Effects of O<sub>2</sub> on Characteristics of Sulfur Added to Petroleum Coke through Reaction with SO<sub>2</sub>
Bibliographic record
Abstract
Alberta oil-sands petroleum coke is an abundant byproduct of the upgrading of bitumen. The current study aims to improve the current understanding of sulfur added to the surface of petroleum coke through reaction with sulfur dioxide (SO 2 ) and how this is affected by a large excess of oxygen (O 2 ). Particular focus is given to the distribution and speciation of sulfur within the coke particles, as well as its thermal stability. Petroleum coke was activated in SO 2 with and without O 2 in a packed bed reactor at 600−800 °C. The activated cokes were characterized with electron probe microanalysis (EPMA), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Cross-sectional analysis with EPMA of activated coke particles revealed that sulfur-rich coke particles (i.e., SIAC) could be produced with and without O 2 . Under low SO 2 (3%), high O 2 (18%) conditions, however, O 2 competitively reacted with coke at 600 °C, and SO 2 only reacted to form a sulfur-rich layer after O 2 had been depleted. Analysis with XPS suggested that the sulfur-rich layer of the coke particles was made up of thiophene from the coke plus carbon−sulfur surface complexes, mainly heterocyclic sulfide and disulfide, while the presence of aliphatic sulfide, thiolactone, and thiol could not be ruled out. TGA and DSC analyses confirmed that sulfur added to activated coke via reaction with SO 2 was not elemental in nature. In both N 2 and air, sulfur added via high-temperature reaction with SO 2 is more thermally stable than that of a commercial SIAC sulfurized at lower temperatures. This may have beneficial implications if these SO 2 activated cokes were to be used to capture mercury, since they could be thermally regenerated with minimal loss of active sulfur surface sites while the captured mercury is collected, avoiding the costly and potentially problematic landfill disposal of Hg-containing activated carbon.
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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".