Might a 2,2-Dimethylbutane Molecule Serve as a Site to Promote Gas Hydrate Nucleation?
Bibliographic record
Abstract
Crystallization is relevant to many disciplines, and the control of crystallization of molecules is of importance to a great range of technological applications. It has been well established that a variety of surfaces can serve as possible nucleation sites for heterogeneous crystallization. However, it is still unknown what features of such system may be crucial and whether just a single molecule might serve as a nucleation site for crystallization. Therefore, to probe this question, we have investigated the nucleation of a prototypical multicomponent crystal, clathrate hydrates. As multicomponent crystalline compounds, clathrate hydrates have drawn considerable attention because of their scientific and industrial importance. Clathrate hydrates can occur in several possible structures, where the size of guest molecules and their ability to fit into water cages is a crucial factor. Despite the fact that in most applications, for example in oil–gas pipelines, clathrate hydrates form from gas mixtures that feature a variety of sizes of guest molecules, the possible roles of these species in hydrate formation has remained essentially unexplored. Herein, we investigate the impact of the presence of 2,2-dimethylbutane (DMB) on the nucleation of methane hydrate. Our simulation results provide clear evidence that DMB can serve as a nucleation site and can promote the formation of methane hydrates. The low mobility of the DMB molecule, and the longer residence time and hydrate-like structure of water molecules in its hydration shell appear as important contributors to its behavior. These results demonstrate that the presence of a somewhat larger hydrocarbon in low concentration can significantly impact hydrate nucleation and hence have immediate impact in, for example, flow assurance in oil–gas pipelines. More generally, the results presented herein indicate that single molecules in an otherwise homogeneous solution can promote crystal nucleation by stabilizing early stage structural fluctuations in the liquid.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".