A Facile Method of Forming Nanoscale Patterns on Poly(ethylene glycol)-Based Surfaces by Self-Assembly of Randomly Grafted Block Copolymer Brushes
Bibliographic record
Abstract
Poly(oligo(ethylene glycol) methacrylate) (POEGMA) block poly(methyl methacrylate) (PMMA) brushes were synthesized on the silicon wafer surfaces by the surface-initiated atom transfer radical polymerization (ATRP) method. Atomic force microscopy, ellipsometry, and water contact angle methods were employed to study the surface morphology and stimulus-response behavior. It was found that simple solvent treatments could induce phase segregation of the POEGMA and PMMA segments thus introducing nanoscale patterns. The feature size could be less than 10 nm and was tunable on the nanoscale. Various patterns including spherical aggregates, wormlike aggregates, stripe patterns, perforated layers, and complete overlayers were obtained through adjusting the upper block layer thickness. These patterns could switch between the different morphologies reversibly after the treatment with selective solvents.
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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".