Bibliographic record
Abstract
The streaming potentials of hyaluronic acid (HA) hydrogel films are measured and theoretically interpreted by systematically varying the HA concentration and the streaming electrolyte pH and ionic strength. While Donnan potentials are expected to vanish with sufficient added salt, apparent ζ-potentials from the Helmholtz–Smoluchowski interpretation remain of the order −20 mV. To theoretically interpret these data, we derived an electrokinetic model (valid in the Debye–Hückel regime) that accounts for ionic and hydrodynamic permeability of the gels. The films could then be ascribed an effective acid dissociation constant p K a ≈ 4.2, specific HA charge ≈−0.1 e mmol g –1, and Brinkman/hydrodynamic permeability l 2 ∼ l 0 2 S 1/3, where l 0 is the Brinkman length for HA solutions in the as-prepared reference state and S is the hydrogel swelling ratio. At an ionic strength of 10 mmol L –1, for example, the HA surface potentials are only ψ D /2 ≈ −8 mV, where ψ D is the Donnan potential, considerably lower than ζ-potentials furnished by the Helmholtz–Smoluchowski interpretation. This insight significantly changes how the films are expected to interact with other surfaces and colloids via Derjaguin–Landau–Vervey–Overbeek-type forces. Our analysis furnishes formulas for the swelling ratio S and hydrodynamic permeability l 2, expressed explicitly as simple power-law functions of the as-prepared HA concentration c ha (wt %), consistent with independent assessments of the HA solution permeability and polyelectrolyte-hydrogel swelling theory. These may prove valuable for extrapolating the results to other combinations of ionic strength, pH, and HA and cross-linking concentrations.
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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) | 0.001 | 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".