Scalable and Uniform Length-Tunable Biodegradable Block Copolymer Nanofibers with a Polycarbonate Core via Living Polymerization-Induced Crystallization-Driven Self-assembly
Why this work is in the frame
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Bibliographic record
Abstract
Uniform 1D block copolymer (BCP) nanofibers prepared by the seeded-growth approach termed living crystallization-driven self-assembly (CDSA) offer promising potential for various applications due to their anisotropy, length tunability, and variable core and coronal chemistries. However, this procedure consists of a multi-step process involving independent BCP synthesis and self-assembly steps, where the latter is performed at low solution concentrations (<1 wt %), hindering scale-up. Here, we demonstrate the use of a one-pot BCP synthesis and self-assembly process, polymerization-induced CDSA (PI-CDSA), to access length-disperse nanofibers with a biodegradable crystalline poly(fluorenetrimethylenecarbonate) (PFTMC) core and a hydrophilic poly(ethylene glycol) (PEG) corona derived from PEG-b-PFTMC at concentrations up to 20 wt %, 400 times higher than those previously reported. Furthermore, living PI-CDSA could be used to access scalable, low dispersity, and length-tunable 1D PEG-b-PFTMC nanofibers at concentrations of up to 10 wt %. This provides the first example of living PI-CDSA involving an all-organic and biodegradable BCP that utilizes a conveniently implemented BCP synthesis protocol and does not involve living anionic polymerization. Significantly, samples of low-dispersity nanofibers of controlled lengths from 100 to 660 nm (Lw/Ln = 1.08–1.20) were prepared, allowing for upscaled access to well-defined biodegradable nanofibers at useful length-scales for applications in nanomedicine. Interestingly, detailed studies revealed a key role for PFTMC homopolymer impurities in the BCP prepared in situ in the formation of nanofibers under the reaction conditions used.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it