Continuous and Segmented Semiconducting Fiber‐like Nanostructures with Spatially Selective Functionalization by Living Crystallization‐Driven Self‐Assembly
Bibliographic record
Abstract
Abstract Fiber‐like π‐conjugated nanostructures are important components of flexible organic electronic and optoelectronic devices. To broaden the range of potential applications, one needs to control not only the length of these nanostructures, but the introduction of diverse functionality with spatially selective control. Here we report the synthesis of a crystalline‐coil block copolymer of oligo(p‐phenylenevinylene)‐b‐poly(2‐vinylpyridine) (OPV5‐b‐P2VP44), in which the basicity and coordinating/chelating ability of the P2VP segment provide a landscape for the incorporation of a variety of functional inorganic NPs. Through a self‐seeding strategy, we were able to prepare monodisperse fiber‐like micelles of OPV5‐b‐P2VP44 with lengths ranging from 50 to 800 nm. Significantly, the exposed two ends of OPV core of these fiber‐like micelles remained active toward further epitaxial deposition of OPV5‐b‐PNIPAM49 and OPV5‐b‐P2VP44 to generate uniform A‐B‐A and B‐A‐B‐A‐B segmented block comicelles with tunable lengths for each block. The P2VP domains in these (co‐)micelles can be selectively decorated with inorganic and polymeric nanoparticles as well as metal oxide coatings, to afford hybrid fiber‐like nanostructures. This work provides a versatile strategy toward the fabrication of narrow length dispersity continuous and segmented π‐conjugated OPV‐containing fiber‐like micelles with the capacity to be decorated in a spatially selective way with varying functionalities.
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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".