Probing the effects of metal loading and calcination temperature on AgOx/Al₂O₃ catalyst in ozonative epoxidation of ethylene
Bibliographic record
Abstract
This work explores the ozonative epoxidation of ethylene to produce ethylene oxide over AgO x /Al₂O₃ catalysts which is a novel reaction pathway that remains underexplored due to its recent emergence. The study focuses on the effects of silver loading and calcination temperature. Higher silver loading was found to increase the abundance of silver species on the support surface, which accelerates ozone decomposition and elevates surface oxygen coverage. This enhanced oxygen coverage, along with reduced ethylene adsorption, promotes the direct formation of ethylene oxide while maintaining high conversion rates. The catalyst with 10 wt% silver achieved an ethylene conversion of 96 % and an ethylene oxide selectivity of 68 %. Increasing the calcination temperature from 350 ºC to 750 ºC altered silver oxidation states and improved catalyst stability and ozone conversion. However, no significant enhancement in ethylene oxide selectivity was observed, likely due to limited improvement in surface oxygen coverage under those conditions. which are considered beneficial for epoxidation. Structural evolution of silver species under different atmospheres was investigated using in situ pair distribution function (PDF) analysis, revealing successive redox transformations during heating. Overall, Ag loading had a more significant impact on ethylene oxide selectivity than calcination temperature, highlighting it as a key factor in optimizing catalyst performance in ozonative epoxidation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".