Effects of Poly(styrene/pentafluorostyrene-block-vinylpyrrolidone) Amphiphilic Kinetic Hydrate Inhibitors on the Dynamic Viscosity of Methane Hydrate Systems at High-Pressure Driving Forces
Bibliographic record
Abstract
Reversible addition-fragmentation chain-transfer polymerization with a switchable chain-transfer agent was employed to synthesize amphiphilic block copolymers poly(styrene-b-vinylpyrrolidone) and poly(pentafluorostyrene-b-vinylpyrrolidone) at 10 wt.% hydrophobic content as kinetic hydrate inhibitors for methane hydrates. The dynamic viscosity of methane hydrate slurries was measured in a high-pressure rheometer up to 15 MPag. At 700 ppm of additives in aqueous media, the relative time for slurries to grow to 200 mPa s was 2.2-2.4 times longer than water reference values for the block copolymers. In contrast, it was only 1.3 for the poly(vinylpyrrolidone) homopolymer, demonstrating a reduced tendency for hydrate particle adhesion in block copolymer solutions. By increasing the concentration to 7000 ppm, however, the relative time only increased to 2.6-2.7. On the other hand, a block copolymer with 5 wt.% poly(pentafluorostyrene) block at 7000 ppm reached 3.5, which may indicate that the optimal hydrophobic content differs for each amphiphilic polymer and depends on monomer selection. No significant effect of polymer aggregation on hydrate growth was observed for the copolymers used in this study, which had the same hydrophobic percentage and molecular weights between 10,000 and 40,000 g/mol.
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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) | 0.001 | 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".