Spatially-Resolved Thermal Degradation Induced Temperature Pattern Changes along a Commercial Lean NOX Trap Catalyst
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The low-temperature performance characteristics of a commercial lean NO<sub>X</sub> trap catalyst were evaluated using infra-red thermography (IRT) before and after a high-temperature aging step. Reaction tests included propylene oxidation, oxygen storage capacity measurements, and simulated cycling conditions for NO<sub>X</sub> reduction, using H₂ as the reductant during the regeneration step of the cycle. Testing with and without NO in the lean phase showed thermal differences between the reductant used in reducing the stored oxygen and that for nitrate decomposition and reduction. IRT clearly demonstrated where NO<sub>X</sub> trapping and regeneration were occurring spatially as a function of regeneration conditions, with variables including hydrogen content of the regeneration phase and lean- and rich-phase cycle times. As expected, lower reductant concentration led to incomplete regeneration, limiting nitrate decomposition to the upstream portions of the sample and therefore isolating NO<sub>X</sub> trapping in the front, or upstream, portion of the catalyst. More reductant, via longer regeneration time or higher reductant concentration, resulted in more catalyst being used for trapping, with the length of catalyst involved in trapping a function of the amount of reductant delivered during the regeneration phase. Tests at 200°C and 300°C also demonstrated differences in the amount of catalyst used for trapping NO<sub>X</sub>, related to the efficiency of reductant use during the rich phase, with 200°C showing poorer performance. Tests with the thermally aged catalyst demonstrated the same trends, but with measured differences in the efficiency of H₂ use during regeneration. The temperature measurement results were consistent with all concentration trends, indicating such measures can predict subsequent catalyst activity and be used as a measure of the extent of degradation.</div></div>
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".