Uniform segmented platelet micelles with compositionally distinct and selectively degradable cores
Bibliographic record
Abstract
The creation of nanoparticles with controlled and uniform dimensions and spatially defined functionality is a key challenge. The recently developed living crystallization-driven self-assembly (CDSA) method has emerged as a promising route to one-dimensional (1D) and 2D core-shell micellar assemblies by seeded growth of polymeric and molecular amphiphiles. However, the general limitation of the epitaxial growth process to a single core-forming chemistry is an important obstacle to the creation of complex nanoparticles with segmented cores of spatially varied composition that can be subsequently exploited in selective transformations or responses to external stimuli. Here we report the successful use of a seeded growth approach that operates for a variety of different crystallizable polylactone homopolymer/block copolymer blend combinations to access 2D platelet micelles with compositionally distinct segmented cores. To illustrate the utility of controlling internal core chemistry, we demonstrate spatially selective hydrolytic degradation of the 2D platelets-a result that may be of interest for the design of complex stimuli-responsive particles for programmed-release and cargo-delivery applications.
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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".