Impact of Clay Minerals on the Dewatering of Coal Slurry: An Experimental and Molecular-Simulation Study
Bibliographic record
Abstract
The cleaning process of coals is challenging due to the existence of clay minerals. The overall objective of this study is to investigate how the dewatering of coal slurry is impacted by the presence of clay minerals, i.e., kaolinite and montmorillonite. Filtration tests were first conducted to investigate the effect of kaolinite and montmorillonite on the dewatering efficiency of coal. Specifically, we measured the filtration velocity, moisture, average specific resistance, and porosity of filter cakes for six slurry samples, in which different amounts of kaolinite and montmorillonite were contained. Filtration tests show that a small amount of kaolinite and montmorillonite leads to a significant reduction in the filtration velocity and porosity, and a big increase in the average specific resistance and the moisture of the filter cake. We observe that most kaolinite existed in the top and middle layers of the filter cake, while most montmorillonite existed in the top layer; on the contrary, little montmorillonite is observed in the middle and bottom layers of the filter cake. Montmorillonite results in a much more deteriorative effect than kaolinite. Considering that the interactions between clay minerals and water may play a key role, we then further investigate the effect of such interactions using molecular simulations. Simulation results show that water molecules could hardly diffuse into kaolinite from the edge, while they could readily penetrate into the montmorillonite layers from the edge surface. This result can be explained by the hydrated cation in montmorillonite. The adsorption density of water on the octahedral surface of kaolinite is higher than that of water on the tetrahedral surface of kaolinite. Furthermore, the adsorption density of water on the double surfaces of kaolinite is higher than that of water on the montmorillonite surface. This research is expected to provide benefits or contributions to the dewatering of clay-rich coal tailings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".