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Record W2327247867 · doi:10.1021/ja400521e

Molecular Insights into Clathrate Hydrate Nucleation at an Ice–Solution Interface

2013· article· en· W2327247867 on OpenAlexafffund
Payman Pirzadeh, Peter G. Kusalik

Bibliographic record

VenueJournal of the American Chemical Society · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Calgary
FundersWestern Canada Research GridUniversity of Calgary
KeywordsChemistryClathrate hydrateHydrateNucleationIce nucleusInterface (matter)MoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

Clathrate hydrates are specific cage-like structures formed by water molecules around a guest molecule. Despite the many studies that have been performed on clathrate hydrates, the actual molecular mechanism of both their homogeneous and heterogeneous nucleation has yet to be fully clarified. Here, by means of molecular simulations, we demonstrate how the interface of hexagonal ice can facilitate the heterogeneous nucleation of methane clathrate hydrate from an aqueous methane solution. Our results indicate an initial accumulation of methane molecules, which promote induction of defective structures, particularly coupled 5-8 ring defects, at the ice surface. Structural fluctuations promoted by these defective motifs assist hydrate cage formation next to the interface. The cage-like structures formed then act as a sink for methane molecules in the solution and enhance the stability and growth of an amorphous nucleus, which can evolve into a hydrate crystal upon annealing. These results are illustrative of how a surface that is structurally incompatible can serve to facilitate heterogeneous nucleation of a new crystalline phase. They should also further our general understanding of the formation of gas hydrates and their critical roles in various industrial and environmental processes, including carbon capture and storage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.222
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations111
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicMethane Hydrates and Related PhenomenaFrench-language works237,207