Hydrophobic nano-asperities in control of energy barrier during particle–surface interactions
Bibliographic record
Abstract
To explain differences in colloidal interactions for spherical hydrophobic particles, a theoretical analysis of the interaction potential was carried out for a model rough particle interacting with a smooth and flat surface in an electrolyte solution. The attractive hydrophobic interaction potential was added to repulsive retarded van der Waals and repulsive electrical double layer interaction potentials. The rough microscopic particles were modeled as spheres decorated with nano-sized hemispherical asperities. Parameters that reflect common flotation separation systems were selected for testing this theoretical model and computation of the energy barrier applicable to particle–surface interactions. It was found that hydrophobic asperities with the radius of only a few nanometers reduced the energy required for particle attachment to a hydrophobic surface by several times. The value of this energy barrier was reduced by as much as two orders of magnitude when the radius of nano-sized asperities increased to a few tens of nanometers. Theoretical analysis also revealed that surface coverage of microscopic particles by nano-sized asperities was not as important as the size of the asperities.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".