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Record W147129566 · doi:10.14447/jnmes.v16i2.31

Effect of Chitin Nanofibres on the Electrochemical and Interfacial Properties of Composite Solid Polymer Electrolytes

2013· article· en· W147129566 on OpenAlexvenueno aff
K. Karuppasamy, S. Thanikaikarasan, S. Balakumar, Paitip Thiravetyan, D. Eapen, P.J. Sebastián, X. Sahaya Shajan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2013
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceNanocompositePolymerCyclic voltammetryBiopolymerElectrolyteMembraneChemical engineeringElectrochemistryIonic conductivityComposite numberPolymer chemistryComposite materialElectrodeChemistry

Abstract

fetched live from OpenAlex

Chitin nanofibres (CNF) are synthesized from a biopolymer chitin by ultra-pure chemical curing method. The nanocomposite solid polymer electrolytes (CSPE) based on PEO-LiBOB with chitin nanofibres as inert nanofiller are prepared by membrane hot-press method. The polymer membrane obtained is subjected to various electrochemical studies such as impedance analysis, cyclic voltammetry and compatibility studies. The crystalline behavior and structural changes in CSPE are investigated by means of XRD and FT-IR analyzes. The filler incorporated membrane shows better electrochemical properties as compared to filler free membrane. The addition of chitin nanofibre in polymer matrix enhances the ionic conductivity and achieves a maximum of 10-3.8 S/cm. Cyclic voltammetry study is used to know the electrochemical activity of prepared polymer electrolytes at ambient temperature. The compatibility studies reveals that the filler incorporated nanocomposite solid polymer electrolytes reduce the value of interfacial resistance (Ri) and it is better compatible with lithium interface.

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)0.001
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 score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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