Uniform 1D Micelles and Patchy & Block Comicelles via Scalable, One-Step Crystallization-Driven Block Copolymer Self-Assembly
Bibliographic record
Abstract
Fiber-like (1D) core-crystalline micelles of uniform length can be obtained in protocols involving multiple steps from block copolymers (BCPs) in which crystallization of the core-forming polymer drives the self-assembly. Here we report a systematic study that shows that adding small amounts (<5 w/w%) of a homopolymer corresponding to the core-forming block of the BCP enables uniform 1D micelles (mean lengths L n = 0.6 to 9.7 μm) to be obtained in a single step, simply by heating the mixture in a selective solvent followed by slow cooling. A series of poly(ferrocenyldimethylsilane) (PFS) BCPs with different corona-forming blocks and different compositions as well as PFS homopolymers of different lengths were examined. Dye labeling and confocal fluorescence microscopy showed that the homopolymer ends up in the center of the micelle, signaling that it served as the initial seed for epitaxial micelle growth. The rate of unimer addition was strongly enhanced by the length of the PFS block, and this enabled more complex structures to be formed in one-pot self-assembly experiments from mixtures of two or three BCPs with different PFS block lengths. Furthermore, BCP mixtures that included PFS- b -PI (PI = polyisoprene) and PFS- b -PDMS with similar PFS block lengths resulted in simultaneous addition to growing micelles, resulting in a patchy block that could be visualized by staining the vinyl groups of the PI with Pt nanoparticles. This approach also enabled scale up, so that uniform 1D micelles of controlled architecture can be obtained at concentrations of 10 w/w % solids or more.
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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) | 0.001 | 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 | 0.001 |
| 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".