Enhancing catalytic activity of V<sub>2</sub>O<sub>5</sub>/TiO<sub>2</sub> in H<sub>2</sub>S selective oxidation by modulating oxygen adsorption conditions
Bibliographic record
Abstract
This paper aimed to reveal the effects of chemisorbed oxygen species on selective catalytic oxidation applied for H2S removal. A sequence of thermal treatments were conducted on V2O5/TiO2 samples to prepare catalysts that possess different distributions of oxygen species. Characterization by X-ray photoelectron spectroscopy enabled a distinction among three different chemisorbed oxygen species: O–, O22–, and O2–. In addition, the dominance of the O– species, which is a very reactive oxygen species for catalytic oxidation reactions, was observed when the catalyst was exposed to 5% O2/N2 gas at the low temperature of 30 °C. It was also found that the N400A30 with the highest ratio of O– species was superior to others at converting H2S into elemental sulfur over the whole range of temperatures: the best S yield of N400A30 was 85% at 130 °C. These results are promising, as thermal treatments for oxygen adsorption were adopted for the first time to improve the catalytic activity of H2S removal by modulating the proportion of highly reactive O– species.
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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".