Patchy colloidal particles at the fluid–fluid interface
Bibliographic record
Abstract
Colloidal particles have significantly different characteristics when they are at interfaces from when they are in the bulk. In this study, we applied Monte Carlo simulations to investigate the stability and dynamics of smooth patchy particles and rough patchy particles near or at the fluid-fluid interface. By adjusting the surface area ratio of the two faces of a smooth Janus particle, we show how its stability, in terms of free energy, in either side of the interface can be tuned relative to the smooth homogeneous particle. We demonstrate how roughness can affect the stability and the orientation of a colloidal particle. Moreover, position-dependent diffusion constants in directions parallel and perpendicular to the interface are calculated for the colloidal particles as a function of distance from the interface. We report drastic slowdowns in the perpendicular diffusivity (and less severe slowdowns for the parallel diffusivity) for all the colloidal particles when they approach the fluid-fluid interface. While such a slowdown is well-known for the fluid-solid interface in the literature in terms of frictional force in hydrodynamics, why this happens for the fluid-fluid interface has not been adequately discussed. We provide evidence for the decrease in terms of discrepancy in the fluid density that leads to depletion forces.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".