Zone Length Optimization to Improve PGM Utility
Bibliographic record
Abstract
“Zoning” a catalytic converter involves placing higher concentrations of platinum group metals (PGM) in the inlet portion of the substrate. This is done to optimize the cost-to-performance tradeoff by increasing the reaction rate at lower temperatures while minimizing PGM usage. A potentially useful application of catalyst zoning is to improve performance using a constant PGM mass. A study was performed to assess what the optimum ratio of front to rear palladium zone length is to achieve the highest performance in vehicle emission testing. Varying the zone ratio from 1:1 to 1:9 shows a clear hydrocarbon performance optimum at a 1:5.66 (15%/85%) split. This performance optimum shows as both a minimum in FTP75 non-methane organic gas (NMOG) emissions as well as a minimum in hydrocarbon, carbon monoxide, and nitrogen oxide light-off temperature. Overall, an improvement of 18%, or 11 mg/mi of combined NMOG+NOx emissions was obtained without using additional PGM. This study shows how the competing forces of active PGM site concentration and available surface area interact in modern three way catalyst design.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".