AuCu@Pt Nanoalloys for Catalytic Application in Reduction of 4-Nitrophenol
Bibliographic record
Abstract
To enhance and optimize nanocatalyst ability for nitrophenol (4-NP) reduction reaction we look beyond Au-metal nanoparticles and describe a new class of Au nanoalloys with controlled composition for core of AuCu-metals and Pt-metal shell. The reduction of 4-NP was investigated in aqueous media spectroscopically on 7.8 nm Au nanospheres (AuNSs), 8.3 nm AuCuNSs, and 9.1 nm AuCu@Pt core-shell NSs in diameter. The rate constants of the catalyzed reaction at room temperature, activation energies, and entropies of activation of reactions catalyzed by the AuCu@Pt core-shell NSs are found to have different values to those of the pure metal NSs. The results strongly support the proposal that catalysis by nanoparticles is taking place efficiently on the surface of NSs. These core-shell nanocatalysts exhibited stability throughout the reduction reaction and proved that heterogonous type mechanisms are most likely to be dominant in nanoalloy based catalysis if the surface of the NSs is not defected upon shell incorporation.
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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".