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Record W2744656951 · doi:10.1002/chem.201703117

Understanding Carbon Dioxide Solubility in Ionic Liquids by Exploring the Link with Liquid Clathrate Formation

2017· article· en· W2744656951 on OpenAlexafffund
Steven P. Kelley, Luis A. Flores, Matthew S. Shannon, Jason E. Bara, Robin D. Rogers

Bibliographic record

VenueChemistry - A European Journal · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsMcGill University
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of CanadaAmerican Chemical Society Petroleum Research FundCanada Excellence Research Chairs, Government of Canada
KeywordsSolubilityClathrate hydrateIonic liquidDicyanamideDissolutionChemistryBenzeneIonMoleculeMolar volumeSolventInorganic chemistryPhysical chemistryOrganic chemistryHydrateThermodynamics

Abstract

fetched live from OpenAlex

Abstract The solubilities of the quadrupolar molecules benzene and CO2 in various ionic liquids (ILs) are compared in order to determine the connection between aromatic liquid clathrate formation and CO2 dissolution in ILs. It was found that both CO2 Henry's law constants and benzene solubility are remarkably well correlated with each other and with IL molar volume, suggesting both phenomena depend more on the strength of interionic interactions between the ions of an IL rather than the identity of either ion. However, IL ion‐quadrupole interactions were found to have an effect for dicyanamide ([N(CN)2]−), where solubility of CO2 and benzene are affected by destabilizing and stabilizing interactions with [N(CN)2]−, respectively. The results suggest both solubility phenomena are related to the incorporation of the solute into an IL host network. Aromatic liquid clathrate formation thus has potential as a facile experimental probe for predicting the relative ability of ILs to physisorb CO2.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.091
GPT teacher head0.235
Teacher spread0.143 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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Same venueChemistry - A European JournalSame topicIonic liquids properties and applicationsFrench-language works237,207