Well-Defined Homopolymer Nanoparticles with Uniaxial Molecular Orientation by Synchronized Polymerization and Self-Assembly
Bibliographic record
Abstract
Synthesizing anisotropic polymeric nanoparticles (NPs) with well-defined shapes, dimensions, and molecular orientations is a very challenging task. Herein, we report the synthesis of surprisingly highly uniform shape-anisotropic polymer NPs with uniaxial internal molecular orientation. Keys to our method are synchronized polymerization and self-assembly (SPSA), which can even be realized by regular dispersion polymerization. This is demonstrated using a monomer containing a rigid 4-nitroazobenzene (NAB) side group. The short nucleation period, the completion of microphase separation before molecular motion is frozen, and sufficient low particle/solvent interfacial tension are shown to be the origins of the highly uniform dimensions, single liquid crystal domains, and well-defined anisotropic shape of particles. The liquid crystallization ability of the polymers, control of molecular weight distribution, and the polymerization kinetics are identified as three key factors controlling the NP formation. The uniformity of these NPs facilitates their SA formation into colloidal crystals. The particles exhibit optically anisotropic properties depending on orientations and, in particular, show intriguing photoswitchable LC-glass (order-disorder) transition, which can be used for the detection of ultraviolet (UV) light and allows the fabrication of photoreversible colloidal films.
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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".