Hydroprocessing of synthetic kerosene over a non‐sulphided Ni/ <scp> Al <sub>2</sub> O <sub>3</sub> </scp> catalyst: Impact of alcohols and ketones on alkene conversion
Bibliographic record
Abstract
Abstract Synthetic jet fuel containing non‐petroleum‐derived kerosene can be produced from synthetic kerosene obtained through processes that include a hydroprocessing step. The potential use of non‐sulphided (reduced) nickel supported on alumina (Ni/Al 2 O 3 ) was evaluated as an alternative to sulphided catalysts to saturate alkenes in sulphur‐free synthetic kerosene during hydrotreating operations. Performance of a 5 wt.% Ni/Al 2 O 3 catalyst for hydrotreating a model feed comprising n ‐decane, 1‐dodecene, and cumenes was evaluated at 50°C–220°C, 2 MPa, weight hourly space velocity of 1.75 h −1 , and a normal volumetric H 2 ‐to‐feed ratio of 500 m 3 /m 3 . At 50°C–110°C, alkene conversion was incomplete. Initial selectivity of alkene conversion was 20%–40% toward double bond isomerization (catalyzed by Ni) and about 60%–80% toward hydrogenation to alkanes. Aromatic saturation under these conditions was <4%. At 220°C, alkene saturation was nearly complete, and aromatic saturation was 40%–50%. A kerosene hydrotreater with steam heating, as opposed to furnace heating, could therefore be considered when using non‐sulphided Ni/Al 2 O 3 . Additionally, the impact of co‐feeding 1‐octene with oxygenates was determined. At 100°C, the presence of either alcohol or ketone co‐feed suppressed alkene conversion and shifted the selectivity toward double bond isomerization. These effects persisted after the oxygenate co‐feed was discontinued. At 220°C, co‐feeding alcohol led to near‐complete alkene conversion, but suppressed aromatic conversion, while oxygenate conversion remained incomplete. The threshold oxygenate tolerance of the catalyst was not established. In conclusion, the non‐sulphided Ni/Al 2 O 3 could be used for hydrotreating sulphur‐free synthetic kerosene to saturate alkenes; however, its performance is adversely affected when the feed contains oxygenates at percentage levels.
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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 | 0.000 | 0.001 |
| 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".