Corrosion Resistance and Stability of the Pt-Ni and Pt-Co Nanoparticles Prepared by the Double Potential Step Electrolysis
Bibliographic record
Abstract
The Pt-Ni and Pt-Co nanoparticles covered with a Pt skin layer were prepared by the double potential step electrolysis (DPSE), which composed of potential steps for electrodeposition of the Pt-Ni and Pt-Co alloy and the following selective dissolution of the Ni and Co component, respectively. With this method, the Pt alloy nanoparticles covered with a Pt skin layer could be prepared just in one process, and the composition and size of the Pt alloy nanoparticles could be easily controlled by changing the electrode potential and plating bath composition. Both the nanoparticles by the DPSE exhibited higher corrosion resistance and oxygen reduction reaction (ORR) activity than the Pt nanoparticles even after deterioration test, and the surface contents of them were kept constant around 4 % Co and 8 % Ni measured by XPS over the wide range of Pt alloy compositions, respectively. Comparing the Pt-Ni with Pt-Co nanoparticles, the Pt-Co nanoparticles were found to be more stable than the Pt-Ni nanoparticles, and suggested that a Pt-skin layer on Pt alloy particles had an important role in their performances.
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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 | 0.001 |
| 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 | 0.001 |
| 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".