Synthesis of clay‐armored coatable sulfonated polyimide nanocomposites as robust polyelectrolyte membranes
Bibliographic record
Abstract
Abstract Herein, coatable sulfonated polyimide (SPI) and clay‐reinforced SPI membranes SPI‐clay 3%, SPI‐clay 5%, and SPI‐clay 7% were successfully fabricated by one‐step high temperature via direct imidization method. The membranes were cast as a coatable thin film using a solution casting method and grafted vermiculite clay nanoparticle were incorporated into the neat SPI as reinforcement by the sonication method. Three different formulated nanocomposite membranes were investigated using different characterization techniques such as Fourier transform infrared spectroscopy as peaks at 1166 and 1227 cm −1 confirmed successful sulfonation. In Proton ( 1 H) NMR synthesis of SPI confirmed as aromatic proton at 7.3–8.8 ppm depicts successful sulfonation and X‐ray diffraction results confirmed the crystalline structure of clay, as its content increased (7%) clear diffraction peak arises at 6 and 25°. Scanning electron microscopy (SEM) provides information about surface morphology of clay reinforced SPI membranes, and SEM micrographs shown uniform dispersion of clay nanofillers and developed easy transfer of electron. Thermogravimetric analysis was performed to investigate the thermal stability of synthesized films, results of thermographs shown degradation in the range of 510–600°C. Different physicochemical parameters employed and their results show the effectiveness of synthesized clay reinforced SPI membranes. Water uptake (WU%) about 0.96%, hydrolytic about 98 h and oxidative stability up to 80°C, ions exchange capacity about 3.16 mmol/g for synthesized clay reinforced SPI membranes. Measurement regarding Dimensional changes was also investigated and dimensional changes (1.557 ∆t/∆l). All these results reveal that the clay‐reinforced coatable SPI membranes are a promising material for polymer electrolyte membranes to be used in fuel cell energy applications.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".