Electro-oxidation of CO<sub>chem</sub> on Pt Nanosurfaces: Solution of the Peak Multiplicity Puzzle
Bibliographic record
Abstract
An understanding of the oxidation of chemisorbed CO (CO(chem)) on Pt nanoparticle surfaces is of major importance to fuel cell technology. Here, we report on the relation between Pt nanoparticle surface structure and CO(chem) oxidative stripping behavior. Oxidative stripping voltammograms are obtained for CO(chem) preadsorbed on cubic, octahedral, and cuboctahedral Pt nanoparticles that possess preferentially oriented and atomically flat domains. They are compared to those obtained for etched and thermally treated Pt(poly) electrodes that possess atomically flat, ordered surface domains separated by grain boundaries as well as those obtained for spherical Pt nanoparticles. A detailed analysis of the results reveals for the first time the presence of up to four voltammetric features in CO(chem) oxidative stripping transients, a prepeak and three peaks, that are assigned to the presence of surface domains that are either preferentially oriented or disordered. The interpretation reported in this article allows one to explain all features within the voltammograms for CO(chem) oxidative stripping unambiguously.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".