Theoretical Investigation of On-Chip Multi-Species Transport in Micro-Channels for Analysis Applications
Bibliographic record
Abstract
A complete mathematical model is developed for application to simulate the unsteady two-step on-chip sample injection and separation processes in microfluidic devices. The origin and applicability of the slip-wall velocity boundary condition is discussed. Due to electrophoresis effect, migration influence of every species is considered in the model and then solved for separation analysis. The model is non-dimensionalized in a unique manner to reveal effects of some key fundamental parameters: the Reynolds-Schmidt number, electrophoretic mobility of sample species, applied potentials, etc. In particular, the influence of ReSci is examined over the commonly encountered range and the effect of electrophoretic mobilities on separation is investigated for three different types of samples. Results include center-line concentration profiles as well as concentration contour plots over a range of nondimensional time (less than 400). Resolution is defined and employed to evaluate the separation results. The magnitude of calculated separation resolution (around 2.0) is comparable to experimental results. Through parametric studies, the characteristics of both injection and separation are revealed numerically and well understood for future effective control and innovative chip design.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".