Nucleation of CO<sub>2</sub> Hydrate in Quasi-Free Droplets of Dilute Electrolytes
Bibliographic record
Abstract
Salts are known to be thermodynamic inhibitors of gas hydrates at high concentrations by lowering the activity of water and shifting the phase boundary of gas hydrates to lower temperatures and higher pressures. However, some salts have been reported to kinetically promote the formation of gas hydrates at low concentrations. Studies on kinetic promotions of clathrate hydrate formation in dilute salt solutions are rare, and the mechanisms are poorly understood. The impact of solid walls on heterogeneous nucleation of gas hydrates is complex and depends on the nature of the solid walls, and it is difficult to decouple the impact of solid walls from that of dilute electrolytes when they are present. In particular, a solid wall often becomes charged when in contact with an aqueous phase, and the binding of the counterions to the solid wall in an aqueous phase further complicates the investigations of heterogeneous nucleation of gas hydrates. Here, we investigated the nucleation rates of CO 2 hydrate in quasi-free droplets of sodium chloride (NaCl) and potassium iodide (KI) at low concentrations (≤10 mM). The results showed that NaCl solution had no inhibition effect while KI solution had a weak promotion effect at low concentrations, and the nucleation rates were largely independent of the salt concentrations up to 10 mM. The impacts of dilute NaCl and KI solutions on the nucleation of CO 2 hydrate in this study were broadly similar to the previous findings of the methane–propane mixed gas hydrates in Sowa et al.’s study.
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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".