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Record W4408618810 · doi:10.3390/nano15060464

Multiscale Interfacial Structure and Organization of sII Gas Hydrate Interfaces Using Molecular Dynamics

2025· article· en· W4408618810 on OpenAlexafffund
Samuel Mathews, Phillip Servio, Alejandro D. Rey

Bibliographic record

VenueNanomaterials · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMolecular dynamicsNucleationCharacterization (materials science)DipoleContext (archaeology)Materials scienceHydrateChemical physicsClathrate hydrateLayer (electronics)Interface (matter)NanotechnologyChemistryPhysicsComputational chemistryThermodynamicsContact angleComposite material

Abstract

fetched live from OpenAlex

Gas hydrate systems display complex structural arrangements in their bulk and interfacial configurations. Controlling nucleation and growth in the context of potential applications requires a characterization of these structures such that they can be manipulated at the atomic and molecular scale to fine tune macroscale applications. This work uses molecular dynamics to show the different methods of identifying interface location and thickness, the drawbacks of certain methods, and proposes improved methodology to overcome sampling issues. We characterize the interfacial position and thickness using structure and dipole-based methods at different conditions for water/sII natural gas hydrate mixtures. We find that phases with similar densities are particularly sensitive to the regression technique employed and may not resolve the thickness of the complex pre-melting layer adequately, while the dipole moments may provide better resolution. The dipole shows the complex natural of the small and compressed layer that presents on the hydrate surface. These results show that the interface is thin but dynamic and careful characterization required analysis of multiple molecular phenomena.

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 categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

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)0.0010.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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