Liquid Phase Selective Hydrogenation of Citral over Bimetallic Transition Metal Catalysts
Bibliographic record
Abstract
Silica supported bimetallic catalysts of Co-Ni, Ni-Cu and Cu-Co were prepared by deposition precipitation method, calcined at two different temperatures 475°C and 675°C. The prepared catalysts were characterized by BET surface area, SEM, EDX, FT-IR, thermogravimetry and XRD techniques. The XRD measurement of Ni–Cu/SiO2 catalyst has peaks due to CuO and NiO oxides. The catalytic activity and selectivity of these prepared catalysts towards liquid phase selective hydrogenation were studied. Amongst the studied catalysts, Co–Ni/SiO2 cacined at 475°C had presented higher selectivity in terms of citral towards unsaturated alcohols (geraniol and nerol) in a isopropanol solvent medium and 0.2% catalyst loading, at 90°C temperatures under 4 bar pressure with 750 rpm agitation.
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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".