Deactivation of Pd Catalysts by Water during Low Temperature Methane Oxidation Relevant to Natural Gas Vehicle Converters
Bibliographic record
Abstract
Effects of H2O on the activity and deactivation of Pd catalysts used for the oxidation of unburned CH4 present in the exhaust gas of natural-gas vehicles (NGVs) are reviewed. CH4 oxidation in a catalytic converter is limited by low exhaust gas temperatures (500–550 °C) and low concentrations of CH4 (400–1500 ppmv) that must be reacted in the presence of large quantities of H2O (10–15%) and CO2 (15%), under transient exhaust gas flows, temperatures, and compositions. Although Pd catalysts have the highest known activity for CH4 oxidation, water-induced sintering and reaction inhibition by H2O deactivate these catalysts. Recent studies have shown the reversible inhibition by H2O adsorption causes a significant drop in catalyst activity at lower reaction temperatures (below 450 °C), but its effect decreases (water adsorption becomes more reversible) with increasing reaction temperature. Thus above 500 °C H2O inhibition is negligible, while Pd sintering and occlusion by support species become more important. H2O inhibition is postulated to occur by either formation of relatively stable Pd(OH)2 and/or partial blocking by OH groups of the O exchange between the support and Pd active sites thereby suppressing catalytic activity. Evidence from FTIR and isotopic labeling favors the latter route. Pd catalyst design, including incorporation of a second noble metal (Rh or Pt) and supports high O mobility (e.g., CeO2) are known to improve catalyst activity and stability. Kinetic studies of CH4 oxidation at conditions relevant to natural gas vehicles have quantified the thermodynamics and kinetics of competitive H2O adsorption and Pd(OH)2 formation, but none have addressed effects of H2O on O mobility.
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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) | 0.000 | 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 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".