The 2D microfluidics cookbook – modeling convection and diffusion in plane flow devices
Bibliographic record
Abstract
A growing number of microfluidic systems operate not through networks of microchannels but instead through using 2D flow fields. While the design rules for channel networks are already well-known and exposed in microfluidics textbooks, the knowledge underlying transport in 2D microfluidics remains scattered piecemeal and is not easily accessible to experimentalists and engineers. In this tutorial review, we formulate a unified framework for understanding, analyzing and designing 2D microfluidic technologies. We first show how a large number of seemingly different devices can all be modelled using the same concepts, namely flow and diffusion in a Hele-Shaw cell. We then expose a handful of mathematical tools, accessible to any engineer with undergraduate level mathematics knowledge, namely potential flow, superposition of charges, conformal transforms and basic convection-diffusion. We show how these tools can be combined to obtain a simple "recipe" that models almost any imaginable 2D microfluidic system. We end by pointing to more advanced topics beyond 2D microfluidics, namely interface problems and flow and diffusion in the third dimension. This forms the basis of a complete theory allowing for the design and operation of new microfluidic systems.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".