Formation and Regulation of Multicompartment Vesicles from Cyclic Diblock Copolymer Solutions: A Simulation Study
Bibliographic record
Abstract
Abstract The self-assembly of a cyclic AB copolymer system with relatively long A blocks and short B blocks in B-selective solvents is investigated using a simulated annealing method. By investigating the effect of the lengths and solubilities of A and B blocks (NA and NB, εAS and εBS), the incompatibility between A and B blocks (εAB), as well as the polymer concentration (Cp) and the conditions for the formation of multicompartment vesicles in cyclic diblock copolymer solutions, is predicted. The phase diagrams in terms of NB, εAS, and Cp are constructed. The mechanism of the morphological transition is elucidated. It is shown that for cyclic copolymers the change in the above factors relating to the polymer and solvent properties all can lead to the transition from simple vesicles to multicompartment vesicles, but two different transition mechanisms are revealed. In addition, our simulations demonstrate that the self-assembly of cyclic copolymers could provide a powerful strategy for regulating the compartment number and the wall thickness of the multicompartment vesicles by adjusting the block solubilities and block lengths, respectively. These findings will facilitate the application of multicompartment architectures in cell mimicry, drug delivery, and nanoreactors.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".