Proton Diffusion across Membranes of Vesicles of Poly(styrene-<i>b</i>-acrylic Acid) Diblock Copolymers
Bibliographic record
Abstract
A study of proton diffusion across membranes of block copolymer vesicles in dilute solution is described. The vesicles were formed by the self-assembly of a diblock copolymer of poly(styrene-b-acrylic acid) (PS(310)-b-PAA(36), where the numbers represent the degree of polymerization for individual blocks). A pH gradient was created across the vesicle membrane with the interior pH (pH(in)) of ca. 2.9 and the exterior pH (pH(out)) of ca. 8.5. The permeability of the polystyrene (PS) membrane was tuned by the addition of different amounts of dioxane (0-40 wt %) to the external aqueous solution. Proton concentrations in the solution outside of the vesicles were followed by monitoring the spectrum of a pH-sensitive fluorescent dye, namely 8-hydroxypyrene-1,3,6-trisulfonate. After the start of the experiment, the proton concentrations increase linearly with the square root of time, while the slopes of the lines increase with dioxane content. To calculate the diffusion coefficients of the protons across the vesicular membrane, the concentration data were fitted using a model, which describes the diffusion of species across the membrane of a reservoir. The apparent diffusion coefficient (D*, which equals the true diffusion coefficient multiplied by the partition coefficient of protons between PS and water) increases from 1.1 x 10(-18) cm(2)/s at 7 wt % dioxane in the external solution to 1.2 x 10(-14) cm(2)/s at 40 wt %. The increase of D* with dioxane content is related to its plasticization of the PS membrane, which can be used as a gating mechanism.
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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 | 0.001 |
| 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".