pH‐Responsive Porous Nanocapsules for Controlled Release
Bibliographic record
Abstract
In this work pH-responsive porous nanocapsules have been successfully prepared from a ternary graft copolymer, poly(glycidyl methacrylate)-g-[poly(2-cinnamoyloxyethyl methacrylate)-r-poly(ethylene glycol) methyl ether-r-poly(2-diethylaminoethyl methacrylate)] or PGMA-g-(PCEMA-r-MPEG-r-PDEAEMA). The graft copolymers were fabricated by grafting three types of polymer chains onto the backbone polymer by using click chemistry. These ternary copolymers underwent self-assembly to form vesicles in a DMF/water solvent mixture. While the MPEG chains served as the corona and stabilized the vesicles, the vesicle wall was composed of a dominant PCEMA continuous phase that was interspersed by PDEAEMA domains. After photo-cross-linking, the PDEAEMA domains were embedded in the structurally locked PCEMA wall. By decreasing the pH of the external solution, we were able to trigger the release of encapsulated pyrene due to the capsule wall becoming porous as a result of the PDEAEMA chains bearing positively charged amine groups stretching into the water. While these pH-responsive porous nanocapsules exhibited potential applications in drug delivery, detection and catalysis, the strategy reported in this contribution also represented a new paradigm for the design and preparation of other novel stimuli-responsive porous nanocapsules.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".