Effect of Poly(acrylic acid) Block Length Distribution on Polystyrene-<i>b</i>-Poly(acrylic acid) Aggregates in Solution. 1. Vesicles
Bibliographic record
Abstract
The effect of polydispersity on the self-assembly of block copolymer aggregates in solution was studied under two sets of conditions. A series of polystyrene- block -poly(acrylic acid) copolymers of an identical polystyrene length of 310 units but of varying degrees of polymerization of the poly(acrylic acid) (PAA) was synthesized. Mixtures of the copolymers were made to artificially broaden the molecular weight distribution of the PAA at a constant number average of 28, in the polydispersity index (PI) range of 1.1−2.1. The samples were dissolved in two different solvent systems (dioxane and a mixture of tetrahydrofuran (THF)/ N, N -dimethyl formamide (DMF)), and self-assembly was induced by the slow addition of water. The samples were quenched at a predetermined water content. Transmission electron microscopy and dynamic light scattering were used to measure sizes and size distributions of the aggregates. At a low PAA polydispersity index (PAA PI ∼ 1.1), in the THF/DMF system, large polydisperse vesicles of a diameter of 270 ± 220 nm were seen. Generally the size of the vesicles decreased with increased PAA polydispersity. For example, in the THF/DMF system, at a PAA PI of 1.8, the average vesicle size was 80 ± 20 nm. The trend is explained qualitatively by the length segregation of the PAA chains (large chains segregate to the outer surface while smaller chains prefer the inner surface of the vesicle) and the ratio of short chains to long chains in the mixtures. The presence of only vesicles in mixtures containing polymers that do not form vesicles by themselves, but rather spheres and large compound micelles, suggests that there is no significant segregation of chains between aggregates, but only segregation of chains within individual vesicular aggregates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".