Trade‐offs in stability and activity: A study of ordered mesoporous alumina and γ‐Al <sub>2</sub> O <sub>3</sub> supported Ni catalysts for CO <sub>2</sub> methanation
Bibliographic record
Abstract
Abstract A series of K‐Ni‐γ‐Al 2 O 3 samples containing 15 wt.% Ni and varying potassium loadings (0–10 wt.%) were synthesized via incipient wetness impregnation and evaporation‐induced self‐assembly (EISA) for CO 2 methanation. The latter method resulted in ordered mesoporous alumina (OMA) catalysts exhibiting superior CO 2 conversion, CH 4 selectivity, and thermal stability compared to their γ‐Al 2 O 3 ‐supported counterparts. The 0.5K15NiOMA catalyst demonstrated the highest performance, achieving 85% CO 2 conversion at 450°C under atmospheric pressure, 15% higher than the unpromoted 15NiOMA catalyst. Under high‐pressure conditions (450°C, 9 atm, and 180 L N g cat −1 h −1 GHSV), the 0.5K15NiOMA catalyst achieved a CO 2 conversion of 94%. Long‐term stability tests over 150 h at 300°C showed no deactivation, maintaining a stable CO 2 conversion of 38% and CH 4 selectivity of 84%. In contrast, γ‐Al 2 O 3 ‐supported catalysts demonstrated higher turnover frequencies despite their lower methane reaction rates. For example, at 350°C, 0.5K15Ni/Al 2 O 3 achieved a TOF of 1.00 s −1 , almost double than its unpromoted counterpart and over double the TOF of 0.5K15NiOMA. This suggests that the higher surface availability of potassium in impregnated catalysts enhances CO 2 adsorption, compensating for the partial blockage of nickel sites. These results highlight the trade‐offs between stability and activity, with OMA supports excelling in long‐term high‐temperature applications and γ‐Al 2 O 3 supports offering a cost‐effective solution with simpler preparation methods for large‐scale CO 2 methanation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".