Self-Assembled Morphologies of Diblock Copolymer Brushes in Poor Solvents
Bibliographic record
Abstract
Self-assembled morphologies of grafted linear AB diblock copolymers are investigated by a simulated annealing method. The copolymers are tethered to a flat substrate by the ends of the A blocks and immersed in a solution that is poor for both A and B components but exhibits a slight preference for one of the blocks. The morphological dependence of the system on the solvent selectivity, polymer grafting density, and the block lengths is investigated systematically. Phase diagrams for systems with two different grafting densities are constructed for the case where the chains are tethered by the less insoluble blocks. At a moderate grafting density, a variety of complicated morphologies, such as spherical pinned micelles, wormlike micelles, and stripe structures, are observed by varying the block lengths. Other complicated morphologies, such as perforated layers and complete layers, can be formed at a relatively high grafting density. More interestingly, by adjusting the length of copolymer chains and the volume fraction of the more insoluble block, some novel morphologies can be induced, ranging from “spheres-in-stripe” and “rods- in-stripe” structures at the moderate grafting density to “spheres-in-layer” and “rods-in-layer” structures at the higher grafting density. It is also observed that garlic-like and caterpillar-like structures can be obtained only when the solvent is more selective for the top block, consistent with previous theoretical results. Furthermore, the effect of the incompatibility of the two blocks on the structural evolution is also investigated.
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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".