Liquid–Liquid Phase Equilibria in Asphaltene + Polystyrene + Toluene Mixtures at 293 K
Bibliographic record
Abstract
The phase behavior of hydrocarbon mixtures where one of the constituents self-aggregates is a subject of significant industrial and academic interest. Here, a nonintrusive acoustic phased-array technique operated in pulse echo mode is used to investigate the phase behavior of asphaltenes, a well-known self-aggregating species, in mixtures with polystyrene and toluene at 293 K and atmospheric pressure. This mixture exhibits liquid–liquid phase behavior where both liquids are opaque to visible light, are of uniform composition, and are stable over broad ranges of composition. One phase is asphaltene rich and the other phase is polystyrene rich. Varying the polystyrene mean molar mass had little impact on the liquid to liquid–liquid phase boundaries. Liquid–liquid critical points were identified and phase compositions were confirmed for a fixed global composition using the UV–visible spectrophotometry and mass balance equations. This is the first report of liquid–liquid phase behavior for such mixtures. Depletion flocculation is hypothesized to be the mechanism causing phase separation in this ternary mixture.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, 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".