Perfectly Ordered Patterns via Corner-Induced Heterogeneous Nucleation of Self-Assembling Block Copolymers Confined in Hexagonal Potential Wells
Bibliographic record
Abstract
The ordering dynamics of cylinder-forming diblock copolymer/homopolymer blends confined in hexagonal potential wells is systematically investigated using time-dependent Ginzburg–Landau (TDGL) theory. It is demonstrated that a high-efficient method to obtain large-scale ordered hexagonal patterns is to utilize corner-induced heterogeneous nucleation processes, in which nucleation events with controlled positions and orientations are triggered exclusively at the six corners of the confining hexagonal wells. Subsequent growth of the six domains originated from the corners leads to the formation of perfectly ordered patterns occupying the entire hexagonal well. The heterogeneous nucleation rate is regulated by the homopolymer concentration as well as the surface potential of the confining walls. Defect-free hexagonal patterns are obtained in hexagons with a diagonal size containing up to 61 cylinders (about 2 μm). The robustness of the method is examined by studying the tolerance window of the size-commensurability of the confining wells. The results indicate that controlled heterogeneous nucleation provides an efficient method for the fabrication of large-scale ordered patterns using graphoepitaxy of block copolymer self-assembly.
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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".