Comparative Study of Nanoporous Pt, PtRu and PtRuIr Catalysts Using Electrochemical FTIR Spectroscopy
Bibliographic record
Abstract
In recent years much effort has been put towards developing efficient Pt-based electrocatalysts for applications in fuel cells. With the rising cost of precious metals such as Pt,the need to enhance the activity and to decrease the load of catalysts is prominent. Herein we report on the synthesis and comparative study of nanoporous Pt,PtRu and PtRuIr electrocatalysts. The nanoporous electrodes were fabricated using a hydrothermal method and characterized by scanning electron microscopy (SEM) ,energy dispersive spectroscopy (EDS) ,X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) . The electrocatalytic activity of the fabricated nanopo- rous materials was evaluated using both CO stripping experiments and methanol oxidation reactions,revealing that the addition of Ir greatly improved the activity of the nanoporous PtRu. To decipher the origin of the significant enhancement,in-situ electrochemical FTIR spectroscopy was employed to study the oxidation of methanol on the nanoporous Pt,PtRu and PtRuIr electrodes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".