Influence of Hydrated Silica Surfaces on Interfacial Water in the Presence of Clathrate Hydrate Forming Gases
Bibliographic record
Abstract
We study the hydrated silica–water interface in the presence of methane or carbon dioxide gas with molecular dynamics simulations. The simulations are performed with a limited amount of water, which forms a meniscus between two hydroxylated silica surfaces separated by 40 to 60 Å. Simulations were performed with the remaining space of the simulation cell left empty or filled with different numbers of methane or carbon dioxide gas molecules. The meniscus is used to determine the contact angle between water and silica in the absence and presence of the gases. The distribution profiles of the water and gas phases are determined over the duration of the simulation. The water number density in the layers adjacent to the silica is higher, and these layers are more structured and less mobile compared with water layers far from the surface. Additionally, the concentrations of the gases are significantly higher at the liquid and silica interfaces than in other locations in the gas phase. We speculate that the enhanced concentration of gases at the interface along with the extended contact area (curved meniscus compared with flat interface in the absence of silica surfaces) between water and guest molecules at the meniscus as well as lesser mobility of water molecules near the silica surface may provide a mechanism for the heterogeneous nucleation of the clathrate hydrate in water-wetting porous medium.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".