Role of the Metal‐Oxide Support in the Catalytic Activity of Pd Nanoparticles for Ethanol Electrooxidation in Alkaline Media
Bibliographic record
Abstract
Abstract The promotional role of oxide supports (CeO2, SnO2, TiO2) on ethanol electrooxidation in alkaline media over Pd nanoparticles (NPs) is presented and compared to Pd on carbon. XPS revealed a shift to lower binding energy of the Pd 3d peak when Pd NPs were deposited on metal oxides, implying a charge transfer from the oxides to the Pd. The catalytic activity of the supported NPs for ethanol electrooxidation was assessed by using cyclic voltammetry and chronoamperometry. The electrooxidation products were monitored in situ, using polarization modulation–infrared reflection absorption spectroscopy (PM‐IRRAS), which revealed that the supports influence the selectivity of reactions on Pd. Pd/CeO2 has superior selectivity towards breaking the C−C bond to produce CO2 compared to the other three supports. Acetate, as a product, was evident on all of the catalysts, but at different ratios. Pd supported on metal oxides showed higher activity and, in particular, CeO2 and SnO2 stand out as the best supports.
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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".