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Record W7083690644 · doi:10.1016/j.cattod.2025.115572

CO2 methanation over BEA zeolite catalysts: Effect of MgO and in-situ Ni incorporation

2025· article· en· W7083690644 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCatalysis Today · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologies
KeywordsMethanationCatalysisZeoliteSelectivityCarbon fibersScanning electron microscopeMethaneNon-blocking I/O

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.241
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it