Influence of Pt Loading in Aged NOx Storage and Reduction Catalysts
Bibliographic record
Abstract
A series of Pt/BaO/Al 2 O 3 samples have been prepared with nominal Pt loadings ranging from 0.5 to 3.5 wt %. These samples were characterized in their fresh state and then subjected to an accelerated, mild, aging process which involved exposure of the catalysts to alternating rich and lean gas mixtures at 773 K. Characterization and storage results for the aged catalysts have been obtained. Aging effects were dependent on Pt loadings although there was no clear correlation between loading and the extent to which dispersion was lost during the accelerated aging process. Particular attention was given to the loadings and their temperature sensitive impacts on the form of the storage and release profiles including the NOx release spike accompanying the switch from lean to rich operation. Higher Pt loadings reduce the extent of NOx slip during lean to rich transition for low temperature operation.
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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 | 0.000 | 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".