Use of CuNi/YSZ and CuNi/SDC Catalysts for the Reverse Water Gas Shift Reaction
Bibliographic record
Abstract
Cu50Ni50 nanoparticles were synthesized using a modified polyol method and deposited on samarium-doped ceria, SDC, and yttria-stabilized zirconia, YSZ, supports to form reverse water-gas shift, RWGS, catalysts. The best CO yields, obtained with the Cu50Ni50/SDC catalyst, were about 90% of the equilibrium CO yields. In contrast CO yields using Pt/SDC catalysts were equal to equilibrium CO yields at 700°C. Catalyst selectivity to CO was 100% at hydrogen partial pressures equal to CO2 partial pressures, 1 kPa, and decreased as methane was formed when the hydrogen partial pressure was 2 kPa or greater. The reaction results were explained using a combination of Eley-Rideal and Langmuir-Hinshelwood mechanisms that involved adsorption on the metal surface and the concentration of oxygen vacancies in the support. Finally the Cu50Ni50/SDC catalyst was found to be thermally stable for 48 hours at 600/700°C.
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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 | 0.001 | 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".