γ‐Alumina supported Cu‐Ni bimetallic catalysts: Characterization and selective hydrogenation of 1,3‐butadiene
Bibliographic record
Abstract
Abstract Addition of a second metal often improves the selectivity of a supported catalyst for the hydrogenation of 1,3‐butadiene. Catalysts containing 15 wt% Ni and varying amounts of Cu were prepared and characterized by TPR, XRD and XPS. The Cu‐Ni interaction affects the reduction behavior of the catalysts. TPR result shows that the synergetic effect of copper and nickel modifies the capability of metal to combine with hydrogen in bulk phase. The Ni 2p spectra in XPS shows significant shifts toward lower binding energies with increasing copper loading. From XRD results it is represented that aggregation of nickel occurs more easily due to the copper addition. The adding of copper on Ni/Al 2 O 3 makes the conversion rate decreased and increases the selectivity to 1‐butene.
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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) | 0.000 | 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) | 0.000 | 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".