Kinetics of Fusion of Polystyrene-<i>b</i>-poly(acrylic acid) Vesicles in Solution
Bibliographic record
Abstract
Polystyrene- b -poly(acrylic acid) vesicles prepared in dioxane/water mixtures are equilibrium structures that respond to changes in the solvent composition by changing their size. An increase in vesicle size can be induced by adding water and occurs by vesicle fusion, while a decrease in vesicle size involves vesicle fission and can be induced by decreasing the water content in the solvent mixture. In this study, the kinetics of increase in vesicle size were examined. We evaluate the relaxation times of the process and determine the effect of factors such as the water content in the solvent mixture, the extent of perturbation in the solvent composition, the initial polymer concentration, and the acrylic acid block length on the rates. After adding water, the fusion of vesicles in solution was followed by measuring the change in turbidity as a function of time, and the relaxation times were extracted from the resulting turbidity vs time plots. The results show that the kinetics of increase in vesicle size become progressively slower as the water content increases, while increasing the magnitude of perturbation (i.e., the amount of water added) results in faster rates. Increasing the initial polymer concentration or the acrylic acid block length changes vesicle size and vesicle concentration and causes an increase in the rate of vesicle fusion.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".