Sonochemical and impregnated Co-W/γ-Al2O3 catalysts : performances and kinetic studies on hydrotreatment of light gas oil
Bibliographic record
Abstract
-Al O 2 3 supported Co-W based catalysts with varying Co (1 -3 wt %) and W (7 -13 wt %) loadings were prepared using impregnation and sonochemical methods.All prepared catalysts were characterized with elemental analysis, BET analysis, X-ray diffraction (XRD), NH 3 temperature programmed desorption (TPD), temperature programmed reduction (TPR) and thermogravimetry analysis (TGA).The performances of all the synthesized catalysts were tested at a pressure of 8.9MPa, LHSV of 2 h -1 and temperatures of 340350 and 360 C in a laboratory trickle bed microreactor for hydrodesulphurization (HDS) and hydrodenitrogenation (HDN) of light gas oil (LGO) derived from Athabasca bitumen.The performance tests with impregnated catalysts indicated a maximum in activity for HDS and HDN reactions (sulfur and nitrogen conversions at 93.0 and 57.1 % at 360 C) for Co(3 wt %)-W(10 wt %)/-Al O 2 3whereas the performance tests with sonochemically prepared catalysts showed a maximum in activity (sulfur and nitrogen conversions at 87.9 and 42.5 % at 360 C) for Co(3 wt %)-W(11.5 wt %)/ -Al 2 O 3 .These two catalysts were selected for detail performance, optimization and kinetic studies.The effects of reaction temperature (340 -380 C), pressure (7.6 -10.3 MPa), liquid hourly space velocity (1.5 -2.0 h -1 ) and hydrogen gas/gas oil ratio (400 -800 mL/mL) were examined on HDS and HDN of LGO with these catalysts.The reaction kinetics for HDS was best fitted with a Power Law model whereas same for HDN was found to be best represented by a Langmuir-Hinshelwood model with a reasonable accuracy (0.90 <R 2 <0.95).The activation energy for HDS of LGO were 14 and 12 kJ/mol for selected impregnated and sonochemically
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".