CO2 methanation over BEA zeolite catalysts: Effect of MgO and in-situ Ni incorporation
Bibliographic record
Abstract
Carbon dioxide methanation is a promising carbon management technology that reduces CO 2 concentrations and facilitates the long-term storage of excess renewable energy, thereby closing the carbon cycle. This study investigates the catalytic performance of BEA zeolite-based catalysts in the methanation of CO 2 , focusing on the role of MgO as a promoter and investigating the incorporation of Ni by in-situ method. The catalysts were synthesized via two methods: post-modification with Ni and MgO loading, and in-situ incorporation of Ni within the zeolite framework. Characterization techniques, including X-ray diffraction (XRD), Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), H 2 -TPR, and CO 2 -TPD, were used to evaluate the physical and chemical properties of the catalysts. The results demonstrated that MgO promoted the catalytic activity of BEA zeolites, enhancing CO 2 conversion and methane selectivity at lower reaction temperatures. The in-situ incorporation of Ni showed negligible activity at temperatures below 350 °C but outperformed post-modified catalysts at higher temperatures, particularly above 400 °C. These findings suggest that while post-modified catalysts are more effective at lower temperatures, in-situ Ni incorporation offers superior catalytic performance at elevated temperatures, making it a promising approach for high-temperature methanation reactions. This work contributes to the development of efficient catalysts for CO 2 methanation, supporting carbon capture and utilization efforts. Beta (BEA) zeolite structure modified by post and in-situ methods. The in-situ method incorporated Ni into BEA zeolite structure by replacing silicon or aluminum atoms, while the post-modification method disperses NiO on both the surface and within the pores of the BEA zeolite structure • BEA zeolite synthesized, modified with MgO, and 13 wt% Ni via post-modification. • MgO in BEA catalysts boosts CO 2 conversion and methane selectivity. • 5 wt% MgO and 13 wt% Ni catalyst showed optimal performance and over 50 h stability. • Ni incorporated successfully into the BEA zeolite framework using in-situ method. • In-situ Ni method achieved 6.6 h −1 TOF vs. 14 h −1 for post-modification.
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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) | 0.001 | 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".