Kinetic Analysis of the Inhibition of CH<sub>4</sub> Oxidation by H<sub>2</sub>O on PdO/Al<sub>2</sub>O<sub>3</sub> and CeO<sub>2</sub>/PdO/Al<sub>2</sub>O<sub>3</sub> Catalysts
Bibliographic record
Abstract
Addition of CeO 2 to a PdO/Al 2 O 3 catalyst, assessed for the oxidation of CH 4 in the presence of 5% H 2 O at various temperatures, reduces the inhibition effects of H 2 O. A simplified kinetic analysis that assumes Langmuir adsorption of H 2 O on the catalyst active sites is used to model both the dynamic response and the steady-state CH 4 conversion following H 2 O addition to the feed gas and to quantify the effect of CeO 2 addition. The analysis shows that less H 2 O is adsorbed on the 2.9Ce/6.5Pd/Al 2 O 3 than the 6.5Pd/Al 2 O 3 catalyst and that the rate of H 2 O desorption is higher on the Ce-promoted catalyst. Both factors result in reduced inhibition of CH 4 conversion by H 2 O on the 2.9Ce/6.5Pd/Al 2 O 3 catalyst compared to the 6.5Pd/Al 2 O 3 catalyst. The apparent activation energy for CH 4 oxidation over the 2.9Ce/6.5Pd/Al 2 O 3 catalyst (61 ± 11 kJ mol –1 ) is shown to be statistically the same over the 6.5Pd/Al 2 O 3 (56 ± 9 kJ mol –1 ). Catalyst characterization data show minimal changes in catalyst properties after reaction, and removal of H 2 O from the reactant feed gas results in partial recovery of the catalyst activity. The data are consistent with H 2 O adsorption on the catalyst/support that may also inhibit O exchange with Pd-*/PdO site pair (Pd-* is an O-vacancy), the effect of which is reversible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".