Uniform Biodegradable Fiber-Like Micelles and Block Comicelles via “Living” Crystallization-Driven Self-Assembly of Poly(<scp>l</scp>-lactide) Block Copolymers: The Importance of Reducing Unimer Self-Nucleation via Hydrogen Bond Disruption
Bibliographic record
Abstract
Fiber-like micelles based on biodegradable and biocompatible polymers exhibit considerable promise for applications in nanomedicine, but until recently no convenient methods were available to prepare samples with uniform and controllable dimensions and spatial control of functionality. "Living" crystallization-driven self-assembly (CDSA) is a seeded growth method of growing importance for the preparation of uniform 1D and 2D core-shell nanoparticles from a range of crystallizable polymeric amphiphiles. However, in the case of poly(l-lactide) (PLLA), arguably the most widely utilized biodegradable polymer as the crystallizable core-forming block, the controlled formation of uniform fiber-like structures over a substantial range of lengths by "living" CDSA has been a major challenge. Herein, we demonstrate that via simple modulation of the solvent conditions via the addition of trifluoroethanol (TFE), DMSO, DMF and acetone, uniform fiber-like nanoparticles from PLLA diblock copolymers with controlled lengths up to 1 μm can be prepared. The probable mechanism involves improved unimer solvation by a reduction of hydrogen bonding interactions among PLLA chains. We provide evidence that this minimizes undesirable unimer aggregation which otherwise favors self-nucleation that competes with epitaxial crystallization from seed termini. This approach has also allowed the formation of well-defined segmented block comicelles with PLLA cores via the sequential seeded-growth of PLLA block copolymers with different corona-forming blocks.
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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".