Ozone oxidation of nitric oxide: Promoting effect of phosphorus and inhibitory effect of phosphoric acid
Bibliographic record
Abstract
Abstract This work presents experimental and density functional theory theoretical methods to carry out the catalytic role and reaction mechanism of phosphorus (P4) for liquid phase catalytic oxidation nitric oxide. Meanwhile, it carries out the promoting effect of phosphorus and inhibitory effect of phosphoric acid in the ozone oxidation of nitric oxide. The work reveals the significant involvement of P4 in facilitating the NO catalytic oxidation process by generating O3. Meanwhile, the presence of phosphoric acid (H3PO4) hindered the NO catalytic removal process. The calculation results highlight that P4 promoted the formation of O3 and favoured the oxidation pathway (oxidation‐hydration, NO ➔ NO2 ➔ HNO3). During the liquid‐phase NO catalytic removal process, O2 and NO dissolved into the solution, where O2 exhibited preferential adsorbed on P4, promoting the O3 formation. Subsequently, O3 first oxidized NO to NO2. Then, HNO2 and HNO3 were generated under the hydration reaction of NO2 and H2O. Next, O3 further oxidized the generated HNO2 to HNO3, realizing the complete oxidation of NO. The hydration step of NO2 was identified as the key step in the O3 oxidation processes. Furthermore, the generation of H3PO4 led to the consumption of P4 and inhibited the NO removal process. O3 played the crucial role in liquid phase NO oxidation.
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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".