences of 2.26, 22.62, and 226.24 μA/cm2 galvanostatic polarization (GAL) data for three CuFeS2 origins from Figure 63 and Figure 64 at various exposure times. Negative values represent first listed origin having the lower potential. GAL CuFeS2 Origins mV @ Exposure Time μA/cm2 0.1 s 60 s 600 s 3600 s 2.26 A vs. B 43.2 60.5 141.5 201.7 A vs. C 19.8 52.9 152.5 242.4 C vs. B 23.4 7.6 -11.0 -40.7 22.62 A vs. B -2.5 54.8 37.2 21.0 A vs. C -33.4 75.9 92.2 17.2 C vs. B 30.9 -21.1 -55.0 3.8 226.24 A vs. B 100.4 -11.4 -3.6 -11.2 As alluded to in the introduction of this section and by the Warren et al. (1982) quote, the expected performance of minerals changes with elevated potentials. This has been presented by potentiostatic polarization and anodic polarization curves built from 30 mV/min potentiodynamic polarization (Warren et al., 1982) as well as by 4 â 100 mV/s linear sweep voltammetry, cyclic voltammetry, and potentiostatic electrolysis (Biegler & Swift, 1979). My masked galvanostatic polarization data in Figure 56 â Figure 60 from 4.3.4 Galvanostatic Polarization on Masked Massive Electrodes provide support for this statement with regards to a single massive electrode. Figure 64 and Table 22 confirm this trend across three chalcopyrite origins. These trends can also be found within the same origin. Figure 65, Figure 66, and Table 23 show the decreasing separation between different electrodes constructed from Origin B as applied current density rises. Figure 64: Galvanostatic polarization (GAL) applied at 10 and 100 μA data for three CuFeS2 originsâ massive electrodes with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Origin characterization data: Table 5 - Table 17, Figure 17 â Figure 31. Surface area with mask = 0.442 cm2. All lines are average of multiple experiments with two-sided t-distribution 95% CI error bars. (Origin â number of electrodes â number of experiments): 22.62 μA/cm2 = A â 1 â 3, B â 3 â 10, C â 1 â 3 | 226.24 μA/cm2 = A â 1 â 3, B â 1 â 2. 98 Figure 65: Galvanostatic polarization (GAL) applied at 1 μA data for three CuFeS2 Origin B massive electrodes (characterization data: Table 5 - Table 17, Figure 20 â Figure 25) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. All data represent average of three experiments, except B2 average of four. All data with two-sided t-distribution 95% CI error bars. Figure 66: Galvanostatic polarization (GAL) applied at 10 and 100 μA data for three CuFeS2 Origin B massive electrodes (characterization data: Table 5 - Table 17, Figure 20 â Figure 25) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. All data represent average of three experiments, except B1 @ 226.24 μA/cm2 average of two and B2 average of four. All data with two-sided t-distribution 95% CI error bars. 99 Table 23: Differences of 2.26 and 22.62 μA/cm2 galvanostatic polarization (GAL) data for three CuFeS2 origins from Figure 65 and Figure 66 at various exposure times. Negative values represent first listed origin having the lower potential. GAL CuFeS2 Electrode mV @ Exposure Time μA/cm2 0.1 s 60 s 600 s 3600 s 2.26 B1 vs. B2 -105.0 -91.4 -116.7 -170.3 B1 vs. B3 -45.9 -49.6 -102.6 -247.4 B3 vs. B2 -59.1 -41.8 -14.1 77.1 22.62 B1 vs. B2 -109.1 -50.2 -79.5 -65.8 B1 vs. B3 -75.8 -43.1 -123.3 -95.4 B3 vs. B2 -33.4 -7.0 43.8 29.5 This data can be used to construct anodic polarization curves as was done for Figure 58 in 4.3.4.1 Anodic Polarization Curves from Galvanostatic Polarization. Figure 67 shows how mineral origin affects step-wise built anodic polarization curves for two chalcopyrite mineral originsâ massive electrodes in masked and unmasked conditions. These curves provide support for convergence of masked and unmasked electrodes as well as electrodes from different origins above a current density of approximately 10-4.25 A/cm2. The separation grows larger as the current density decreases. Figure 67: Galvanostatic polarization (GAL) data at 1 hour for 0.1, 0.3, 0.5, 1, 10, and 100 μA and 1 mA for step-wise building of anodic polarization curves from CuFeS2 massive electrodes Origin A â A1 and Origin B â B1 (characterization data in Table 5 â Table 17, Figure 18 â Figure 21) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area masked = 0.442 cm2; A1 unmasked = 1. 012 â 3.024 cm2; B1 unmasked = 1.294 â 3.569 cm2. Masked data represent average of three experiments, except 10 and 100 μA average of four and B1 at 1 mA average of two. A1 unmasked data represent average of four experiments, except 1 μA represents three. B1 unmasked represent average of three experiments, except 100 μA is one. All data with two-sided t-distribution 95% CI error bars. 100 The masked data can then be used to rebuild the step-wise anodic polarization curves from Figure 60 to compare massive electrodes from different origins in Figure 68 with data from Viramontes et al. (2007). The analysis from 4.3.4.1 Anodic Polarization Curves from Galvanostatic Polarization holds true across different mineral origins. The best explanation for deviations seen between step-wise potentiodynamic polarization and step-wise building from galvanostatic polarization data remains to be that Viramontes et al. (2007) âbaked inâ polarization history as a result of not polishing between observations. The importance of mineral characterization to understand experimental data is highlighted by Origin B â B3 producing data more similar to Origin A â A1 than to Origin B â B1. These same curves are shown in Figure 69 overlaid onto the Warren et al. (1982) anodic polarization curves from Figure 13. The present workâs data corroborates the statements made by Warren et al. (1982) regarding potential and current density variation. My data does not present the passive region shown by Warren et al. (1982); however, the 30 mV/min fast sweep they performed does not accurately represent leaching timescales. They present the effects of scan rate showing data for 6, 30, and 60 mV/min where 6 mV/min produces current densities approximately 100.5 A/cm2 lower than 30 mV/min. They also presented data showing the effect of pH using 1, 0.1, and 0.01 M H2SO4. The 0.01 M data presented up to a 200 mV decrease in potential above approximately 10-5.0 A/cm2 compared to 1 M. Viramontes et al. (2007) saw similar reactions with 2, 30, and 100 g/L H2SO4 showing over 100 mV separation. If both the scan rate and concentration of Warren et al. (1982) data was reduced, they may present data very similar to the present work. However, potentiodynamic polarization also âbakes inâ polarization history as a new surface is not provided when raising potential, showing passive transition. Figure 68: Comparison of two originsâ three CuFeS2 masked massive electrodesâ galvanostatic polarization (GAL) data using the compilation method from Figure 58 overlaid on 1 hour step-wise potentiodynamic (swPOTD) polarization in 2 g/L H2SO4 at 25°C reproduced from Figure 4a in (Viramontes et al., 2007). 101 Figure 69: Comparison of two originsâ three CuFeS2 masked massive electrodesâ galvanostatic polarization (GAL) data using the compilation method from Figure 58 overlaid on a reproduction of âAnodic polarization curves for CuFeS2 from 6 different locations in 1 M H2SO4, 30 mV/min, 25°Câ (Warren et al., 1982). 4.5 Effects of Solution Agitation Agitated solutions are used throughout electrochemistry to ensure fresh solution is always being supplied to the experimental surface/interface. While this is common practice, not all literature uses agitation or reports it the same when used. It is important to understand how agitation affects the results of experimental data to allow for data comparison. The two most common laboratory techniques for agitation are controlled mixing with a magnetic stir bar and sparging (a.k.a. de-aeration, bubbling, gassing, purging, deoxygenating). Sparging is performed by passing inert gas (nitrogen or argon), air, or oxygen through solution to remove or control oxygen content, resulting in agitation. These two methods can also be combined. A third method is spinning the massive electrode (a.k.a. rotating disk electrode), which can also be used in combination with the other methods. This is a less common method and results in other experimental surface/interface interactions not covered in this work. I am not the first to mention that reporting on agitation methods is varied (Kimball et al., 2010; Li et al., 2013). Many works report the stirring speed with a magnetic stirrer in rotations per minute (rpm) (Barton & Hiskey, 2022a; Córdoba et al., 2009; Falagán et al., 2017; Ghahremaninezhad et al., 2012; Han et al., 2018; Hirato et al., 1987; Kaplun et al., 2011; J. Li et al., 2010; Yubiao Li et al., 2017; Linge, 1976; Majima et al., 1985; Olvera et al., 2014; Qian et al., 2014; Ren et al., 2022a; Ren et al., 2022b; Velásquez-Yévenes et al., 2010) or per second (s-1) (Mehta & Murr, 1983). Others either simply state the solution was agitated/stirred (Kametani & Aoki, 1985; Tanne & Schippers, 2021; Warren et al., 1985; Warren et al., 1982; Watling, 2013) or qualify the stirring (e.g. maximum magnetic agitation, vigorous magnetic agitation, vigorous stirring, less vigorous stirring, slower stirring, rapid stirring) (Kimball et al., 2010; Saavedra et al., 2018; Viramontes-Gamboa et al., 2006; Viramontes et al., 2007; Warren et al., 1985). 102 When sparging, the type of gas is usually all that is reported (Chmielewski & Kaleta, 2011; Frangini & De Cristofaro, 2003; Ghahremaninezhad et al., 2012; Ghahremaninezhad et al., 2013; Ghahremaninezhad et al., 2015; Nicol, 2022; Nicol et al., 2017; Olvera et al., 2014, 2016; Stockert et al., 1985; Viramontes-Gamboa et al., 2010, 2006; Viramontes et al., 2007; Warren et al., 1985; Watling, 2013; Yue & Asselin, 2014); although, a few state flow rate (Falagán et al., 2017) or dissolved oxygen concentration (Velásquez-Yévenes et al., 2010). If sparging was performed prior to the experiment, some do state the length of time (Eghbali et al., 2011; Frangini & De Cristofaro, 2003; Nicol et al., 2017; Olvera et al., 2014, 2016; Stockert et al., 1985; Yue & Asselin, 2014); however, others do not (Chmielewski & Kaleta, 2011; Viramontes-Gamboa et al., 2010, 2006; Viramontes et al., 2007; Warren et al., 1985). The works referenced here are not an exhaustive list, rather a representation of the trends of agitation reporting. The information detailing experimental setups is vital to accurate accounts of data acquisition, allowing for reproducible data and third party analysis. Educational guesses should not be required to recreate a workâs experimental setup. The minutia of these details will affect results, albeit to a much lesser extent than whether agitation was used or not. The intent of this section is to present general agitation effects leading to expected trends and how they would affect any data presented or referenced by this work. 4.5.1 Effects of Solution Stirring Stirring was performed for 10 min prior to polarization and continued through polarization by a 12.7 mm long, 8 mm diameter Fisherbrandâ¢ Octagon Spinbarâ¢ magnetic stirring bar (catalog #14-513-58) with a rotations per minute (rpm) controller accurate to 1 rpm. The working electrode was only placed in solution immediately prior to polarization. This stir bar was selected based on being the largest that freely spun in my experimental setup. The peripheral tip speed is calculated in Table 24 for the range of common stirring rpm reported throughout literature for various length stir bars commonly used. 0.33 m/s (12.7 mm @ 250 rpm) was selected for experimentation to represent low speed (less vigorous, slower) stirring due to my stir barâs peripheral tip speed being comparable to longer stir bars at 100 rpm (lowest rpm I found reported in literature). 1.00 m/s (12.7 mm @ 750 rpm) was selected for experimentation to represent high speed (maximum magnetic agitation, vigorous magnetic agitation, vigorous) stirring due to any higher rpm producing a vortex above the stir bar and cavitation in my experimental setup (1002 rpm was the highest rpm I found reported in literature). I have no way to confirm that vortexes are not produced in literature while high speed stirring; however, due to my experimental setup not including baffles to introduce turbulence, I avoided the production of a vortex. 103 Table 24: Peripheral tip speed calculations for various industry standard magnetic stir bars and commonly reported rpm [Peripheral Tip Speed = (rpm / 60 s) * circumference of stirring path = (rpm / 60 s) * 2 * Ï * (stir bar length in meters)] Fisherbrandâ¢ Octagon Spinbarâ¢ Diameter Length Peripheral Tip Speed (m/s) Catalog # mm mm 100 rpm 250 rpm 500 rpm 750 rpm 1000 rpm 14-513-58 8.0 12.7 0.13 0.33 0.66 1.00 1.33 14-513-62 8.0 15.9 0.17 0.42 0.83 1.25 1.67 14-513-59 8.0 25.4 0.27 0.66 1.33 1.99 2.66 14-513-60 8.0 38.1 0.40 1.00 1.99 2.99 3.99 14-513-61 8.0 50.8 0.53 1.33 2.66 3.99 5.32 While reporting rpm is convenient, peripheral tip speed presents a more accurate account of solution movement under stirring. The peripheral tip speed is linearly proportional to the length of the stir bar (i.e. if length is doubled, peripheral tip speed doubles for the same rpm). Therefore, if choosing to report with rpm, it is essential to also report the length of stir bar. If choosing to report with peripheral tip speed, it is not essential. However, for completeness in both cases, it is suggested the model used be reported as depending on the experimental setup, the diameter, thickness, and shape may result in more effective stirring. 4.5.1.1 Open Circuit Potential Open circuit potential is considered a fundamental measurement of a mineral. However, the conditions under which OCP is measured will affect the reported value. The literature data collected for Table 2 in 2.4 Mineral Variability in Literature suggests the majority of reported OCP measurements occur in stagnant solution, showing only one experiment that used magnetic stirring and another that used electrode spinning. Due to the limited use of electrode spinning throughout mineral electrochemistry and the nature of my experimental setup, magnetic stirring is the only method explored here. OCP data for CuFeS2 massive electrode Origin C â C2 is shown in Figure 70 for stagnant and stirred conditions. Table 25 displays the mV difference in measured OCP from Figure 70 between the three conditions at three exposure times. Within the first second of exposure, 1.00 m/s stirring resulted in a decreased OCP of approximately 31 mV compared to stagnant solution, raising to approximately 37 mV at 720 s of exposure. In all stirring conditions, the OCP value rises as time progresses; literature suggests some form of passivation is responsible (see section 2.3 Chalcopyrite Passivation). However, the mV separation between stirring conditions also rises as time progresses, suggesting a decrease in passivation rate. The average rate of separation is also greater the faster the peripheral tip speed. When peripheral tip speed is increased by 3 times, it results in an approximately 2 times reduction in measured OCP versus stagnant solution. This relationship suggests a rate of diminishing returns as the limit of stirringâs ability to effect OCP measurement is approached. If non-baffled vortex stirring is used, this analysis may not directly translate due to laminar solution flow. If stirring in a container with baffles, faster peripheral tip speeds may be achieved. Although within experimental error, it should be noted that data acquired under stirring fluctuates more than data without stirring (i.e. if extracting slopes, non-agitated solutions will provide cleaner lines). This may be a result of experimental setup where the magnetic stirrer produces vibrations that transfer to the massive electrode, causing it to move in relation to the Luggin capillary/reference electrode that is anchored independent of the stirrer. 104 Figure 70: OCP data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. Table 25: Differences in OCP data from Figure 70 between stagnant and stirred conditions at three exposure times and average rate of separation OCP mV @ Exposure Time Average Rate of Separation Stir Condition 0.1 s 60 s 720 s mV/min Stagnant vs. 0.33 m/s 16.8 17.6 19.5 0.23 Stagnant vs. 1.00 m/s 30.9 32.4 36.7 0.49 0.33 m/s vs. 1.00 m/s 14.1 14.8 17.2 0.26 4.5.1.2 Galvanostatic Polarization Given the effects presented on OCP in the previous section, stirring is expected to also lower observed potential for galvanostatic polarization, but the effectiveness may be different. The data in Figure 56 from 4.3.4 Galvanostatic Polarization on Masked Massive Electrodes shows that increasing applied current results in smaller increases in observed potential. Therefore, it should be expected that the greatest effect of stirring is at lower applied currents. Figure 71 presents galvanostatic polarization at 2.26 μA/cm2 for CuFeS2 massive electrode Origin C â C2 under stagnant and stirred conditions. Table 26 displays the mV difference in measured potential from Figure 71 between the conditions at five exposure times. The lower speed stirring at 0.33 m/s appears to have little effect on observed potential before 1800 s of exposure versus stagnant solution. The error in observed potential may be lower than the stagnant before this time, but after it grows larger. Any changes in slope of the data fall within the increased error produced by fluctuating values, while the stagnant shows stable data with decreasing error. The higher speed stirring at 1.00 m/s produced significant effect. Within the first second of exposure 1.00 m/s stirring resulted in a decreased observed potential of approximately 11 mV compared to stagnant 105 solution, raising to approximately 15 mV at 3600 s of exposure. The average rate of separation appears to be relatively unaffected by peripheral tip speed; however, the separation does continue to increase with time. This suggests a decrease in passivation rate versus stagnant solution. Compared to OCP, galvanostatic polarization required 3 times the peripheral tip speed to result in a similar reduction in observed potential. This confirms there is a rate of diminishing returns as the limit of stirringâs ability to effect potential measurement is approached. As stated previously, a container with baffles will be required for faster peripheral tip speeds, but may result in more data fluctuations. Figure 71: Galvanostatic polarization (GAL) applied at 1 μA data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. Table 26: Differences in galvanostatic polarization data from Figure 71 between stagnant and stirred conditions at five exposure times and average rate of separation GAL @ 2.26 μA/cm2 mV @ Exposure Time Average Rate of Separation Stir Condition 0.1 s 60 s 720 s 1800 s 3600 s mV/min Stagnant vs. 0.33 m/s 0.5 0.6 0.0 2.2 6.0 0.09 Stagnant vs. 1.00 m/s 10.8 10.8 12.1 13.3 15.2 0.07 0.33 m/s vs. 1.00 m/s 10.3 10.2 12.1 11.0 9.2 -0.02 4.5.2 Effects of Solution Sparging Sparging was performed with â¥ 99.995% nitrogen at 10 mL/min through a glass frit sparger placed as close to the working electrode as possible without being in the line-of-sight of the working electrode to the counter electrode or stir bar. Both stirring and sparging were performed for 10 min prior to polarization and continued through polarization with the working electrode placed in solution immediately prior to polarization. The only quoted flow rate I encountered in literature was 1 L/min. This flow rate resulted in agitation comparable to producing a vortex and cavitation during spinning. 106 Agitation similar to simmering water was deemed sufficient to be comparable to the stirring speeds selected for experimentation. A 10 mL/min flow rate was selected as it provided this agitation. The data provided here with nitrogen is expected to be comparable to other inert gases such as argon. Air and oxygen may affect the rates of oxidation, dissolution, and passivation that may have a measurable effect independent of agitation. 4.5.2.1 Galvanostatic Polarization The effects of stirring suggest that any agitation will result in a decrease in observed potential. Sparging is therefore expected to have a similar effect as stirring, although with greater effect due to the spargerâs random pattern release of gas acting similar to cavitation. Figure 72 presents the data from Figure 71 compared to the same conditions with sparging applied. Table 27 displays the mV difference in measured potential from Figure 72 between the conditions at five exposure times. Within the first second of exposure 10 mL/min N2 sparging resulted in a decreased observed potential of approximately 12 mV compared to stagnant solution, raising to approximately 15 mV at 3600 s of exposure. This provided very similar results as stirring at 1.00 m/s; however, the error encompasses the entire data set for all conditions. Due to the random nature of gas flow from the sparger and its stationary positioning within the experimental setup, the consistency of effect may result in varying experimental conditions. The dissolved oxygen content will need to be measured to ensure consistency between experiments. This error source may be reduced by allowing the solution to sparge longer before polarization. I encountered sparging lengths between 15 â 80 min in literature. My selection of 10 min was to ensure my agitation pre-polarization was the same for both stirring and sparging and to determine a minimum requirement when performing these agitation methods. Figure 72: Galvanostatic polarization (GAL) applied at 1 μA data for CuFeS2 Origin C â C2 (characterization data: Table 5 - Table 17, Figure 30 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. Solution sparged with nitrogen at 10 mL/min. Solution stirred with 12.7 mm magnetic stir bar at stated peripheral tip speed. Each line is average of three experiments with two-sided t-distribution 95% CI error bars. 107 Table 27: Differences in galvanostatic polarization data from Figure 72 between stagnant and stirred conditions at five exposure times and average rate of separation GAL @ 2.26 μA/cm2 mV @ Exposure Time Average Rate of Separation Agitation Condition 0.1 s 60 s 720 s 1800 s 3600 s mV/min Stagnant vs. 10 mL/min Nâ Sparging 12.0 8.1 9.1 10.9 15.0 0.05 Stagnant vs. 0.33 m/s 0.5 0.6 0.0 2.2 6.0 0.09 Stagnant vs. 0.33 m/s & 10 mL/min Nâ Sparging 31.4 29.1 32.3 36.3 42.3 0.18 Stagnant vs. 1.00 m/s 10.8 10.8 12.1 13.3 15.2 0.07 Stagnant vs. 1.00 m/s & 10 mL/min Nâ Sparging 42.0 39.6 42.1 44.1 44.5 0.04 0.33 m/s vs. 1.00 m/s 10.3 10.2 12.1 11.0 9.2 -0.02 0.33 m/s vs. 0.33 m/s & 10 mL/min Nâ Sparging 30.9 28.5 32.3 34.0 36.3 0.09 1.00 m/s vs. 1.00 m/s & 10 mL/min Nâ Sparging 31.2 28.7 30.1 30.8 29.2 -0.03 0.33 m/s & 10 mL/min Nâ Sparging vs. 1.00 m/s & 10 mL/min Nâ Sparging 10.6 10.4 9.8 7.8 2.1 -0.14 The lower speed stirring at 0.33 m/s paired with 10 mL/min N2 sparging decreased observed potential approximately 31 mV compared to stagnant solution within the first second of exposure, raising to approximately 42 mV at 3600 s. This was very similar to 1.00 m/s paired with 10 mL/min N2 sparging which decreased by approximately 42 mV in the first second and approximately 45 mV at 3600 s. The errors associated with this data are comparable to the stagnant and stirring only conditions. This suggests stirring allows sparging to more effectively remove dissolved oxygen as well as homogenizes the gas flow from the sparger making agitation more consistent. The average rate of separation is most affected by the combination of slow peripheral tip speed with sparging. Otherwise, the separations are consistent with the effects of stirring. The flow rate of the sparging gas has a greater effect on observed potential than the speed of stirring, decreasing it approximately 3 times in the first second of exposure and 2 times at 3600 s of exposure. Both agitation methods in any combination appear to retain the rate of passivation while reducing the potential required for dissolution. Sparging combined with stirring produces the expected result of faster non-laminar stirring. The rate of diminishing returns is more quickly approaching the limit of agitationâs ability to effect potential measurement as the increased stirring rates show less separation outside of calculated experimental error. 108 4.6 Mineral Massive Electrode Lifespan Electrochemical experimentation provides data impossible to gather by other methods. However, it is a destructive experimental method, meaning the working electrode is irreversibly consumed as a result of experimentation. I suggest experimentation with mineral massive electrodes to be semi-destructive rather than destructive. This workâs experimental data shows massive electrodes capable of reproducible data when a fresh surface is exposed through proper polishing between experiments. The length of exposure time an electrode is able to produce reliable data will be referred to as its lifespan. With the lack of available experimental data in literature, an electrodeâs lifespan can only by identified once the electrode is no longer reliable. I consider an electrodeâs lifespan terminated when three consecutive experiments produce unreliable data. There are many reasons a mineral massive electrode may become unreliable. This section will only focus on reasons that I have experimental data to assist in my assertion that a massive electrodeâs lifespan is complete. Due to no data being found at time of publishing of this work regarding massive electrode lifespans, all data was collected as a forensic account allowing for the identification of preventive measures (see section 5.3 Recommended Techniques for Reproducible Data in Mineral Electrochemistry). All my chalcopyrite mineral massive electrodes were therefore tracked from creation to last electrochemical experiment (data summarized in Table 28). This ensured that when a discrepancy was encountered, there was record of the lifespan that led to it. This process led to the identification of three main root causes: cracks in the mineral, thickness of the mineral, and connection wire degradation. 109 Table 28: Experimental lifespan for 7 CuFeS2 massive electrodes from 3 origins (characterization data: Table 5 - Table 17, Figure 18 â Figure 31). All experiments were performed in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Massive electrode C2 used stirring and/or N2 sparging for some experiments while masked. CuFeS2 purity from Table 10 and Table 11 shows masked and unmasked surface areas. Galvanostatic (GAL) and potentiostatic (POT) polarization show minimum and maximum applied currents and potentials, respectively. Massive Electrode Interface Masking Exposure Type Exposure Time Total Exposure Time Total Experiments Electrode Status (CuFeS2 Purity) Mask / No Mask (Polarization Range) h h # After Last Test (Thickness) A1 (99%) No Mask OCP 8.6 145.2 197 Connection Wire Failure (2.3 mm) GAL (0.001 - 1 mA) 35.7 Mask OCP 2.0 GAL (0.0001 - 1 mA) 89.6 POT (297 - 432 mV) 9.3 B1 (71%) No Mask OCP 0.7 24.8 33 Mineral Cracks + Thin Mineral (0.9 mm) GAL (0.001 - 0.1 mA) 9.0 Mask OCP 0.7 GAL (0.0005 - 1 mA) 14.4 B2 (68%) Mask OCP 0.8 23.9 18 Ready to Use (4.2 mm) GAL (0.0001 - 0.1 mA) 23.1 B3 (95%) Mask OCP 0.6 43.4 46 Ready to Use (3.2 mm) GAL (0.0001 - 0.01 mA) 22.0 POT (273 - 685 mV) 20.8 B4 (89%) Mask OCP 0.8 11.8 11 Mineral Cracks (3.0 mm) GAL (0.0001 - 0.1 mA) 11.0 C1 (73%) No Mask GAL (0.001 - 0.01 mA) 4.1 13.8 15 Mineral Cracks (4.1 mm) Mask OCP 0.6 GAL (0.001 - 0.1 mA) 9.1 C2 (75%) No Mask GAL (0.01 mA) 3.9 25.3 31 Ready to Use (2.9 mm) Mask OCP 2.5 GAL (0.001 mA) 19.0 4.6.1 Effects of Cracks in Massive Electrodes Mineral massive electrodes rely on an uninterrupted surface to achieve predictable electrochemical results. The presence of cracks, voids, and pits result in a varying surface with increased surface area and regions were crevice corrosion dominates dissolution rates. While similar in nature to the resin-mineral interface, the effects can present different results for a number of reasons. Cracks have all edges participating in dissolution and they exist internally, only having access to the external surface when truncating at an edge. With the resin-mineral interface, one face is inert and there is direct access to the entire external surface. Voids may introduce unidentified inclusions or significantly different concentrations. Pits provide initiation sites for pitting corrosion which can lead to crevice corrosion while increasing the surface area. These defects can have a significant effect on experimental results. Due to the presence of voids being unknown regardless of care taken during electrode construction and pitting being effectively removed by polishing to 1200 grit with carbide paper, the focus of this section is on the effect of cracks. While they can be avoided by intentional electrode construction, they may form 110 as a result of experimentation and may go undetected depending on imagery techniques available. Experimental data may provide insight that can be misinterpreted as mineral variability. 4.6.1.1 Open Circuit Potential When only using naked eye visual inspection, it is easy to misidentify hairline cracks as inclusions or grain boundaries. An example of this is my CuFeS2 Origin B â B4 massive electrode shown in Figure 73 (partially reproduced from 3.1.3 Optical, SE, and BSE Imagery with EDS Mapping of Chalcopyrite Massive Electrodes; see Figure 20, Figure 22, and Figure 24 for Origin B â B1, B2, and B3, respectively for comparison). There are two cracks running horizontally through the center of the electrode that might be identified by visual inspection. However, the upper left and bottom center of the mineral host multiple hairline cracks that were only observed by SE (OM may have been able to identify these, but I was already performing EDS characterization). The region the mineral was produced from appeared free of cracks and voids although did have visual inclusions. Once polished sufficiently, the defects appeared at the surface. The effect cracks and voids can have on OCP data are shown in Figure 75, comparing four electrodes from Origin B. I believe most researchers would refrain from using an electrode that presents as many cracks as Origin B â B4 unless it is the only representative electrode. However, it is possible the finer cracks go undetected, depending on observation techniques available. Figure 73: Chalcopyrite massive electrode Origin B â B4 (Left) Optical imagery (native camera sensor and application on an iPhone 8 running iOS 14.4) polished to 1200 grit with carbide paper in overhead white light (Center) Optical imagery of sample masked to surface area = 0.442 cm2 (Right) SE polished to 1 μm diamond polish at 7x magnification The OCP data shown in Figure 74 and Figure 75 are the first experiments run on all Origin B and Origin C massive electrodes after construction. My Origin A â A1 electrode underwent a different experimental schedule resulting in the first five masked OCP data being Test 147 â 151 acquired by a 10 second measurement followed by potentiostatic polarization at a set potential above the measured OCP. This was then performed again for Test 153 after a potentiostatic polarization. Multiple galvanostatic experiments were run followed by an OCP measurement for Test 182. Data comparisons are shown in Table 29 for first second of exposure. 111 Figure 74: OCP data for CuFeS2 massive electrodes (characterization data: Table 5 - Table 17, Figure 18 â Figure 19, Figure 28 â Figure 31) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. (Left) Origin C â C1 and C2 with data for first experiments run on these electrodes (Right) Origin A â A1 with data for first masked OCP experiments Figure 75: OCP data for CuFeS2 Origin B (characterization data: Table 5 - Table 17, Figure 20 â Figure 27) in 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area exposed with mask = 0.442 cm2. These are the first experiments run on these electrodes. (Top Left) Origin B â B1 crack free (Top Right) Origin B â B2 crack free (Bottom Left) Origin B â B3 crack free (Bottom Right) Origin B â B4 with cracks present in both expsosed and masked surfaces 112 Table 29: OCP data for CuFeS2 electrodes from Figure 74 and Figure 75 comparing first three experiments (Origin A â A1 Test 1, 2, and 3 are 147, 148, and 149, respectively) Experiment mV @ First Second of Exposure A1 B1 B2 B3 B4 C1 C2 Test 1 506.3 494.4 496.2 494.4 538.2 495.6 484.5 Test 1 vs. Test 2 19.9 3.7 5.2 18.7 24.2 9.2 9.5 Test 2 vs. Test 3 2.8 -0.3 0.0 -0.3 6.4 4.9 -8.0 The OCP data from all CuFeS2 massive electrodes exhibit the same phenomena: the first masked OCP measurement presents a higher potential than all following measurements. The cracked Origin B â B4 electrode exhibited three differences. First, it produced the highest OCP of all experimented electrodes regardless of origin by 31.9 mV and was 42.0 mV above the next highest Origin B electrode. Second, all measured OCP were above the highest OCP of all other origin electrodes (Origin B4 â Test 3 was 1.2 mV above Origin A â A1 â Test 147 [Test 1]). Third, it produced the largest drop in OCP between Test 1 and Test 2, being 4.3 mV more than Origin A â A1 and 5.5 mV more than Origin B â B3. The characterization data in Table 5 - Table 17 do not present any inclusions that could account for these differences. 4.6.1.2 Galvanostatic Polarization The OCP data for Origin B â B4 appeared uncharacteristic when compared to other Origin B electrodes as well as Origin A and C electrodes. The galvanostatic polarization data may present similar deviation when cracks are present. Figure 76 shows data for the experiments run on Origin B â B4 after OCP. The first 2.26 μA/cm2 data presented potentials expected from a non-cracked electrode. The 22.64 μA/cm2 data does as well, except for a sudden drop in potential before the 1 hour mark. A similar potential drop is seen in the second 2.26 μA/cm2 that is performed after the 226.24 μA/cm2, which shows noisy data suggesting active dissolution rather than the expected passivation. These values are comparable to the galvanostatic polarization data for Origin B â B1 and B2 electrodes, shown in Figure 77. Origin B â B4 seemed capable of producing stable data at low current densities, so three experiments were performed at 0.23 μA/cm2 (see Figure 76). The first produced expected data, but the next two produced unstable data outside of experimental error at 81.6 and 106.4 mV below the first, respectively. It may be possible to achieve data for a single experiment when the electrode is cracked, but the data is not repeatable and calls into question whether the data that was acquire is an accurate representation of the mineral. 113 Figure 76: Galvanostatic polarization (GAL) applied at 0.1, 1, 10, and 100 μA data for CuFeS2 Origin B â B4 massive electrode (characterization data: Table 5 - Table 17, Figure 26 â Figure 27) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Cracks are present in both expsosed and masked surfaces. Figure 77: Galvanostatic polarization (GAL) data for CuFeS2 Origin B â B4 from Figure 76 overlaid on Figure 65 and Figure 66 from section 4.4.2 Galvanostatic Polarization 4.6.2 Effects of Mineral Thickness in Mineral Massive Electrodes The thickness of a mineral massive electrode can be influenced by a variety of factors. The availability of the mineral can limit maximum thickness while experimentation will result in polishing. The porosity and brittleness can greatly reduce the usable quantity of a mineral. Voids can be exposed when polishing or a crack may result during experimentation from high voltage paired with a thin mineral. The most vital region under experimentation is the volume of material directly behind the exposed surface area that produces the shortest path to the connection wire. As stated in section 3.2.1 Massive Electrode Construction, maximum thickness was restrained between 3 â 5 mm to minimize thickness induced resistance while maximizing lifespan. The nature of electrochemical experimentation suggests a minimum thickness is required to produce stable and reproducible data. The final thicknesses of my chalcopyrite massive electrodes are shown in Table 28. The thinnest was Origin B â B1 at 0.9 mm with all others above 2 mm. Figure 78 shows Origin B â B1âs 114 final nine experiments. Using my electrode lifespan metric (three consecutive experiments producing unreliable data) âTest 33â terminates Origin B â B1âs lifespan. The experimental field notes state the mineral massive electrode is in proper form. Therefore, it is concluded that mineral massive electrodes require a minimum 1 mm thickness to produce reliable electrochemical data. I suggest not experimenting with minerals less than 1.5 mm. Figure 78: Galvanostatic polarization (GAL) applied at 0.5 and 100 μA and 1 mA data for CuFeS2 Origin B â B1 massive electrode (characterization data: Table 5 - Table 17, Figure 20 â Figure 21) with and without resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2; without = 1.294 â 3.569 cm2. Final mineral thickness 0.9 mm. 4.6.3 Effects of Connection Wire in Mineral Massive Electrodes A functional massive electrode is predicated on using low-resistance wires effectively attached to the mineral with a low-resistance connector (see 3.2.1 Massive Electrode Construction and 5.3.1.2 Wire Preparation). Assuming an appropriate wire is used, it is the connection between the wire and electrode that can increase resistance and affect electrochemical measurements. My electrode copper wires were affixed by silver paste (Enson EN-06B8, surface resistivity â¤20 mΩ/square/mil) or copper tape (resistance through adhesive = 3 â 5 mΩ/square). Silver is known to increase dissolution rates in chalcopyrite (Córdoba et al., 2008; Crundwell, 2015; Ghahremaninezhad et al., 2012; Hackl et al., 1995; Li et al., 2013; Miller et al., 1981; Nazari et al., 2011, 2012; Nikoloski et al., 2017; Olvera et al., 2014, 2016; Price & Warren, 1986; Tapera & Nikoloski, 2019; Tapera et al., 2018; Watling, 2013), although the extent to which the silver paste affects data has not been directly studied. All but one of my electrodes were constructed with copper tape to avoid silver-related effects. However, there is a higher probability of air entrainment between the copper wire, copper tape, and mineral surface due to the tape being hand applied. When properly applied, the tape should provide a connection comparable to alligator clips commonly used to temporarily connect wires to a potentiostat. There also exists the possibility that while the wire is properly affixed, it may experience physical degradation from handling during experimental setup. If the wire is bent back and forth, cyclic strain may result in some wire strands experiencing plastic deformation and eventually fracture, increasing the wireâs resistance. This increases the electrodeâs observed resistance of the mineral. 115 4.6.3.1 Galvanostatic Polarization Figure 79 shows the final three experiments run on Origin A â A1 (silver paste connection) compared to earlier data. âTest 195â at 0.68 μA/cm2 produced expected potentials, consistent with other results at this applied current. âTest 196â at 11.31 μA/cm2 showed potentials elevated by approximately 150 mV, and âTest 197â was even higher. Since âTest 195â produced expected results, the deviation likely originated between its conclusion and the setup for âTest 196.â Experimental field notes confirm all procedures remained consistent and the solution was drawn from the same batch. Mineral thickness changes would be expected to cause gradual drift, not an abrupt change. The most likely cause is mechanical degradation of the connection wire. Due to the method of electrode construction (sections 3.2.1 Massive Electrode Construction and 5.3.1.2 Wire Preparation), the connection wire exits 90° or 180° relative to the mineral surface (Figure 80 â Left) and must be bent for each experiment and during polishing. Thus, the connection wire for Origin A â A1 was bent back and forth at least 90° at the same location over 195 cycles. This cyclic strain likely caused plastic deformation or fractured wire strands. Prior experiments were conducted at low applied currents (0.23, 0.68, 1.13 μA/cm2), possibly masking early signs of increased resistance. After âTest 176,â experimental field notes state the wire shielding pinched at the bend location, potentially allowing solution ingress and strand corrosion. Although inert shielding was then applied (Figure 80 â Right), pre-existing damage may have compromised the wire. The wires used were designed for stationary use â not cyclic bending â while being submerged in 2 g/L H2SO4, making it vulnerable to fatigue and corrosion-induced failure. Figure 79: Galvanostatic polarization (GAL) applied at 0.1, 0.3, 0.5, 1, 5, 10, and 100 μA and 1 mA data for CuFeS2 Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) with resin-mineral interface masking in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Lines with two-sided t-distribution 95% CI error bars represent average of three experiments. Connection wire suspected of cyclic strain resulting in fractured strands, increasing resistance. 116 Figure 80: CuFeS2 Origin A â A1 massive electrode in solution showing connection wire bend to allow proper exposed surface orientation. (Left) Test 142 (Right) Test 195 showing reinforcement and inert shielding added to bend location 117 Chapter 5: Conclusions and Recommendations 5.1 Conclusions and Recommendations on Reporting Copper remains an un-substitutable material. With ore grades declining, chalcopyrite will supply most of the worldâs Cu. As a result, chalcopyrite research has experienced increased attention. Nevertheless, its passivation â and resulting recalcitrance to commercially viable hydrometallurgical extraction methods â has limited actionable results. Despite the wealth of existing work on the subject, a surprising lack of agreement remains. Ineffective communication of methods and lack of standardization continue to plague progress. Greater focus must be placed on reporting methods and reproducing the data of others before for any true advances can be made. It may not be possible to infer leaching behavior from discrete electrochemical measurements, especially with respect to rate. However, general mechanistic behavior and the influence of catalysts can be inferred â as long as best practices are followed. My recommendations to accomplish this experimentally are shared in the following section (5.3 Recommended Techniques for Reproducible Data in Mineral Electrochemistry). My recommendations for mineral characterization reporting are shared in 3.1.6 Conclusions on Reporting Mineral Characterization. My recommendations for general data reporting are shared throughout Chapter 4: Investigation of the Variability in Mineral Electrochemistry, where all figures and tables leave no question as to what they represent or how they were acquired. In-depth analysis of data will vary with context, but by ensuring collection intent is made clear, followed by un-biased presentation, the data can be received with proper perspective and conclusions more easily drawn. The lack of data agreement across existing literature can be attributed to many factors, but an outlier for importance is the drawing of broad conclusions from a single data point derived from an un-replicated experiment. All the data I present is self-replicated when physically possible. In other words, each experimental condition is performed multiple times with the same mineral massive electrode and presented as a statistical representation of the probable data set. Only then is that data compared to other data, which were given the same treatment. Due to the nature of mineral electrochemistry, data variability is limited by the consistency of mineral composition; minerals are discovered, not engineered. Therefore, any single experiment must be treated as a potential outlier until proven otherwise. I believe Barton & Hiskey (2022b) accurately noted the current state of mineral electrochemistry: Only a large series of very well-controlled experiments on a wide variety of chalcopyrites could identify such a universal mechanism or explanation for all observed phenomena, and this is not the direction that current research is trending. Most mechanisms proposed to date, like most leaching studies, test only one or two minimally characterized chalcopyrite samples. To extrapolate the results out to a theory covering chalcopyrite leaching in general is to ignore the enormous range of variation in major-, minor-, and trace-element compositions, crystallinity, electromagnetic properties, and accompanying mineral species. 118 5.2 Data Summary and Conclusions The data presented in this work confirms that experimental methods play a larger role in mineral electrochemistry than previously assumed under current laboratory practices and reporting standards. Since the publishing of Warren et al. (1982), mineral origin has been colloquially accepted as the final, unavoidable error source. Works published thereafter have leaned on its analysis as the crutch, using it to explain away any unaccountable variation and to frame mineral origin as the sole remaining reason for the lack of reproducibility and replicability. While the intent and analysis of Warren et al. (1982) still holds mostly true, its blanket application has become the red herring of mineral electrochemistry. This is due, in large part, to the absence of standardized laboratory practices. The governing bodies (ASTM International, ANSI, ISO, NACE International, and NISO) that provide proven techniques for non-mineral materials (e.g. steel, copper, aluminum) have not extended their resources to mineral electrochemistry. Any existing laboratory practices have been colloquially adapted and adopted from non-mineral corrosion electrochemistry. Knowledge acquired from non-mineral electrochemistry, paired with relatively basic chemistry, has long proven that temperature, solution type and concentration, and applied potentials all have an effect on mineral electrochemical results. This comes as no surprise. The important conclusion, however, is that they do not affect reproducibility or replicability. While conclusions drawn from data analysis may vary across works, the general trends resulting from varying these conditions hold true. This once again leaves mineral origin as the culprit. My experimental data even agrees, showing that different mineral origins can result in data variation upwards of 242 mV (mineral origin purity â¥ 83%, galvanostatic polarization at 2.26 μA/cm2 in 2 g/L H2SO4 at 21°C). However, my data goes further, showing that this variation is also observed within the same mineral origin, producing variation upwards of 247 mV (mineral origin purity = 87%). Therefore, mineral origin cannot be the driver for the lack of reproducibility and replicability. It must be composition. But this too remains a red herring, as it still points at the mineral itself being responsible. The colloquially adapted and adopted laboratory practices have been overlooked, overshadowed by the inherited knowledge from non-mineral electrochemistry. None of these methods have been proven in the field of mineral electrochemistry. Given the trend of poor reporting on mineral composition, electrode fabrication processes, and experimental conditions, even if researchers are aware of the shortcomings of their techniques, there is â at the time of publishing this work â no publicly available documentation. This prompted my exploration into variability in mineral electrochemistry, seeking to document mitigation methods and set a standard of reporting. Given the unknown nature of the error source, I chose to follow standard laboratory practice and critically observe the decisions made. The first step in mineral electrochemistry is obtaining a mineral. Therefore, I started by fully documenting my minerals used for experimentation, both the parent ore as well as the specific surfaces intended for solution exposure. Visual observation and optical microscopy allowed for preliminary mineral qualification. Then XRD, SE and BSE imagery with EDS mapping, and ICP-OES were used to quantify mineral composition. A few potential sources of error were discovered: 119 a) operating under a false assumption of the true mineral purity and inclusion types b) using the parent ore characterization as a replacement for the surface characterization c) using data from multiple electrodes from the same parent ore as interchangeable for analysis The second step in mineral electrochemistry is the production of the working electrode, in my case a mineral massive electrode. The procedure for its construction is very similar to that of a non-mineral massive electrode, see section 5.3.1 Mineral Massive Electrode Construction for my recommended techniques. So long as care is taken in its production and that quality is maintained for every electrode produced, the construction process should be considered to produce negligible error. However, two error sources are present from the nature of massive electrodes: a) resin-mineral interface allows for experimental solution to penetrate below the desired exposed surface and introduces crevice corrosion and increases the exposed surface area by an unknown amount b) unknown interaction of silver epoxy with copper bearing minerals as silver is known to increase its extraction The resin-mineral interface has proven to be the linchpin. Isolating this interface from solution with masking has allowed for reproducible and replicable data in mineral electrochemistry. Masking increases confidence in acquired data resulting from the knowledge that only the desired surface area is exposed, which also extends the lifespan of the mineral massive electrode. The data acquired with masking resulted in upwards of 100 mV difference and a different data slope versus no masking under galvanostatic polarization. Literature review revealed poor reporting on solution agitation and largely treated varying rates and types of agitation as equal. Once the resin-mineral interface masking was verified and all other variables controlled, solution agitation was considered as a source of error. Experimentation revealed that magnetic stir bar stirring and/or nitrogen sparging can result in upwards of 45 mV in decreased observed potential under galvanostatic polarization. Both agitation methods in any combination appear to retain the rate of passivation while reducing the potential required for dissolution. The flow rate of the sparging gas has a greater effect on observed potential than the speed of stirring, decreasing it approximately 3 times in the first second of exposure and 2 times at 3600 seconds of exposure. There were a few potential error sources discovered: a) increasing agitation results in increasingly less smooth data, performing overly aggressive agitation (i.e. producing a vortex and cavitation) may result in unreliable data b) too low a flow rate of sparging gas produces inconsistent agitation, producing varying results across multiple experiments - this speaks to the literature trend of incomplete reporting on flow rates (i.e. either not at all or qualitative rather than quantitative) and the equipment being used All details affect the ability to acquire reproducible and replicable data in mineral electrochemistry. Intentional choices and clear reporting have allowed for identification of mitigation and isolation methods that provide context for other variations or effects observed in experimental setup. 120 5.3 Recommended Techniques for Reproducible Data in Mineral Electrochemistry The data presented in Chapter 4: Investigation of the Variability in Mineral Electrochemistry has elucidated how experimental method and electrode construction can influence results and the interpretation of them. The suggestions presented in this section are a merging of standard laboratory practices with new methods that were trialed, verified, and then used to perform the reproducible data of this work. None of these methods are presented as a perfect solution, but rather a collection of intentional choices intended to mitigate specific challenges produced by the boundaries set by mineral massive electrode electrochemistry. 5.3.1 Mineral Massive Electrode Construction The construction methods used to produce a mineral massive electrode can impact experimental results. This is more easily understood when considering the selection of a particular piece of mineral to study, but is less obvious when considering connection wires or resin preparation. By ensuring every detail of construction is intentional, data can be avoided that leads to inaccurate claims and provides reproducible and replicable data. Small changes to existing standard laboratory practices can lead to more stable and reliable data across multiple experiments and mineral types. The following sections present mitigating methods for each step of the mineral massive electrode construction process. Figure 81 shows an exemplar image for each step of the process. Figure 81: Reproduction of Figure 33 from 3.2.1 Massive Electrode Construction â Example of massive electrode construction. (Left, Center Left, Center) 5.3.1.1 Mineral Selection and Preparation (Center Right) 5.3.1.2 Wire Preparation (Right) 5.3.1.3 Resin Preparation 5.3.1.1 Mineral Selection and Preparation The most important aspect of mineral massive electrode construction is the mineral itself. The selection of a representative piece of mineral is pivotal to understanding the results of the intended experimental method. This method will have a large impact on what a representative piece may look like. Some research focuses on a specific mineral origin (e.g. a mining companyâs proprietary ore), so finding the section that is closest to the average composition may be best. The majority of literature seeks information as it applies to the pure version of the mineral, so finding a section of the mineral that has the least amount of impurities is ideal. In both cases, finding multiple electrodes with a similar purity may not always be possible, so an intentionally wide range of purities may be more representative. Regardless of your selection, being mindful of this can put data analysis into perspective. 121 Mineral characterization techniques are able to assist in narrowing this selection. Visual inspection and optical microscopy are the simplest qualification methods. If ample mineral is available, it may be more efficient to make multiple electrodes and select the best representatives for your work. If the entire mineral sample on hand is used to produce the electrode, then the methods chosen to quantify will change. For example, using a chemical assay is no longer viable since the material would be consumed during analysis, so EDS may become the main quantification method. It would be beneficial to recover any waste product in the manufacturing of the electrode as there may be a chance you have enough powder to perform XRD. At least two quantification methods should be used since no method is perfect. Figure 82: Chalcopyrite from raw ore to prepared for electrode (Left) raw ore, section cut with diamond saw rock cutter, smaller section cut with diamond saw rock cutter, hand polished to 1200 grit with carbide paper (Right) raw ore, section fractured off while hand sawing, hand polished to 1200 grit with carbide paper Having selected a representative ore, ensure that there is a region free of cracks and voids. Their presence can result in wasted material and time. Ensuring the general area is free of cracks and voids does not guarantee the final piece you have is, but it greatly reduces the likelihood it will. Every mineral is different and even different origins of the same mineral can have large variations in composition and structure. This becomes important to the electrode construction as the more brittle a mineral is the more difficult it is to produce a desired shape from it. Trying to hand saw a brittle material may work with large sections, but it will not with smaller pieces. Figure 82 shows an ore prepared with a diamond saw rock cutter and one where hand sawing was too aggressive. Even using too coarse a grit of carbide paper can result in the small mineral piece not being able to keep a 90° edge and chip out. It is best to obtain a piece of mineral roughly two to three times the desired final size, then using finer grit (800 â 1200) carbide paper gently hand polish your way down to final dimensions. The size multiple can be reduced for tougher materials or when supply it limited. Working gently down to the final size will ensure the sample never experiences high stresses, which can result in external and internal cracking. If cracking occurs or voids exist, they can greatly affect experimental results, similar to the resin-mineral interface. This will drastically decrease the life of the electrode and confidence in data it produces, as shown in 4.6.1 Effects of Cracks in Massive Electrodes. Figure 83 shows prepared CuFeS2 mineral sections exhibiting cracks. Crack-free samples are preferred, but if mineral availability is limited they may be usable if the cracked regions are removed or properly isolated with masking. 122 Figure 83: CuFeS2 polished to 1200 grit with carbide paper. (Left) two roughly shaped pieces: left - two regions of large inclusions, right - region of large inclusions and an exposed crack (Center) Origin B â B1 exhibiting isolable cracks resulting from experimentation (Right) Origin B â B4 exhibiting cracks through entire sample that cannot be polished out or masked The final shape of the electrode should closely resemble a rectangular prism. The closer the cross section can get to a square the simpler it will be to calculate the surface area and volume. This is also a simple shape to polish evenly while retaining purchase without applying large, uneven forces. The two large faces of the square prism should be equal in size and approximately 1 â 3 cm2. Selecting the exact size will depend on available material, the type of experimentation and its setup, and the desired exposed surface area after applying a mask (see sections 4.3.2 Masking Effectiveness on a Massive Electrode and 5.3.2 Masking). This range is suitable for the majority of typical experimentation, allowing for a maximum circular masked surface area ranging from 0.785 â 2.356 cm2 (1 cm2 is ideal for data processing). In order to ensure proper analysis and uniformity of experimentation, the resulting exposed surface area after masking should be the same across all electrodes, regardless of their original surface areas before masking. It is, therefore, ideal to make all electrodes the same size prior to masking. Due to material constraints, my smallest electrode was Origin A â A1 with a pre-mask exposed surface area of 1.012 cm2; although, it was not a perfect square or rectangular prism (Figure 84). This set the largest possible masked surface area to 0.442 cm2 for all seven electrodes used for experimentation. Figure 84: Chalcopyrite Origin A â A1 max diameter of 0.75 cm restricting masking to 0.442 cm2 The next consideration is mineral thickness. Approximately 3 â 5 mm provides a nice balance â any thicker and there is a risk of too high internal resistance and any thinner and the sample will not last for a sufficient number of experiments. The minimum thickness suggested for experimentation is 1.5 mm (see section 4.6.2 Effects of Mineral Thickness in Mineral Massive Electrodes). Once the mineral is nearly 123 to size, one of the two largest parallel faces should be selected as more ideal for experimentation. Given that the sample should be less than or equal to 5 mm thick, there should be little difference between the two faces. If choosing between multiple electrodes, uniformity through the entire thickness is more ideal compared to higher purity with side variation. This will allow for consistency throughout experimentation as the sample gets polished between experiments. The final step in mineral preparation before wire connection is polishing the edges. This piece of mineral is to be encased in casting resin that adheres better to slightly roughened surfaces. Too rough and there is a risk of separation where the resin may be too viscous to flow into and entrain air bubbles. Conversely, too smooth and the resin may not be able to make good purchase and not properly secure the mineral during handling. Since I highly recommend resin-mineral interface masking, resin purchase to mineral becomes much less important. I suggest polishing to 1200 grit with carbide paper and gently breaking the edges at the same grit to strengthen the corners of brittle minerals, an example is shown in Figure 82. 5.3.1.2 Wire Preparation Once the mineral is prepared, the next step is affixing a way to electrically connect it to the experimental circuit. A single stranded copper wire could sufficiently transfer current with minimal resistance; however, a multi-stranded copper wire would allow for better electrical contact over the entire surface. Single stranded copper wires are not sufficiently tough when cyclically bent, as may be necessary in experimental setups; multi-stranded wires are substantially more durable. With enough strands, a multi-stranded copper wire would provide a minimized least resistance path directly through the minerals thickness for the entire exposed surface. This gives the entire volume of the mineral an increased chance of being involved in the transfer of electrons, giving more accurate data. Therefore, I recommend avoiding single-stranded wires. Calculated wire resistances based on Equation 31 are shown in Table 30 for the multi-stranded copper wires used in this work, examples shown in Figure 85. Table 30: Reproduction of Table 18 from section 3.2.1 Massive Electrode Construction â Copper connection wires from Figure 85 with gauges determined by measurement and calculated resistance based on Equation 31 where ÏCu = 1.682*10-8 Ω m @ 21°C and L = 6 in. = 0.1524 m Massive Electrode Connection Wire Strand Size AWG Strands Effective Cable Size Effective AWG Resistance Color Ã mm Single Strand # mm2 Ã mm Multi-Strand mΩ A1 blue 0.27 29.5 12 0.687 0.935 19 AWG 12/30 3.7 B1, B2, B4 yellow 0.63 22.2 7 2.182 1.667 14 AWG 7/22 1.2 B3, C2 white 0.16 34 41 0.824 1.024 18 AWG 41/34 3.1 C1 green 0.16 34 41 0.824 1.024 18 AWG 41/34 3.1 (jkl = mjk #lânj#l"j#l [Equation 31] where: R = resistance of the conductor [ohms, Ω] Ï = resistivity of the conductor material [ohm meter, Ω m] L = length of conductor [m] A = cross-sectional area of conductor [m2] 124 Figure 85: Reproduction of Figure 32 from 3.2.1 Massive Electrode Construction â Four easily accessible wires considered for massive electrode construction. (Left - Red) multi-strand iron wire with too small gauge and strand count, but good single-strand gauge; avoid using if possible (Left - Blue) multi-strand copper wire with good gauge, single-strand gauge, and strand count â 19 AWG 12/30 (Left - White) multi-strand copper wire with ideal gauge, single-strand gauge, and strand count â 18 AWG 41/34 (Left - Yellow) multi-strand copper wire with good gauge, large single-strand gauge, and low strand count â 14 AWG 7/22 (Right) Wire scale shown next to ball point pen, approximately 6 in. = 0.1524 m. based on minimum distance to potentiostat connection Viramontes et al. (2007) performed measurements on resistance and found the combined resistance of solution and CuFeS2 massive electrodes to be â5.1 Ω at 25°C and 2 g/L of H2SO4â and the data corrections made based on this were well within experimental error. Therefore, all multi-stranded copper wires used for connection in this work produce negligible resistance, being 3 orders of magnitude smaller with the largest being 3.7 mΩ. Reducing the length of the wire can further reduce its resistance; however, the experimental setup may restrict minimum length. The length chosen for this work (L = 6 in. = 0.1524 m) was the minimum distance required to ensure the wireâs live end was clear of the solution and able to reach the potentiostat connection with no strain on the wire. Therefore, the attachment area between the mineral surface and wire is the only remaining way to reduce resistance. A number of methods have been used to do this, most notably: silver epoxy, copper tape, and soldering. The latter is typically not done in research as it requires heating up a localized area on the surface of the mineral which can cause cracking and the method typically uses specialized equipment, not simple hand soldering. The other two are wide spread with silver epoxy being the main method and shown in Figure 86. Silver epoxy (Enson EN-06B8, surface resistivity â¤20 mΩ/square/mil) is typically preferred as it fully encases the wire and allows for complete covering of the sample surface with little to no air gaps. The copper tape (resistance through adhesive = 3 â 5 mΩ/square) method completely covers the sample surface, although it relies on the physical contact of the wire to the mineral surface and can allow for small air gaps between the tape, wire, and mineral surface. It is a comparable connection to alligator clips commonly used to temporarily connect wires in research applications, notably to a potentiostat. This method was prioritized in this work as the interactions between the silver in the epoxy and CuFeS2 are not fully understood; silver is known to increase dissolution rates in chalcopyrite. This interaction may not be an issue for other mineral electrochemistry. The resistance of both methods is within 1 order of magnitude of the multi-stranded copper wire and can therefore be considered negligible to experimental data. See section 4.6.3 Effects of Connection Wire in Mineral Massive Electrodes for data effects resulting from the connection wire. 125 Figure 86: (Left Two) Enson EN-06B8 silvery epoxy and it securing a copper wire to a CuFeS2 mineral shown before resin application (Right Two) ¼â copper tape and it securing a copper wire to a CuFeS2 mineral shown after resin application 5.3.1.3 Resin Preparation Mineral massive electrodes are designed to isolate a single surface of a mineral for experimentation. In order to accomplish this, all but one surface must be coated in a chemically and electrically inert substance. Casting resin is an easy choice for ease of application and confidence in repeatable quality. There are many commercial and consumer grade resins suitable for this application, but epoxy resins are able to withstand higher temperatures and harsher chemical environments (both acidic and basic). Refer to the manufacturerâs technical and safety sheets to ensure it meets, and ideally exceeds, the requirements of experimentation. Currently no other material has been found to rival epoxy resin for this application. When working with resins, ensure that all processes where uncured resin is present are performed in a well ventilated area, a fume hood is suggested. Casting epoxies are typically two part resins in which a hardener (part B) is added to resin (part A). The amount of hardener varies for each product; some are 1 to 1, some are 2 to 3 by weight, and others are 2 to 3 by volume. To ensure the epoxy properly cures, follow the selected resinâs specific mix ratio. There is also a specified mixing time suggested by the manufacturer to guarantee proper curing. It is good practice to measure out the correct amounts of parts A and B in separate containers, however this can occur in the same container if care it taken when measuring. Once measured and in the same container, mix part A and B together for at least the specified amount of time, and then pour it into another clean container. This further ensures there is no unmixed resin that makes it into the electrode, which can result in the resin not being able to perform at the manufacturerâs quoted performance. There are reusable resin mixing containers available, but any clean polypropylene (PP), polyethylene (HDPE), or silicone container can work. Circular containers are suggested to ease mixing and prevent collection of unmixed resin in corners. Avoid glass containers even if thermal shock and heat resistant as many resins will adhere well to glass. Also avoid wax lined paper cups; while good for mixing, they may not be able to hold shape when under vacuum. The same suggestions hold for mixing sticks, although wooden craft sticks are commonly used as a disposable option, the flat surface allows for effective mixing (Figure 87). 126 Figure 87: Single use wooden stirring sticks. The small is good for low volume resin stirring. Use anything similar to the right side of large when stirring medium volumes of resin. Large volumes may require specialized mechanically assisted stirring. It is then best to de-gas the resin to remove any entrained air bubbles introduced from mixing. Ensure the container holding the resin is at least twice the volume of the mixed resin as too small a container can result in the resin bubbling over the sides while under vacuum. Make note of the stated working time, if the resin starts curing before it is in contact with the mineral, the viscosity greatly increases and will reintroduce bubbles when pouring and not properly encase the mineral. See section 4.3 Effects of Resin-Mineral Interface for data effects and Figure 88 for examples of properly versus improperly de-gassed resin. Figure 88: Mineral massive electrode (Top Three) with entrained air bubbles in resin resulting from lack of proper de-gassing (Bottom Left) with entrained air bubbles resulting from no de-gassing (Bottom Right) with properly de-gassed resin After de-gassing, the resin can then be poured into the mold that contains the mineral with wire affixed. Depending on the experimental setup, the molds may need to be altered to allow the connection wire to exit 90° from the exposed surface (Figure 89). Bostik Blu-Tack® or similar reusable putty-like adhesive 127 material can be used to reinforce the cut section and allow filling above the connection wire. Select a mold large enough that the connection point of the wire and mineral is completely encased as well as 1 â 2 cm of the wire leading from the mineral (Figure 88 â Bottom Left & Right). This prevents weakening of the wireâs connection to the mineral and the resinâs bond to the wire if the wire needs to be moved during polishing or positioning in the experimental apparatus. Figure 89: (Left) 3 sizes of resin molds (Center) Section removed on blue molds to allow connection wire to exit 90° to the exposure surface to allow for better positioning in experimental setup (Right) Cured resin encasing mineral with connection wire attached with copper tape exiting 90° to the exposure surface It is common practice to use a flame or heat gun to pop any bubbles remaining on the surface of the de-gassed resin once poured over the mineral in the mold. This technique is considered due to the short working times of certain epoxies where the bubbles may not have sufficient time to rise and pop themselves. If this is done, use extreme caution as resins are flammable and overheating can also activate curing. Only expose the flame or heat to the resin surface in short bursts (â¤ 1 second). Once the resin has fully cured based on the manufacturerâs recommended time, typically 24 hours, the electrode can be removed from the mold. At this point the electrode can be polished to desired level; wet sanding with DI water recommended. 5.3.2 Masking No matter how well a mineral massive electrode is constructed, there will always be a resin-mineral interface and it is always subject to an imperfect bond. As shown in section 4.3 Effects of Resin-Mineral Interface, this interface plays a large role in experimental data. Rather than mitigating its effects, a better solution is isolating the interface from solution. Traditional nail polish does this quite well. Other similar lacquers can work, but are typically more expensive and less simple to work with. Traditional nail polish is widely available and comes in a quick drying version which allows for minimized wait times prior to experimentation. It can also be easily removed using a paper towel and acetone. Nail polishâs effectiveness has been confirmed through visual inspection, shown in Figure 90, as well as via SEM imaging in section 4.3 Effects of Resin-Mineral Interface. The exposed area can be clearly seen as it appears much darker, even grey in color, compared to the typical golden color of chalcopyrite. 128 Figure 90: Chalcopyrite Origin B - B1 massive electrode: (Top Left) Step 1 â polished with 1200 grit carbide paper (Top Center) Step 2 â mask boundary marked at SA = 0.442 cm2 (Top Right) Step 3 â nail polish mask applied at least 2 mm past resin-mineral interface (Bottom Left) Step 4 â galvanostatic exposure at 1 mA in 100 mL of 2 g/L H2SO4 @ 21°C (Bottom Right) Step 5 â mask removed with paper towel soaked in acetone Before masking can be applied, the electrode surface should be prepared for experimentation. This typically means the mineral should be polished. It is beneficial to sonicate for a minimum of 1 min in de-ionized (DI) water to remove any debris from polishing and allowed to dry naturally for a minimum of 5 min, either in stagnant air or gently forced air from a fume hood. A forced air dryer (i.e. hair dryer, heat gun) can heat or cool the surface of the electrode and/or dry it out to quickly, causing cracking. Wiping can damage the polished surface, leave foreign residues or particles that can affect experimental conditions, and will not remove water trapped in the mineralâs pours or the resin-mineral interface. Once dry, the desired experimental surface can now be isolated as shown in Figure 90. This area is typically selected during electrode production as the mineral should be large enough to allow space between the resin-mineral interface and the edge of isolation. The surface area is marked with a permanent marker using a stencil for reproducibility. Color selection of the permanent marker and mask should allow for quick visual identification of the mask boundary (blue), mask (red), and mineral (gold). A circle is the ideal shape for the majority of experiments as it removes the possibility for geometric corrosion tendencies to effect results. The permanent marker acts as an effective mask; however, there is no consistent way to ensure the entire surface is covered as a 1200 grit polished surface still has many undulations that permanent marker ink cannot consistently permeate into. Therefore, the mask material should start from the inside edge of the circle and move outwards to a minimum of 2 mm past the resin-mineral interface. This ensures that in the event the mask does not effectively adhere at the 129 resin-mineral interface, there is enough surrounding mask to compensate and ensure complete isolation from solution. After experimentation, the mask and circle can be removed with a paper towel soaked with acetone. This surface is now ready for observation or it can be polished and the masking process repeated for further experimentation. 5.3.3 Luggin Capillary Mitigating, isolating, or controlling all variables in mineral electrochemistry allows for the best opportunity to obtain reproducible and replicable data. Using a Luggin capillary is common laboratory practice as it allows for precise sensing of the working electrode and reduces any potential drop resulting from solution resistance. When combined with masking of a circular surface area, there is increased confidence that the data acquired is accurate to the mineral. The porous glass frit at the solution barrier of the Luggin capillary has the added benefit of minimizing cross-contamination of experimental and reference electrode solutions, especially regarding chloride ions. However, the glass frit has a limited lifespan. There are a few identifiers that the frit is no longer usable and needs to be replaced: a) No longer clear, but cloudy, white, or opaque (see Figure 91) b) Data shows sudden millisecond spikes and/or deviates greatly from expected c) When experimenting in a different solution composition (e.g. H2SO4 to HCl) In order to extend the lifespan of the glass frit, perform a DI water wash between experiments and submerge and fill with DI water when not in use or being stored. Figure 91: (Left & Center) Luggin capillary with un-usable opaque glass frit (Right) Luggin capillary with brand new glass frit The placement of the Luggin capillary in relation to the experimental surface can affect the results obtained. It is common laboratory practice to move the glass frit as close as possible to the edge of the mineral without overlapping, or casting a shadow over, the experimental surface (Figure 92). Specific data effects have not be reported, however covering the surface has been proven by this work to affect results. Until proven otherwise, the recommendation is to continue this practice as well as keeping the working and reference electrodes the same distance from the counter electrode across multiple experiments. 130 Figure 92: Ideal Luggin capillary placement near experimental surface of mineral massive electrode 5.3.4 Summary of Techniques for Reproducible Data in Mineral Electrochemistry Using these recommendations do not guarantee variability free experiments, but rather reduces the variability from external sources. They isolate the variability to the mineral itself, which can then inform mineral processing of its parent ore. Some techniques will have a greater impact than others, but together they have been shown in this work to result in what was previously considered unattainable. 1) Resin-mineral interface masking on mineral massive electrodes a. Circular exposed surface b. Use same exposed surface area for all electrodes used 2) Mineral characterization for each electrode and its parent ore 3) Proper electrode construction practices a. Mineral selection and preparation â intentional selection, avoid cracks and voids b. Connection wire preparation â multi-strand copper wire with low resistance affixing c. Resin preparation â manufacturerâs guidelines and de-gas 4) Luggin capillary a. Proper placement â closest to edge of mask while not overlapping exposed surface area b. Well maintained glass frit 5) Report all experimental conditions a. Solution type and concentration b. Agitation rates â avoid vortex and cavitation formation, too low sparging flow rates c. Temperature 5.4 Recommendations for Further Investigation While investigating variability in mineral electrochemistry, I came across many potential error sources, but determined my focus was best spent on the fundamental methods and those that appeared to be the largest effectors, the main being the resin-mineral interface in mineral massive electrodes. Therefore, I have accumulated exploratory data and trend identifications that require further 131 investigation to further encompass all potential sources of variability. The goals being to remove them from consideration, provide mitigation methods, and/or determine their quantifiable effect to better understand acquired data. 1) Working electrode internal resistance a. A mineralâs internal resistance will have a direct effect on the data acquired. Potential and current are either applied or observed, leaving resistance as the medium through which data is collected. Therefore, resistance provides inherent characterization of a mineral. Observed variation in data may be further decreased if it can be normalized through resistance values and may provide unique insight to hydrometallurgical dissolution recalcitrance in copper sulfites. b. A way to confidently and reliably measure internal resistance will need to be standardized. Using a multimeter (e.g. Fluke 289 True RMS Multimeter) with traditional point source leads will provide varying value readouts across the surface. Bespoke leads may need to be crafted. c. The changing thickness of a mineral massive electrode resulting from polishing between experiments suggests that the internal resistance may change a non-negligible amount as more experiments are run on a sample and effect acquired data 2) Working electrode mineral porosity, crystal structure, and grain structure a. A mineralâs porosity will directly affect its reactiveness and result in a similar effect as seen by a more course surface polish and/or the resin-mineral interface. Determining a way to repeatedly measure/quantify porosity may provide more insight to what is currently considered under the umbrella of mineral variability, including what was measure by this workâs data. i. A mitigation method needs to be determined that is as effective as the masking of the resin-mineral interface. Therefore, the method should allow for quick confirmation of effectiveness and confidence in application method. ii. This method may also be able to effectively isolate cracks in the mineral, mitigating the results of section 4.6.1 Effects of Cracks in Massive Electrodes b. A mineralâs crystal and grain structures will directly affect its reactiveness and dissolution rates. These are largely unreported across literature. There are some literature doing specific studies on crystal structure that make comment on this, but otherwise they are effectively ignored. Understanding these may provide more insight to what is currently considered under the umbrella of mineral variability, including what was measure by this workâs data. 3) Silver paste effect on Cu containing minerals a. Related to working electrode internal resistance, the internal resistance and/or observed polarization data of Cu bearing minerals may appear lower than true in mineral massive electrodes given silverâs ability to increase Cu dissolution 4) Distance between working electrode and counter electrode in traditional three-electrode cell a. This is effectively suggesting solution resistance may play a role in variability. The solution resistances I have seen published in literature, their reported negligence, and 132 observation of my low error data in which millimeter variations in distance between WE and CE placement occurred, this appears to have a negligible effect. However, I have not been able to find a published work where this effect is directly studied. There may exist a traditional cell orientation that solution resistance becomes non-negligible, especially when compared to experiments with substantially less distance between the WE and CE 5) Working electrode and Luggin capillary orientations in relation to counter electrode in traditional three-electrode cell a. Related to WE and CE separation distance, I have not been able to find published work on the effect of WE or Luggin capillary orientation. All data reported in this work were acquired with the WE surface and Luggin capillary being perpendicular to the CE (see Figure 37 and Figure 38 in section 3.4 Electrochemical Cell and Figure 92 in section 5.3.3 Luggin Capillary). How might the data change if the WE stayed perpendicular, but the Luggin capillary moved in line? What if the Luggin capillary stayed perpendicular, but the WE faced the CE? 6) Non-electrically connected conductive and non-conductive rod interaction with working electrode by shielding/casting a shadow across it, or in physical contact a. Reference electrode/Luggin capillary (investigation preceded the determination of masking importance and recommended techniques for reducing variability in mineral electrochemistry) â RE is connected to potentiostatâs electrical circuit, but observations of RE positioning resulted in further experimentation with non-electrically connected electrical path obstructions. Investigation of electrically connected obstructions may be more indicative of mineral interactions in solution when considering effects in slurries (related to coupled massive electrode WE experimentation, e.g. pyrite and chalcopyrite) and worth exploring. Visual observation of passivating coloration on WE surface suggesting interaction resulting from RE being placed over/shielding/casting a shadow on the WE surface is shown in Figure 93 and Figure 94. i. I postulate this may have occurred at least in part by chloride from the RE interacting with the WE surface given no Luggin capillary was used Figure 93: Galvanostatic polarization (GAL) applied at 1 mA (WE unmasked, no Luggin capillary) for 360 s to an Origin A CuFeS2 massive electrode (characterization data in Table 5 â Table 17) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area = 3.011 â 6.481 cm2. (Left) polished pre-exposure (Center) electrochemical cell with RE close to resin-mineral interface (Right) post-exposure showing visually different passivation near RE placement 133 Figure 94: Galvanostatic polarization (GAL) applied at 1 mA (WE unmasked, no Luggin capillary) for 360 s to an Origin A CuFeS2 massive electrode (characterization data in Table 5 â Table 17) in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area = 3.011 â 6.481 cm2. (Left) Luggin capillary distance from WE surface (Center) RE placed directly over WE surface (Right) post-exposure showing visually different passivation near RE placement b. Conductive (e.g. carbon used for CE) and non-conductive (e.g. HDPE) non-electrically connected rods in contact with WE surface. Three conductive and one non-conductive rod lengths were investigated (Table 31). Experimental setup identical to description in section 3.4 Electrochemical Cell with addition of non-electrically connected rod (Figure 95). Rod is not connected to potentiostatâs electrical circuit, it is simply in solution and centered on massive electrode exposed surface. Rod is weighed down to ensure constant contact. WE surface after galvanostatic polarization (Table 32, Table 33) and comparative data (Figure 97). Figure 96 is a diagram of theorized interaction. Figure 95: Images of an experiment showing electrochemical cell experimental setup. Luggin capillary intentionally placed to not cover mineral and have WE and RE in-line with CE. The non-electrically connected rods were weighed down (Bottom Center) Version 1 = 102.64 g (Bottom Right) Version 2 = 104.00 g â reduced rod holder overhang, made rod switching simpler 134 Table 31: Dimensions and surface areas for non-electrically connected rods in carbon and plastic Rod Material Carbon Plastic Reference Name Large Medium Small HDPE Length (cm) Diameter (cm) Rod End SA (cm2) 0.196 0.196 0.196 0.385 Total SA (cm2) 2.867 1.296 0.511 4.783 Table 32: Images of chalcopyrite Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 100 μA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. SAMasked = 0.442 cm2. Non-electrically connected rod placed in contact in center of massive electrode for duration of experimentation. Reference Table 31 for rods used. Galvanostatic Polarization [Current Density] Rod [Contact SA (cm2)] Before Exposure After Exposure After Acetone 100 μA [226.24 μA/cm2] No Rod Carbon â Large [0.196] Carbon â Medium [0.196] Carbon â Small [0.196] Plastic â HDPE [0.385] 135 Figure 96: Diagram of theorized interaction between non-electrically connected conductive and non-conductive rods contacting WE surface when polarized. A competing theory is the first state shown remains with the passivated area increasing with time, but not moving under the contact area of the rod. Table 33: Images of chalcopyrite Origin A â A1 massive electrode (characterization data in Table 5 â Table 17, Figure 18 â Figure 19) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. SAMasked = 0.442 cm2. Non-electrically connected rod placed in contact in center of massive electrode for duration of experimentation. Reference Table 31 for rods used. Galvanostatic Polarization [Current Density] Rod [Contact SA (cm2)] Before Exposure After Exposure After Acetone 1 mA [2262.44 μA/cm2] No Rod Carbon â Large [0.196] Carbon â Medium [0.196] Carbon â Small [0.196] Plastic â HDPE [0.385] 136 Figure 97: Galvanostatic polarization (GAL) applied at 1, 10, and 100 μA and 1 mA data for CuFeS2 massive electrode Origin A â A1 (characterization data in Table 5 â Table 17, Figure 18, Figure 19) masked in 100 mL of stagnant 2 g/L H2SO4 @ 21°C polished to 1200 grit with carbide paper. Surface area with mask = 0.442 cm2. Non-electrically connected rods from Table 31 placed in contact with WE surface. All lines represent average of four experiments except 2.26 μA/cm2 â Plastic HDPE represents three. All lines with two-sided t-distribution 95% CI error bars. c. Conductive (e.g. carbon used for CE) and non-conductive (e.g. HDPE) non-electrically connected rods suspended at a varying distances above the WE. Same experimental conditions and rods as the previous investigation suggestion (Figure 95, Table 31) except rod is suspended 5 mm above WE (Figure 98). No data is displayed for experiments due to resin-mineral interface not being masked and reference electrode not placed in Luggin capillary. See Table 34 for observed surfaces post experimentation. Similar theory is expected as shown in Figure 96 and Figure 100, but is observed to a lesser extent. 137 Figure 98: Images of an experiment showing electrochemical cell experimental setup. Reference electrode (without Luggin capillary) intentionally placed to not cover mineral and have working and reference electrode in-line with counter electrode. Non-electrically connected rod suspended at 5 mm above, with bottom surface parallel to, WE surface. Table 34: Images of two chalcopyrite massive electrodes (top and bottom Origin A: SAA = 3.011 â 6.481 cm2 and middle Origin B: SAB = 3.137 â 6.679 cm2) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Non-electrically connected rod placed 5 mm over center of massive electrode for duration of experimentation. Reference Table 31 for rods used. Galvanostatic Polarization [Current Density] Rod 5 mm from WE [Parallel SA (cm2)] Before Exposure After Exposure 1 mA [332.12 â 154.29 μA/cm2] Carbon â Large [0.196] 1 mA [318.78 â 149.72 μA/cm2] Carbon â Medium [0.196] 1 mA [332.12 â 154.29 μA/cm2] Carbon â Small [0.196] 138 d. Conductive (e.g. carbon used for CE) and non-conductive (e.g. HDPE) non-electrically connected rods placed at a varying distances between the WE and CE. Same experimental conditions and rods as the previous investigation suggestion (Figure 95, Table 31) except rod is centered in front of WE which is facing the CE (Figure 99). Multiple rods can be placed in-between WE and CE. No data is displayed for experiments due to resin-mineral interface not being masked and reference electrode not placed in Luggin capillary. See Table 35 for observed surfaces post experimentation. Figure 100 is a diagram of theorized interaction, similar to that shown in Figure 96. Figure 99: Images of an experiment showing electrochemical cell experimental setup. Reference electrode (without Luggin capillary) intentionally placed to not cover mineral and have working and reference electrode in-line with counter electrode. (Top Three) Non-electrically connected rod suspended at 2 mm in front of and parallel to WE surface in line with CE (Bottom Left) Non-electrically connected rod suspended at 2 mm in front of and parallel to WE surface in line with CE (Bottom Right) Non-electrically connected rod placed halfway between first rod and CE, approximately 1.5 cm space on either side 139 Table 35: Images of two chalcopyrite massive electrodes (1st and 4th Origin A: SAA = 0.816 â 2.623 cm2 ; 2nd, 3rd, and 5th Origin A: SAA = 3.011 â 6.481 cm2) via native camera sensor and application on an iPhone 8 running iOS 14.4 after galvanostatic polarization applied at 1 mA for 360 s in 100 mL of 2 g/L H2SO4 @ 21°C polished to 1200 grit. Non-electrically connected rod placed 2 mm in front of and centered on massive electrode whose surface is facing counter electrode for duration of experimentation. Reference Table 31 for rods used. Galvanostatic Polarization [Current Density] Rod 2 mm from WE [Diameter (cm)] Experimental Setup Before Exposure After Exposure 1 mA [1225.49â381.29 μA/cm2] Carbon â Large [0.5] 1 mA [332.12 â 154.29 μA/cm2] Carbon â Large [0.5] 1 mA [332.12 â 154.29 μA/cm2] Carbon â Large (2 mm) Carbon â Large (15 mm) [0.5] 1 mA [1225.49â381.29 μA/cm2] Plastic â HDPE [0.7] 1 mA [332.12 â 154.29 μA/cm2] Plastic â HDPE [0.7] Figure 100: Diagram of theorized interaction between non-electrically connected conductive and non-conductive rods near WE surface when polarized. A competing theory is the first state shown remains with the passivated area increasing with time, but not moving under the shielded area of the rod. 140 5.4.1 Graduate Studies Welcome Package Whenever a graduate student enters into the research portion of their degree, it is very common for them to experiment without clear direction. Sometimes this can result in unintentional observations that result in exciting discoveries; however, this is quite rare. Much time is lost floundering around with experiments as they seem to provide data and therefore must be valuable. While it is the intent for the act of going through graduate studies to provide the space to teach the graduate student and provide them space to fail and learn from it, there is a surprisingly large gap between where the graduate student needs to be for successful and usable data and where they start out. A lot of the information the student comes in with is a result of limited, guided laboratory time through undergraduate studies. This is obvious and intended as the stepping stone to even be considered a graduate. However, the jump from guided to autonomous is large and lots gets lost in between. This is all to say, there is valuable information the myriad graduate students before have learned that does not get passed on to the next class. When it comes to mineral electrochemistry, industry and research is far behind the likes of non-mineral electrochemistry. With this comes much confusion as published works are still unable to agree on best methods for performing what should be basic experiments; hence the inspiration for this masterâs thesis. In short, it is advised that this thesis is provided to all incoming graduate students within the materials engineering department as part of a welcome package of papers published from the department to provide them with the advantage of understanding the importance of the actions they take to acquire their data and have a more clear understanding about how those actions can affect their data and provide a way to decipher and translate it for others to understand and use. 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Minerals, 9(1). https://doi.org/10.3390/min9010011
Thesis/Dissertation
eng
Materials Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Asselin, Edouard
Exploring variability in mineral electrochemistry using chalcopyrite as an example
Text