Comparison of different kinetic models for NO<sub>X</sub> storage on a lean NO<sub>X</sub> trap
Bibliographic record
Abstract
The kinetics of NOX storage on a lean NOX trap (LNT) were studied using NOX breakthrough curves measured with a laboratory reactor. A much wider range of temperatures (125–450°C) was used than in most studies to facilitate discrimination between potential models. The breakthrough curves were run until the LNT was saturated to (i) enable NO oxidation to NO2 to be studied in the absence of NOX storage, (ii) to enable the effective NOX capacity as a function of temperature to be determined, and (iii) to provide a more demanding test for potential models. Breakthrough curves for 125 and 450°C were very similar, while curves at intermediate temperatures initially followed that for 125°C before breaking away from this curve at a point that became earlier with increasing temperature. Thus, the breakthrough curves have a temperature independent initial portion, followed by a temperature dependant portion. This was explained by there being two types of site: fast sites and slow sites. Fast sites are responsible for the initial part of the curve; both the rate of storage on these sites and the available capacity are independent of temperature. The rate of storage on slow sites, on the other hand, is temperature dependant, as is the available storage capacity. Slow sites are more abundant than fast sites. The performance of three NOX storage models for these sites was compared. The amount of NOX stored as a function of temperature was bell‐shaped. The models naturally predicted that storage was limited by kinetics at lower temperatures and nitrate stability at higher temperatures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".