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Record W2052568054 · doi:10.1021/cm504228a

Phase Behavior and Electrochemical Characterization of Blends of Perfluoropolyether, Poly(ethylene glycol), and a Lithium Salt

2014· article· en· W2052568054 on OpenAlexfundno aff
Dominica H. C. Wong, Alessandra Vitale, Didier Devaux, Austria Taylor, Ashish Pandya, Daniel T. Hallinan, Jacob L. Thelen, Sue J. Mecham, Simon Lux, Alexander M. Lapides, Paul R. Resnick, Thomas Meyer, Robert Kostecki, Nitash P. Balsara, Joseph M. DeSimone

Bibliographic record

VenueChemistry of Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsnot available
FundersBasic Energy SciencesOffice of Naval ResearchVehicle Technologies ProgramNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsLithium (medication)Materials scienceEthylene glycolElectrolyteIonic conductivityElectrochemistryGlass transitionAmorphous solidSalt (chemistry)PolymerChemical engineeringPEG ratioPolymer chemistryIonic liquidPhase (matter)Organic chemistryChemistryPhysical chemistryComposite materialElectrode

Abstract

fetched live from OpenAlex

Electrolytes consisting of low molecular weight perfluoropolyether (PFPE), poly(ethylene glycol) (PEG), and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) blends were prepared and systematically studied for salt concentration and stoichiometry effects on the materials’ thermal and electrochemical properties. Herein we report that the tunable ratios of PFPE and PEG allow for precise control of crystalline melting and glass transition temperature properties. These blended liquid polymer electrolytes are inherently nonflammable and remain stable in the amorphous phase from approximately 150 °C down to −85 °C. The ionic conductivity of the electrolytes are on the order of 10 –4 S/cm at 30 °C, which makes them suitable for rechargeable lithium batteries.

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 score0.002
Threshold uncertainty score0.524

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 head0.219
Teacher spread0.214 · 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".

Quick stats

Citations76
Published2014
Admission routes1
Has abstractyes

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