Improved surface hydrophilicity and antifouling property of nanofiltration membrane by grafting <scp>NH</scp><sub>2</sub>‐functionalized silica nanoparticles
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Bibliographic record
Abstract
Organic fouling has been a major impediment for the widespread application of nanofiltration membranes because it could degrade the performance and shorten the service life of such membranes. In this study, the NH 2 ‐functionalized silica nanoparticles (NH 2 –SiO 2 NPs) were grafted on the surface of commercial NF90 membrane to improve the hydrophilicity and antifouling property with the N ‐(3‐dimethylaminopropyl)‐ N ‐ethylcarbodiimide hydrochloride coupled with the N ‐hydroxysuccinimide (EDC/NHS) to activate carboxyl groups on the membrane surface. The surface roughness (Ra) of this modified membrane decreased from value of 47.4 nm of the pristine membrane to 43 nm. The water contact angle of the modified membrane decreased from 48.4° to 15°, indicating the high hydrophilicity of the surface. Moreover, the EDC/NHS membrane showed good stability when it was exposed to the ruinous physical stress (2‐min sonication). The optimized grafting conditions, including the SiO 2 concentration (0.5 wt%), the activation time of EDC/NHS (20 min), and the reaction time of NH 2 –SiO 2 NPs with membrane surface (12 h), were obtained by a series of experiments. Under the antifouling test of 36 hours with bovine serum albumin (BSA) and hexadecyltrimethylammonium bromide (CTAB) as foulants, the EDC/NHS membrane lost 42.1% and 49.6% of its initial flux, respectively, which is lower than that of the pristine membrane (52.2% and 68%, respectively). After cleaning with deionized water for 2 hours, the EDC/NHS membrane also showed significant improvement of flux recovery ratio (92% and 87%, respectively) than did the pristine membrane (70.3% and 60%, respectively).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it