Factors Affecting the Temporal Stability of Semipermanent Bilayer Coatings in Capillary Electrophoresis Prepared Using Double-Chained Surfactants
Bibliographic record
Abstract
Surfactants such as didodecyldimethylammonium bromide (DDAB) adsorb onto fused-silica capillaries to form semipermanent bilayer coatings. However, such coatings must be regenerated between runs to maintain efficiency and reproducibility. In this paper, chemical and physical factors affecting the stability of DDAB coatings are investigated. Chemical factors such as ionic strength and the nature of the buffer anion (e.g., from acetate to phosphate), which decrease the critical micelle concentration of DDAB, improve the coating stability. Increasing buffer pH also increases the coating stability. Finally, reducing the capillary diameter and reducing the volume of buffer flushed through the capillary enhance the coating stability. Using 50 mM acetate, pH 5.0, in a 25-microm-i.d. capillary, cationic proteins were separated with efficiencies of 1.05 million plates/m and a run-to-run migration time reproducibility of 0.6-0.8% RSD for 10 successive runs without regeneration of the DDAB coating between runs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".