Hydrodesulphurization of dibenzothiophene on NiMoS catalysts: Impact of the carbon support on the reaction kinetics
Bibliographic record
Abstract
The hydrodesulphurization (HDS) activity of nickel molybdenum sulphided catalysts supported on activated carbon (NiMoS/AC), activated petroleum coke (NiMoS/APC), and conventional alumina (NiMo/γ‐Al2O3) have been compared using dibenzothiophene (DBT) as a model reactant. The reactions were carried out in a slurry‐phase batch microreactor at different reaction times (30–120 min) and temperatures (588–638 K) and a fixed H2 pressure (4.8 MPa). The NiMoS/APC catalyst had higher dispersion than the NiMoS/AC catalyst, resulting in a higher DBT conversion activity per gram of catalyst on the NiMoS/APC catalyst. However, similar activities were obtained on both catalysts when accounting for the NiMoS dispersion. The NiMoS/APC activity was marginally lower than the NiMoS/γ‐Al2O3 commercial catalyst, suggesting that activated petcoke is a promising support for NiMoS catalysts. The pseudo 1st order rate constants for both the direct desulphurization (DDS) and hydrogenation (HYD) reaction pathways were of similar magnitude on the NiMoS/APC catalyst, as were the apparent activation energies. Hence the selectivities for HYD versus DDS were favoured equally on the NiMoS/APC, unlike on NiMoS/Al2O3 where the DDS of DBT is favoured, or the NiMoS/AC where the DDS of DBT is favoured at higher temperatures (> 603 K). The results of this study demonstrate that raw petcoke derived from Canadian oilsands can be converted to a useful catalyst support for hydrotreating catalysts that have high NiMoS dispersion and HDS activity, comparable to that of a commercial NiMoS/Al2O3 catalyst.
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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".