Electrokinetic dewatering of mine tailings from hydrometallurgical processes
Bibliographic record
Abstract
Fine-grained tailings (leach residue and gypsum) resulting from hydrometallurgical processes (acid leach followed by lime neutralisation) of nickel laterite ores are proving difficult to dewater using conventional dewatering methods (thickeners/vacuum filters). To generate a dense non-segregating slurry or paste that can be deposited on surface in the form of a stable stack, more innovative dewatering methods are required. The current work involves working on thickened nickel laterite tailings to produce a paste product for surface disposal. Achieving greater dewatering would offer advantages compared to conventional slurry deposition such as reducing the size of impoundments; reducing the size and costs of containment dams; and decreasing water sent to the impoundment. It also offers environmental advantages, including reduced leachate generation and decreased permeability of paste (homogeneous mass). Electrokinetic (EK) consolidation is a soil improvement technique that has been mostly used for soft fine-grained soils, such as silts and clays. The treatment involves applying a direct current across electrodes embedded into the soil. The current induces the movement of soil–water from the anode (positive pole) toward the cathode (negative pole). Dewatering and consolidation are achieved when the water is permitted to drain at the cathode and prohibited to enter the anode. The electrochemical reactions are associated with the EK process, which leads to a pH gradient in soil, generation of hydrogen and oxygen gases at electrodes and corrosion of consumable anodes, which must be addressed on a project-specific basis. The objective of this research is to study the viability of using EK to dewater tailings (leach residue and gypsum) from hydrometallurgical processes. The electroosmotic (EO) flow rate and coefficient of EO permeability (ke) are measured to assess the effectiveness of EK dewatering. The study includes comprehensive material characterisation and EK cell tests. The results of the study indicate: EO generated significant water flow in the tailings sample. The tailings have stable electrical conductivity, i.e. the applied current can be maintained relatively constant over time under a constant voltage. The ke values are in the range of 1.00 × 10-9 to 7.00 × 10-9 m2/V/sec, which is considered very favourable for EO dewatering. The electric conductivities of the saturated tailings are in the range of 2,000–2,300 S/cm, and the tailings porewater has the electric conductivity of 8,000 S/cm, which is considered favourable in terms of power consumption for EK dewatering. The zeta potentials of the tailings before and after EO tests are stable in the pH range of 4–9, indicating EO dewatering would be effective in tailings without pre-treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".