Understanding the Role of Ir during Methanol Oxidation at Pt<sub>x</sub>Ir<sub>y</sub>Alloy Nanoparticles
Bibliographic record
Abstract
The formation of Pt x Ir y alloy nanoparticles (NPs), having a controlled bulk and surface composition over a wide range of Ir content (35-90 at% Ir), was reported in our recent work.While this prior work did examine the activity of these NPs toward the methanol oxidation reaction (MOR), this was done only per mass of catalyst and only under RT conditions.Here, the MOR activity is reported based on the real surface area of the NPs, determined using several electrochemical methods as well as TEM analysis, in both room temperature (RT) and 60 • C methanol-containing 0.5 M H 2 SO 4 solutions.These more comprehensive results suggest that the bi-functional effect of Ir on Pt activity plays the most significant role in catalyzing the MOR, with the optimum Ir content found to be ca.35 at% and 50 at% at low and high potentials, respectively, at both temperatures.This demonstrates that less Ir is needed when the CO production rate is low, as is the case for methanol oxidation at the low potentials desired in operating direct methanol fuel cells.
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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".