Competitive no, co and hydrocarbon oxidation reactions over a diesel oxidation catalyst
Bibliographic record
Abstract
Abstract The oxidation of NO, CO and hydrocarbons (HC) individually, in mixtures, and with NO2 were investigated over a monolith‐supported Pt/Al2O3 catalyst under oxidising conditions. Although competitive adsorption and inhibition by other species on oxidation reactions is a relatively well‐known phenomenon, this study represents a more comprehensive examination of such effects between key components in vehicle exhaust gases. NO2 was completely reduced by CO and C3H6, under NO2 limited conditions, at temperatures as low as 110°C and at temperatures above 140°C with dodecane and m‐xylene. NO2 was then again observed once the extent of oxidation of the other species by oxygen was significant. Under the conditions tested, NO, CO and HC oxidation was inhibited by NO2 in the feed gas mixture. HC were also found to inhibit the oxidation of NO and other HC species due to site adsorption competition. For CO, HC did not change the onset of oxidation, but did inhibit the extent after their light off began. At low temperatures, CO was initially found to inhibit NO oxidation, but at higher temperatures, once CO oxidation was significant, CO promoted NO conversion to NO2. The observed inhibition effects of the different gases on HC oxidation were not additive, indicating one species would cause inhibition, but once its inhibition ended, another species could still then cause inhibition. The combined effect of C3H6, NO and NO2 on CO conversion was found to be additive. This is because CO oxidation started prior C3H6. © 2011 Canadian Society for Chemical Engineering
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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) | 0.001 | 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".