In situ Raman spectroscopic observation of the temperature-dependent partition of CH<sub>4</sub> and CO<sub>2</sub> during the growth of double hydrate from aqueous solution
Bibliographic record
Abstract
Sequestration of CO2 in hydrate form within deep oceanic sediments, to simultaneously replace methane trapped in submarine hydrate, has been considered as an efficient method for CO2 reduction. Consequently, research efforts are underway to deeply understand the properties of CH4 and CO2 hydrates. In this work, CH4 + CO2 double hydrate crystals were grown from aqueous solution in a capillary high-pressure optical cell. The quantitative relationships between Raman intensity and dissolved gas (i.e., CH4 and CO2) concentration in water and in hydrate were established. The partition coefficients of CH4 and CO2 between the hydrate and aqueous phases were measured at 5 constant temperatures from 275.15 to 293.15 K. The equilibrium concentrations of dissolved CH4 and CO2 decrease with decreasing temperatures, indicating more dissolved CH4 and CO2 will be transferred from the aqueous to the hydrate phase at lower temperature. With decreasing temperature, the molality of CO2 in hydrate increases and the molality of CH4 in 51262 cavities decreases, while the sum of the molality of CH4 in 51262 cavities and molality of CO2 in hydrate keeps constant, indicating that CO2 molecules can replace more methane molecules under lower temperature only by occupying the 51262 cavities.
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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) | 0.001 | 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".