Gyroid-Forming Diblock Copolymers Confined in Cylindrical Geometry: A Case of Extreme Makeover for Domain Morphology
Bibliographic record
Abstract
The self-assembly of gyroid-forming diblock copolymers confined in cylindrical geometry is studied using a combination of computer simulations and experiments. The simulations, based on a system qualitatively representative of poly(styrene- b -isoprene), are performed with cylindrical nanopores of different diameter ( D ) and surface selectivity. The effects of the pore size and surface selectivity on morphology are systematically investigated. Different morphological sequences are predicted for two gyroid-forming diblock copolymers. The experiments are carried out on two gyroid-forming poly(styrene- b -dimethylsiloxane) block copolymer samples confined in the core of continuous core−shell nanofibers of different diameters, which are obtained by a coaxial two-fluid electrospinning technique. The internal microphase-separated morphologies of these fibers are investigated by transmission electron microscopy (TEM). Both simulations and experiments demonstrate that a rich variety of structures spontaneously form for the gyroid-forming diblock copolymers, depending on the conditions of cylindrical confinement. Many of these confinement-induced structures are quite different from those of cylinder-forming or lamella-forming block copolymers. Simulations further show that these structures depend sensitively on the block copolymer composition, surface selectivity, and the ratio D / L 0 where L 0 is the period of the equilibrium gyroid phase. While the simulation and experimental systems are representative of different chemistries, the morphological predictions of simulations are qualitatively consistent with the experimental observations.
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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".