Invertible vesicles and micelles formed by dually-responsive diblock random copolymers in aqueous solutions
Bibliographic record
Abstract
Dually responsive diblock random copolymers poly(nPA0.8-co-DEAEMA0.2)-block-poly(nPA0.8-co-EA0.2) were made from N-n-propylacrylamide (nPA), 2-(diethylamino)ethyl methacrylate (DEAEMA) and N-ethylacrylamide (EA) via reversible addition-fragmentation chain transfer (RAFT) polymerization. Copolymers of different block length ratios, poly(nPA28-co-DEAEMA7)-block-poly(nPA29-co-EA7) (P1) and poly(nPA28-co-DEAEMA7)-block-poly(nPA70-co-EA18) (P2), self-assemble into vesicles and micelles, responding to external stimuli in aqueous solutions, and both show "schizophrenic" inversion behavior when the pH and temperature are varied. The relative lengths of the two blocks are shown to affect the self-assembly of amphiphilic diblock copolymers. P1 has a similar length for both blocks and forms spherical vesicles with the first block poly(nPA29-co-EA7) as the membrane inner layer at pH 7 and 37 °C (above the cloud point of the more hydrophobic block, CP1), while spherical micelle-like aggregates are obtained at pH 10 and 25 °C (above CP1) with the second block poly(nPA28-co-DEAEMA7) as the core. In comparison, P2 has a different block length ratio (1 : 3, thus a much longer second block) and forms spherical micelles above CP1 at both pH 7 (the second block as the core) and pH 10 (the first block as the core). Further aggregation was observed by heating the polymer solution above the cloud point of the more hydrophilic block (CP2). The variation of the length and chemical composition of the blocks allows the tuning of the responsiveness of the block copolymers toward both pH and temperature and determines the formation of either micelles or vesicles during the aggregation.
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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".