Mechanisms, Growth Rates, and Morphologies of Gas Hydrates of Carbon Dioxide, Methane, and Their Mixtures
Bibliographic record
Abstract
Mechanisms of growth and dissociation, growth rates, and morphology of gas hydrates of methane, carbon dioxide, and two CH4:CO2 mixtures (80:20 and 30:70 nominal concentration) were studied using using high resolution images and very precise temperature control. Subcooling and a recently proposed mass transfer-based driving force were used to analyze the results. When crystal growth rates did not exceed 0.01 mm/s, all systems showed faceted, euhedral crystal habits at low driving forces. At higher driving forces and growth rates, morphologies were different for all systems. These results solve apparent contradictions in literature about the morphology of hydrates of methane, carbon dioxide, and their mixtures. Differences in the growth mechanism of methane-rich and carbon dioxide-rich hydrates were elucidated. It was also shown that hydrate growth of methane, carbon dioxide, and their mixtures proceed via partial dissociation of the growing crystal. Temperature gradients were used to dissociate hydrates at specific locations, which revealed a most interesting phenomenon: On dissociation, carbon dioxide-rich hydrates propagated onto the bare substrate while drawing water from the opposite side of the sample. Furthermore, it was shown that an abrupt change in morphology common to all systems could be correlated to a change in the slope of growth rate data. This change in morphology was explained by a shift in the crystal growth mechanism.
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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".