Evaluating Surfactants and Their Effect on Methane Mole Fraction during Hydrate Growth
Bibliographic record
Abstract
Little work has been done to characterize the effects of surfactant concentration on hydrate growth. The focus of this study is to investigate the effects of gemini and conventional surfactants on hydrate growth and evaluate growth promotion of a variety of surfactants in a consistent manner. The effects of sodium dodecyl sulfate (SDS) and DOWFAX 8390 surfactants on methane hydrates formed in a stirred 600 cm 3 reactor containing 343 cm 3 of liquid were investigated. Solubility experiments under liquid–hydrate–gas equilibria were conducted at 275.1K with pure water and solutions of each surfactant. Kinetic experiments were performed at 275.1 K and 4545 kPa with surfactant concentrations ranging from 0 to 1150 ppm for SDS and 0 to 200 ppm for DOWFAX 8390. Methane mole fraction measurements were taken at various times throughout the kinetic experiments. Both surfactants were found to have no effect on methane solubility in a gas–liquid–hydrate system at equilibrium. The surfactants did however have a pronounced effect on bulk methane mole fraction during kinetic experiments at surfactant concentrations that significantly promoted hydrate growth. Average hydrate growth rate was measured at various surfactant concentrations, and a sigmoidal trend was observed for both surfactants. Data showed a smooth rather than instantaneous increase in growth rate. A mathematical model is proposed and applied to compare the effectiveness of both surfactants at promoting hydrate growth. DOWFAX 8390 and SDS solutions both promote growth more than 4.5 times that of water samples, but DOWFAX 8390 achieves this promotion at 1/4 the concentration of SDS and has a larger increase in promotion per unit mass of surfactant added. The role of surfactants at the hydrate–liquid and gas–liquid interfaces is discussed.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".