Numerical modeling and experimental optimization of Taylor dispersion analysis with and without an electric field
Bibliographic record
Abstract
Abstract Numerical modeling of Taylor dispersion analysis (TDA) was performed using COMSOL Multiphysics to facilitate better and faster optimization of the experimental conditions. Parameters, such as pressure, electric field, diameter, and length of capillary on the TDA conditions, were examined for particles with hydrodynamic radius ( R h ) of 2.5–250 Å. The simulations were conducted using 25, 50, and 100 cm length tubes with diameters of 25, 50, and 100 µm. It was shown that particles with larger diffusion coefficients gave more accurate results at higher velocities, and in longer and wider columns; particles with smaller diffusion coefficients gave more accurate results at smaller velocities, and in shorter and thinner columns. Moreover, the effect of electric field on the validity and the applicability of TDA was studied using TDA in conjunction with capillary electrophoresis. Diffusion coefficients were obtained using a pressure and the TDA equation and compared with those obtained with a pressure in combination of an electric field for fluorescein, FD4, FD20, FD70, and FD500. We found that TDA can be used with the presence of moderate electrophoretic migration and electroosmotic flow, when appropriate conditions were met.
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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".