Detailed kinetic modelling of automotive exhaust NO<sub><i>x</i></sub> reduction over rhodium catalyst
Bibliographic record
Abstract
The reduction of NO with CO and H2 as the reductants was investigated on the rhodium‐based catalyst over a temperature range of 150–400 °C. Micro‐kinetic modelling method was utilized to compare the activities of CO and H2. Quasi‐elementary mechanisms of NO‐CO and NO‐H2 consisting of 11 and 25 steps, respectively, were proposed. The reaction steps and kinetic parameters were derived from literature and some parameters were optimized to fit the experimental data. Furthermore, to verify the validity range of the developed mechanism, the reaction intermediate N2O reduction by CO and by H2 over Rh were investigated. Over a wide range of reaction conditions, the detailed mechanism predicted experimental results quite well for both NO and N2O conversions with CO and/or H2 as reductant. The phenomenon that NO‐CO and NO‐H2 reactions commenced at similar temperature can be interpreted by the hindered H2 dissociative adsorption steps by extensive NO adsorption. Reaction profiles such as fractional coverages, reaction pathway and sensitivity analysis provided valuable insight into the reaction systems. N2O plays a crucial role in N2 formation for both NO‐CO and NO‐H2 reaction systems. The routes involving N2O formation and decomposition were identified as the dominant pathway in N2 formation at low 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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".