Optimized Pore‐Filled <scp>PTFE</scp> Anion Exchange Membranes Incorporating Graphene Oxide for Durable Electrochemical Applications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".