Effect of the carrier nitrogen doping on NO &toluene synergistic degradation over VPOTi catalysts: Structure-activity relationship and reaction mechanism
Bibliographic record
Abstract
Herein, a series of nitrogen-doped TiO 2 carriers were synthesized using urea impregnation and loaded with VPO active components to evaluate NO x &toluene synergistic degradation. Carrier nitrogen doping improved the conversion rates of NO x and toluene, and the complete conversion of dual pollutants was achieved on VPOTiN 0.02 catalyst at 250 ∼ 350 ℃. The doping of N atoms into the TiO 2 lattice promotes the growth of the (1 0 1) plane and increases the grain size. Structurally, nitrogen doping enriched the concentrations of oxygen vacancies and active oxygen species on the VPOTi catalyst, regulated the electron distribution around Ti atoms. The redox properties of the catalyst and the reactivity of the unit catalytic site were improved by constructing the electron enrichment region of Ti 3+ -O v . NO x and toluene on the catalyst followed E-R&L-H co-existence and MvK mechanisms, respectively. in NH 3 -SCR and toluene catalytic oxidation . The conversion rates of NO x and toluene may be mutually inhibited by competitive adsorption of reactants. Furthermore, carrier nitrogen doping was beneficial in regulating the stability of surface nitrate species and promoting the deep oxidation of toluene.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".