XRD and XPS Study of Cu−Ni Interactions on Reduced Copper−Nickel−Aluminum Oxide Solid Solution Catalysts
Bibliographic record
Abstract
Copper−nickel−aluminum oxide solid solutions were reduced in hydrogen to produce alumina-supported copper−nickel alloy catalysts. XRD patterns of reduced oxides showed that the type of active metals which emerged upon reduction were sensitive to the reduction temperature and the copper content. Variations from +0.8 to +1 eV were found in the experimental Ni 2p 3/2 binding energy (BE) of nickel in the solid solutions compared to the experimental Ni 2p 3/2 BE of bulk nickel, attributed to the Ni−Ni arrangements in the solid solution. Also, when the curve-fitted BE values of Ni 2p 3/2 and Cu 2p 3/2 of different reduced solid solutions were compared, it was found that copper and nickel were in different chemical states depending on reduction temperature and the amount of the copper. Changes in Ni 2p 3/2 BE in the reduced solid solutions were also discussed in terms of the filling of nickel d-hole bands due to nickel−copper d−d band interactions. At both high copper content and reduction temperature, copper had a tendency to segregate in order to reduce the interfacial surface energies. This was postulated based on the observation that the Ni 2p 3/2 curve-fitted BE values were restored to somewhat close to bulk nickel at a copper content of 11 mol % and reduction temperature of 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 | 0.000 | 0.001 |
| 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".