Performance evaluation of fixed‐bed, millistructured, and metallic foam reactor channels for CO<sub>2</sub> methanation
Bibliographic record
Abstract
Abstract Power‐to‐gas technologies, combining hydrogen produced by water electrolysis with carbon dioxide to produce substitute natural gas (SNG), can support the increased penetration of renewable electricity sources. However, the technical and economic feasibility of these technologies requires the conversion efficiency of the whole process, including the methanation step. This paper provides an experimental performance comparison of three catalytic methanation reactor concepts, a fixed‐bed reactor, a millistructured reactor, and a metallic foam reactor with the same nickel‐alumina catalyst. The response of each reactor was analyzed in light of five performance criteria, representing the methane yield, the reactor compactness, and the maximum temperature elevation. The millistructured reactor channel showed a higher methane space‐time yield and volumetric productivity than the other reactors, but a significant catalyst temperature elevation. The metallic foam reactor showed a much lower space‐time yield and volumetric productivity, but very good thermal management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".