Insights into the Mechanism of Cumene Peroxidation Using Supported Gold and Silver Nanoparticles
Bibliographic record
Abstract
Due to the considerable industrial implications, an in-depth study of cumene peroxidation using supported gold and silver nanoparticles was carried out to gain more insight into the mechanism of this reaction. Supported gold nanoparticles were found to efficiently catalyze the decomposition of cumene hydroperoxide with a selectivity of 25% at 80 °C when using gold supported on hydrotalcite (AuNP@HT), and 2-phenyl-2-propanol (i.e., cumyl alcohol) was the main product. Further, silver nanoparticles supported on hydrotalcite (AgNP@HT) converted cumene to cumene hydroperoxide at 80 °C with 80% selectivity. Both benchtop and oxygen-uptake experiments were used to probe the reaction mechanism and suggest that formation of a peroxyl radical-nanoparticle adduct is an important step in the peroxidation pathway and may be directly involved in the formation of the major cumyl alcohol product.
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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 | 0.000 | 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 | 0.001 |
| 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".