“Decoration” of Shell Cross-Linked Reverse Polymer Micelles Using ATRP: A New Route to Stimuli-Responsive Nanoparticles
Bibliographic record
Abstract
We demonstrate the use of atom transfer radical polymerization (ATRP) to graft polymers onto preformed shell cross-linked reverse micelles (SCRM). Reverse polymer micelles are first obtained in organic solvents and stabilized by cross-linking of the shell using the photoinduced dimerization of coumarin groups (>310 nm). The structurally locked SCRM are then used as micellar macroinitiators for further polymerization from their surface of monomers such as styrene and dimethylaminoethyl methacrylate (DMAEMA) via ATRP. The decoration of an outer corona of PDMAEMA renders the nanoparticles containing a hydrophilic core soluble in water, with the solubility being sensitive to changes in pH and temperature. In addition, such decorated SCRM are light-responsive. The photoinduced cleavage of cyclobutane bridges (<260 nm) leads to the de-cross-linking of the shell and thus the disintegration of the micellar aggregates. The characterization results, using size-exclusion chromatography (SEC), dynamic light scattering (DLS), and transmission electron microscope (TEM), show an excellent control over the reactions, the molar mass, and the polydispersity of SCRM before and after the surface-initiated ATRP. The “decoration” of SCRM offers a new route to designing stimuli-responsive polymer nanostructures that cannot be prepared through only block copolymer self-assembly.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".