Tuning of the electronic structure of W=O in <i>h</i>-BN-supported monosubstituted Keggin polyoxotungstate for oxidative desulfurization
Bibliographic record
Abstract
Oxidative desulfurization (ODS) is a promising strategy for the removal of sulfur compounds from fuel because of its mild conditions and high selectivity. Furthermore, its efficiency may be notably improved through the precise regulation of the microenvironment surrounding the catalytically active sites. In this work, a series of monosubstituted Keggin polyoxometalates incorporating different transition metals (Fe, Co, Ni) were designed and immobilized on the surface of hexagonal boron nitride (h-BN) using ionic liquids ([C4mim]BF4), affording novel supported catalysts for ODS. The Ni-substituted catalyst (PW11Ni-C4/BN) exhibited high activity and excellent recyclability, which was attributed to the specific electronic structure of the W=O active centers and the strong adsorption capability of the h-BN support. Under optimal conditions (catalyst dosage: 20 mg, O/S ratio: 3, temperature: 60 °C, sulfur content: 500 ppm dibenzothiophene (DBT) in n-octane), sulfur was completely removed within 40 min. In addition, mechanistic studies revealed that hydroxyl radicals (·OH) and superoxide radicals (·O2−) collaboratively drive the catalytic reaction.
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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".