Slurry rheology in mineral processing unit operations: A critical review
Bibliographic record
Abstract
ABSTRACT Knowledge of slurry rheology in mineral processing is essential for the optimization of wet‐grinding, dewatering, transport, and tailings management and it is becoming important in flotation due to the increasing need to process complex ores with a high clay mineral content. Slurries of these ores often display complex rheological behaviour even at low solids concentration, and traditional rheology measurements in mineral processing, such as yield stress and apparent viscosities, may not provide the critical information needed for process optimization. The objective of this paper is to provide a comprehensive review of some of the previous rheology studies performed at the bench, pilot plant, and industrial scale for different unit operations and to discuss the potential for alternative rheology measurements to provide a better insight into colloidal particle interactions in slurries with clay minerals. Firstly, the fundamentals of slurry rheology and the influence of colloidal particles are presented. Secondly, rheology measurements for suspensions are described briefly. Thirdly, a review of rheology studies in grinding, classification, flotation, dewatering, and tailings management is done, outlining possible ways of determining types of particle associations in slurries. Finally, recommendations for future research directions are provided.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".