Dielectric friction as a mechanism for selectivity alteration in capillary electrophoresis using acetonitrile-water media
Bibliographic record
Abstract
The mobilities of a series of aromatic carboxylates and sulfonates, ranging in charge from -1 to -4, were investigated as a function of acetonitrile concentration in the electrophoretic buffer. Absolute mobilities were determined by extrapolation of the effective mobilities to zero ionic strength according to the Pitts' equation. In general, anions of higher charge were more strongly influenced by ionic strength, with similarly charged anions experiencing ionic strength effects that were not significantly different at the 95% confidence level. Furthermore, the relative magnitudes of the Onsager slopes varied with acetonitrile content according to the z/(etaepsilon(1/2)) dependence in the electrophoretic effect of the Pitt's equation. Addition of acetonitrile to the electrophoretic media resulted in changes in the absolute mobilities of the anions. These acetonitrile-induced selectivity alterations were attributed to dielectric friction. As predicted by the Hubbard-Onsager model of dielectric friction, changes in sulfonate mobility were shown to correlate to changes in solvent viscosity (eta), dielectric constant (epsilon), and relaxation time (tau). The combined effects of ionic strength and dielectric friction caused analytes with higher charge-to-size ratios to be slowed to a greater extent upon addition of acetonitrile compared to those with lower charge-to-size. For example, at 75% acetonitrile and 20 mM ionic strength, a migration order reversal occurred between the triply and singly charged sulfonates.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".