Basic rules of NO oxidation by Fe<sup>2+</sup>/H<sub>2</sub>O<sub>2</sub>/AA directional decomposition system
Bibliographic record
Abstract
Abstract Basic rules of NO oxidation by a Fe 2+ /H 2 O 2 /AA directional decomposition system were researched based on the technical background of flue gas NO x removal. Effects of gas‐liquid interfacial area, main gas, and solution parameters on NO oxidation efficiency ( η ) were analyzed. The results showed that adequate contact area was the precondition for high η by a Fe 2+ /H 2 O 2 /AA system. η decreased with the increase in NO concentration, which illustrated that this method would be efficient in oxidizing NO at a low concentration. η tended to decrease linearly with the growth in gas flow, however, the NO oxidation rate ( v ) rose with the increase in NO concentration and gas flow. η increased with the initial concentrations of H 2 O 2 and Fe 2+ , but the amplitude decreased. Controlling the initial concentrations of H 2 O 2 and Fe 2+ to achieve reasonable synergies between generation rate and consumption rate of ·OH could weaken the invalid consumption of reactants. η increased with the increase in temperature in the range 30–60 °C, but it nearly did not change with temperature after 60 °C. This oxidation technology and the traditional wet flue gas desulphurization technology exhibited temperature synergy. Under typical pH of wet desulphurization, η and H 2 O 2 consumption rate did not change obviously.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".