Efficient manganese decorated cobalt based catalysts for hydrogenation of 5‐hydroxymethylfurfural (HMF) to 2,5‐dimethylfuran (DMF) biofuel
Bibliographic record
Abstract
Abstract 2,5‐dimethylfuran (DMF) is a promising compound in the production of biofuel with high‐quality properties. In this study, it is aimed to develop new efficient catalysts to synthesize DMF from 5‐hydroxymethylfurfural (HMF). Co, Mn/Co, and Ru/Co catalysts were prepared using the NaBH4 reduction method. The catalysts were subjected to activity tests for the hydrogenation of HMF to DMF by changing the reaction parameters, such as temperature and time. Mn/Co catalysts prepared from metal precursors at various molar ratios of Mn/Co were found to be effective in hydrogenation reactions of HMF to DMF. A 91.8% DMF yield was achieved in the presence of a Mn/Co (50/50) catalyst without noble metal at 180°C for 4 hours. The Brunauer‐Emmet‐Teller (BET) method, x‐ray diffraction (XRD), x‐ray photoelectron spectroscopy (XPS), and induction coupled plasma mass spectroscopy (ICP‐MS) techniques were used to characterize the efficient Mn/Co catalyst.
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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 | 0.000 |
| 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) | 0.001 | 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".