Sulfonated Polyethersulfone (SPES) – Charged Surface Modifying Macromolecules (cSMMs) Blends as a Cation Selective Membrane for Fuel Cells
Bibliographic record
Abstract
Abstract Polyethersulfone (PES) was sulfonated by chlorosulfonic acid and concentrated sulfuric acid. The pure sulfonated PES (SPES) and modified SPES membranes were prepared by blending with different charged surface modifying macromolecules (cSMMs) namely, SPES/DEG‐HBS, SPES/PEG‐HBS, and SPES/PPG‐HBS. Membranes were characterized for their morphology, physical properties, and electrochemical properties in order to evaluate these membranes as cation exchange membranes. The blended membranes showed an increase in hydrophilicity, water uptake, and proton conductivity compared to the pure SPES membranes. The highest values of water uptake and proton conductivity were obtained for the SPES/PPG‐HBS blended membrane. Morphological studies revealed that the nodule size and surface roughness also influenced the water uptake, apart from the additional –SO3H group. Among the modified membranes, the SPES/DEG‐HBS blended membrane exhibited a lower methanol permeability value of 8.895 × 10−8 cm2 s−1 than the corresponding SPES membrane. The other two cSMM blended membranes showed higher methanol permeability values than SPES but still a smaller value than Nafion 117. The highest selectivity ratio (i.e., ratio of proton conductivity to methanol permeability) was obtained with the SPES/DEG‐HBS cSMM blended membrane. These results showed that the SPES/cSMM blended membranes have promise for possible use as a cation exchange membrane in fuel cells and electrolyzer 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".