Adsorbents for adsorption separation of <scp>CO<sub>2</sub></scp> and <scp>CH<sub>4</sub></scp>: A literature review
Bibliographic record
Abstract
Abstract Natural gas consisting mainly of methane is becoming increasingly prominent as a clean energy source. However, the major impurity, carbon dioxide, can adversely affect the performance of natural gas. Therefore, separating CO2 from CH4 is necessary to decrease the erosion of pipelines and increase the calorific value. This paper aimed at reviewing the performances, mechanisms, and novel developments of common adsorbents to adsorb pure CH4, pure CO2, and their mixtures. Several studies suggest that zeolites exhibit better separating performance than metal organic frameworks (MOFs) except the modified amine‐MIL group. Activated carbons may not be suitable adsorbents due to low selectivity between CO2 and CH4. The modified amine‐MIL group are the best type of adsorbent to separate CO2 from CH4 and its best operating conditions are at low pressure (<2 bar), low feed composition of CO2, and near room temperature using pressure swing adsorption (PSA) method.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".