Phase equilibria of hydrates from ternary mixtures of methane + ethane + propane and methane + propane + carbon dioxide
Bibliographic record
Abstract
Abstract Hydrate–liquid–vapour (HLV) equilibrium of aqueous clathrates formed from gas mixtures can be complex compared to hydrates formed with single guests. Typically, pressure and temperature are controlled to obtain these data, but for multicomponent systems, it is necessary to control/report more intensive variables, namely, composition. Metastability, manifested as impractically long experimental times, has been reported to be a challenge with some multicomponent systems. We present HLV equilibrium conditions of two ternary gas mixtures: methane + ethane + propane (90:7:3 molar ratio) and methane + propane + carbon dioxide (55:5:40 molar ratio). Conditions varied in the temperature range of 275–285 K and the pressure range of 1.24–4.75 MPa. Experimental standard uncertainties were on average 0.10 K and 0.005 MPa for methane + ethane + propane and 0.19 K and 0.005 MPa for methane + propane + carbon dioxide. Our technique allowed us to bypass the limitations reported in the literature and provided fast, reproducible HLV equilibria for gas‐dominated systems.
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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 | 0.001 |
| 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) | 0.002 | 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".