Catalytic Bitumen Partial Upgrading under Methane Environment over Ag-Mo-Ce/ZSM-5 Catalyst and Mechanistic Study Using<i>N</i>-Butylbenzene as Model Compound
Bibliographic record
Abstract
Bitumen extracted from oil sands which is abundant in Canada needs to be partially upgraded to meet pipeline specifications before being sent to downstream refineries. Hydrotreating where expensive hydrogen is involved at high pressure (15–20 MPa) is commonly employed as the technique to satisfy the upgrading requirement. In this study, it is reported that a partially upgraded crude oil can be readily produced from bitumen under a methane environment at mild conditions (400 °C and 3 MPa) without H 2 engagement under the facilitation of 1%Ag-5%Mo-10%Ce/ZSM-5 (Si/Al = 23:1). Moreover, methane participation into the upgrading process was evidenced by model compound reactions employing n -butylbenzene as a model compound to typify heavy oil and clearly observed in 1 H and 2 D NMR spectra when CD 4 was engaged as the methane source. Through extensive catalyst characterizations using TEM, XRD, and XPS, the excellent catalytic upgrading performance might be closely related to the highly dispersed silver and molybdenum oxide on the zeolite support at reduced oxidation state for better methane activation and partially reduced cerium oxide for coke reduction owing to its high oxygen mobility. The outcomes from this research could not only create an innovative route for more profitable natural gas utilization but also benefit bitumen partial upgrading in a more economical and environmentally friendly way.
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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".