Temperature-Independent Colloidal Phase Behavior of Maya Asphaltene + Toluene + Polystyrene Mixtures
Bibliographic record
Abstract
Polystyrene, a non-adsorbing polymer, has been shown to cause Maya and Athabasca asphaltene + toluene mixtures to split into two stable liquid phases at room temperature. One phase is enriched in polystyrene and toluene. The other phase is enriched in asphaltene and toluene. The phase boundaries, tie lines, and critical points for Maya asphaltene + toluene + polystyrene ( M w = 393 000 and 700 000 g/mol) and Athabasca asphaltene + toluene + polystyrene ( M w = 393 000 g/mol) have also been simulated at room temperature using a modified Fleer–Tuinier colloid phase behavior model. In this work, the temperature dependence of the depletion flocculation-driven phase behavior is investigated for Maya asphaltene + toluene + polystyrene ( M w = 393 000 g/mol) mixtures both experimentally and theoretically. The coincidence of experimental two-phase to one-phase boundaries, including liquid–liquid critical points and tie lines at 248 and 298 K, illustrates the temperature-independent nature of this phase behavior. This outcome is interpreted and predicted in terms of the known temperature dependence of the radius of gyration of polymer molecules, possible impacts of temperature variation on mean asphaltene aggregate size, and relative importance of steric repulsion and depletion attraction effects in determining the phase behavior of asphaltene + toluene + polystyrene mixtures. Experimental and modeling outcomes are discussed.
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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 | 0.000 |
| 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) | 0.001 | 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".