Amorphous Silica-Alumina-Catalyzed Alkene-Aromatic Alkylation of Cracked Naphtha: Cyclopentene Species as Precursors for Catalyst Deactivation
Bibliographic record
Abstract
Acid-catalyzed alkene-aromatic alkylation of cracked naphtha is a process of interest for partial upgrading of bitumen without hydrogen. The time-on-stream period before catalyst regeneration is necessary and is affected by formation of carbonaceous deposits (coking). It was postulated that 5-membered ring cyclic alkenes like cyclopentenes were important precursors for catalyst deactivation by coking, compared to linear alkenes. Using cracked naphtha, it was demonstrated that at 300 °C, cyclopentene species were converted both thermally and catalytically. The extent of catalytic conversion increased with Brønsted acidity of the catalyst. To better interpret the findings, model mixtures comprising cyclopentene, 1-hexene, ethylbenzene, and n -heptane were used to compare the impact of the different alkenes to catalyst coking. The three main products detected from acid-catalyzed cyclopentene reactions were trans -decalin, cis -decalin, and bicyclopentylidene. A plausible explanation of the pathway with a common intermediate was presented. Differences between conversion of cyclopentene and 1-hexene were explained in terms of the lower basicity of cyclopentene compared to that of 1-hexene, which also explained why cyclopentene conversion was suppressed by ethylbenzene through competitive adsorption on the acid catalyst but not that of 1-hexene. Catalyst coking was evaluated using electron spin resonance spectrometry. Compared to 1-hexene, cyclopentene produced 3–4 times more products with persistent free radicals and was not affected by the presence of ethylbenzene in the reaction mixture, evidencing that it has a more pronounced impact in catalyst coking. However, the extent of coking on the silica-alumina catalyst caused by cyclopentene was insufficient to account all the coking of cracked naphtha, which on equal alkene concentration basis was 2 times more prone to coking than cyclopentene.
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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".