Mesoscale Organization in a Physically Separated Vacuum Residue: Comparison to Asphaltenes in a Simple Solvent
Bibliographic record
Abstract
Physical separation of heavy oils and bitumen is of particular interest because it improves the description of the chemical and structural organization in these industrial and challenging fluids ( Zhao, B.; Shaw, J. M. Composition and size distribution of coherent nanostructures in Athabasca bitumen and Maya crude oil. Energy Fuels 2007, 21, 2795−2804). In this study, permeates and retentates, differing in aggregate concentrations and sizes, were obtained from nanofiltration of a vacuum residue at 200 °C with membranes of varying pore size. Elemental composition and density extrapolations show that aggregates are best represented as n -pentane asphaltenes, while the dispersing phase corresponds to n -pentane maltenes. Small-angle X-ray scattering (SAXS) measurements are processed, on this basis, to calculate the size and mass of the aggregates. Aggregates in the vacuum residue are similar in size and mass to asphaltenes in toluene, and temperature elevation decreases the size of the aggregates. Wide-angle X-ray scattering (WAXS) highlights a coherent domain observed for fluids containing aggregates, corresponding to aromatic stacking described for dry asphaltenes. The scattered signal in this region, not observed in maltenes, grows as aggregate content increases, and the signal persists up to 300 °C. A generic behavior of aggregation in the vacuum residue is depicted, from nanoaggregates to large fractal clusters with high aggregation numbers, that is similar to the organization in toluene.
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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".