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Record W2325362958 · doi:10.1021/am4045103

A Comparative Study of Nano-SiO<sub>2</sub> and Nano-TiO<sub>2</sub> Fillers on Proton Conductivity and Dielectric Response of a Silicotungstic Acid–H<sub>3</sub>PO<sub>4</sub>–Poly(vinyl alcohol) Polymer Electrolyte

2013· article· en· W2325362958 on OpenAlexafffund
Han Gao, Keryn Lian

Bibliographic record

VenueACS Applied Materials & Interfaces · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceDielectricElectrolyteConductivityProtonSilicotungstic acidNano-PolymerVinyl alcoholCapacitorAnalytical Chemistry (journal)Chemical engineeringComposite materialPhysical chemistryOrganic chemistryChemistryOptoelectronicsElectrode

Abstract

fetched live from OpenAlex

The effects of nano-SiO2 and nano-TiO2 fillers on a thin film silicotungstic acid (SiWA)-H3PO4-poly(vinyl alcohol) (PVA) proton conducting polymer electrolyte were studied and compared with respect to their proton conductivity, environmental stability, and dielectric properties, across a temperature range from 243 to 323 K. Three major effects of these fillers have been identified: (a) barrier effect; (b) intrinsic dielectric constant effect; and (c) water retention effect. Dielectric analyses were used to differentiate these effects on polymer electrolyte-enabled capacitors. Capacitor performance was correlated to electrolyte properties through dielectric constant and dielectric loss spectra. Using a single-ion approach, proton density and proton mobility of each polymer electrolyte were derived as a function of temperature. The results allow us to deconvolute the different contributions to proton conductivity in SiWA-H3PO4-PVA-based electrolytes, especially in terms of the effects of fillers on the dynamic equilibrium of free protons and protonated water in the electrolytes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.013
GPT teacher head0.227
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; both teacher heads agree on what is shown here.

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

Citations46
Published2013
Admission routes2
Has abstractyes

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