Uniform Toroidal Micelles via the Solution Self-Assembly of Block Copolymer–Homopolymer Blends Using a “Frustrated Crystallization” Approach
Bibliographic record
Abstract
Toroidal nanostructures are of growing importance due to their unique geometry and potential utility in materials fabrication. Although a variety of amphiphilic block copolymers has been shown to self-assemble into toroidal micelles, the conventional methods used are often very slow with little control over the size of the resulting nanostructures. Here, we report a rapid and efficient synthetic route to prepare toroidal micelles of near uniform diameter through the cooperative coassembly of amorphous blends of polyferrocenylsilane block copolymer and homopolymer, where the degree of polymerization of the core-forming metalloblock in the former is greater than for the latter. The self-assembly process is accomplished within a few minutes, and the ring size of the toroids can be varied between 30 and 90 nm by adjusting the mass ratio of the block copolymer and homopolymer. The kinetic stability of the resulting toroidal micelles can be enhanced by frustrating core crystallization through solvent modulation and the toroids can also be readily used as templates to fabricate circular arrays of metal nanoparticles.
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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".