Phase separation dynamics in binary fluids containing quenched or mobile filler particles
Bibliographic record
Abstract
The dynamics of phase separation of binary fluids in the presence of quenched or mobile filler particles, with preferential attraction for one of the two fluid components, is investigated by means of extensive molecular dynamics simulations in two dimensions. When the filler particles are quenched, we found that they lead to a slowing-down of the kinetics that is enhanced as the density of the filler particles is increased. The domain growth in this case is found to follow a crossover scaling form which links domain growth in pure binary mixtures to that in the presence of quenched filler particles. On the other hand, when the filler particles are annealed, systematic simulations for various values of single filler particle mass, μc, and filler particle density, ρc, show that the filler particles only affect the nonuniversal prefactor of the power law. The power law itself remains given by t2/3, characteristic of inertial growth that is typically observed in pure binary fluid mixtures. The prefactor is found to depend on μc as μc−1/3 as expected in phase separating fluid in the inertial regime.
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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 | 0.000 | 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".