Insight into Oxidative Desulfurization Mechanism from the Interaction between Different Facets of TiO<sub>2</sub> and V Single Atom or V<sub>2</sub>O<sub>5</sub> Cluster
Bibliographic record
Abstract
This research was devoted to investigating the oxidative desulfurization (ODS) reaction of thiophene over V 1 –TiO 2 and V 2 O 5 –TiO 2 surfaces through density functional theory calculations. The calculation results showed that V single atoms and V 2 O 5 clusters exhibited significantly different binding energies and charge transfer characteristics over the different TiO 2 facets. The density of states and orbital interaction analyses further revealed that V single atoms exhibited a more pronounced advantage in adsorbing and activating the O 2 molecules compared to the V 2 O 5 clusters, which was primarily attributed to their unique electronic structure and coordination environment. Based on the calculation results, the V single atoms exhibited the highest catalytic activity in the formation of sulfoxide over the TiO 2 (101) facet. Additionally, this work found that the extra oxygen (O ext ) species also played a key role in reducing the reaction barriers and promoting the formation of sulfoxides, with O ext species directly contributing to the V 2 O 5 -catalyzed thiophene ODS reaction. The O ext species also promoted the continuous conversion of sulfoxides to sulfones. Comprehensive analysis indicated that there was a significant synergistic effect between V single atoms and V 2 O 5 clusters, which collectively promoted the effective ODS process of thiophene.
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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".