Diffusion and Partitioning of Solutes in Agarose Hydrogels: The Relative Influence of Electrostatic and Specific Interactions
Bibliographic record
Abstract
The nature and density of charged sites in an agarose gel have been studied. Diffusion and partition coefficients of various organic and inorganic ions have been measured as a function of ionic strength, μ, and pH to investigate the solute−gel interactions resulting from charge effects and specific complexation. The majority of binding sites in the gel are pyruvate groups, with an intrinsic protonation constant of log K a int = 3.9. We measured the charge density of the gel as a function of added salt and pH and evaluated the Donnan potential. The partition coefficients of cations decrease and those of anions increase with increasing ionic strength because of progressive screening of the anionic sites in the gel, as predicted by the Boltzmann and Poisson−Boltzmann equations. The charges in the gel become completely screened at μ ≈ 10 -2 . As predicted with the Smoluchowski−Poisson−Boltzmann theory, the diffusion coefficient of cationic species is reduced at low ionic strength. We tested both cylindrical and spherical symmetries of Poisson−Boltzmann cell models to describe these variations and obtained better results with the former. In addition to electrostatic effects, we detected specific interactions between metal ions and the gel, and we determined the intrinsic association constants. General models are presented for the partitioning and diffusion of solutes in the gel, which consider steric, electrostatic, and chemical interactions.
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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) | 0.000 | 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".