Customized antifouling polyacrylonitrile ultrafiltration membranes for effective removal of organic contaminants from aqueous stream
Why this work is in the frame
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Bibliographic record
Abstract
Abstract BACKGROUND Ultrafiltration (UF) is a promising separation technique for the removal of macromolecular contaminants. However, the hydrophobic polymeric UF membrane performance suffers from fouling in the long run due to clogging by contaminants at the surface and pores. In this study, anti‐fouling hydrophilic polyacrylonitrile (PAN) UF membranes in the presence of an amphiphilic triblockcopolymer, Pluronic F127 (PF127) were prepared via a phase inversion technique. RESULTS The effect of varying concentrations of PF127 on PAN UF membranes was analyzed by attenuated total reflectance–Fourier transform infrared spectroscopy (ATR‐FTIR), by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The filtration characteristics of the membranes were measured in terms of pure water flux, membrane porosity and water content. The separation efficiency of the membranes is explored for contaminants such as bovine serum albumin (BSA), humic acid (HA) and oil. The results revealed that the PAN membrane with 4 wt% of PF127 produced greatest permeate flux of 391 L m −2 h −1 with minimal fouling. A higher solute rejection of more than 90% was observed for the tailored membranes due to the improvement in surface properties. CONCLUSION The inherent hydrophilicity of the high density poly (ethylene oxide) brush‐like layer of PF127 at the membrane–water interface is utilized effectively to restrict the adsorption of the organic contaminants onto the membrane surface. After simple hydraulic washing of PAN/PF127 UF membranes, the flux recovery ratio was augmented which is ascribed to their excellent antifouling property and potential use in water treatment. © 2018 Society of Chemical Industry
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 it