Nanoscopic Ni Interfaced with Oxygen Conductive Supports: Link between Electrochemical and Catalytic Studies
Bibliographic record
Abstract
Nickel NPs of ~70 nm diameter were tested for their catalytic and electrochemical performance when free-standing or supported at 1 wt.% on CeO 2 or YSZ conductive supports. Nickel showed a high catalytic conversion (43 %) when supported on CeO 2 and to a less extent when supported on YSZ (38%) compared to free-standing Ni (5%), for the ethylene oxidation reaction at 350 o C. The electrochemical tests consisted of polarization measurements at constant oxygen partial pressure. The corresponding Tafel plots allowed us to find the exchange current density, i o , of the catalysts. Using i o , the self-induced Faradaic efficiency L MSI was calculated for the two supported catalysts and was found to be almost the double for Ni/CeO 2 compared to Ni/YSZ, with both being much higher than that of free-standing Ni NPs. These results suggested that more oxygen ions from CeO 2 are able to act as promoters at the gas/catalyst surface interface than in the case of YSZ, thus resulting in the highest catalytic performance. When correlating the exchange current density to the catalytic performance of Ni, Ni/YSZ and Ni/CeO 2 , the same trend was found as for the noble metals (Pt, Ru, Ir) reported previously, showing that the lower i 0 correlates with a higher catalytic reaction rate. This correlation suggests that for nanoscopic Ni catalysts interfaced with oxygen conducting ceramics, the mechanism of metal-support interaction (MSI) is similar to that in electrochemical promotion of catalysis (EPOC).
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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 | 0.001 | 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".