Morphology Study of Structure I Methane Hydrate Formation and Decomposition of Water Droplets in the Presence of Biological and Polymeric Kinetic Inhibitors
Bibliographic record
Abstract
The effect of kinetic inhibitors on the morphology of methane structure I hydrate was observed using a high pressure sapphire crystallizer. Two kinetic inhibitors were studied, poly(VP/VC), a lactam ring copolymer of polyvinylpyrrolidone (PVP) and polyvinylcaprolactam (PVCap), and type-I antifreeze protein (AFP). The experiments were performed at temperatures ranging from 274.2 to 275.2 K and pressures from 4200 to 7200 kPa. The experiments were conducted on three droplets simultaneously (a pure water droplet, a droplet containing 0.01 mol/m 3 poly(VP/VC), and a droplet containing 0.01 mol/m 3 AFP). The morphology and translucency were compared and found to vary significantly due to the presence of kinetic inhibitors. Hydrates formed under a higher driving force had dendrite formation on all but the AFP droplet. Low driving force experiments produced noticeably smoother surfaces on all droplets compared to high driving force experiments. Translucency also varied with AFP and poly(VP/VC) having the appearance of thinner films. Hydrate decomposition was also studied. The pure water droplet had the fastest rate of decomposition, followed by the droplet containing the AFP. The poly(VP/VC) droplet has a visible hydrate skin for a substantially longer period of time than the pure water and the AFP droplet.
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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".