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Record W1978693629 · doi:10.1021/jp077583k

Heterogeneous Crystal Growth of Methane Hydrate on Its sII [001] Crystallographic Face

2008· article· en· W1978693629 on OpenAlexaff
Jenel Vatamanu, Peter G. Kusalik

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHydrateMethaneNucleationClathrate hydrateCrystal growthMoleculeChemistryCrystallographyCrystal (programming language)Aqueous solutionSupersaturationCrystal structureChemical engineeringMaterials sciencePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This paper presents a systematic molecular simulation study of the heterogeneous crystal growth of methane hydrate sII from supersaturated aqueous methane solutions. The growth of sII hydrate on the [001] crystallographic face is achieved through utilization of a recently proposed methodology, and rates of crystal growth of 1 A/ns were sustained for the molecular models and specific conditions employed in this work. Characteristics of the crystals grown as well as properties and structure of the interface are examined. Water cages with a 5(12)6(3) arrangement, which are improper to both sI and sII structures, are identified during the heterogeneous growth of sII methane hydrate. We show that the growth of a [001] face of sII hydrate can produce an sI crystalline structure, confirming that cross-nucleation of methane hydrate structures is possible. Defects consisting of two methane molecules trapped in large 5(12)6(4) cages and water molecules trapped in small and large cages are observed, where in one instance we have found a large 5(12)6(4) cage containing three water molecules.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations71
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicMethane Hydrates and Related PhenomenaFrench-language works237,207