A comparative study of the catalytic nitration of toluene over bimetallic <scp>Ce‐Mn</scp> modified Hβ zeolite
Bibliographic record
Abstract
Abstract Bimetallic cerium‐manganese modified Hβ zeolite sample (Ce/Mn‐Hβ) was prepared by ultrasonic assisted impregnation method and applied in nitration of toluene. The characterization results show that the active components (Ce and Mn) are successfully introduced into the framework of Hβ zeolite. The catalyst shows excellent catalytic activity and reusability for the nitration of toluene, giving high para selectivity. Under optimized conditions, it gives 68.7% selectivity to para ‐nitrotoluene at 88.6% conversion over Ce/Mn‐Hβ in the presence of acetic anhydride (Ac 2 O). The theoretical calculations indicate that the Ce/Mn bimetallic active sites in modified Hβ zeolite can easily activate the nitrification reagent (AcONO 2 ), and the enhancement of para selectivity is owing to the steric hindrance of catalyst. Furthermore, the reaction mechanism was proposed by the combination of experimental results and theoretical calculations.
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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".