Methane gas hydrate kinetics with mixtures of sodium dodecyl sulphate and tetrabutylammonium bromide
Bibliographic record
Abstract
The effect of combining a thermodynamic promoter, tetrabutylammonium bromide (TBAB), with a kinetic promoter, sodium dodecyl sulphate (SDS), to a methane clathrate system was investigated. Kinetic growth experiments were conducted in a semi‐batch stirred tank crystallizer at driving forces of 1500 kPa using a range of 100 to 1500 ppm SDS and 200 to 200 000 ppm TBAB. Solutions containing low concentrations of TBAB in water reduced methane hydrate growth rates up to 55 % for 1250 ppm TBAB compared to pure water. Solutions containing 900 ppm SDS in water enhanced the growth rate by 880 % compared to pure water. Solutions were then tested combining both promoters. The gradual addition of SDS from concentrations between 100 to 1250 ppm to low‐concentration TBAB systems between 200 to 1250 ppm was initially found to reduce growth kinetics, but eventually increased the growth rates once a threshold SDS concentration was reached. In all cases, the promoting effect of the SDS was more pronounced in the absence of the TBAB. The growth kinetics of systems containing 5 and 20 wt% TBAB also followed a similar inhibition‐promotion trend with the SDS concentration. An increase of 177 % in the gas consumption rate was observed when 1500 ppm SDS was added to the 20 wt% TBAB clathrate system. This work demonstrates that SDS can be added to a TBAB‐water‐methane system to enhance gas consumption rates, but care must be taken to ensure that the concentration of the additives places the system in a promotion regime.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".