Graphene Produced in RF-ICP Thermal Plasma Reactor: A Ni-Catalyst Support for CO <sub>2</sub> Methanation
Bibliographic record
Abstract
This study investigates a methane-to-graphene-to-methane cycle as a sustainable approach for graphene synthesis and greenhouse gas mitigation. Few-layer graphene (FLG) sheets were synthesized via methane pyrolysis in an RF-ICP thermal plasma reactor and characterized using TEM, SEM, Raman spectroscopy, TGA, and BET surface area analysis. The synthesized graphene exhibited a high specific surface area and stability, enabling uniform nickel nanoparticle dispersion through wetness impregnation. The resulting Ni/graphene catalyst demonstrated strong performance in CO 2 methanation. Without prereduction, 58% CO 2 conversion and 74% CH 4 selectivity were achieved under atmospheric pressure at a gas hourly space velocity of 12,000 mL g –1 h –1 . In situ H 2 reduction enhanced performance, yielding 72.5% CO 2 conversion and 90% CH 4 selectivity. These findings highlight graphene’s potential as an efficient catalyst support and underscore the benefits of pressure optimization for improving CO 2 conversion and methane yield.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".