Physicochemical characteristics of polysulfone nanofiber membranes with iron oxide nanoparticles via electrospinning
Bibliographic record
Abstract
Abstract Hydrophilicity is one of the ideal properties for water treatment membrane. In addition, higher surface area with a porous structure results in extraordinary permeability and selectivity, thus making it a good candidate for water permeability. This study used iron oxide nanoparticles (IONPs) as polysulfone (PSf) membrane nanofillers to enhance the physicochemical properties. Nanofiber membranes were characterized in terms of morphology, wettability, and pure water permeability (PWP). The concentration of IONPs was varied from 0.5% to 2.0% (w/v). From the scanning electron microscope images, all produced membranes were smooth and contain bead‐free nanofibers. The produced nanofiber membrane with 1% (w/v) of IONPs concentration was found to be optimum since it had the highest porosity, lower contact angle, and desirable fiber thickness and diameter. In order to find the best PSf solution concentration, the loadings of PSf were varied from 18% to 27% (w/v). The PSf/IONPs with 25% (w/v) provided the best results in terms of fiber thickness and diameter, porosity and morphology. The contact angle also confirmed that in the presence of IONPs, the nanofiber structure produced with 25% PSf was less hydrophobic and had the highest PWP (70.27 L/m 2 h bar).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".