Influence of Graphene Oxide on Mechanical and Morphological Properties of Nafion® Membranes
Bibliographic record
Abstract
This study explored the influence of graphene oxide (GO) on morphological and mechanical properties of Nafion® 115 membranes with the objective of enhancing the mechanical properties of the most widely employed membrane in Proton Exchange Membrane Water Electrolyzers (PEMWE) applications. The membrane surface was modified by ultrasonically spraying a GO solution and different annealing temperatures were tested. Scanning Electron Microscopy (SEM) cross-sectional images revealed that annealing the composite membranes was sufficient to favor an interaction between the graphene oxide and the surface of the Nafion® membranes. The GO covering only 35% of the membrane surface increased the composite’s wettability from hydrophobic (105.2°) to a highly hydrophilic angle (84.4°) while slightly reducing membrane swelling. Tensile tests depicted an increase in both the strain levels and tensile loads before breaking. The samples with GO presented remarkable mechanical properties when the annealing time and temperature increased; while the Nafion® control samples failed at elongations of 95% and 98%, their counterparts with GO on the surface achieved elongations of 248% and 191% when annealed at 80 °C and 110 °C respectively, demonstrating that the presence of GO mechanically stabilizes the membranes under tension. In exchange, the presence of GO altered the smoothness of the membrane surface going from an average 1.4 nm before the printing to values ranging from 8.4 to 10.2 nm depending on the annealing conditions which could affect the quality of the subsequent catalyst layer printing. Overall, the polymer’s electrical insulation was unaffected, making the Nafion®-GO blend a more robust material than those traditionally used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".