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Record W1977922346 · doi:10.1149/2.017404jes

Conductivity and Electrochemistry of Ferrocenyl-Imidazolium Redox Ionic Liquids with Different Alkyl Chain Lengths

2014· article· en· W1977922346 on OpenAlexafffund
Bruno Gélinas, John C. Forgie, Dominic Rochefort

Bibliographic record

VenueJournal of The Electrochemical Society · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologies
KeywordsIonic liquidAlkylChemistryRedoxElectrochemistrySolventInorganic chemistryPropylene carbonateIonic conductivityMoietyEthylene carbonatePolymer chemistryPhysical chemistryOrganic chemistryElectrolyteElectrodeCatalysis

Abstract

fetched live from OpenAlex

Electroactive ionic liquids obtained by modifying imidazolium with ferrocenyl moiety and alkyl chains of different lengths (n = 1, 4, 8 and 12) were studied in their pure form and dissolved in ethylene/diethylene carbonates (EC/DEC) solvent. Bis(trifluoro-methanesulfonyl)imide (TFSI) was used as the anion. The conductivity of the pure ionic liquids (0.1 to 0.04 mS·cm −1 ) was found to decrease with the increase in alkyl chain length as expected from larger van der Waals interactions. The conductivities of carbonate solutions of redox ionic liquid (50% vol.) were less affected by the chain length but were strongly dependent on the presence of Li ions due to their coordination with TFSI, providing viscous solutions (86–111 cP) which decreased the self-diffusion of the redox imidazolium by a factor of 6. The equilibrium potential of the RIL dissolved in the carbonate solvent was not affected by the alkyl chain length, but mass transport by migration caused a distortion in cyclic voltammograms for highly concentrated solutions.

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)0.0010.000
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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations21
Published2014
Admission routes2
Has abstractyes

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Same venueJournal of The Electrochemical SocietySame topicIonic liquids properties and applicationsFrench-language works237,207