Efficient and Controlled Seeded Growth of Poly(3-hexylthiophene) Block Copolymer Nanofibers through Suppression of Homogeneous Nucleation
Bibliographic record
Abstract
Low-dispersity, length-tunable block copolymer nanofibers with spatially controlled functionalization and a crystalline core have recently become accessible using the ambient temperature, living crystallization-driven self-assembly (CDSA) seeded-growth method. The crystallizable π-conjugated polymer, poly(3-hexylthiophene) (P3HT), is of particular interest as a core-forming block as a result of its useful optoelectronic properties. However, attempts to apply the living CDSA method to P3HT diblock copolymers have had limited success as, in addition to seeded growth, homogeneous nucleation events result in the spontaneous formation of new fibers, which leads to a loss of length control. Herein, we demonstrate that by performing detailed variable temperature ultraviolet–visible (UV–vis) spectroscopic studies of the homogeneous nucleation of rr P3HT 106 - b - rs P3HT 47 block copolymer ( rr = regioregular and rs = regiosymmetric, respectively) we were able to identify conditions (40 °C) under which spontaneous (homogeneous) nucleation is suppressed. Addition of preformed seeds under these conditions allowed for highly efficient living CDSA to yield nanofibers with a rr P3HT 106 core and controllable lengths up to ca. 4 μm with low length dispersity. Analogous use of this technique also allowed the efficient preparation of B-A-B triblock comicelles through the growth of P3HT 70 - b -PS 197 from the termini of rr P3HT 106 - b - rs P3HT 47 nanofibers that function as seed micelles, and also multiarm starlike arrays of fiberlike micelles with variable arm lengths, which were formed when seed micelles derived from rr P3HT 150 homopolymer were used.
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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".