Sonochemical Synthesis of Cu@Pt Bimetallic Nanoparticles
Bibliographic record
Abstract
Reducing the amount of noble metals in catalysts for electrochemical conversion devices is paramount if these devices are to be commercialized. Taking advantage of the high degree of particle property control displayed by the sonochemical method, we set out to synthesize Cu@Pt bimetallic nanocatalysts in an effort to improve the mass activity towards the hydrogen evolution reaction. At least 17 times higher mass activity was found for the carbon supported Cu@Pt bimetallic nanocatalyst (737 mA mg−1, E = −20 mV) compared to carbon supported Pt nanocatalysts prepared with the same ultrasound conditions (44 mA mg−1, E = −20 mV). The synthesis was found to proceed with the sonochemical formation of Cu and Cu2O nanoparticles with the addition of PtCl4 leading to galvanic displacement of the Cu-nanoparticles and the formation of a Pt-shell around the Cu-core.
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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 | 0.001 |
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".