Structural and Electrochemical Properties of Nanocrystalline PtRu Alloys Prepared by Crossed-Beam Pulsed Laser Deposition
Bibliographic record
Abstract
Mixed Pt−Ru thin films were prepared by crossed-beam pulsed laser deposition. The depositions were performed at different He background gas pressures, and the composition was varied over the whole composition range. X-ray diffraction patterns and X-ray photoelectron spectroscopy were used to assess the structure, the surface composition, and the electronic structure of the catalysts. The electrochemical properties of the films were assessed through cyclic voltammetry and CO stripping measurements in acidic solution. Consistent with the binary Pt−Ru phase diagram, it is shown that fcc Pt(Ru) is formed for [Pt] bulk ≥ 40 atom %, whereas hcp Ru(Pt) is obtained for [Pt] bulk ≤ 20 atom %. Likewise, X-ray photoelectron spectroscopy revealed that the Pt surface composition of Pt x Ru 100− x thin films closely follows the bulk Pt concentration. There is a ca.0.8 eV difference in the value of Δ(Ru 3d 5/2 −Pt 4f 7/2 ) as the [Pt] bulk is increased from 0 to 100 atom %, indicating that the alloy is present at the surface of the film. Alloying of Pt and Ru leads to a negative (less anodic) shift of the CO stripping peak potential, and this effect is maximal (210 mV shift) for a Pt 50 Ru 50 . Increasing the He background gas pressure in the deposition chamber increases the porosity of the films and roughness factor, defined as the ratio of the electrochemically active surface to the geometric surface of the substrate, and a value as high as ca. 100 is obtained for Pt 50 Ru 50 deposited at 3.5 Torr He.
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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".