Experimental Analysis of a Sabatier Reactor for Renewable Natural Gas Generation from Biogas: Ignition, Parameter Sensitivity Analysis, and Stability
Bibliographic record
Abstract
Biogas is a product of anaerobic fermentation, which is rich in CO 2 . The upgrade of biogas to renewable natural gas (RNG) is commercially achieved by separating carbon dioxide (CO 2 ) and impurities to improve its quality. As an alternative, the CO 2 contained in biogas can be directly converted into CH 4 via the thermocatalytic Sabatier reaction without separation, using H 2 generated by water electrolysis (utilizing renewable or surplus, low-carbon-footprint electricity). One of the major elements of this technology is the configuration of the Sabatier reactor. For industrial applications, it is beneficial to eliminate the energy-intensive CO 2 separation step, converting biogas to RNG directly. In this study, we report the experimental lab-scale proof of concept of the autothermal Sabatier reactor for direct biogas upgrade. We demonstrate a completely autothermal operation of the air-cooled, stainless steel reactor using a commercial Ni catalyst with a synthetic biogas feed. The effects of feed temperature, space velocity, and reactor cooling were investigated using three prototypes with different sizes and configurations. The maximum CO 2 conversion of 91% with 100% selectivity to CH 4 generation was achieved in a 10″-length reactor, over 100 h of continuous, stable operation, without any external reactor heating or feed preheating.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".