Hybrid Star-Shaped Block Copolymers for Fabricating Fouling-Resistant Membranes
Bibliographic record
Abstract
Star-shaped block copolymers (SPs), comprising a hydrophobic cross-linked polystyrene (PS) core with extended hydrophilic polyethylene glycol (PEG) arms, showed high promise as a class of branched amphiphilic coating material, since the coatability and antifouling properties of the SPs could be tailored simply by tuning the core and/or arm compositions. However, the complex reaction sequences required for synthesizing SPs have been an obstacle for scale-up and, therefore, their practical applications. Herein, we have developed an SP architecture from an inorganic silica nanoparticle (SiO 2 NP) core, significantly simplifying the synthesis and enabling scale-up at much lower costs. The pressure-assisted coatability of three SiSPs with three different PEG lengths (i.e., SiSP1, SiSP2, and SiSP3 with 28, 54, and 129 PEGMA repeating units) on polysulfone ultrafiltration membranes was evaluated by scanning electron microscopy (SEM) and contact angle measurement. The SiSPs with medium PEG arm length (i.e., SiSP2 with 54 PEGMA repeating units) demonstrated superior thin-layer coatability and UV-induced stabilization. The protein solution filtration exhibited very low fouling, ca. 3% flux decline ratio (FDR) and ca. 97% flux recovery ratio (FRR), for UV-SiSP2 coated PSF UF membrane compared to significant fouling for pristine membrane (ca. 41% FDR and ca. 71% FRR). The three times enhancement in oleophobicity of the SiSP2 coated membrane has endowed almost seven times improvement in the permeation flux during oil emulsion filtration and 100% FRR contrary to zero flux recovery for pristine membrane. This study offers insights regarding the cost-efficient and facile synthesis of block copolymer nanoarchitecture SiSPs, which has the potential for water purification, lubrication, emulsification, and biomedical applications.
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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) | 0.000 | 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 | 0.000 |
| 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 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".