Conjugated core–shell bottlebrush polymers that exhibit crystallization-driven self-assembly
Bibliographic record
Abstract
Bottlebrush polymers are complex architectures with densely grafted polymer side chains along polymeric backbones. The dense and conformationally extended chains in bottlebrush polymers give rise to unique properties, including low chain entanglement, low critical aggregation concentrations, and elastomeric properties in the bulk phase. Conjugated polymers have garnered attention as lightweight, processible, and flexible semi-conducting materials. They are promising candidates in electronic devices and sensors, but their optoelectronic properties depend on adequate polymer ordering, π-π interactions, and crystallization. Crystallization-driven self-assembly of conjugated polymers has become a prominent method to optimize properties including band energies, redox potentials, and exciton diffusion and transport. Much progress has been made in controlled block copolymer self-assembly, but despite their promising properties, reports of conjugated bottlebrushes have been limited, and their self-assembly is relatively unexplored. For the first time, we report the synthesis of conjugated core-shell bottlebrush polymers. These materials contain poly(3-hexylthiophene) (P3HT) and poly(ethylene glycol) (PEG) in either core or shell position. We demonstrate that the use of P3HT as a crystallizable conjugated polymer and PEG as a colloidally stabilizing and disaggregating block facilitates their self-assembly into a number of unique crystalline morphologies with longer conjugation lengths and lower exciton bandwidths relative to analogous diblock copolymers. These include intramolecularly self-assembled segregated bottlebrush polymers, short nanofibers formed by end-on-end stacking of bottlebrush molecules, extremely long >20 μm nanofibers formed exclusively by end-on-end stacking, and >15 μm nanoribbons formed from both end-on-end and side-by-side stacking of bottlebrush polymers.
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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".