Fiberlike Micelle Networks from the Solution Self-Assembly of B–A–B Triblock Copolymers with Crystallizable Terminal Polycarbonate Segments
Bibliographic record
Abstract
Although the formation of spherical micelle networks from the solution self-assembly of B–A–B triblock copolymers (triBCPs) with solvophobic terminal “B” blocks has been widely studied, the introduction of intermicellar linkages between fiber-like micelles is virtually unexplored. Herein, a B–A–B triBCP with crystallizable “B” blocks was used to achieve nanofiber aggregation and network formation. Crystallization of the solvophobic terminal blocks in the cores of distinct nanofibers resulted in nanofibers physically linked together by the solvophilic coronal “A” block. The triBCP used in this work, PFTMC14-b-PEG900-b-PFTMC14, contains two crystallizable terminal poly(fluorenetrimethylene carbonate) (PFTMC) “B” blocks and a central poly(ethylene glycol) (PEG) “A” block. Performing seeded growth/living crystallization-driven self-assembly (CDSA) with the triBCP at low concentrations (2 mg/mL) and with a low fraction of common solvent (10%) at 20 °C led to the formation of low-dispersity flowerlike nanofibers of controlled lengths with crystalline PFTMC cores and looped coronal chains. In contrast, when self-assembly of the triBCP was conducted at high concentration (>5 mg/mL) with high common solvent fraction (20%) at ≥70 °C with subsequent cooling to 20 °C, networks of nanofibers were obtained. Networks were also accessible from preformed nanofibers of controlled length prepared from PFTMC15-b-PEG265 diBCP via the addition of the triBCP under similar conditions. Bundling and entanglement of the nanofibers were observed by TEM and AFM. Macroscopic gels were formed when self-assembly was performed at very high concentrations (e.g., 20 mg/mL) and common solvent fractions (20%). Upon future extension to aqueous systems, the nanofiber network formation process would provide a route to hierarchical assemblies that are of potential interest as gel-like scaffolds for tissue engineering as well as other applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".