Unraveling Interaction Mechanisms between Molybdenite and a Dodecane Oil Droplet Using Atomic Force Microscopy
Bibliographic record
Abstract
) is a mineral that has drawn great interest because of its potential application in various fields. To facilitate the flotation of molybdenite, the mineral pulp is commonly treated with nonpolar oil additives to promote hydrophobicity and to form an oil bridge between ultrafine molybdenite particles for agglomeration. In this study, dodecane was chosen as a model oil to investigate the flotation mechanisms of molybdenite with nonpolar oil. The interaction forces between a micrometer-sized dodecane droplet and the molybdenite basal plane in various electrolyte solutions were directly measured by the atomic force microscope droplet probe technique. The effects of added salts, ionic strength, and solution pH on interaction forces were evaluated by considering van der Waals, electrical double-layer (EDL), and hydrophobic forces. The experimentally measured force curves were found to agree well with the Reynolds lubrication model and the augmented Young-Laplace equation. The results show that the competition between repulsive EDL forces and attractive hydrophobic forces was directly responsible for oil-molybdenite attachment behavior. High pH and low salinity (<24 mM NaCl) led to strong repulsive EDL forces, which stabilized the interaction and prevented the attachment of oil to molybdenite. Both low pH and high salinity facilitated the attachment of oil to molybdenite through the depression of EDL force, allowing attractive hydrophobic force to dominate. The hydrophobic attraction was quantified with an exponential decay length of 1.0 ± 0.1 nm. Furthermore, calcium ions decreased the magnitude of the surface potentials of both oil and molybdenite more than that seen with the same ionic strength of sodium ions, suggesting the suppressed EDL repulsion. This study provides quantitative information about the surface forces between oil and the molybdenite basal plane and an improved understanding of the fundamental interaction mechanisms governing molybdenite recovery by mineral flotation.
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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 | 0.000 |
| 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 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".