Catalytic Oxidative Valorization of Biobased 5-Hydroxymethylfurfural over Multi-ligand Functionalized Polyoxovanadates
Bibliographic record
Abstract
The oxidative conversion of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF) is an important reaction for the utilization of biomass resources. This process has garnered considerable research attention in both industry and academia, yet it still presents considerable challenges. To achieve an effective and mild oxidative upgrade of the HMF molecule, a multiorganic-ligand-functionalized polyoxovanadate catalyst, V 6 O 6 (OCH 3 ) 4 (mIM) 6 (C 6 H 5 PO 3 ) 4 ( P 4 V 6 ), has been successfully prepared by using both oxygen- and nitrogen-containing ligands. P 4 V 6, characterized by its unique candy-like structure, demonstrates remarkable catalytic performance in converting HMF, achieving 95% conversion and 94% selectivity toward DFF under an O 2 atmosphere. Furthermore, P 4 V 6 exhibits good stability and can be reused over five consecutive cycles without any substantial changes to its structure and catalytic performance. Comprehensive mechanistic investigations, supported by control experiments, kinetic studies, and spectral analyses, indicate a plausible four-step catalytic mechanism. This work provides a new perspective on the design of polyoxovanadate-based catalysts for biomass valorization.
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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 | 0.001 | 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".