Furfural hydrogenation to 2‐methylfuran over efficient sol‐gel copper‐cobalt/zirconia catalyst
Bibliographic record
Abstract
Abstract 2‐Methylfuran (MF) is a candidate to be a high‐quality fuel additive. For the first time, efficient Co‐Cu/ZrO 2 catalysts were prepared by the sol‐gel method and herein used for MF synthesis from furfural. Although a 9.2% MF yield and no MF was obtained using Cu/ZrO 2 and Co/ZrO 2 , respectively, a 77.5% MF yield was observed at 200°C, under 1.5 MPa initial H 2 pressure for 4 hours using a Co‐Cu/ZrO 2 catalyst. The Co amount was changed in the catalyst structure and the effect of the Co amount on furfural hydrogenation was investigated. The most effective catalyst was the Co‐Cu/ZrO 2 catalyst, with 0.08 g/g (8 mass%) Cu and 0.118 g/g (11.8 mass%) Co. The activity tests of the catalysts were carried out for hydrogenation of furfural to MF by changing reaction parameters such as pressure, loading of catalyst, temperature, and time. A 94.1% MF yield was achieved in the presence of the Co‐Cu/ZrO 2 catalyst with 0.08 g/g (8 mass%) Cu and 0.118 g/g (11.8 mass%) Co at 200°C for 6 hours under 1.5 MPa H 2 pressure. The catalyst also showed good reusability properties after the fifth use. The catalysts were characterized by Brunauer‐Emmet‐Teller method, X‐ray diffraction, X‐ray photoelectron spectroscopy, and temperature programmed reduction techniques.
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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".