Direct oxidation esterification of methacrolein with methanol: Oxygen vacancy promotion of Zr‐doped Au/CeO<sub>2</sub> nanorods
Bibliographic record
Abstract
Abstract A series of Zr‐doped CeO2 nanorods supported by Au nanoparticle catalysts with different morphologies were prepared for methyl methacrylate (MMA) synthesis via direct oxidation esterification of methacrolein (MAL) with methanol. Catalytic activities under mild conditions (0.3 MPa; 80°C) were evaluated in the kettle reactor. Different characterization methods, such as XRD, Raman, N2 adsorption, ICP, TEM, SEM, XPS, and H2‐TPR techniques, were applied to study the relationship between catalytic activity and structural characteristics, especially the form of Zr doped into the lattice of CeO2 and the promotion mechanism of selective oxidation. The influence of Au supported on Ce0.6Zr0.4O2 nanorods (Au/CZ‐R) was also discussed. The results exhibited that the highest catalytic activity for the oxidative esterification with a MAL conversion of 99% and a MMA selectivity of 74% was achieved. The MMA synthesis performance correlated well with the surface oxygen vacancies, in particular for the active oxygen species around the Au particles.
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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".