Highly active and stable Ru‐promoted Ni/<scp>CeO<sub>2</sub></scp> catalysts for <scp>CO<sub>2</sub></scp> methanation reaction
Bibliographic record
Abstract
Abstract Biogas is not only a promising renewable source of energy that can be integrated into existing infrastructures, but biogas could also be a CO 2 source for green methane synthesis by hydrogenation with renewable energy‐derived hydrogen. Since biogas is a mixture of CO 2 and CH 4 , we targeted to accomplish direct methanation of CO 2 in CH 4 ‐rich gases that are supposed to be a simulated biogas without any processes for CH 4 and CO 2 separation in biogas. This direct CO 2 methanation in biogas can be a more sustainable and environmentally friendly approach. Methane production from biogas‐derived CO 2 by conventional methods has some difficulties, including (1) the vast energy cost for separation process of CO 2 and CH 4 and (2) the slow rate of the reaction in biochemical CO 2 methanation. In this paper, we developed active and durable catalysts in direct methanation of CO 2 contained in biogas. The focus was on the effect of coexisting CH 4 and steam in biogas on CO 2 methanation activity and durability of CeO 2 supported Ni catalysts. Among all prepared catalysts, a 1 wt.% Ru‐10 wt.% Ni/CeO 2 catalyst exhibited 90% CO 2 conversion and 100% CH 4 selectivity at 275°C reaction temperature. Adding steam to the standard reaction gas mixture (CO 2 /H 2 /N 2 = 1/4/5) did not impact CO 2 conversion in the temperature range investigated, whereas adding CH 4 to the standard reaction gas mixture had only a minute decrease (i.e., 86.9% CO 2 conversion and 100% CH 4 selectivity at 275°C temperature). Furthermore, the 1 wt.% Ru‐10 wt.% Ni/CeO 2 catalyst demonstrated remarkable stability in the CO 2 methanation reaction.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".