Relating Nanoparticle Shape and Adhesiveness to Performance as Flotation Collectors
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Cationic polystyrene-core-poly( n -butyl methacrylate)-shell (PS–PB) nanoparticles perform as flotation collectors as they spontaneously adsorb onto 43 μm glass beads in water, promoting glass bead attachment to air bubbles. Under our flotation conditions at room temperature, polystyrene is a hard plastic, whereas, with glass transition near room temperature, poly( n -butyl methacrylate) is a soft polymer. Colloidal probe atomic force microscopy measurements revealed that the pull-off forces and the work of adhesion of PS–PB nanoparticles to glass were significantly higher than observed with harder PS particles. Glass bead recovery in laboratory flotation experiments increased significantly with thickness of the soft PB shells on the PB–PS core/shell nanoparticles. Ninety-two nm Janus particles consisting of one PS and one PB lobe were also very effective collectors. We propose that high nanoparticle/glass bead adhesion minimizes nanoparticle removal by bead/bead collisions (nanoscale ball milling) during mixing and flotation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.001 | 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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".