Oxygen Reduction Kinetics on Pt[sub x]Ni[sub 100−x] Thin Films Prepared by Pulsed Laser Deposition
Bibliographic record
Abstract
Mixed Pt–Ni thin films were prepared by crossed beam pulsed laser deposition. The depositions were performed at high kinetic energy conditions in the presence of 0.1 Torr He. X-ray diffraction patterns and X-ray reflectometry measurements showed that all films are made of a single face-centered cubic phase compound whose lattice parameter and density vary linearly with the bulk Pt composition. Likewise, X-ray photoelectron spectroscopy revealed that the Pt surface composition of thin films closely follows the bulk Pt concentration. The electrochemical active surface area (EASA) was evaluated by estimating , the hydrogen desorption charge in the potential region of ca. 0.05–0.35 V (where UPD stands for underpotential deposited). is almost constant for with but increases steadily for lower values of . This is thought to reflect the fact that dissolution of Ni atoms occurs, leading to an increase in the EASA and Pt enrichment at the surface of the films, as determined by XPS measurements. A positive potential shift (60 mV) of the half-wave current potential for oxygen reduction is observed as the Pt content is reduced from to . This effect is mostly related to an increase in the EASA as the intrinsic ORR activity of thin films, as determined from normalized kinetic current density values, is constant and does not vary with the bulk Pt content of the film.
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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".