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Record W4415080992 · doi:10.1002/app.58072

Optimized Pore‐Filled <scp>PTFE</scp> Anion Exchange Membranes Incorporating Graphene Oxide for Durable Electrochemical Applications

2025· article· en· W4415080992 on OpenAlexaff
H Maleki, Mohammad Ali Aroon, Takeshi Matsuura

Bibliographic record

VenueJournal of Applied Polymer Science · 2025
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Ottawa
FundersIran National Science Foundation
KeywordsMembraneGrapheneOxideNanoparticleElectrochemistryIon exchangePolymerUltimate tensile strength

Abstract

fetched live from OpenAlex

ABSTRACT Pore‐filled anion exchange membranes (AEMs) were fabricated by impregnating a porous polytetrafluoroethylene (PTFE) support with a cross‐linked poly (vinyl benzyl chloride) (PVBC) matrix and graphene oxide (GO) nanoparticles. The influence of GO loading (0.5–7 wt%) on membrane performance was evaluated. Structural and thermal analyses confirmed uniform pore filling and stable GO integration within the polymer matrix. The optimized membrane containing 5 wt% GO exhibited an ion exchange capacity of 1.47 meq/g, water uptake of 48%, and tensile strength of 24.85 MPa, along with improved hydrophilicity and alkaline stability. Excessive GO incorporation led to nanoparticle agglomeration and performance decline. Compared with previously reported PTFE‐based AEMs, the developed membranes combine enhanced mechanical robustness with competitive conductivity and chemical stability. These results demonstrate that controlled nanoparticle incorporation is a promising strategy to improve the durability of AEMs for electrochemical energy and water treatment applications.

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 score0.240
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.212
Teacher spread0.207 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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