MétaCan
Menu
Back to cohort
Record W2071055087 · doi:10.1149/2.010308jes

Fabrication and Characterization of an Effective Polymer Nanocomposite Electrolyte Membrane for High Performance Lithium/Sulfur Batteries

2013· article· en· W2071055087 on OpenAlexafffund
Kazem Jeddi, Yan Zhao, Yongguang Zhang, Aishuak Konarov, P. Chen

Bibliographic record

VenueJournal of The Electrochemical Society · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrolyteNanocompositeMaterials scienceMembraneChemical engineeringDissolutionIonic conductivityElectrochemistryHexafluoropropylenePolyvinylidene fluorideLithium (medication)PolymerElectrochemical windowSilicateInorganic chemistryChemistryNanotechnologyElectrodeCopolymerComposite material

Abstract

fetched live from OpenAlex

One of the major drawbacks of lithium/sulfur (Li/S) batteries is the dissolution of polysulfides into liquid electrolytes. In order to overcome this difficulty, polymer/silicate nanocomposite electrolytes composed of polyvinylidene fluoride-co-hexafluoropropylene (PVdF-HFP) and different types of nano-layered silicates were fabricated and analyzed. All the electrolyte membranes showed ionic conductivity of 5–7 mS/cm at room temperature and electrochemical stability window up to 4.8 V. Tested by two different sulfur composite cathodes, PVdF-HFP/organically-modified-silicate (OMMT) nanocomposite electrolyte delivered a higher discharge capacity and showed an improved cyclability compared to the other cells. Such electrochemical performance is attributed to the small and uniformly distributed pores within the structure of the polymer nanocomposite membrane, which promotes immobilizing the electrolyte solution and prevents dissolution of polysulfides.

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 score0.010
Threshold uncertainty score0.287

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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

Citations42
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicAdvanced Battery Materials and TechnologiesFrench-language works237,207