Direct Measurements of Effect of Counterion Concentration on Mechanical Properties of Cationic Vesicles
Bibliographic record
Abstract
Theoretical analyses of charged membranes in aqueous solutions have long predicted that the electric double layer surrounding them contributes significantly to their mechanical properties. Here we report the first, direct experimental measurements of the effect of counterion concentration on the bending and area expansion modulus of cationic surfactant vesicles. Using the classical technique of micropipet aspiration coupled with a modified experimental protocol that is better suited for cationic vesicles, we successfully measure the mechanical properties of a double-tailed cationic surfactant, diethylesterdimethyl ammonium chloride (diC18:1 DEEDMAC) in CaCl2 solutions. It is observed that the area expansion modulus of the charged membrane exhibits no measurable dependence on the counterion concentration, in accordance with existing models of bilayer elasticity. The measured bending modulus, however, is found to vary nonmonotonically and exhibits a minimum in its variation with counterion concentration. The experimental results are interpreted based on theoretical calculations of charged and bare membrane mechanics. It is determined that the initial decrease in bending modulus with increasing counterion concentration may be attributed to a decreasing double layer thickness, while the subsequent increase is likely due to an increasing membrane thickness. These mechanical moduli measurements qualitatively confirm, for the first time, theoretical predictions of a nonmonotonic behavior and the opposing effects of ionic strength on the bending rigidity of charged bilayers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".