Metals Removal from Metal-Bridged Molecules by Acid Treatment of Oilsands Bitumen and Subfractions
Bibliographic record
Abstract
Multivalent metals in oilsands bitumen can be present in metal-bridged structures that keep smaller molecules together. Oilsands bitumen, maltenes, and asphaltenes were treated with hydrochloric acid to remove metals from these materials and evaluate the hypothesis that metals removal would improve asphaltenes to maltenes transformation. Single step acid treatment was effective for metal removal, particularly from asphaltenes. About 2600 μg/g divalent metals could be removed from the asphaltenes by washing with a 1 N HCl solution in a 4:1 mass ratio with the asphaltenes. Acid washing also resulted in some ester hydrolysis. Around 8 wt % of the asphaltenes fraction consisted of maltenes that were in the asphaltenes fraction as result of bridging and that could be returned to the maltenes fraction by acid treatment. It was estimated that the average molecular mass of these molecules liberated by acid treatment was of the order 700 g/mol. Water and/or acid washing did not meaningfully remove V and Ni. Multivalent metals were present predominantly in the organic phase, not in the connate water, and were removed mainly by acid washing. Water washing was deleterious and promoted emulsion formation. It was proposed that a pH-sensitive change in the relative concentration of phenol and phenoxide groups to increase the concentration of hydrophilic phenoxide groups was responsible for increased emulsion formation, and spectroscopic evidence in support of this was presented.
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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".