One-Pot Environmentally Friendly Approach toward Highly Catalytically Active Bimetal-Nanoparticle-Graphene Hybrids
Bibliographic record
Abstract
A one-pot universal approach with simple metal sputtering onto room temperature ionic liquids has been developed to prepare bimetal-nanoparticle (NP)-graphene hybrids, and the process is environmentally friendly and completely free of additives and byproducts. The graphene-supported bimetallic NPs have an Ag-based core and an Au/Pd-rich shell, demonstrated by the scanning transmission electron microscopy. The X-ray absorption near-edge spectroscopy using synchrotron radiation reveals the occurrence of charge redistribution at both the Ag@Au and Ag@Pd core-shell interfaces. The as-prepared Ag@Au and Ag@Pd bimetal-NP-graphene hybrids are highly catalytically active for reduction of 4-nitrophenol, whose catalytic activity is superior to the corresponding monometallic hybrids. The catalytic superiority is ascribed to the electronic structure modification and morphological irregularity of the graphene-supported bimetallic NPs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".