The Impact of CeO2 Loading on the Activity and Stability of PdO/γ-AlOOH/γ-Al2O3 Monolith Catalysts for CH4 Oxidation
Bibliographic record
Abstract
This study reports on the activity and stability of PdO/γ-AlOOH/γ-Al2O3 monolith catalysts, promoted with varying amounts of CeO2, for CH4 oxidation. Although the beneficial effects of CeO2 have been reported for powdered catalysts, this study used a cordierite (2MgO.2Al2O3.5SiO2) mini-monolith (400 cells per square inch, 1 cm diameter × 2.5 cm length; ~52 cells), washcoated with a suspension of γ-Al2O3 combined with boehmite (γ-AlOOH), followed by sequential deposition of Ce and Pd (0.5 wt.%) by wetness impregnation. The monolith catalysts’ CH4 oxidation activity and stability were assessed in the presence of CO, CO2, H2O and SO2 at low temperature (≤550 °C), relevant to emission control from lean-burn natural gas vehicles (NGVs). The CeO2 loading (0 to 4 wt.%) did not significantly impact the adhesion and thermal stability of the washcoat, but CeO2 reduced the inhibition of CH4 oxidation by H2O and SO2. The catalyst activity, measured by temperature-programmed methane oxidation (TPO) in a dry feed gas with 0.07 vol.% CH4, showed that adding CeO2 to the γ-AlOOH/γ-Al2O3 washcoat suppressed the activity of the catalysts; whereas, CeO2 improved the catalyst activity when H2O (2 and 5 vol.%) was present in the feed gas. Moreover, adding CeO2 decreased catalyst deactivation that occurred in the presence of 10 vol.% H2O and 5 ppmv SO2 at 500 °C, measured over a 25 h time-on-stream (TOS) period. The highest catalyst activity and stability for CH4 oxidation in the presence of H2O was obtained by adding 2 wt.% CeO2 to the washcoat.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".