Molecular dynamics of <scp> CH <sub>4</sub> </scp> / <scp> CO <sub>2</sub> </scp> on calcite for enhancing gas recovery
Bibliographic record
Abstract
Abstract The effect of temperature and pressure on the adsorption of CO 2 and CH 4 gases on calcite (104) has been studied by means of classical molecular dynamics. The results show that carbon dioxide greatly improves methane desorption in the 323–373 K range, even at low CO 2 concentrations. However, this effect is less pronounced for very high temperatures (423 K), where most of the methane is desorbed and CO 2 tends to desorb in large quantities. Radial distribution function (RDF) analysis reveals two distinct peaks for CO 2 (0.36 and 0.47 nm) and two for methane (0.87 and 0.57 nm) and the intensities of these peaks tend to decrease with increasing temperature. Such peaks are always clearly visible for CO 2, while the methane profile gets very broad already for mild conditions of temperature and CO 2 concentration. These results highlight how the CO 2 geometry of adsorption is well defined and characterized by strong interaction, while methane adsorption is quite loose and depicts a very dynamic picture. Focusing on the effect of pressure, RDF peaks intensities increase, although this effect is limited to the 1–5 MPa range. Moreover, the high CO 2 presence further decreases the effect of pressure on methane adsorption. In fact, from pure methane to 20/80 CO 2 /CH 4 , methane adsorption increases linearly with pressure. For gas mixtures with a CO 2 concentration higher than 40%, higher pressure has less impact on methane adsorption. Overall, the results obtained yield important details to tune the gas composition and conditions for efficient and enhanced natural gas recovery and sequestration of CO 2 .
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".