Compositional and Morphological Changes of Ordered Pt<sub><i>x</i></sub>Fe<sub><i>y</i></sub>/C Oxygen Electroreduction Catalysts
Bibliographic record
Abstract
Abstract Changes in the O2 reduction activity (ORR) and structure of carbon‐supported catalysts upon electrochemical stress testing are investigated. Focus is placed on two alloy catalysts of nominal Pt3Fe/C and Pt3Fe2/C compositions. Energy dispersive X‐ray spectroscopy (EDXS) spot and line analyses reveal a dependence of the Fe composition on the particle size, particularly for the two as‐prepared catalysts. The catalyst particles are shown to have a Pt‐enriched shell and a PtxFey alloy core. Larger (>≈10 nm) particles are shown to have a higher Fe content that approaches the nominal composition, which suggests that the smaller (<≈6 nm) Pt catalyst particles are more difficult to alloy. High‐angle annular dark‐field scanning transmission electron microscopy (HAADF‐STEM), XRD, and SEM with EDXS show that Fe is lost gradually from the catalyst particles as a result of extensive potential (E)‐cycling. Changes upon E‐cycling are observed most clearly for the small (<3 nm) particles, in which Fe is almost entirely depleted. However, the catalytic ORR activities remain constant over an extensive cycling period for the PtxFey/C catalysts and the mass ORR activities decrease proportionally with Pt surface area (APt). The histograms before and after cycling are compared to observed changes in APt and are discussed in comparison to E‐holding experiments. It is concluded that the dissolution of Pt is a strong contributor for the observed decrease in APt and mass ORR activity for the PtxFey/C catalysts. The continuous transition between Pt oxide formation and its reduction to Pt metal is suggested to play a major role in the degradation of the PtxFey/C catalysts studied in this work.
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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 | 0.000 |
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".