Influence of pH and salt solution on the sedimentation properties of fine bauxite tailings
Bibliographic record
Abstract
Bauxite tailings slurry is a type of solid waste produced in the process of bauxite washing and beneficiation. It has poor engineering properties, that is, self-consolidation settlement unusually cannot be completed during several decades. To investigate the sedimentation properties of bauxite tailings, bauxite tailings slurry, phyllite residual soil, and kaolinite, we conduct sedimentation tests on these materials in varying pH and salt solution environments. The influence mechanism of the surface electrical properties of clay particles on the settlement of tailings slurry is investigated using the zeta potential test. The findings reveal that increases in the cation concentration and valence state lead to compression of the electric double layer on the surface of three types of soil particles, resulting in a decline in the repulsive potential energy and an increase in the gravitational potential energy. This in turn contributes to a reduction in the settling stable void ratio. As the pH increases, the zeta potentials of the three soils gradually decrease from positive to negative. A change in the pH at the isoelectric point, PZCedge, triggers the transformation of the kaolinite mineral arrangement. When the pH is either greater than or less than the isoelectric point, an increase or decrease in the pH results in expansion of the electric double layer of the clay particles and an increase in the pore content. The results of this study suggest that bauxite tailings mud is more likely to settle in an acidic environment than in an alkaline environment, thus an acidic settling environment should be utilized for bauxite tailings produced in industrial production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".