Self-assembled coating for modification of the electro-osmotic flow in nonaqueous capillary electrophoresis using formamide
Bibliographic record
Abstract
The use of pure nonaqueous solvents in capillary electrophoresis (CE) can alter the separation selectivity and enhance the solubility of hydrophobic compounds and enables the use of higher voltages. However, control of the electro-osmotic flow (EOF) is essential. In this work, we report the use of self-assembled coatings for EOF modification and elimination of analyte adsorptions onto silica capillaries in pure formamide. Bilayer capillary coatings derived from the double chain cationic surfactant dimethyldioctadecylammonium bromide (2C18DAB) reverses the EOF in buffers such as acetate, formate, and phosphate. Reversed EOF of >1.1 × 10–4 cm2/Vs enables the separation of the pharmaceutical drugs propranolol, metoprolol, chloroquine, and chloropheniramine in less than 5 min with efficiencies of 0.2–0.5 million plates/m (66 000 to 165 000 plates). Chemical and physical factors affecting the coating stability and their influence on separation speed and efficiency of the cationic drugs in formamide are also investigated.Key words: capillary electrophoresis, cationic surfactants, electro-osmotic flow, formamide, nonaqueous solvents.
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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 | 0.000 |
| Research integrity | 0.001 | 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".