Rationally designed bimetallic Au@Pt nanoparticles for glucose oxidation
Bibliographic record
Abstract
Bimetallic nanoparticles (NPs) have aroused interest in various fields because of their synergetic and unique properties. Among those nanoparticles, we strategically approached and synthesized Au@Pt NPs via the sonochemical method with different molar ratios (e.g. 3:7, 5:5, and 7:3) of Au to Pt precursors. The particle structure was confirmed to be core-shell, and the size was estimated to be 60, 52, and 47 nm, respectively, for 3:7, 5:5, and 7:3 ratios of Au to Pt. The detailed structure and crystallinity of as-prepared Au@Pt NPs were further studied by scanning electron microscopy, transmission electron microscopy with element mapping, and X-ray diffraction. It should be noted that thickness of the dendritic Pt shell in the core-shell structure can be easily tuned by controlling the molar ratio of Au to Pt. To explore the possibility of this material as glucose sensor, we confirmed the detection of glucose using amperometry. Two dynamic ranges in a calibration plot were displayed at 0.5-50.0 µM and 0.05-10.0 mM, and their detection limit as glucose sensor was determined to be 319.8 (±5.4) nM.
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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 | 0.001 | 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".