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Record W2296819017 · doi:10.1149/ma2016-03/2/1057

Correlation Between Free Volume and Ionic Conductivity of Non-Aqueous Lithium Battery Electrolyte Solutions over a Wide Concentration Range

2016· article· en· W2296819017 on OpenAlexaff
Yaser Abu‐Lebdeh, Jasper Tam, Hayden Greentree Soboleski

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of WaterlooNational Research Council Canada
Fundersnot available
KeywordsElectrolyteEthylene carbonatePropylene carbonateChemistryThermodynamicsConductivityMolar conductivityIonic conductivityAqueous solutionIonic bondingInorganic chemistryAnalytical Chemistry (journal)IonPhysical chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

There is little known about the transport behavior of ions in electrolyte solutions at very high concentration and there is currently no satisfactory theory/equation to describe it [1,2]. In this work electrolyte solutions of lithium salts of various anions: [(CF 3 SO 2 ) 2 N]°¥, (TFSI), [PF 6 ]°¥ and [BF 4 ]°¥ dissolved in polar solvents and solvent mixtures up to saturation have been prepared. The solvents are propylene carbonate (PC), acetonitrile (ACN), adiponitrile (ADN) and ethylene carbonate:dimethyl carbonate (1:1 v/v) (EC:DMC). The Ionic conductivity and density of the electrolyte solutions have been measured over a wide concentration range (up to 5.4 M). The specific ionic conductivity (κ) vs. C plots show a non-ideal behavior with very strong dependence on concentration (a typical Gaussian-like function) while the molar conductivity (Λ) vs. C plots show an exponential decrease similar to the behavior of weak electrolyte solutions. The conductivity vs. concentration data were fitted to various equations of known models (Debye-Hückel-Onsager’s square-rate law: Λ vs. C^1/2, Cubic-root law: Λ vs. C^3, Casteel-Amis equation: κ/κ max vs. C/C max , or the corresponding state-law equation based on the pseudo-lattice theory: κ/κ max vs. C/C max .The models show good fit only in the low concentration, with the last two models fail to show universal behavior beyond the concentration of maximum conductivity, C max . However, we have derived a new, semi-empirical equation that shows a very good fit over the whole concentration range and can correlate molar ionic conductivity to changes in free volume within the liquid solution: Λ = A' exp [-B C], B =-γ Vo/Vf, and Vf = V-Vo Where V ƒ is the free volume which can be calculated from the difference between the measured volume, V, of the liquid (from density measurements) and the Van der Waal “molecular “volume, V o , which can be obtained from XRD data at low temperatures or calculated using chemical models. C is concentration, A’ is a pre-exponential factor that can be related to limiting molar conductivity and square root of temerature. γ is a correction factor for overlapping holes with a value between 0.5 and 1. These preliminary results are encouraging in bringing us closer to a free volume-based approach to explain the behavior of ionic conductivity of electrolyte solutions at very high concentrations. However, more work is underway to study more solutions with different chemical and physical properties, including aqueous solutions, to test the validity of this approach. [1] S. I. Smedley, The Interpretation of Ionic Conductivity in Liquids, Springer, 1980 [2] C.A. Angell, J. Phys. Chem., 70, 1966, 3988

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 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 score0.439
Threshold uncertainty score0.482

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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 teacher head, 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
Published2016
Admission routes1
Has abstractyes

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