A new nanocomposite membrane based on sulfonated polysulfone boron nitride for proton exchange membrane fuel cells: Its fabrication and characterization
Bibliographic record
Abstract
• SPSf-2 %hBN PEM with a proton conductivity of 10.8 mS cm −1 was developed. • The mechanical strength of SPSf-based PEM is increased with hBN nanoparticle. • hBN additive improves the thermal and oxidation properties of the SPSf-based PEM. • Highly effective non-agglomeration PEM based on hBN and SPSf can be produced. Sulfonated polysulfone (SPSf) polymer is an alternative raw material in producing commercially used proton exchange membranes. On the other hand, hexagonal boron nitride (hBN) is one of the additives of interest for nanocomposite PEMs. In this study, nanocomposite membranes is fabricated and characterized with SPSf and hBN nanoparticles. The degree of sulfonation of the sulfonated polysulfone is determined by titration, and sulfonic acid bonds are investigated by Proton Nuclear Magnetic Resonance ( 1 H NMR) analysis. SPSf is dissolved with dichloromethane, and hBN nanoparticles are added. After homogenizing the prepared solution with magnetic and ultrasonic stirrers, membranes are formed using Dr. Blade. 1 H NMR, Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), X-Ray Diffractometer (XRD), and Thermogravimetric Analysis (TGA) analysis are examined the morphological, thermal, and organic compound structures of the membranes. Water uptake capacity, swelling ratio, proton conductivity, oxidative resistance, and mechanical properties of the membranes are determined. The highest water uptake capacity is obtained as 40.08 % in the membrane named SPSf-3 %hBN. Using hBN additive improved swelling ratio and thermal and mechanical strength properties. The proton conductivity values of polysulfone (PSf), SPSf, SPSf-1 %hBN, SPSf-2 %hBN, and SPSf-3 %hBN membranes are determined as 2.89, 6.84, 3.57, 10.8 and 5.12 mS cm −1 , respectively. As a result of the analysis, it is observed that the nanocomposite membrane structure has both amorphous and crystalline homogeneous structure.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".