Applied Science, Faculty of
Mining Engineering, Keevil Institute of
DSpace
UBCV
Boldbaatar, Serdamba
Master of Applied Science - MASc
University of British Columbia
Efficiently removing water from oil sands tailings remains a persistent challenge for the oil sands industry. Although substantial research has focused on flocculating these tailings, a direct link between rapid settling rates and effective filtration has not been fully established. This thesis investigates how major cations and anions in industrial process water affect both flocculation and subsequent vacuum filtration of a model blend (75% quartz, 25% kaolinite) that simulates mature fine tailings (MFT). In addition, it explores the potential to enhance flocculated sediment structure during vacuum filtration by introducing coagulants (specifically calcium and aluminum) after flocculation. Experimental findings revealed that measuring settling rates and turbidity in suspensions exceeding 20-25 wt% solids was challenging due to extremely slow settling, even when higher polymer dosages and prolonged settling times were employed. Consequently, all flocculation tests were performed at 10–15 wt% solids. Zeta potential analyses demonstrated the key role of calcium in reducing the negative surface charge on quartz and kaolinite, thus promoting the flocculation of model blends. Although introducing calcium improved supernatant clarity, it also yielded smaller flocs. In contrast, conditions that promoted the formation of larger flocs resulted in higher filtrate volumes, underscoring the importance of floc size for filtration performance. Post-flocculation additions of calcium or aluminum improved filtration under low vacuum conditions; however, excess aluminum was found to hinder performance by causing polymer chain collapse and reducing floc size.
STRENGTHENING FLOC STRUCTURE DURING FILTRATION OF FLOCCULATED TAILINGS by Serdamba Boldbaatar B.Sc., Donetsk National Technical University, 2012 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 (Mining Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) June 2025 © Serdamba Boldbaatar 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: Strengthening Floc Structure During Filtration of Flocculated Tailings submitted by Serdamba Boldbaatar in partial fulfillment of the requirements for the degree of Master of Applied Science in Mining Engineering Examining Committee: Dr. Marek Pawlik, Professor, Mining Engineering, UBC Supervisor Dr. Maria E. Holuszko, Associate Professor, Mining Engineering, UBC Supervisory Committee Member Dr. Scott Dunbar, Professor, Mining Engineering, UBC Supervisory Committee Member iii Abstract Efficiently removing water from oil sands tailings remains a persistent challenge for the oil sands industry. Although substantial research has focused on flocculating these tailings, a direct link between rapid settling rates and effective filtration has not been fully established. This thesis investigates how major cations and anions in industrial process water affect both flocculation and subsequent vacuum filtration of a model blend (75% quartz, 25% kaolinite) that simulates mature fine tailings (MFT). In addition, it explores the potential to enhance flocculated sediment structure during vacuum filtration by introducing coagulants (specifically calcium and aluminum) after flocculation. Experimental findings revealed that measuring settling rates and turbidity in suspensions exceeding 20-25 wt% solids was challenging due to extremely slow settling, even when higher polymer dosages and prolonged settling times were employed. Consequently, all flocculation tests were performed at 10–15 wt% solids. Zeta potential analyses demonstrated the key role of calcium in reducing the negative surface charge on quartz and kaolinite, thus promoting the flocculation of model blends. Although introducing calcium improved supernatant clarity, it also yielded smaller flocs. In contrast, conditions that promoted the formation of larger flocs resulted in higher filtrate volumes, underscoring the importance of floc size for filtration performance. Post-flocculation additions of calcium or aluminum improved filtration under low vacuum conditions; however, excess aluminum was found to hinder performance by causing polymer chain collapse and reducing floc size. iv Lay Summary Dealing with the leftover mix of water and fine minerals called tailings. It is one of the big challenges in oil sands operations. Removing water from tailings more effectively not only cuts down on waste but also makes it possible to reuse that water, which helps lower costs and reduce environmental impact. In this study, a mix of quartz and kaolinite was used to mimic real tailings. The author looked at a process called flocculation, where added chemicals help tiny particles stick together and settle out of the water. When calcium, something already found in process water, was added, the water became noticeably clearer. That is because the calcium helped reduce the surface charge on the particles, making it easier for them to clump together. Even better results came when small amounts of calcium or aluminum were added after flocculation, improving the filtration step. But too much aluminum actually made things worse, making water removal harder. These results offer useful guidance for improving water recovery in tailings treatment, benefiting both industry performance and environmental sustainability. v Preface This research began with a concept proposed by Dr. Marek Pawlik, who suggested that improving the mechanical strength of flocculated sediments could lead to better dewatering outcomes. That idea became the starting point for the bench-scale flocculation experiments that followed. As part of the study, I conducted zeta potential measurements using the Zeta View® PMX 100 V2.0 and ran vacuum filtration tests with a Millipore setup. The process water used in the experiments was generously provided by Dr. Givemore Sakuhuni from Imperial Oil, and water chemistry was analyzed through a commercial lab. All experimental work for this thesis was carried out by me at the University of British Columbia between 2022 and 2024. I was responsible for preparing samples, performing the tests, collecting results, and analyzing the data. Throughout the project, I met regularly with Dr. Pawlik and Dr. Sakuhuni, whose feedback and advice helped guide the work and improve the overall direction of the study. Generative AI tools were not used in any aspect of the research, analysis, writing, or preparation of this thesis. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables .............................................................................................................................. viii List of Figures ............................................................................................................................... ix List of Pictures................................................................................................................................x List of Symbols ............................................................................................................................. xi List of Abbreviations .................................................................................................................. xii Acknowledgements .................................................................................................................... xiii Chapter 1: Introduction ................................................................................................................1 1.1 Introduction and Research Objectives ............................................................................ 1 1.2 Background ..................................................................................................................... 2 1.3 Experimental Procedure .................................................................................................. 4 1.3.1 Materials ................................................................................................................. 4 1.3.2 Flocculation Tests ................................................................................................... 8 1.3.3 Turbidity Measurement ......................................................................................... 10 1.3.4 Zeta Potential Experiments ................................................................................... 11 1.3.5 Vacuum Filtration Tests ........................................................................................ 13 Chapter 2: Optimum Flocculation Conditions..........................................................................16 2.1 Flocculation Tests ......................................................................................................... 16 2.1.1 Flocculation Tests at Natural pH .......................................................................... 16 vii 2.1.2 Flocculation Tests of Pure Quartz and Kaolinite .................................................. 20 2.2 Effect of Industrial Process Water on the Flocculation of Model Blend ...................... 24 Chapter 3: The Zeta Potential of Quartz and Kaolinite ..........................................................29 Chapter 4: Vacuum Filtration Tests ..........................................................................................32 4.1 Baseline Test Using 0.01 mol/ NaCl ............................................................................. 32 4.2 Effect of Calcium Ions on Vacuum Filtration............................................................... 34 4.3 Effect of Floc Size on Vacuum Filtration Performance................................................ 36 4.4 Effect of Adding Ca2+ and Al3+ After Flocculation on Filtration.................................. 40 4.4.1 Hypothetical Decantation Scenario and Water Balance ....................................... 43 Chapter 5: Recommendation for Further Research .................................................................46 Chapter 6: Conclusion .................................................................................................................47 Bibliography .................................................................................................................................51 Appendix A Particle size analysis of quartz and kaolinite ........................................................... 53 Appendix B BET Specific Surface Area Results .......................................................................... 55 Appendix C Flocculation tests data .............................................................................................. 57 Appendix D Zeta potential test data.............................................................................................. 59 Appendix E Vacuum filtration ...................................................................................................... 62 viii List of Tables Table 1. Degree of anionicity of CYFLOCTM flocculants .............................................................. 6 Table 2. Process water analysis ...................................................................................................... 7 Table 3. BET-specific surface area of quartz and kaolinite from various studies ........................ 22 Table 4. Conversion of Process Water Results from mg/L to mol/L............................................ 25 Table 5. Salt Additions to Reproduce the Ion Composition of Industrial Process Water ............ 25 Table 6. Flocculant selection tests in 0.01 mol/l NaCl at natural pH ........................................... 57 Table 7. Flocculation tests on pure quartz and kaolinite samples ................................................. 57 Table 8. Flocculation test results .................................................................................................. 58 Table 9. Zeta potential of quartz in NaCl ..................................................................................... 59 Table 10. Zeta potential of quartz in NaHCO3 ............................................................................. 59 Table 11. Zeta potential of quartz in Na2SO4 ............................................................................... 59 Table 12. Zeta potential of quartz in CaSO4 ................................................................................. 60 Table 13. Zeta potential of kaolinite in NaCl ............................................................................... 60 Table 14. Zeta potential of kaolinite in NaHCO3 ......................................................................... 60 Table 15. Zeta potential of kaolinite in Na2SO4 ........................................................................... 61 Table 16. Zeta potential of kaolinite in CaSO4 ............................................................................. 61 Table 17. Effect of vacuum pressure on filtration performance ................................................... 62 Table 18. Effect of the flocculant dosages on filtration performance ........................................... 62 Table 19. Effect of adding calcium after flocculation on filtration performance ......................... 63 Table 20. Effect of adding aluminum after flocculation on filtration performance ...................... 63 ix List of Figures Figure 1. Particle size distribution of quartz and kaolinite ............................................................. 5 Figure 2. The settling rate and supernatant turbidity vs solids percentage for flocculant selection in 0.01 mol/l NaCl at natural pH. Tests were conducted using the flocculants dosage of 100 g/t, and the results represent the average of duplicate tests. ............................................................... 17 Figure 3. Relationship between surface charge and the properties of concentrated suspensions (The figure came from Laskowski and Pugh, 1992) ..................................................................... 19 Figure 4. The settling rate and supernatant turbidity vs solids percentage for quartz and kaolinite in 0.01 mol/l NaCl at pH 5.9, with flocculant A-110 at 100 g/t ................................................... 21 Figure 5. Effect of process water major cations and anions on the flocculation of model blend in 0.01 mol/l NaCl at pH 8. The test results represent the average of duplicate tests....................... 27 Figure 6. Flocculation tests on industrial and synthetic process water. The test results represent the average of duplicate tests ........................................................................................................ 27 Figure 7. Zeta potential of quartz vs CaSO4, NaCl, NaHCO3 and Na2SO4 concentrations ........... 30 Figure 8. Zeta potential of kaolinite vs CaSO4, NaCl, NaHCO3 and Na2SO4 concentrations ...... 30 Figure 9. Baseline vacuum filtration test results of a model blend using 0.01 mol/L NaCl. The test results represent the average of duplicate tests. ..................................................................... 33 Figure 10. Vacuum filtration tests using NaCl vs NaCl+CaSO4 as background electrolytes. ..... 34 Figure 11. Effect of the polymer dosages on filtration performance ............................................ 36 Figure 12. Effect of adding calcium and aluminum after flocculation on filtration performance 40 x List of Pictures Picture 1. Malvern Mastersizer 2000 .............................................................................................. 5 Picture 2. 4 L mixing beaker, plunger, and 2 L graduated cylinder setup ...................................... 9 Picture 3. Turbidity measurement using the Hach Model 2100AN laboratory turbidimeter (left) and turbidity calibration standards from 75 to 2000 NTU (right). ............................................... 10 Picture 4. Zeta potential analysis using the ZetaView® PMX 100 V2.0 instrument (left) and a representative output report for kaolinite particles (right), showing particle count, zeta potential distribution, and electrophoretic mobility analysis. ...................................................................... 11 Picture 5. Process flow diagram of vacuum filtration test ............................................................ 14 Picture 6. Settling rate measurement based on interface height difference .................................. 17 Picture 7. Floc formation at increasing A-110 polymer dosages using 0.01 mol/L NaCl + 0.0023 mol/L CaSO₄ as the background ....................................................................................... 38 Picture 8. Vacuum filtration test showing floc structure at the beginning (left) and end (right) of a 20-minute cycle at 5 kPa. .............................................................................................................. 39 Picture 9. Vacuum-filtration after post-flocculation aluminum additions: (a) 50 g/t (left) coarse, porous cake and clear supernatant; (b) 200 g/t (right) fines with cloudy supernatant. ................. 41 Picture 10. Initial stage of filtration showing clear supernatant and settled flocs ........................ 43 xi List of Symbols Δh [cm] Suspension height difference Δt [sec] Settling time Filt % [%] Accumulated filtrate percentage 𝑀𝑓 [g] Mass of the filtrate 𝑀𝑖 [g] Mass of the initial water for a test P kPa Applied Vacuum during filtration tests V [m/h] or [cm/sec] Settling rate vol % [%] Volume concentration wt % [%] Mass concentration ζ mV Zeta potential of a particle xii List of Abbreviations A-110 - Anionic PAM flocculant BET SSA - Brunauer-Emmett-Teller Specific Surface Area CaSO4 - Calcium Sulfate FCF - Flocculation-Coagulation-Flocculation MFT - Mature Fine Tailings MgSO4 - Magnesium Sulfate NaCl - Sodium Chloride NaHCO3 - Sodium Bicarbonate Na2SO4 - Sodium Sulfate NTU - Nephelometric Turbidity Unit PAM - Polyacrylamide PSD – Particle Size Distribution PW - Process Water SSA - Specific Surface Area TOC - Total Organic Carbon xiii Acknowledgements I am incredibly grateful to Dr. Marek Pawlik for his steady guidance and mentorship throughout my research. His encouragement made a real difference, and I deeply appreciate being welcomed into his research group. It was a great place to learn and grow, both academically and personally. Studying at UBC, especially in the Mining Engineering Department, has been an unforgettable experience. I would also like to thank Dr. Givemore Sakuhuni for his honest advice and for sharing his practical knowledge. His input gave this work a stronger connection to industry. I am thankful to Frank Yan for helping with equipment setup, and his support helped keep everything running smoothly. Lastly, I want to thank my partner, Anudari, for always being patient and encouraging. And to our son, Temuujin, thank you for reminding me every day why this work matters. 1 Chapter 1: Introduction 1.1 Introduction and Research Objectives Alberta’s oil sands are one of Canada’s most important natural resources, playing a central role in the national economy and energy supply. With an estimated reserve of 158.9 billion barrels, they rank as the fourth-largest crude oil deposit in the world, behind Venezuela, Saudi Arabia, and Iran (Oil Sands Facts and Statistics | Alberta.Ca, 2024). However, industrial processes used to extract and upgrade bitumen, such as surface mining and hot water separation, produce large volumes of tailings. These tailings are known as mature fine tailings (MFT), which contain about 30–40 wt% fine clays and 1–3 wt% residual bitumen. One of the major environmental challenges associated with MFT is their long-term water retention. The fine particles in MFT settle very slowly, and the water trapped within the structure of the flocs can take decades to release naturally. As a result, tailings ponds continue to expand, posing environmental and operational concerns. By 2020, these ponds covered an estimated 270 square kilometers in northern Alberta (Alberta, 2010). Improving water recovery from MFT is a critical step toward more sustainable tailings management. Dewatering technologies make it possible to recycle process water and reduce the environmental footprint of tailings storage. However, efficient dewatering depends not only on sedimentation but also on the formation of strong, permeable flocs that can retain their structure during mechanical filtration or drying. This study explores the influence of process water quality and the addition of coagulants after flocculation on filtration outcomes. By systematically adjusting these variables, the research aims to promote the formation of floc structures that improve water removal during dewatering. The 2 objective is to understand better the relationship between water chemistry, post-treatment additives, and the physical characteristics of flocs that contribute to efficient filtration. 1.2 Background Tailings management plays a critical role in oil sands and mineral processing operations, where the emphasis is on recovering as much water as possible while reducing the accumulation of fine solid waste. As particles become finer, the performance of traditional dewatering methods, such as thickening, centrifugation, and filtration, tends to decline. To overcome these limitations, many operations adopt flocculation techniques. In this process, high molecular weight polymers are used to bridge fine particles, encouraging the formation of larger clusters called flocs. These flocs tend to settle more quickly, and their formation often leads to a clearer supernatant. Both traits are commonly regarded as indicators of successful flocculation. However, strong settling performance and supernatant clarity do not always translate to improved results in downstream dewatering steps. Earlier studies have shown that combining coagulation with flocculation can enhance settling rates (Kitchener, 1972). More recently, advanced strategies such as sequential flocculation–coagulation–flocculation (FCF) have aimed to produce larger flocs and achieve better overflow clarity by targeting different particle populations in each step (Yuan & Shaw, 2007). Despite these improvements in settling behavior, the influence of such strategies on filtration performance remains unclear. A key factor that connects upstream flocculation to downstream outcomes is floc strength, which refers to a floc’s resistance to disruption under shear, pumping, or compressive forces. Flocs that are mechanically weak tend to fragment under stress, releasing fine particles that reduce permeability and impede water removal. Researchers have used a range of tools from shear and ultrasonication testing to microscopic analysis to evaluate this property. The results show that 3 small, tightly bonded flocs are generally more stable (Klimpel & Hogg, 1991), while large macro-flocs often exhibit weaker mechanical stability. Vold (1963) described these macro-structures as being held together by loose physical entanglement rather than strong chemical bonds, making them more susceptible to breakage. Although large floc size is often associated with improved filtration, empirical evidence supporting this assumption is limited. For example, Zhu et al., (2017) found that dual-polymer systems applied to oil sands tailings did not consistently lead to higher solids content in filter cakes, even at elevated polymer dosages. In contrast, Loerke et al., (2017) reported better filtration outcomes when using polyethylene oxide (PEO) instead of polyacrylamide. The improved performance was attributed to the greater chain flexibility of PEO, which allowed for the creation of more compact and robust flocs that were less prone to collapsing during filtration. Advanced imaging techniques, such as X-ray computed tomography, have further clarified how floc structures change under pressure. MacIver et al., (2019) observed that large flocs tend to fragment into smaller sub-units during low-pressure filtration, leading to denser sediments composed of intermediate-sized flocs. At higher filtration pressures, even these compact aggregates may collapse, reducing permeability further (MacIver et al., 2022). These findings suggest that while large flocs may benefit settling, they can become unstable and hinder filtration performance under mechanical stress. Taken together, these studies point to an important conclusion: settling behavior alone is not a reliable predictor of filtration efficiency. Because flocs experience structural changes during compression, evaluating their performance requires understanding not only their initial formation but also how they behave under shear and pressure. Polymer characteristics, bonding mechanisms, and the arrangement of solids all influence this behavior. For these reasons, it is essential to assess 4 flocculation strategies with both settling and filtration performance in mind to improve overall tailings dewatering outcomes. 1.3 Experimental Procedure 1.3.1 Materials Pure quartz (Fisher Scientific) and kaolinite (Ward's Science) were selected as model minerals to represent the primary constituents of mature fine tailings (MFT). Illite shale rock (Ward's Science) was also initially considered. Quartz and kaolinite were received in fine pulverized form, while the illite shale was supplied as coarse, flat rock pieces. Despite multiple attempts using dry pulverization methods, the illite samples did not meet the required particle size criteria. Therefore, illite was excluded from further testing. A simplified model blend consisting of 75% kaolinite and 25% quartz by mass was prepared to mimic the dominant mineral components found in MFT. This decision was based on both the literature and technical guidance. Early studies, including Sworska et al., (2000), confirmed the presence of kaolinite, quartz and illite, as the principal minerals in Syncrude MFT, though without reporting specific percentages. Subsequent work by Yuan & Shaw, (2007) provided detailed compositional data across multiple samples, reporting ranges of 28–52% quartz, 28–35% kaolinite, and 18–36% illite, depending on the sampling location. More recently, Loerke et al., (2017) reported a mineral composition of 36.0% kaolinite, 27.4% quartz, and 30.7% illite based on XRD analysis of Syncrude fine tailings. These studies consistently support kaolinite and quartz as the dominant phases in MFT. After consulting with Dr. Givemore Sakuhuni (Imperial Oil), the 75:25 kaolinite-to-quartz ratio was selected as a practical and representative model system. 5 The particle size distribution of pure quartz and kaolinite was determined using a Malvern Mastersizer 2000 particle size analyzer (Picture 1). The specific surface area of quartz and kaolinite samples was measured using a BET analyzer. Picture 1. Malvern Mastersizer 2000 Figure 1. Particle size distribution of quartz and kaolinite 6 As shown in Figure 1, the pure kaolinite sample has a particle size of Dv (10) <1.7 μm, Dv (50) <5.4 μm, and Dv (90) <23.7 μm. Meanwhile, the particle distribution for quartz showed values of Dv (10) <0.7 μm, Dv (50) <2.2 μm, and Dv (90) <8.1 μm. Polyacrylamide (PAM)-based CYFLOCTM A-100, A-110 and A-130 flocculants were provided by Solvay. These flocculants differ in their degree of anionicity, which influences their interaction with mineral surfaces and, consequently, their flocculation performance. The degrees of anionicity, as reported by Arinaitwe & Pawlik, (2009) are summarized in Table 1. Table 1. Degree of anionicity of CYFLOCTM flocculants Flocculant Degree of anionicity CYFLOC™ A-100 10.2 % CYFLOC™ A-110 18.2 % CYFLOC™ A-130 30.3 % All three flocculant samples were received in the form of dry white granules and were utilized without any further treatments or purification. For this research, a fresh 0.5 g/l flocculant solution was prepared by mixing the required amount of flocculant in distilled water at room temperature. Two buckets of industrial process water samples were received at a UBC mining laboratory in 2022 from an oil sand operation in northern Alberta. Representative water samples were collected from each bucket and sent to a commercial lab for water analysis. Based on the results of the water analysis, the effect of individual ions of industrial process water on flocculation was studied. The zeta potential of quartz and kaolinite was measured in different concentrations of individual major cations and anions of process water. The process water analyses are shown in Table 2. 7 Table 2. Process water analysis Category UNITS Process water sample 1 Process water sample 2 ANIONS Nitrite (N) mg/L <0.0050 <0.0050 Calculated Parameters Filter and HNO3 Preservation N/A LAB LAB Dissolved Hardness (CaCO3) mg/L 213 208 Ion Ratio (cation sum/anion sum) N/A 1.0 1.0 Calculated Total Dissolved Solids mg/L 840 810 Misc. Inorganics Conductivity µs/cm 1400 1300 pH pH 8.12 8.16 Anions Alkalinity (Total as CaCO3) mg/L 210 210 Bicarbonate (HCO3) mg/L 260 260 Carbonate (CO3) mg/L <1.0 <1.0 Chloride (Cl) mg/L 33 33 Sulphate (SO4) mg/L 380 370 Nutrients Nitrate plus Nitrite (N) mg/L 0.653 0.598 Dissolved Metals by ICPMS Dissolved Iron (Fe) µg/L <5.0 <5.0 Dissolved Manganese (Mn) µg/L <1.0 <1.0 Dissolved Calcium (Ca) mg/L 46.8 45.9 Dissolved Magnesium (Mg) mg/L 23.3 22.6 Dissolved Potassium (K) mg/L 12.4 12.3 Dissolved Sodium (Na) mg/L 211 199 8 Sodium chloride, sodium bicarbonate, calcium sulfate, magnesium sulfate, sodium chloride and other analytical-grade salts from Fisher Scientific were utilized to mimic process water quality and to investigate the role of individual ions on flocculation and filtration. Additionally, analytical-grade sodium hydroxide and hydrochloric acid were used to adjust the pH of the test slurries. 1.3.2 Flocculation Tests Flocculant solutions at 0.5 g/L concentration were prepared by weighing 0.1 g of the flocculant and dissolving it in the distilled water (199.9 ml) in a 500 ml beaker at room temperature. A magnetic stirrer was utilized to create a strong vortex within the solution. The top of the beaker was then covered with parafilm, and the flocculant solution was left to mix overnight, ensuring complete dissolution of the flocculant. A polymer solution was prepared one day before each test, ensuring the solution was fresh and promoting consistent, reliable results. Flocculation tests were conducted in 2 L graduated cylinders. First, based on the solids percentage of each flocculation condition, between 0.2-0.5 kg of model blend and 1.7-1.8 L of background solutions are measured and transferred to a 4 L mixing beaker. A control overhead stirrer with two radial blades was installed above the beaker. The transferred liquid and solids were mixed at 500 rpm for 5 minutes, and then the speed was reduced to 250 rpm before adding flocculants. The flocculant solution was added continuously to the mixing beaker through a syringe over a period of 30 seconds. Then, mixing continued for another 30 seconds, and mixing was stopped. After conditioning in the beaker, the slurry was immediately transferred to a 2 L graduated cylinder for settling tests. In the graduated cylinder, the flocculated slurry was remixed by moving a plunger up and down five times before measuring the settling rate. The mixing beaker, plunger and graduated cylinder setup are shown in Picture 2. The height of the interface between the sediment and supernatant in the graduated cylinder was recorded as a function of time to calculate the 9 settling rates of the flocculated solids. For each test, a supernatant sample was taken from the top of the graduated cylinder 5 minutes after the start of the tests to measure its turbidity. Settling rates (m/h) and supernatant turbidity values (NTU) were used as indicators of the flocculation performance. Picture 2. 4 L mixing beaker, plunger, and 2 L graduated cylinder setup A 500 ml graduated cylinder setup was used to test the effects of major cations and anions of process water on the flocculation of a model blend. In these tests, the test suspensions were prepared by mixing 25, 50 and 75 g of solids in 450 ml of background solution, depending on the solid percentage of the test, under the same conditions as the flocculation tests. The pH was adjusted using sodium hydroxide (0.5 mol/L) and hydrochloric acid (1 mol/l). 10 1.3.3 Turbidity Measurement In this study, turbidity of the flocculation supernatant was measured using a Hach Model 2100AN laboratory turbidimeter, as shown in Picture 3. This instrument measures turbidity in the range of 0 to 10,000 NTU (Nephelometric Turbidity Units). The optical system of the Model 2100AN consists of a tungsten-filament lamp, lenses and apertures to focus the light, a 90° detector to monitor scattered light, a forward-scatter light detector, a transmitted-light detector, and a back-scatter light detector (Hach company, 2022). As light passes through the sample, particles suspended in the liquid scatter light in different directions. This scattering effect is directly proportional to the number of particles present, thereby affecting the clarity of the water. The intensity of the scattered light is measured and converted into turbidity values. Picture 3 shows a calibration standard set ranging from 75 to 2000 NTU, which was used to verify instrument performance. These calibration vials display increasing turbidity from left to right, visually confirming the instrument's ability to detect a broad range of particulate concentrations. Picture 3. Turbidity measurement using the Hach Model 2100AN laboratory turbidimeter (left) and turbidity calibration standards from 75 to 2000 NTU (right). 11 1.3.4 Zeta Potential Experiments Zeta potential experiments were carried out utilizing the Zeta View® PMX 100 V2.0 instrument to determine the surface charge properties of the pure quartz and kaolinite samples in the presence of various concentrations of background salts. Picture 4 shows the instrument setup and measurement output. Picture 4. Zeta potential analysis using the ZetaView® PMX 100 V2.0 instrument (left) and a representative output report for kaolinite particles (right), showing particle count, zeta potential distribution, and electrophoretic mobility analysis. The background electrolytes, sodium bicarbonate, sodium sulfate, sodium chloride, and calcium sulfate, were selected based on process water chemistry, as shown in Table 2. Each salt was tested at concentrations of 0.001, 0.002, 0.004, 0.008, and 0.016 mol/L. Since sodium bicarbonate produced a natural pH of 8, the pH of all test solutions was adjusted to pH 8 using 0.5 mol/L NaOH to ensure comparability. 12 Each test involved preparing 300 mL of 0.01 mol/L sodium chloride as a base electrolyte, to which the appropriate concentration of the test salt was added. Then, 15–20 mg of either quartz or kaolinite was introduced, and the mixture was stirred for 10 minutes to allow for equilibration and pH stabilization. The prepared suspensions were loaded into the ZetaView sample cell, taking care to avoid air bubbles or debris. An electric field was applied across the cell, causing particles to migrate based on their surface charge. The instrument tracked 1500 to 2000 particles per sample using a laser-illuminated video microscope, and their electrophoretic mobility was calculated based on the velocity of movement. The electrophoretic mobility of individual particles was measured from their velocity under the electric field. The Smoluchowski equation was used to convert mobility values into zeta potential, taking into account the medium's viscosity and conductivity. The equation is shown below. 𝜇𝑒 =𝜀ϛ4𝜋𝜂 where: 𝜇𝑒= V/E V = measured velocity E = electrical field = applied voltage/ electrode distance 𝜂 (T) = viscosity of the medium ϛ (𝑇) = dielectric constant of the medium At the end of the measurement, the instrument generates a distribution of zeta potential, from which the mean zeta potential was calculated to represent the surface charge behavior of the 13 samples. To ensure the accuracy and reliability of the result, measurements were conducted twice for each sample. 1.3.5 Vacuum Filtration Tests Vacuum filtration is widely used in mineral processing laboratories and test works to separate solids from liquids after processes such as thickening, flocculation, and sedimentation. The efficiency of filtration depends on several factors, including particle size distribution, particle surface charges, flocculant dosage, coagulant presence, and the interactions between minerals, reagents, and water chemistry. The main objective of this vacuum filtration test was to investigate the effect of various additives on the resistance (strength) of the flocculated sediment against mechanical forces just before or even during the early stages of filtration. The primary approach involved flocculation and settling to form a sediment, after which the sediment was treated with various additives in order to strengthen the sediment for subsequent filtration. The main additives were coagulants, such as calcium and aluminum cations, added in the form of calcium sulfate and aluminum sulfate, respectively. The working hypothesis was that these coagulants would introduce additional attractive forces between the flocs within the sediment, thus increasing the sediment's resistance to mechanical degradation during filtration. The bench scale vacuum filtration tests were conducted to evaluate the applicability of the coagulation approach to pressure filtration. A filtration unit consisted of a 1 L Millipore filtration funnel and a fritted base with filter paper, as well as a vacuum pump. The Whatman grade 4 (Sigma-Aldrich) filter paper with a pore size of 20-25 μm was used as the filtration medium, and the total diameter of the filter paper was 47mm. Each filtration test was run for 20 mins. The process flow diagram of the vacuum filtration setup is schematically shown in Picture 5. 14 A laboratory vacuum pump equipped with an integrated gauge was used to apply suction. The vacuum level was adjusted manually and verified using the gauge prior to each test. Filtration tests were conducted at four different absolute vacuum pressures: 5 kPa, 10 kPa, 20 kPa, and 40 kPa. These values represent increasing levels of suction pressure (i.e., decreasing absolute pressure), simulating a range of practical vacuum filtration conditions. The consistent application of vacuum across tests allowed for comparative evaluation of filtration performance under varying driving forces. Picture 5. Process flow diagram of vacuum filtration test In a typical filtration test, the slurry was prepared by combining 50 g of model blend (75% kaolinite and 25% quartz) with 450 ml of background electrolyte solutions in a beaker. The suspension was mixed at 500 rpm for 5 minutes, and the pH was adjusted to 8 using 0.5 mol/L sodium hydroxide. The mixing rate was reduced to 250 rpm before adding the flocculant. After 60 seconds of flocculant conditioning, the required amount of coagulant (calcium or aluminum at dosages of 50, 15 100, or 200 g/t) was added. After an additional 60 seconds of conditioning, the slurry was immediately transferred to the filtration unit and the vacuum test was initiated. Each filtration test was carried out over a 20 minute period, with filtrate collected and weighed at 5-minute intervals (5th, 10th, 15th, and 20th minutes). The volume collected at each point was measured, and the total volume was determined by adding these individual measurements. These values were then used to track how filtration progressed over time. To evaluate performance, the results were expressed as accumulated filtrate (%), which refers to the total volume of water collected divided by the initial water volume used in the test. This allowed for consistent comparisons between tests conducted under different conditions. 16 Chapter 2: Optimum Flocculation Conditions 2.1 Flocculation Tests 2.1.1 Flocculation Tests at Natural pH Flocculation tests were performed on a model mixture containing 10%, 15%, 20% and 25% solids in a 0.01 mol/L NaCl background solution. The pH of the tests was not adjusted, and the tests exhibited a natural pH of 4.6. Three weekly anionic polymers (A-100, A-110, and A-130) were evaluated at a dosage of 100 g/t to compare their effectiveness and select the optimal flocculant for further studies. All tests were carried out in duplicate. Settling rates were calculated individually for each run, and the average values are reported here. Figure 2was calculated using the following equation. 𝑉 = 𝛥ℎ𝛥𝑡 where: - V: Settling rate. - Δh: Difference between the initial and the final suspension height. - Δt: Time required for the flocculated interface to settle over the height Δh. For instance, in a test conducted with 15% solids concentration using polymer A-100, the measured settling time was 175 seconds, and the settling height was 10.9 cm. The corresponding settling rate was calculated as: 𝑆𝑒𝑡𝑡𝑙𝑖𝑛𝑔 𝑟𝑎𝑡𝑒 = 10.9 𝑐𝑚175 𝑠= 0.0625𝑐𝑚𝑠𝑜𝑟 2.25 𝑚/ℎ A visual of the settling rates measurement process is shown in Picture 6. 17 Picture 6. Settling rate measurement based on interface height difference Figure 2. The settling rate and supernatant turbidity vs solids percentage for flocculant selection in 0.01 mol/l NaCl at natural pH. Tests were conducted using the flocculants dosage of 100 g/t, and the results represent the average of duplicate tests. 18 Figure 2 presents the flocculation results at natural pH, showing that all three polymers showed a comparable settling rate in tests with 15 % solids. However, flocculant A-110 demonstrated slightly higher settling rates compared to flocculants A-100 and A-130 in tests with 10% solids. At higher solids concentrations (20% and 25%), smaller flocs were visually observed. However, these flocs did not settle and remained suspended, even after increasing flocculant dosage to 200 g/t and 300 g/t. No measurable improvements in settling were achieved, and supernatant turbidity was not recorded under these conditions due to the lack of interface formation. This shift in behavior, where particle flocculation still occurs but settling is no longer measurable, suggests that a critical solids concentration lies between 15% and 20%. This threshold appears to mark the transition from settling to non-settling systems. To better align with theoretical modelling practices, the solids concentrations were also converted to volume concentrations using true densities of 2.65 g/cm3 for quartz and 2.58 g/cm3 for kaolinite. The calculated volume concentrations for the test slurries were approximately: • 10 wt% → 4.1 vol% • 15 wt% → 6.4 vol% • 20 wt% →8.8 vol% • 25 wt% → 11.4 vol% No settling occurred at volume concentrations of 8.8% and 11.4%, suggesting that the flocculated system transitions into a structurally stable network at or above these levels. The observed behavior at higher solids concentrations, where flocculated particles remain suspended despite polymer addition, is consistent with the framework described by (Laskowski J.S & Pugh R.J, 1992). The author noted that while flocculation increases the size of the settling aggregates, it also reduces the density difference between the flocs and the surrounding fluid. This 19 is due to immobilization of liquid within the floc structure, which lowers the effective particle density and reduces settling. As solids concentration increases, the system may evolve into a more interconnected structure where flocs are densely packed, and gravitational settling becomes progressively limited. This trend is illustrated in Figure 3, which highlights the formation of a stable floc network at higher solids content. In such conditions, traditional settling tests may no longer provide meaningful insight into flocculation effectiveness. Instead, more suitable evaluation methods, such as yield stress or rheological testing, may be needed to assess the strength and cohesion of the flocculated structure. Figure 3. Relationship between surface charge and the properties of concentrated suspensions (The figure came from Laskowski and Pugh, 1992) A number of previous studies also conducted flocculation tests on lower solid percentages. Sworska et al (2000) examined the effects of pH, polymer dosage and Mg2+ and Ca2+ cations concentrations on tailings flocculation. The author carried out tests using fine tailings containing 20 13.5–15.5% solids after decantation of the top portion of the slurry. Similarly, Yuan and Shaw (2007) demonstrated that effective flocculation of fine transition ore tailings could only be achieved after diluting the feed solids concentration from 16% down to approximately 4%, highlighting the importance of operating at lower solids content to enhance flocculation efficiency. It is also worth noting that laboratory flocculation tests are often conducted on diluted tailings. Dilution can make settling behavior easier to observe, particularly when no clear interface forms at higher solids concentrations. However, this approach can be challenging to implement at scale, as it involves adding a substantial amount of water to reduce the solids content and later removing it through filtration or dewatering. Although the settling rates of flocs and supernatant turbidity appear relatively similar across the three flocculants during the tests with 10% and 15 % solids, the A-110 flocculant was selected for the study. This decision was based on the observation that A-110 showed the highest settling rate of 3.1 m/h in experiments conducted at 10% solids. 2.1.2 Flocculation Tests of Pure Quartz and Kaolinite Since the settling behavior could not be reliably measured at 20–25% solids using the standard settling method, this phase of testing focused on lower solids concentrations. Based on the results presented in the previous section, polymer A-110 was selected for this study due to its relatively higher settling rate compared to A-100 and A-130. Pure quartz and pure kaolinite samples were prepared at solid concentrations of 10%, 12.5%, and 15% using A-110 as the flocculant. These initial tests were conducted at a target pH of 5.9. At the time, process water was unavailable, and the appropriate test pH was uncertain. The pH of the quartz suspension naturally stabilized at 5.9, while the kaolinite suspension exhibited a lower pH and was manually adjusted to match the 21 quartz test conditions to ensure consistency. After the process, water became available, pH of 8, reflecting actual plant conditions, was selected for subsequent testing phases. Figure 4 illustrates the measured settling rates and supernatant turbidity as a function of solids concentration for both quartz and kaolinite tests. Quartz demonstrated notably higher settling rates, ranging from 24.5 m/h at 10% solids down to around 16.9 m/h at 15% solids. Visual observations confirmed that the quartz flocculation test resulted in the formation of larger flocs, contributing to the faster settling rates. Rapid settling of quartz is associated with the formation of loosely packed, larger flocs that settle quickly under gravitational force. However, despite settling more quickly, the quartz supernatant maintained significantly higher turbidity (400–500 NTU). In contrast, kaolinite demonstrated slower settling rates, from 2.7 m/h to 0.3 m/h, but achieved significantly clearer supernatants with turbidity levels below 10 NTU. Figure 4. The settling rate and supernatant turbidity vs solids percentage for quartz and kaolinite in 0.01 mol/l NaCl at pH 5.9, with flocculant A-110 at 100 g/t 22 The observed differences likely stem from variations in the surface characteristics of each mineral. At pH 5.9, quartz particles carry a negative surface charge, which results in electrostatic repulsion that limits aggregation. Adding flocculant facilitates polymer bridging between particles, which promotes flocculation. However, some fine particles remain suspended due to persistent repulsive forces, contributing to higher turbidity. Kaolinite behaves differently due to its anisotropic surface charge distribution, which changes with pH. According to Johnson et al., (1998), the silica-like faces of kaolinite are negatively charged across a wide pH range, while the alumina-like edges are positively charged at low pH and become negative as pH increases. The author concluded that at the lowest pH condition, most kaolinite particles are anticipated to interact in edge-face interactions. Thus, at pH 5.9, the natural aggregation of kaolinite particles is facilitated even without flocculant addition. This dual mechanism of polymer-induced and natural aggregation enhances particle removal efficiency and results in lower turbidity. Surface area measurements further clarify the flocculation behaviors observed. Table 3 shows measured BET and Malvern SSA results for both minerals. Table 3. BET-specific surface area of quartz and kaolinite from various studies Mineral BET specific surface area (m2/g) Specific surface area by Malvern instrument (m2/g) Quartz 6.05 3.83 Kaolinite 11.71 1.70 BET analysis shows that kaolinite possesses a greater total surface area (11.71 m2/g) than quartz (6.05 m2/g). However, measurements using the Malvern Mastersizer showed an opposite trend. According to Malvern data, kaolinite exhibits a lower apparent surface area (1.7 m2/g) compared 23 to quartz (3.83 m2/g). This difference highlights a fundamental distinction between the two measurement techniques. BET analysis captures absolute surface area by adsorbing gas molecules onto both external and internal surfaces, including porous features. Meanwhile, the Malvern Mastersizer estimates surface area based on particle size distribution, which reflects only the external dimensions. The inherently anisotropic nature of kaolinite, with its layered crystal structure, leads to the presence of internal interlayer spaces that contribute significantly to BET measurements. However, in practical suspension systems, much of the internal or basal porosity of kaolinite is inaccessible to flocculant adsorption. Therefore, the available surface area for flocculation, better represented by the Malvern measurement, is much lower than the BET surface area suggests. In contrast, quartz particles, isotropic and non-porous, exhibit a closer match between BET and Malvern SSA values. Thus, despite the higher BET surface area of kaolinite, its effective flocculation behavior is more aligned with the lower Malvern SSA value. Therefore, the flocculant demand for kaolinite may not be as high as suggested by BET measurements, aligning more closely with the lower values indicated by particle size-based assessments. Overall, quartz forms larger, faster-settling flocs but leaves behind a turbid supernatant due to incomplete aggregation of fine particles resulting from electrostatic repulsion. Kaolinite, on the other hand, settles more slowly but achieves much lower turbidity, primarily due to both flocculant action and its inherent tendency to aggregate through edge-face interactions under acidic conditions. The varying flocculation behaviors can be primarily attributed to differences in the specific surface areas of the minerals, particle morphology, and the accessibility of flocculant adsorption sites. 24 2.2 Effect of Industrial Process Water on the Flocculation of Model Blend The chemical analysis of the industrial process water, summarized in Table 2, indicated that the major cations are sodium (Na+), calcium (Ca2+), and magnesium (Mg2+), whereas the predominant anions are sulfate (SO42-), chloride (Cl-), and bicarbonate (HCO3-). To investigate how each of these ions influences flocculation behavior, various salts were chosen to replicate the same ionic composition found in industrial process water. • Ca²⁺ and Mg²⁺ supplied by calcium sulfate (CaSO4) and magnesium sulfate (MgSO4). • Na+, Cl-, SO42-, HCO3- introduced through sodium chloride (NaCl), sodium sulfate (Na2SO4), and sodium bicarbonate (NaHCO3). Each salt was added in proportions to closely match the ion concentrations measured in the industrial process water. Table 4 presents a conversion of industrial process water analysis from mg/L to mol/L. Because two process water (PW) samples, PW 1 and PW 2, were analyzed in duplicate, their average molar concentrations were averaged for subsequent testing. A synthetic water sample was then prepared to mimic these ion concentrations by mixing the selected salts at precise molar ratios. Table 5 shows the amounts required to achieve the same total cation and anion levels as the process water. For example, adding 0.0043 mol/L of NaHCO3 ensures the solution contains 0.0043 mol/L of HCO3- and contributes the same amount of Na+. To reach the overall target of 0.0089 mol/L Na⁺, 0.0019 mol/L of Na2SO4 was added next, providing 0.0019 mol/L of SO42- and an additional 0.0038 mol/L of Na+. By following this stepwise method, the ion concentrations in the laboratory‐prepared “synthetic” water closely matched those in the industrial process water, thereby enabling flocculation experiments to proceed under conditions comparable to actual industrial operations. 25 Table 4. Conversion of Process Water Results from mg/L to mol/L Ion Molar mass (g/mol) PW 1 (mg/L) PW 2 (mg/L) PW 1 (mol/L) PW 2 (mol/L) Average (mol/L) Anions HCO3- 61.01 260 260 0.0043 0.0043 0.0043 SO42- 96.06 380 370 0.0079 0.0077 0.0078 Cl- 35.45 33 33 0.0009 0.0009 0.0009 Total anions 0.0131 0.0129 0.0130 Cations Ca2+ 40.07 46.8 45.9 0.0023 0.0023 0.0023 Mg2 24.31 23.3 22.6 0.0019 0.0019 0.0019 Na+ 22.99 211 199 0.0092 0.0087 0.0089 Total cations 0.0134 0.0128 0.0131 Table 5. Salt Additions to Reproduce the Ion Composition of Industrial Process Water Added Salt (mol/L) NaH CO3 Na2SO4 CaSO4 MgSO4 NaCl Total (Created) Total (PW) 0.0043 0.0019 0.0023 0.0019 0.001 Anions HCO3- 0.0043 - - - - 0.0043 0.0043 SO42- - 0.0019 0.0023 0.0019 - 0.0061 0.0078 Cl- - - - - 0.001 0.001 0.001 Total Anions 0.0114 0.0130 Cations Ca2+ - - 0.0023 - - 0.0023 0.0023 Mg2 - - - 0.0019 - 0.0019 0.0019 Na+ 0.0043 0.0038 - - 0.001 0.0091 0.0089 Total Cations 0.0133 0.0131 26 Two complementary approaches were used to evaluate the effect of the process water on flocculation tests: how different ions affect flocculation. 1. Individual ions test. In the first set of experiments, a simple background solution (0.01 mol/L NaCl) was prepared, and only one of the major ions was introduced at the same concentration as that measured in the industrial process water. This approach allowed the specific contribution of each ion to flocculation to be determined, particularly in terms of settling rate and supernatant turbidity. 2. Synthetic Process Water: In the second approach, all the major ions were introduced simultaneously at the concentration measured in the industrial process water, creating laboratory-prepared “synthetic“ process water. This made it possible to replicate the conditions found in the industrial environment while still maintaining tight control over the total ionic composition. Figure 5 compares the effects of individual ions on flocculation. Figure 6 contrasts the performance of industrial and synthetic process water. The experiments demonstrated that calcium and magnesium sulfates notably enhanced flocculation, achieving higher settling rates and cleaner supernatants compared to sodium chloride, sodium sulfate, or sodium bicarbonate. Test results from both industrial and synthetic process waters consistently showed that Ca2+ and Mg2+ ions played the most significant role in enhancing flocculation. Their effectiveness appears linked to their ability to compress the electrical double layer surrounding negatively charged particles, which weakens repulsive forces and encourages aggregation. In contrast, although sodium chloride, sodium sulfate, and sodium bicarbonate supported good settling behavior, the resulting supernatants were notably more turbid. Among these, the sodium bicarbonate test produced the highest turbidity, exceeding 2400 NTU. 27 Figure 5. Effect of process water major cations and anions on the flocculation of model blend in 0.01 mol/l NaCl at pH 8. The test results represent the average of duplicate tests Figure 6. Flocculation tests on industrial and synthetic process water. The test results represent the average of duplicate tests 28 Flocculation tests with both industrial and synthetic process waters showed broadly similar settling rates but diverged in supernatant turbidity. At 10% solids, for instance: • Synthetic Process water: Settling rate of 17.8 m/h with relatively low supernatant turbidity. • Industrial Process water: Settling rate of 22.7 m/h but noticeably higher supernatant turbidity of 324 NTU (nearly double that of the synthetic tests). To clarify this discrepancy, total organic carbon (TOC) measurements were conducted. Industrial process water Error! Reference source not found.contains 56.5 mg/L of carbon in the form of water-soluble organic compounds, which are absent in synthetic process water. These organic compounds may interfere with floc formation by acting as dispersants rather than coagulants, thereby increasing supernatant turbidity. While ion composition clearly influences settling performance, the presence of additional organic matter in the industrial process water appears to be a factor contributing to higher supernatant turbidity. No further investigation into TOC was conducted in this thesis. Furthermore, to gain deeper insight into the contribution of electrostatic surface forces to flocculation, the zeta potential of pure quartz and kaolinite was measured across a range of concentrations (0.001 mol/L to 0.016 mol/L) for sodium bicarbonate, sodium sulfate, sodium chloride, and calcium sulfate. The results of these zeta potential tests are presented in the following section. 29 Chapter 3: The Zeta Potential of Quartz and Kaolinite Understanding how mineral surfaces carry and express electrical charge is key to explaining their behavior during flocculation and dispersion. In previous tests, a model mixture composed of 75% kaolinite and 25% quartz (by mass) was prepared and used to examine flocculation performance under different conditions. Those tests showed that process water composition, especially the presence of divalent cations like calcium and magnesium, can significantly affect settling behavior and supernatant clarity. To better isolate and study the role of electrostatic interactions, the zeta potential (ζ) of pure quartz and pure kaolinite was measured in four different electrolytes: CaSO4, NaCl, Na2SO4, and NaHCO3. The procedure followed the protocol described in Section 1.3.4. Results are presented in Figure 7 and Figure 8, which show how the zeta potential of each mineral varied with electrolyte type and concentration. Each zeta potential measurement tracked between 1500 and 2000 individual particles. Error bars shown in Figure 7 and Figure 8 represent ±1σ (standard deviation) from the mean of each distribution. Zeta potential results show that at pH 8, both quartz and kaolinite particles remained negatively charged over the entire concentration window investigated (0.001–0.016 mol/L). When sodium salts were added (NaCl, Na2SO4, and NaHCO3), the zeta potential of both minerals either became slightly more negative or remained largely unchanged. For NaCl and Na2SO4, increasing concentration caused a slight but consistent decrease in zeta potential (i.e., a shift toward more negative values). NaHCO3 had a milder effect. The zeta potential of quartz became slightly less negative at higher concentrations, while that of kaolinite showed slight variation. These trends deviate from mainstream expectations, which predict that higher ionic strength should compress the electrical double layer and reduce the magnitude of the zeta potential. The origin of this discrepancy is unclear at this time and is not further analyzed here. 30 Figure 7. Zeta potential of quartz vs CaSO4, NaCl, NaHCO3 and Na2SO4 concentrations Figure 8. Zeta potential of kaolinite vs CaSO4, NaCl, NaHCO3 and Na2SO4 concentrations 31 In contrast, the response to CaSO4 was more noticeable and aligned with theoretical predictions. As Ca2⁺ concentration increased, the negative surface charge of both minerals was significantly reduced. For quartz, the zeta potential shifted from approximately -32.4 mV to -17.9 mV, while for kaolinite it changed from about -26.3 mV to -13.8 mV. This strong charge-neutralizing effect of Ca2⁺ is consistent with the improved settling and supernatant clarity observed in earlier flocculation tests. These results suggest that divalent cations such as Ca2⁺ play a much more important role in destabilizing particle suspensions than monovalent sodium ions. For process water control in flocculation systems, maintaining consistent calcium (and possibly magnesium) concentrations is likely more critical than managing sodium levels alone. 32 Chapter 4: Vacuum Filtration Tests 4.1 Baseline Test Using 0.01 mol/ NaCl The baseline tests served as a reference for assessing the filtration performance of the model blend under controlled conditions. Each test was repeated in duplicate to ensure reproducibility. The slurry was prepared using 0.01 mol/L NaCl as the background electrolyte, flocculated, and then filtered under applied pressures of 0, 5, 10, 20, and 40 kPa. Filtration at 0 kPa was carried out without vacuum, relying solely on gravity, and served as the control condition to assess the impact of increasing vacuum pressure. Each run lasted 20 minutes, with filtrate mass recorded at 5-minute intervals (5th, 10th, 15th, and 20th minute). Filtration performance was reported as accumulated filtrate percentage (Filt %), calculated using the following equation: Filt % = 𝑀𝑓𝑀𝑖 𝑋 100 where: - Filt % - accumulated filtrate percentage - 𝑀𝑓 - Mass of the filtrate (g) - 𝑀𝑖 – Mass of the initial water for a test (g) For example, in a test conducted at 40 kPa, the vacuum filtration process collected 6.68 g of filtrate in the first 5 minutes, with an initial water mass of 460 g. The accumulated filtrate percentage was calculated as follows: Filt % = 6.68 𝑔460 𝑔 𝑋 100 = 1.45% 33 Figure 9 presents the baseline filtration results. Overall, increasing the vacuum pressure had only a limited effect on the volume of recovered filtrate. The amount of water recovered from these slurries was very low, less than 7%. Specifically, as the pressure increased from 0 kPa to 40 kPa, the accumulated filtrate increased from 2.4% to 6.4 %. This result establishes a benchmark for assessing the potential improvements in filtration performance when coagulants are introduced in subsequent tests. Figure 9. Baseline vacuum filtration test results of a model blend using 0.01 mol/L NaCl. The test results represent the average of duplicate tests. 34 4.2 Effect of Calcium Ions on Vacuum Filtration Baseline vacuum filtration tests using a 0.01 mol/L NaCl background electrolyte showed limited water recovery: only 6.4% of water was removed within 20 minutes, even at the highest vacuum pressure (40 kPa). These results suggest that pressure-driven filtration alone is not sufficient to improve dewatering efficiency under these conditions. To investigate the effect of calcium ions, calcium sulfate (CaSO4) was added to the background solution at a concentration of 0.0023 mol/L, consistent with that in process water. As shown in Figure 10, the presence of calcium significantly increased the volume of filtrate, particularly under low-pressure conditions. At 0 kPa (gravity drainage), the accumulated filtrate increased from 2.7% (NaCl only) to 5.0% (NaCl + CaSO4). At 5 kPa, the filtrate rose from 3.6% to 7.5%. These results indicate that calcium ions enhance dewatering, even with minimal applied vacuum. Figure 10. Vacuum filtration tests using NaCl vs NaCl+CaSO4 as background electrolytes. 35 However, increasing the vacuum beyond 5 kPa yielded only marginal improvements in filtrate volume. While pressure was increased in the tests to 10, 20, and 40 kPa, the additional gains in filtrate recovery were minimal (7.6%, 8.0%, and 8.3%, respectively). This plateau suggests that once a filter cake is formed, additional vacuum pressure has a limited effect, likely due to increasing resistance from the cake structure. Visual observations revealed that calcium addition resulted in smaller flocs. Sworska et al. (2000) reported that calcium ions contribute to flocculation by reducing the negative surface charge of particles, which facilitates particle aggregation. Their findings suggest that calcium promotes the formation of denser, more compact flocs by weakening electrostatic repulsion and encouraging closer particle associations. Similarly, MacIver et al. (2022, 2019) demonstrated that small flocs exhibit greater resistance to compression compared to larger flocs due to their higher internal solids content and lower porosity. These studies suggest that smaller flocs form a more compact and mechanically stable network, which may reduce permeability, but the resulting network is more resistant to collapsing under vacuum filtration. In summary, calcium ions significantly enhanced dewatering by improving particle aggregation and forming stronger, more resilient flocs. During filtration at higher pressure, these smaller flocs may rearrange into a denser and more tightly packed filter cake, increasing resistance and limiting further water removal. Nonetheless, the presence of calcium had a clear and beneficial effect on overall filtration performance, particularly under low-pressure conditions where the improved floc structure enhanced filtrate recovery. 36 4.3 Effect of Floc Size on Vacuum Filtration Performance Initial flocculation and settling tests confirmed that the baseline polymer dosage was sufficient to achieve stable flocculation and acceptable settling rates. However, vacuum filtration trials under these same conditions resulted in relatively low filtrate recovery. To improve water removal, this stage of testing focused on enhancing the structure and size of flocs to improve cake porosity and permeability. Filtration tests were conducted using 0.01 mol/L NaCl and 0.0023 mol/L CaSO4 as the background electrolyte, with polymer A-110 dosed at increasing concentrations under a constant vacuum pressure of 5 kPa. Figure 11. Effect of the polymer dosages on filtration performance As shown in Figure 11, increasing the polymer dosage from 100 g/t to 250 g/t resulted in a steady increase in accumulated filtrate volume, from 6.9% to a peak of 11.9%. However, further increasing the dosage to 300 g/t caused a slight decrease in filtrate volume to 11.5%, indicating that excess polymer may have begun to impact floc performance negatively. 37 This decline is consistent with a phenomenon known as overdosing, where the polymer fully covers the particle surfaces. Once this surface coverage is reached, there is little opportunity for the polymer to adsorb on several particles at the same time to form bridges between particles, which are necessary for flocculation. Instead, the particles remain apart. This behavior is commonly explained by steric dispersion (stabilization), in which polymer chains extending into the surrounding solution create a physical barrier that resists close approach. When the adsorbed chains between nearby particles start interacting on close approach, they generate repulsive forces due to a combination of osmotic pressure and limited space for chain movement, known as excluded volume effects (Tadros, 1996). As a result, particle collisions become less effective, reducing floc formation and compromising cake permeability. Similar observations were made by Garcia Vidal & Pawlik (2015), who reported that increasing the concentration of guar gum beyond an optimal level led to the re-dispersion of talc particles, attributed to the stabilizing effect of excess polymer. Visual observations during testing showed that higher polymer dosages produced noticeably larger and more voluminous flocs, as illustrated in Picture 7. These larger flocs formed a more open and porous cake structure, facilitating greater water permeability during filtration. While the polymer dosage used in earlier tests was sufficient for flocculation and settling, it did not yield large or porous flocs enough to support efficient filtration. This reinforces a key point: optimum polymer dosage for settling and filtration can differ. In filtration, post-flocculation floc size and structure must be carefully managed to reduce cake resistance and improve water removal. 38 Picture 7. Floc formation at increasing A-110 polymer dosages using 0.01 mol/L NaCl + 0.0023 mol/L CaSO₄ as the background Further visual observations reinforced the role of floc structure throughout the filtration process. As shown in Picture 8, flocs initially appeared large and porous at the start of filtration, promoting good permeability. However, after 20 minutes under constant vacuum, the floc structure visibly collapsed, forming a denser, more compact cake, even at a relatively low pressure of 5 kPa. This confirms that flocs, while initially well-formed, do not maintain their structure throughout the entire filtration cycle. Floc collapse reduces permeability and slows water removal, ultimately limiting overall dewatering performance. 39 Picture 8. Vacuum filtration test showing floc structure at the beginning (left) and end (right) of a 20-minute cycle at 5 kPa. In summary, this stage successfully demonstrated that increasing floc size leads to higher filtrate recovery, even when settling conditions are already optimized. Floc structure is a critical variable in filtration and enhancing it through targeted polymer adjustment offers a direct path to improving dewatering performance. 40 4.4 Effect of Adding Ca2+ and Al3+ After Flocculation on Filtration This section examines how introducing calcium (Ca2+) and aluminum (Al3+) cations after flocculation but before filtration affects dewatering efficiency. In these tests, calcium and aluminum were introduced separately in the form of calcium sulfate (CaSO4) and aluminum sulfate [Al2(SO4)3] at dosages of 50, 100 and 200 g/t. These dosages corresponded to solution-phase concentrations of 0.00014, 0.00027, and 0.00055 mol/L for calcium and 0.00020, 0.00041, and 0.00082 mol/L for aluminum, respectively. The filtration test results are illustrated in Figure 12. Figure 12. Effect of adding calcium and aluminum after flocculation on filtration performance The results show that introducing 50 g/t of calcium after flocculation significantly enhances filtrate volume, increasing the accumulated filtrate volume from 11.9% to 15.2%. However, increasing the dosage to 100 g/t and 200 g/t led to poorer results, with the filtrate volume dropping to 15.0% and 14.3%, respectively. A similar trend was observed for aluminum: adding 50 g/t raised the filtrate volume from 11.9% to 14.0%, whereas 100 g/t and 200 g/t reduced it to 10.5% and 6.5%. 41 These results suggest that while low dosages enhance water release, higher dosages may destabilize floc structure. Visual observations during filtration provided insight into these trends. At low aluminum dosage (50 g/t), the resulting cake appeared coarse and porous, with a clear supernatant (Picture 9 a). In contrast, higher aluminum additions produced finer particles and cloudier supernatants (Picture 9 b), indicating floc breakage and particle re-dispersion. Picture 9. Vacuum-filtration after post-flocculation aluminum additions: (a) 50 g/t (left) coarse, porous cake and clear supernatant; (b) 200 g/t (right) fines with cloudy supernatant. This decline in filtration performance at higher calcium and aluminum dosages can be attributed to the “coiling effect” of weakly anionic flocculants, as reported by Arinaitwe and Pawlik (2013). Their work demonstrates that calcium ions strongly interact with the carboxylate groups of polyacrylamide-based flocculants, significantly reducing the intrinsic viscosity and leading to polymer chain coiling. Even at a relatively low calcium concentration of 0.001 mol/L, the polymer conformation collapses to a limiting coiled state, restricting its bridging ability. Aluminum, with 42 its higher valency (3+), can induce a similar or even stronger interaction with the polymer. As a result, the flocculant’s effectiveness in bridging particles diminishes, and filtration performance declines due to smaller, less porous floc networks. In practice, calcium and aluminum coagulants are useful not only in controlled laboratory tests but are also effective in industrial tailings treatment settings. When used as filtration aids, they can contribute to stronger floc formation, lower cake resistance, and improved water release during dewatering, which can enhance filtration efficiency. For best results, coagulants should be introduced just before filtration. This approach helps prevent floc breakdown during slurry transport and handling, where shear forces are often present. By reinforcing floc structure at this stage, the mechanical integrity of the network is preserved, resulting in better cake consolidation and higher filtrate recovery. It should be noted that adding coagulants directly after the thickener underflow stage is generally not recommended. Doing so can cause a noticeable increase in floc density and slurry viscosity, which may result in practical challenges, such as greater resistance to pumping during tailings transfer. Overall, post-flocculation additions of calcium or aluminum improve filtration by reinforcing existing flocs through additional surface-chemical interactions, creating more porous floc networks that promote better filtration. However, further increases in the calcium dosage did not yield any additional benefit, as indicated by the slight drop in filtrate volume. In contrast, higher dosages of aluminum negatively impacted filtration by screening the anionic sites on the flocculant, causing polymer chains to coil and lose bridging efficiency. As a result, the polymer can no longer effectively link particles, and flocs are reshaped into smaller flocs that remain 43 suspended instead of settling. This leads to a higher fines content in the slurry, reduced porosity of the filter cake, and ultimately impairs overall filtration performance. 4.4.1 Hypothetical Decantation Scenario and Water Balance To further illustrate the effect of calcium addition, Picture 10 shows the filtration setup at the beginning of the vacuum filtration process, following the post-flocculation calcium test. At this stage, a substantial volume of clear supernatant water is visible above the settling solids, while the lower portion shows the early formation of the filter cake. This visual separation indicates efficient flocculation and rapid initial solid–liquid separation. Although no decantation was performed, the image suggests that approximately 325 mL of free supernatant could have been removed prior to filtration through a simple decantation step. Based on this visual observation, a hypothetical filtration scenario was developed to quantify the potential benefit. Picture 10. Initial stage of filtration showing clear supernatant and settled flocs 44 Each test began with a total slurry mass of 525 g, composed of 50 g of dry solids, 450 g of water, and 25 g of flocculant solution (converted from 20 mL, assuming a density of 1 g/mL). The 475 g value (450 g water + 25 g flocculant solution) represents the total liquid content initially added to the slurry and forms the basis for all water removal calculations. In the filtration-only tests, 56.4 g of water was filtered using 250 g/t of flocculant alone, and 72.5 g was filtered when 50 g/t of calcium was added after flocculation. These values represent the amount of water that passed through the filter medium over a 20-minute vacuum filtration period. If 325 g of supernatant water had been decanted before filtration, the total amount of removed water would be: • Without calcium: Total water removed = 325 g (hypothetical decantation) + 56.4 g (filtration) = 381.4 g 381.4475∗ 100% = 80.3% • With calcium: Total water removed = 325 g (hypothetical decantation) + 72.5 g (filtration) = 397.5 g 397.5475∗ 100% = 83.7% The water remaining in the filter cake was estimated by subtracting the total removed water from the initial 475 g: • Without calcium: 475 – 381.4 = 93.6 g remaining in the cake • With calcium: 475 – 397.5 = 77.5 g remaining in the cake The final cake solids content was calculated using the dry solids mass of 50 g and the estimated water retained in the cake: • Without calcium: Solids content 34.8% 45 • With calcium: Solids content 39.2% While this decantation scenario is hypothetical and not implemented in actual tests, the visual and numerical estimates demonstrate that calcium addition enhances early-stage solid–liquid separation. This leads to a drier, more consolidated filter cake and higher overall water recovery. 46 Chapter 5: Recommendation for Further Research While this study confirms that post-flocculation coagulant addition improves vacuum-filtration efficiency, three important research directions remain. • The current work used a synthetic 75 wt % kaolinite / 25 wt % quartz blend. Actual oil-sands tailings contain bitumen residues, dissolved organics, and a broader particle-size distribution that can alter polymer adsorption and floc strength. Repeating the flocculant-coagulant sequence on unmodified tailings, using similar polymer and coagulant dosages and comparable vacuum-pressure settings, will determine whether the gains in filtrate volume, cake solids, and cycle time persist under real tailings chemistry. • Visual observations showed that large, initially porous flocs collapsed within 20 min at only 5 kPa, forming a dense cake that restricted flow. Future studies should pair in-line particle-size or turbidity sensors with stepwise vacuum ramps (0–40 kPa) to track floc break-up and pore-network closure in real time. Correlating these data with polymer and coagulant dosages and with slurry shear history will identify the mechanical limits of the flocs and guide adjustments that preserve permeability throughout the filtration cycle. • Visual observations and earlier research show that flocs begin to collapse even under modest vacuum, limiting permeability. A logical next step is to carry out bench-scale trials on a filter press equipped for controlled, stepwise pressure increases. Tracking filtrate flow, cake moisture, and structural changes at each pressure increment will reveal the point at which permeability is lost and indicate whether coagulant dosage or timing should be adjusted to preserve porosity. The resulting data will establish realistic benchmarks for cake solids, filtrate throughput, and cycle duration under pressure-filtration conditions. 47 Chapter 6: Conclusion The primary goal of this thesis was to identify flocculation chemistries and operating conditions that allow mature fine tailings (MFT) to retain a porous, permeable network throughout filtration, thereby maximizing water release. A model blend of 75 % kaolinite and 25 % quartz was used to represent MFT. The study combined settling tests, turbidity measurements, zeta-potential analyses and vacuum-filtration trials to evaluate the influence of process water ions, polymer dosage, and post-flocculation coagulant additions on floc structure and dewatering performance. The following conclusions are drawn from the experimental findings: • Settling tests were carried out at solids contents up to 25 wt % (11.4 vol %). However, once the concentration exceeded 15 wt % (6.4 vol %), the flocculated sediment no longer settled and no distinct sediment–supernatant interface formed, even with higher polymer dosages and extended settling times. Although the polymer still facilitated floc formation at these levels, the density contrast between the flocs and the surrounding liquid became too small, and the slurry behaved as a continuous, interconnected network, effectively preventing gravitational settling. Consequently, beyond this solids concentration, conventional settling tests are no longer a reliable measure of flocculation performance. • Surface charge drives the fundamentally different floc behaviors of quartz and kaolinite. Quartz carries a uniformly negative charge at the entire pH range, and electrostatic repulsion limits polymer coverage to bridging points only. The result is large, loosely bound flocs that settle quickly but release fines, giving a turbid supernatant. Kaolinite is anisotropic: silica faces remain negative, whereas alumina edges are positive at low pH and become negative as pH rises. At pH 5.9 (initial tests), the edge–face attraction encourages natural flocculation even without polymer, producing smaller flocs and clear 48 supernatant. These observations show that pH-dependent surface charge, not just surface area, governs initial flocculation and supernatant clarity. • The observed accessible surface area matters more than the BET specific surface area in flocculation. Particle size-based SSA (Malvern) indicates higher accessible area for quartz than kaolinite, inverting the BET SSA trend. Flocculant demand is better predicted by this Malvern surface area than by BET values that include internal porosity inaccessible to a flocculant. • The ionic composition of industrial process water has a significant impact on flocculation performance. Sodium salts (NaCl, Na2SO4, NaHCO3) promote high settling rates and tend to result in higher supernatant turbidity. On the other hand, divalent cations calcium (Ca2+) and magnesium (Mg2+) play a crucial role in enhancing settling rates and reducing turbidity of the supernatant in flocculation tests. Zeta-potential measurements showed that Ca2⁺ compresses the electrical double layer and reduces negative charge far more effectively than monovalent ions, promoting better flocculation, faster settling and lower turbidity. • Baseline filtration employing 0.01 mol/L NaCl yielded <7% water recovery at 40 kPa vacuum, underscoring the limited efficacy of pressure alone. Incorporation of calcium (0.0023 mol/L) enhanced low-pressure filtrate yield (5 kPa), indicating structural fortification of flocs under mild vacuum. However, gains plateaued at higher pressures, presumably due to increasing cake resistance. • Fast settling and a clear supernatant do not guarantee good filtration. Tests showed that larger, more permeable flocs are critical: increasing the A-110 dosage from 100 g/t to 250 g/t formed bigger flocs. It increased filtrate recovery from 6.9 % to 11.9 % at 5 kPa, 49 demonstrating that the polymer dosage needed for efficient filtration exceeds that required for good flocculation and rapid settling. • Post-flocculation coagulant additions can modify cake structure, but only when applied at low levels. 50 g/t of Ca2⁺ addition raised the accumulated filtrate from 11.9 % to 15.2 %, and 50 g/t of Al3⁺ addition increased the accumulated filtrate to 14.0 %. Higher amounts proved counterproductive: Ca2⁺ at 100 - 200 g/t gave no further benefit, while Al3⁺ at 100 g/t and 200 g/t reduced recovery to 10.5 % and 6.5 %, respectively. The sharp decline with Al3⁺ is attributed to the polymer chain coiling effect. Excessive aluminum caused a stronger screening of flocculant anionic sites, leading to polymer chain coiling and diminished bridging efficiency. As a result, flocs became smaller, increasing the fines content and impairing overall filtration performance. • Based on a hypothetical decantation scenario, total water removal was estimated to reach 80.3% without calcium and 83.7% with calcium. Corresponding to this, the final cake solids percentage improved from 34.8% (without calcium) to 39.2% (with calcium). While this decantation scenario was not implemented in the test, it was used to illustrate how post-flocculation coagulant addition influences the overall filtrate volume and retained moisture in the cake • The findings from this work offer practical relevance for tailings management in oil sands operations, where reducing fine tailings volume and improving water recovery are key priorities. Conventional flocculation strategies are typically optimized to improve settling; however, this approach may not always enhance filtration. Results from this study show that effective filtration requires consideration of specific properties, such as floc size, porosity, and mechanical stability. These characteristics should guide how flocculants and 50 coagulants are selected and applied when filtration is the primary goal. This research outlines a framework for improving mature fine tailings (MFT) dewatering by emphasizing the need for process-specific flocculation approaches and post-treatment strategies that account for process water chemistry. Aligning reagent strategies with both settling and filtration requirements is essential for advancing water reuse and sustainable tailings storage in large-scale operations. 51 Bibliography Alberta, G. of. (2010, March 13). OSIP - Data Library [Text]. http://osip.alberta.ca/library/Dataset/Details/542 Arinaitwe, E., & Pawlik, M. (2009). A method for measuring the degree of anionicity of polyacrylamide-based flocculants. 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Principles of action of polymeric flocculants. British Polymer Journal, 4, 217–229. Klimpel, R. C., & Hogg, R. (1991). Evaluation of floc structure. Colloids and Surfaces, 55, 279–288. Laskowski J.S, J. S., & Pugh R.J. (1992). Dispersions stability and dispersing agents. In Colloid Chemistry in Mineral Processing (Vol. 12, pp. 115–171). Elsevier. https://doi.org/10.1016/B978-0-444-88284-4.50009-3 Loerke, R., Tan, X., & Liu, Q. (2017). Dewatering of Oil Sands Mature Fine Tailings by Dual Polymer Flocculation and Pressure Plate Filtration. Energy & Fuels, 31(7), 6986–6995. https://doi.org/10.1021/acs.energyfuels.7b00938 52 MacIver, M. R., Alizadeh, H., Kuppusamy, V. K., Hamza, H., & Pawlik, M. (2022). The macro-structure of quartz flocs. Powder Technology, 395, 255–266. https://doi.org/10.1016/j.powtec.2021.09.052 MacIver, M. R., Pawlik, M., & Hamza, H. (2019). Aggregate density changes during the compression of flocculated silica. 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The Canadian Journal of Chemical Engineering, 95(1), 3–10. https://doi.org/10.1002/cjce.22628 53 Appendix A Particle size analysis of quartz and kaolinite 54 55 Appendix B BET Specific Surface Area Results 56 57 Appendix C Flocculation tests data Table 6. Flocculant selection tests in 0.01 mol/l NaCl at natural pH Materials mix ratio Polymer Solid % Flocculant Dosage, g Flocculant dosage, g/t pH Settling rate, m/h Turbidity, NTU Kaolinite 75% + Quartz 25% A100 10.0 40.0 100.0 4.6 2.3 5.6 15.0 60.0 100.0 4.6 0.5 10.0 20.0 80.0 100.0 4.6 n.a n.a 25.0 100.0 100.0 4.5 n.a n.a A110 10.0 40.0 100.0 4.7 3.1 12.1 15.0 60.0 100.0 4.6 0.5 9.9 20.0 80.0 100.0 4.6 n.a n.a 25.0 100.0 100.0 4.4 n.a n.a A130 10.0 40.0 100.0 4.7 2.1 7.8 15.0 60.0 100.0 4.6 0.3 8.1 20.0 80.0 100.0 4.6 n.a n.a 25.0 100.0 100.0 4.4 n.a n.a Table 7. Flocculation tests on pure quartz and kaolinite samples Materials mix ratio Polymer Solid % Flocculant Dosage, g Flocculant dosage, g/t pH Settling rate, m/h Turbidity, NTU Quartz 100% A110 10.0 40.0 100.0 5.9 24.5 478.5 12.5 50.0 100.0 5.8 22.6 475.5 15.0 60.0 100.0 5.8 16.9 455.0 Kaolinite 100% 10.0 40.0 100.0 5.9 2.7 13.3 12.5 50.0 100.0 5.9 0.8 3.8 15.0 60.0 100.0 5.8 0.3 3.6 58 Table 8. Flocculation test results Solids Percentage Synthetic process water Process water NaCl 0.01 [mol/l] CaSO4 0.0023 [mol/l] MgSO4 0.0019 [mol/l] NAHCO3 0.0043 [mol/l] Na2SO4 0.0078 [mol/l] Settling rate, m/h 5% 17.8 22.7 58.1 18.5 36.8 50.0 49.9 10% 3.1 8.5 30.6 2.4 8.5 27.1 24.8 15% 0.6 2.1 2.1 0.4 1.4 5.7 1.4 Turbidity, NTU 5% 116.5 314.0 1022.1 80.6 122.6 2502.0 817.0 10% 80.8 287.0 965.8 69.0 93.3 2513.5 829.5 15% 82.2 237.0 862.6 37.2 69.9 2677.0 542.5 59 Appendix D Zeta potential test data Table 9. Zeta potential of quartz in NaCl Concentration of NaCl Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 54.8 ± 6.4 0.002 - 56.2 ± 6.6 0.004 - 57.6 ± 6.4 0.008 - 59.5 ± 5.9 0.016 - 61.0 ± 6.5 Table 10. Zeta potential of quartz in NaHCO3 Concentration of NaHCO3 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 61.6 ± 7.0 0.002 - 58.5 ± 6.2 0.004 - 59.1 ± 5.9 0.008 - 58.2 ± 6.2 0.016 - 53.2 ± 6.5 Table 11. Zeta potential of quartz in Na2SO4 Concentration of Na2SO4 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 56.8 ± 6.3 0.002 - 59.1 ± 6.4 0.004 - 60.0 ± 6.0 0.008 - 58.2 ± 5.8 0.016 - 60.0 ± 6.5 60 Table 12. Zeta potential of quartz in CaSO4 Concentration of CaSO4 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 32.4 ± 7.2 0.002 - 29.7 ± 6.7 0.004 - 27.0 ± 6.7 0.008 - 24.8 ± 7.0 0.016 - 17.9 ± 7.2 Table 13. Zeta potential of kaolinite in NaCl Concentration of NaCl Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 41.5 ± 7.6 0.002 - 41.2 ± 7.8 0.004 - 44.5 ± 7.4 0.008 - 43.8 ± 7.7 0.016 - 47.3 ± 6.9 Table 14. Zeta potential of kaolinite in NaHCO3 Concentration of NaHCO3 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 45.8 ± 7.2 0.002 - 48.7 ± 7.2 0.004 - 50.1 ± 7.6 0.008 - 50.7 ± 7.7 0.016 - 48.6 ± 8.6 61 Table 15. Zeta potential of kaolinite in Na2SO4 Concentration of Na2SO4 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 42.9 ± 6.9 0.002 - 43.3 ± 6.8 0.004 - 46.6 ± 6.9 0.008 - 49.0 ± 5.8 0.016 - 52.2 ± 7.3 Table 16. Zeta potential of kaolinite in CaSO4 Concentration of CaSO4 Zeta Potential of quartz at pH 8 mol/l mV Standard Deviation 0.001 - 26.3 ± 6.6 0.002 - 23.8 ± 6.2 0.004 - 21.4 ± 6.6 0.008 - 18.8 ± 6.6 0.016 - 13.8 ± 9.3 62 Appendix E Vacuum filtration Table 17. Effect of vacuum pressure on filtration performance Polymer A-100: dosage -100g/t Vacuum pressure Accumulated volume of filtrate, % 5 min 10 min 15 min 20 min 0.01 mol/l NaCl 0 kPa 1.2 1.7 2.1 2.5 5 kPa 1.5 2.3 3.1 3.6 10 kPa 2.3 3.1 3.7 4.3 20 kPa 2.9 4.0 4.9 5.6 40 kPa 3.6 4.6 5.5 6.4 0.0023 mol/l CaSO4 0 kPa 2.8 3.7 4.4 5.0 5 kPa 4.4 5.6 6.6 7.5 10 kPa 4.2 5.5 6.6 7.6 20 kPa 4.5 5.8 7.0 8.0 40 kPa 4.7 6.1 7.3 8.3 0.01 mol/l NaCl + 0.0023 mol/l CaSO4 0 kPa 3.0 3.8 4.6 5.3 5 kPa 3.8 5.0 6.0 6.9 10 kPa 4.1 5.2 6.4 7.3 20 kPa 4.2 5.5 6.6 7.6 40 kPa 4.5 6.0 7.1 8.3 Table 18. Effect of the flocculant dosages on filtration performance 0.01M NaCl + 0.0023M CaSO4 Vacuum pressure Accumulated Volume of filtrate, % 5 min 10 min 15 min 20 min Polymer A110- 100 g/t 5 kPa 3.8 5.0 6.0 6.9 Polymer A110- 150 g/t 3.7 5.3 6.7 8.0 Polymer A110- 200 g/t 3.9 5.6 7.1 8.5 Polymer A110- 250 g/t 5.8 8.2 10.1 11.9 Polymer A110- 300 g/t 5.7 8.1 9.9 11.5 63 Table 19. Effect of adding calcium after flocculation on filtration performance 0.01 mol/l NaCl + 0.0023 mol/l CaSO4 Vacuum pressure Accumulated volume of filtrate, % 5 min 10 min 15 min 20 min Aluminum (50g/t) after flocculation 5 kPa 5.8 8.6 11.6 14.0 Aluminum (100g/t) after flocculation 5.3 7.3 8.7 10.5 Aluminum (200g/t) after flocculation 3.4 4.6 5.6 6.5 Table 20. Effect of adding aluminum after flocculation on filtration performance 0.01 mol/l NaCl + 0.0023 mol/l CaSO4 Vacuum pressure Accumulated volume of filtrate, % 5 min 10 min 15 min 20 min Calcium (50g/t) after flocculation 5 kPa 6.5 9.6 12.5 15.2 Calcium (100g/t) after flocculation 6.5 9.8 13.1 15.0 Calcium (200g/t) after flocculation 6.3 9.4 12.0 14.3
Thesis/Dissertation
eng
Mining Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Pawlik, Marek
Strengthening floc structure during filtration of flocculated tailings
Text