Rheology of Reconstituted Crude Oils: Artifacts and Asphaltenes
Bibliographic record
Abstract
The properties of asphaltenes present in crude oils remain subjects of debate in the literature. In this work, the complex and zero shear viscosities of reconstituted samples prepared by mixing chemically separated pentane asphaltenes and maltenes were obtained. The samples were of four different types, namely: Athabasca asphaltene + Athabasca maltene (reconstituted Athabasca bitumen), Maya asphaltene + Maya maltene (reconstituted Maya crude), as well as cross mixtures comprising Athabasca asphaltene + Maya maltene, and Maya asphaltene + Athabasca maltene. The zero shear viscosities of these samples are compared with one another, with the zero shear viscosities of asphaltene + pure diluent binary mixtures, and with zero shear viscosities of nanofiltered Athabasca bitumen and Maya crude oil samples reported previously. The Maya and Athabasca asphaltene properties in reconstituted samples are shown to differ from one another and from those in nanofiltered samples. However, the large temperature and composition variation of the relative viscosity of such mixtures is attributed primarily to redistribution of residual pentane from the maltenes to the asphaltenes on reconstitution and only secondarily to properties of the chemically separated asphaltenes themselves. The physics and chemistry of asphaltene behavior and of the differences arising from separation methods and diluent environments are not resolved in the present work and remain subjects for ongoing investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".