Surface Reconstruction and Reactivity of Platinum–Iron Oxide Nanoparticles
Bibliographic record
Abstract
The electrochemical stability of platinum–iron oxide nanoparticles has been studied using X-ray absorption spectroscopy. Samples were monitored for changes in their surface structure and elemental composition after electrochemical cycling in acidic media, which were then correlated with their electronic properties and a thorough analysis of their electrocatalytic activities. In addition to the observation of significant surface restructuring, greater Fe content following electrochemical treatment was found to be associated with higher half-wave potentials and specific current densities (up to 0.965 ± 0.001 V RHE and 1.32 ± 0.03 × 10 –5 mA cm –2, respectively). This work highlights the potential to improve the electrocatalytic activity of platinum–iron oxide nanoparticles by controlling the Fe content and platinum–iron bonding, and demonstrates the critical importance of characterizing these nanocatalysts both before and after use.
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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".