Two-Stage Hydrotreating of Athabasca Heavy Gas Oil with Interstage Hydrogen Sulfide Removal: Effect of Process Conditions and Kinetic Analyses
Bibliographic record
Abstract
Two-stage hydrodenitrogenation (HDN)−hydrodesulfurization (HDS) of heavy gas oil, derived from Athabasca bitumen, has been carried out in a trickle-bed microreactor using a commercial NiMo/Al 2 O 3 catalyst. The operating conditions for the experiments were varied as follows: temperature range of 340−420 °C, reactor pressure of 950−1600 psig, liquid hourly space velocity range of 0.5−2.0 h -1, and hydrogen to heavy gas oil ratio of 600 mL/mL. Variation in the catalyst loading between stages I and II was also studied. Stage I products were stripped off any generated hydrogen sulfide and further hydrotreated in stage II to see the impact of hydrogen sulfide interstage removal on the hydrotreating activities. A comparison of the two-stage results to those of the single-stage results shows an enhancement in the hydrotreating activities. For instance, a 12.6 wt % increase in the conversion of nonbasic nitrogen was observed. The optimum conditions for higher gain in HDN and HDS due to hydrogen sulfide removal were found to be 380 °C, 7.6 MPa, and 1:3 (w/w) catalyst loading. A Langmuir−Hinshelwood model developed for the hydrogen sulfide inhibition predicts sufficiently the observed data of the two-stage process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".