A novel integrated rotary reactor for <scp>NOx</scp> reduction by <scp>CO</scp> and air preheating: <scp>NOx</scp> removal performance and mechanism
Bibliographic record
Abstract
Abstract A novel integrated rotary reactor for NOx reduction by CO and air preheating (iNA reactor) was proposed. NOx removal performance was investigated in a fixed‐bed reactor, which was used to simulate the working conditions change in the iNA reactor. Lab‐synthesized Cu/FeCeOx were used as the catalyst. Two different modes were tested with the iNA reactor: short cycles and long cycles. Excellent NOx removal efficiencies of over 95% and 90% for short cycles and long cycles, respectively, were observed in the iNA reactor. Moreover, compared with the constant‐temperature rotary reactor, better H2O and SO2 resistances were also found in the iNA reactor. The reaction mechanism was proposed based on in situ diffuse reflectance infrared Fourier transform study. In the iNA process, NOx was stored as nitrates in the adsorption zone, and then decomposed rapidly by both high temperatures and CO, leading to the deep catalyst regeneration. Therefore, temperature swinging and the feed of CO were key to having high iNA reactor performance for NOx removal.
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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 | 0.001 | 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".