Functional Brush Poly(2‐ethyl‐2‐oxazine)s: Synthesis by CROP and RAFT, Thermoresponsiveness and Grafting onto Iron Oxide Nanoparticles
Bibliographic record
Abstract
Abstract Brush polymers are highly functional polymeric materials combining the properties of different polymer classes and have found numerous applications, for example, in nanomedicine. Here, the synthesis of functional phosphonate‐ester‐bearing brush polymers based on poly(2‐oxazine)s is reported through a combination of cationic ring‐opening polymerization (CROP) of 2‐ethyl‐2‐oxazine and reversible addition‐fragmentation chain transfer (RAFT) polymerization. In this way, a small library of well‐defined (Đ ≤ 1.17) poly(oligo(2‐ethyl‐2‐oxazine) methacrylate) P(OEtOzMA)n brushes with tunable lower critical solution temperature (LCST) behavior and negligible cell toxicity is prepared. Upon deprotection, the phosphonic acid end‐group of the P(OEtOzMA)n brush enables the successful grafting‐onto iron oxide nanoparticles (IONPs). Colloidal stability of the particle suspension in combination with suitable magnetic resonance imaging (MRI) relaxivities demonstrates the potential of these particles for future applications as negative MRI contrast agents.
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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) | 0.001 | 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 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".