Performance of Ni/Si‐MCM‐41 catalysts in CO <sub>2</sub> methanation
Bibliographic record
Abstract
Abstract The production of methane from the methanation reaction between H 2 and CO 2 , also known as the Sabatier reaction, is one way to diversify the global energy matrix, providing a use for CO 2 . This work evaluates the performance in this reaction of Ni catalysts supported on type MCM‐41 silica, synthesized y a wet impregnation method. Catalytic tests were performed for 2.5 h under atmospheric pressure. The reaction variables considered were the catalyst nickel mass content (5% and 10%), temperature ( T = 400 and 550°C), reactant ratio (H 2 /CO 2 = 4 and 2.5), and space velocity (VHSV = 5 and 10 L g −1 h −1 ). The catalysts were characterized by Brunauer–Emmett–Teller (BET), X‐ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive x‐ray spectroscopy (EDS) analyses before the reactions, and by thermogravimetric analysis (TGA), SEM, and EDS analyses after the reactions. The reaction variables were evaluated using an experimental design with 2 factors and 4 variables, in order to determine the effects of the reaction conditions on catalyst selectivity, reactant conversion, and reaction yields in terms of CH 4 and CO. The best result was obtained using a reactant ratio of 2.5, space velocity of 5 L g −1 h −1 , and reaction temperature of 550°C, resulting in 93.7% selectivity for methane, 69.4% CO 2 conversion, 74% H 2 conversion, and methane yield of 20.69%. Findings show Ni/Si‐MCM‐41 catalyst's applicability in methanation, advancing CH 4 production technology, and addressing local demand while reducing CO 2 emissions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".