Chemical Characterization of GPC Fractions of Athabasca Bitumen Asphaltenes Isolated before and after Thermal Treatment
Bibliographic record
Abstract
The object of this work was to determine whether new information could be obtained by using gel permeation chromatography (GPC) to fractionate asphaltene samples prior to analysis. In particular, GPC elution profiles, elemental analyses, molecular weights by vapor pressure osmometry (VPO), and boiling point distributions of the asphaltenes isolated from the original Athabasca bitumen feed (Feed) and from its total liquid product (TLP) after visbreaking were compared. The analyses showed that for GPC run using chloroform, fractionation was based on size where elemental analyses and boiling point distributions indicated that the earlier eluting fractions were not aggregates of later eluting fractions. The largest TLP asphaltene species were slightly smaller in size (by GPC and VPO) to those in the Feed asphaltenes; the smallest TLP asphaltene species were smaller than those isolated from the Feed asphaltenes and contained material with an initial boiling point of 340 °C despite both vacuum distillation (524 °C cutpoint) and pentane extraction being used during asphaltene preparation. For comparable molecular sizes by GPC and VPO, the TLP asphaltene fractions had lower H/C ratios and so were more aromatic and consisted of higher boiling material than the Feed asphaltene fractions. VPO results and elemental analysis trends confirmed that pentane extraction leaves behind molecules (asphaltenes) on the basis of some combination of size, aromatic content, and polarity. The significance of the various fractions of asphaltene species isolated remains to be evaluated in terms of their contributions to bitumen and heavy oil behavior during both production and thermal processing.
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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) | 0.000 | 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 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".