Microscopic characterization of antifouling membrane coated by core-shell star block copolymers
Bibliographic record
Abstract
Nano-sized core shell star block copolymers which have a hydrophobic core and hydrophilic arms have attracted considerable attention in recent years since their high areal density generate a thin and stable coating on various membrane surfaces through a self-assembly process for better antifouling properties of ultrafiltration system. This unique structure of star block copolymers makes it stick to the hydrophobic surface and render highly hydrophilic membrane surface for the better antifouling property. Therefore, complete understanding of its detail structures depending on temperature is the key of utilizing this product in membrane applications. In this study, a novel ultra-thin coating consisting of self-assembled star-shaped block copolymers which have different types of arms was used to increase the antifouling properties of membrane. In order to understand the relationship between the surface structure of coating and antifouling properties, various cutting-edge microscopic characterization methods such as scanning electron microscopy (SEM), focused ion beam (FIB), transmission electron microscopy (TEM) and atomic force microscopy (AFM) were used. Especially, new phase mode AFM imaging was introduced for the illustration of local hydrophobicity/hydrophilicity on the surface of star polymer (SP) coated membrane.
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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) | 0.001 | 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".