Halogenation of Oilsands Bitumen, Maltenes, and Asphaltenes
Bibliographic record
Abstract
Bromination of oilsands-derived materials was investigated as part of a search to find conversion pathways other than traditional hydroprocessing and thermal processing for the upgrading of asphaltenes. The working hypothesis was that the insertion of a bulky halogen substituent on an aromatic carbon of a multinuclear aromatic might sterically disrupt π–π ring stacking. Mild bromination (1–3 wt % Br incorporation) caused observable changes in the physical appearance of bitumen, maltenes, and asphaltenes. The hardness was increased and the asphaltenes gained solvent resistance, suggesting potential application as pretreatment for road paving asphalt. UV–vis spectrometry indicated that metalloporphyrin structures were disrupted, suggesting possible demetalation. There was also an increased association of oxygenate-rich asphaltenes with iron pyrite particulates already present in this fraction. Bromination was deleterious in its effect on bitumen and the maltenes, resulting in a decrease in straight run vacuum gas oil yield and increase in microcarbon residue. Conversely, bromination of asphaltenes resulted in an increase in straight run vacuum gas oil yield from 2.0 ± 0.3 wt % to 7.5 ± 1.8 wt % without affecting the microcarbon residue. It was not possible to unequivocally attribute the observed changes in the asphaltenes to the disruption of π–π ring stacking.
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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".