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Record W2008740333 · doi:10.1139/cjc-2014-0558

Clathrate hydrate equilibrium modeling: Do self-consistent cell models provide unique equilibrium solutions?

2015· article· en· W2008740333 on OpenAlexfundvenueno aff
Patrick G. Lafond, R. Gary Grim, Amadeu K. Sum

Bibliographic record

VenueCanadian Journal of Chemistry · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsClathrate hydrateChemistryXenonHydrateDissociation (chemistry)ThermodynamicsDifferential scanning calorimetryChemical physicsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

When clathrate hydrates of xenon gas are formed deep within the stability field, anomalous melting behavior is readily observed in differential scanning calorimetry (DSC). In the DSC thermograms, multiple dissociation events may be observed, suggesting the presence of more than one solid phase. Following a suite of diffraction and NMR measurements, we are only able to detect the presence of simple structure I hydrate. Recognizing that hydrates are nonstoichiometric compounds, we look back to how the molar composition of a hydrate phase is determined. Making a mean-field improvement to current equilibrium models, we find that some conditions yield multiple solutions to the cage filling of the hydrate phase. Though the solutions are not truly stable, they would result in a kinetically trapped system. If such a case existed experimentally, this could explain the dissociation behavior observed for xenon hydrates. More importantly, this raises the question of how well defined the equilibrium condition is for a cell potential model, and whether or not multiple equilibrium solutions could exist.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.207
Teacher spread0.176 · 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 designSimulation or modeling
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

Citations4
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Chemistry→Same topicMethane Hydrates and Related Phenomena→French-language works237,207→