Selective Aerobic Oxidation of 5‐Hydroxymethylfurfural to 2,5‐Diformylfuran or 2‐Formyl‐5‐furancarboxylic Acid in Water by using MgO⋅CeO<sub>2</sub> Mixed Oxides as Catalysts
Bibliographic record
Abstract
Abstract Mixed oxides based on MgO ⋅ CeO 2 were used as efficient catalysts in the aerobic oxidation of 5‐hydroxymethylfurfural (5‐HMF) to afford, with very high selectivity, either 2,5‐diformylfuran (DFF, 99 %) or 2‐formyl‐5‐furancarboxylic acid (FFCA, 90 %), depending on the reaction conditions. 5‐Hydroxymethyl‐2‐furancarboxylic acid (HMFCA, 57–90 %) was formed only at low concentration of 5‐HMF (<0.03 m ) or in presence of external bases. The conversion of 5‐HMF ranged from a few percent to 99 %, according to the reaction conditions. The oxidation was performed in water, with O 2 as oxidant, without any additives. The surface characterization of the catalysts gave important information about their acid–base properties, which drive the selectivity of the reaction towards DFF. FFCA was formed from DFF at longer reaction times. Catalysts were studied by XPS and XRD before and after catalytic runs to identify the reason why they undergo reversible deactivation. XRD showed that MgO is hydrated to Mg(OH) 2 , which, even if not leached out, changes the basic properties of the catalyst that becomes less active after some time. Calcination of the recovered catalyst allows recovery of its initial activity. The catalyst is thus recoverable (>99 %) and reusable. The use of mixed oxides allows tuning of the basicity of the catalysts, avoiding the need for external bases for efficient and selective conversion of 5‐HMF and waste formation, resulting in an environmentally friendly, sustainable process.
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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) | 0.001 | 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 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".