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Record W2785219079 · doi:10.1149/ma2018-01/39/2289

Electrical Response of a New Lipophilic Ionic Liquid and the Effect of CO<sub>2</sub> on Its Conductivity Mechanism

2018· article· en· W2785219079 on OpenAlexaff
Federico Bertasi, Keti Vezzù, Gioele Pagot, Giuseppe Pace, Enrico Negro, Yaser Abu‐Lebdeh, Michel Armand, Vito Di Noto

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsIonic liquidFormamidiniumConductivityMaterials scienceCharge carrierElectrical resistivity and conductivityIonic bondingIonic conductivityChemical physicsChemical engineeringChemistryElectrodePhysical chemistryInorganic chemistryOrganic chemistryElectrolyteHalideCatalysisOptoelectronicsIon

Abstract

fetched live from OpenAlex

Ionic liquids (ILs) have drawn sustained attention in the last twenty years due to their unique combination of intrinsic conductivity, very low vapour pressure and their ability to be tailored to an application via facile chemical modification [1]. As a consequence, the development of new ILs with improved properties and an in-depth understanding of the interplay existing between structures and properties are particularly active research fields. In this report preparation and study of a new lipophilic tetraoctyl-formamidinium bis(trifluoromethanesulfonyl) imide (TOFATFSI) ionic liquid [2], will be discussed. Tetraoctyl-formamidinium (TOFA) TFSI proved to be a water-insoluble IL that is completely miscible with the lower alkanes and the solutions are ionic conductors. Therefore, we were intrigued if conductivity could be induced in an even more demanding medium, i.e. supercritical carbon dioxide (scCO2) [3,4]. Following this, the conductivity and relaxation phenomena of this new IL are revealed through the analysis of the broadband electric spectra with a particular emphasis on the effect of temperature and CO2 pressure on the IL conductivity. It is found that temperature boosts the conductivity via an increase in the charge carrier mobility. Also, CO2 absorption affects both the conductivity and the permittivity of the material due to the presence of CO2–IL interactions that modulate the nanostructure and the size of the TOFATFSI aggregates, which increases both the mobility and the density of the charge carriers. Acknowledgements The authors wish to thank the Strategic Project of the University of Padova “Materials for Membrane-Electrode Assemblies to Electric Energy Conversion and Storage Devices (MAESTRA)” for funding. V.D.N. thanks the University Carlo III of Madrid for granting him the “Catedra de Excelentia” (Chair of Excellence). References [1] F. Bertasi, K. Vezzù, G. Nawn, G. Pagot, V. Di Noto, Interplay Between Structure and Conductivity in 1-Ethyl-3-methylimidazolium tetrafluoroborate/(δ-MgCl2)f Electrolytes for Magnesium Batteries, Electroch. Acta, 219, 152-162 (2016). [2] Federico Bertasi, Guinevere A. Giffin, Keti Vezzù, Pace Giuseppe, Yaser Abu-Lebdeh, Michel Armand, Vito Di Noto, A lipophilic ionic liquid based on formamidinium cations and TFSI: The electric response and the effect of CO2 on conductivity mechanism, PCCP, 19, 26230 – 26239 (2017). [3] V. Di Noto, K. Vezzù, F. Conti, G.A. Giffin, S. Lavina, A. Bertucco. Broadband electric spectroscopy at high CO2 pressure: Dipole moment of CO2 and relaxation phenomena of the CO2 - poly(vinyl chloride) system. J. Phys. Chem. B, 115, 9014-9021 (2011). [4] S. Kitajima, F. Bertasi, K. Vezzu’, E. Negro, Y. Tominaga, V. Di Noto. Dielectric relaxations and conduction mechanisms in polyether-clay composite polymer electrolytes under high carbon dioxide pressure. Phys. Chem. Chem. Phys., 15, 16626-16633 (2013). Figure 1

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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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueECS Meeting AbstractsSame topicIonic liquids properties and applicationsFrench-language works237,207