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Record W2126473608 · doi:10.1149/2.068308jes

Effect of Graphene on Sulfur/Polyacrylonitrile Nanocomposite Cathode in High Performance Lithium/Sulfur Batteries

2013· article· en· W2126473608 on OpenAlexafffund
Yongguang Zhang, Yan Zhao, Zhumabay Bakenov, Moulay‐Rachid Babaa, Aishuak Konarov, Cong Ding, 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 CanadaCanada Research ChairsChina Scholarship CouncilMcMaster University
KeywordsPolyacrylonitrileGrapheneMaterials scienceCathodeNanocompositeSulfurLithium (medication)Chemical engineeringDielectric spectroscopyComposite numberElectrochemistryLithium–sulfur batteryComposite materialElectrodeNanotechnologyChemistryPolymerMetallurgy

Abstract

fetched live from OpenAlex

A novel sulfur/polyacrylonitrile/graphene nanocomposite has been synthesized via a simple combination of ballmilling with low temperature heat-treatment. The nanocomposite was examined as a cathode for high performance lithium/sulfur batteries. The SEM and TEM observations revealed that sulfur/polyacrylonitrile particles are incorporated into graphene networks homogenously. Charge/discharge tests and ac impedance spectroscopy have shown improved conductivity and electrochemical properties of the composite with the addition of graphene. The lithium cell with this ternary composite cathode delivered a discharge capacity of 612 mAh g−1 in the second cycle at 0.1 C, and retained about 77% of this value over 100 cycles. Even up to 4 C rate, the lithium cell demonstrated an excellent rate capability, delivering a highly reversible discharge capacity of 360 mAh g−1.

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 score0.442

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 head0.193
Teacher spread0.190 · 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

Citations72
Published2013
Admission routes2
Has abstractyes

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