Key factors affecting the manufacture of hydrophobic ultrafiltration membranes for surface water treatment
Bibliographic record
Abstract
Abstract As part of the development of poly(ether sulfone) (PES) membranes whose surface is modified by the incorporation of a newly synthesized hydrophobic surface modifying macromolecule (nSMM) additive, this study investigates the impact of four key membrane preparation factors. They are concentration of PES, concentration of nSMM, casting thickness, and casting speed. The synthesis and characterizations of nSMM by nuclear magnetic resonance, gel permeation chromatography, differential scanning calorimeter, and elemental analysis have been presented. The changes in characteristics and performance of the membranes have been evaluated via Fourier transform infrared spectroscopy, contact angle analysis, scanning electron microscopy, and solute transport tests. The addition of 0.5 wt % of nSMM increased the contact angle of PES membranes by 20°; however, higher nSMM concentrations did not increase the hydrophobicity any further. Only the additive concentration had a statistically significant impact on flux reduction and dissolved organic carbon rejection. Even though other factors such as membrane thickness may alter the pore characteristics, their effect on membrane performance was marginal. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010
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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 | 0.000 |
| 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".