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Record W2160209271 · doi:10.1002/ceat.201300285

Kinetic Modeling of Methane Hydrate Formation in the Presence of Low‐Dosage Water‐Soluble Ionic Liquids

2013· article· en· W2160209271 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemical Engineering & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHydrateIsochoric processChemistryMethaneClathrate hydrateNucleationDissociation (chemistry)Kinetic energyIonic bondingInorganic chemistryThermodynamicsPhysical chemistryOrganic chemistryIon

Abstract

fetched live from OpenAlex

Abstract The kinetic and thermodynamic effects of three typical low‐dosage imidazolium‐based ionic liquids (ILs) on methane hydrate formation and dissociation were investigated, considering the anion nature and subcooling and/or overpressure driving forces. Isochoric hydrate formation and dissociation data were obtained by the modified slow step‐heating method. ILs proved to have a dual effect on both formation and dissociation of methane hydrate including thermodynamic and kinetic inhibition. Kinetic modeling of methane hydrate inhibition by low‐dosage ILs was performed. Kinetic analysis showed that IL inhibitors mainly cause a delay in the nucleation or hydrate growth step. The related inhibition mechanism was resolved regarding the ionic nature and electrostatic interactions of ILs with water molecules. Two binomial exponential kinetic relations were derived and used for simple methane hydrate formation in the presence of ILs as kinetic hydrate inhibitors. The proposed relations can serve for a quick estimation of the nature, extent, strength, and effectiveness of ILs on various gas hydrates.

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.

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 score0.167
Threshold uncertainty score0.273

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 head0.005
GPT teacher head0.182
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