Hierarchical H-ZSM5 zeolites based on natural kaolinite as a high-performance catalyst for methanol to aromatic hydrocarbons conversion
Bibliographic record
Abstract
The present work introduces a good prospect for the development of hierarchical catalysts with excellent catalytic performance in the methanol to aromatic hydrocarbons conversion (MTA) process. Hierarchical H-ZSM5 zeolites, with a tailored pore size and different Si/Al ratios, were synthesized directly using natural kaolin clay as a low-cost silica and aluminium resource. Further explored for the direct synthesis of hierarchical HZSM-5 structures was the steam assisted conversion (SAC) with a cost-effective and green affordable saccharide source of high fructose corn syrup (HFCS), as a secondary mesopore agent. The fabricated zeolites exhibiting good crystallinity, 2D and 3D nanostructures, high specific surface area, tailored pore size, and tunable acidity. Finally, the catalyst performance in the conversion of methanol to aromatic hydrocarbons was tested in a fixed bed reactor. The synthesized H-ZSM5 catalysts exhibited superior methanol conversion (over 100 h up to 90%) and selectivity (over 85%) in the methanol conversion to aromatic hydrocarbon products.
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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".