Mesostructured Zn/ZSM‐5 Zeolite as Catalyst for Furan Deoxygenation,
Bibliographic record
Abstract
Abstract The furan conversion into aromatics over zinc promoted ZSM‐5 zeolites was studied in a continuous‐flow fixed‐bed reactor. Two series of microporous and mesoporous catalysts were prepared at different zinc loadings of 2 and 5 wt.%. It was intended to optimize the overall aromatics production and control coke accumulation over novel synthesized mesoporous ZSM‐5 catalyst, in a continuous flow reactor. The catalysts were characterized using X‐ray diffraction (XRD), nitrogen adsorption/desorption, ammonia temperature programmed desorption (TPD) and X‐ray photoelectron spectroscopy (XPS). The zinc loaded mesoporous materials exhibit an XRD pattern that matches with the ZSM‐5 XRD reference pattern. No extra peaks were observed in the XRD results indicating the high dispersion of zinc species. The initial furan conversion rate was higher over the microporous catalysts, and increased upon increasing metal loading, however contrary to the mesoporous samples, the microporous ones deactivated rapidly over 2 hours of time on‐stream. The results indicated that around 40 % of carbon in the fed furan, was recovered in aromatics when the new mesostructured zeolite catalyst was used, whereas this could be further increased to 50 % by the addition of zinc in the catalyst, benzene being the major product.
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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) | 0.000 | 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 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".