The Properties and SCR de‐NO <sub>x</sub> Application of Supported V <sub>2</sub> O <sub>5</sub> /TiO <sub>2</sub> Catalysts with Different Polymerization State of VO <sub>x</sub> Species Controlled by the pH Value of Their Precursors
Bibliographic record
Abstract
Abstract NO x is the main pollutant in the air, which causes many harmful effects on society. The V 2 O 5 /TiO 2 catalysts are very important to reduce the NO x from the heat engine plants and vehicle exhausts. However, various reasons will affect the performance of the catalysts. In this paper, the polymerization state of surface VO x of supported V 2 O 5 /TiO 2 catalysts was controlled by changing the pH value of the impregnation precursor solutions, and the redox and acidity properties of the catalysts can be adjusted consequently. The Raman spectroscopy, 51 V magic‐angle spinning nuclear magnetic resonance (MAS NMR), H 2 ‐temperature‐programmed reduction (H 2 ‐TPR), NH 3 ‐temperature‐programmed desorption (NH 3 ‐TPD), NH 3 ‐temperature‐programmed oxidation (TPO) and 15 NH 3 ‐NO‐O 2 ‐temperature‐programmed surface reaction (TPSR) were mainly used for the characterization and properties tests of the samples. Although all catalysts in this work had similar surface morphology and the same vanadium loading, the catalyst oxidability decreased while acidity increased with the increasing of VO x polymerization, which causes the NO conversion increases with the increasing of VO x polymerization below 300 °C in selective catalytic reduction (SCR) de‐NO x reaction. This work will promote the advance in catalysis and anti‐pollution fields for human and nature.
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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".