Competitive reactive adsorption desulphurization of dibenzothiophene and hydrogenation of naphthalene over Ni/ZnO
Bibliographic record
Abstract
Abstract Ni‐based catalysts are good alternatives to noble metal ones for hydrogenation. However, few effective sulphur‐resistant supported Ni catalysts are available commercially so far. This paper presents a Ni/ZnO catalyst prepared by coprecipitation. The optimal calcination temperature is found to be 350 °C. A set of experiments were conducted with addition of naphthalene and dibenzothiophene (DBT) as a model diesel. The reactive adsorption desulphurization activity increases with increasing reaction pressure. The Ni/ZnO catalyst exhibits high activity for naphthalene hydrogenation. The presence of naphthalene caused inhibition of the hydrogenation route and the conversion of DBT decreased slightly. DBT inhibited the hydrogenation of naphthalene and the conversion of naphthalene is 98 % and remained unchanged before 20 h time on stream at 0.4 MPa.
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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) | 0.000 | 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) | 0.000 | 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".