Capillary force mediated flow patterns and non‐monotonic pressure drop characteristics of oil‐water microflows
Bibliographic record
Abstract
We report the capillary and frictional force mediated transitions of morphologies of an oil‐water flow inside a microchannel using experiments and computational fluid dynamic simulations. A number of steady and time‐periodic flow patterns were reported with the variations in the interfacial tension, exchange of inlets, flow ratio, and viscosity ratio of the phases. Transitions from slug to plug to droplet to stratified flow patterns were obtained by tuning the interfacial tension. Progressive reduction in the interfacial tension transformed big slugs into smaller plugs, plugs into droplets, and droplets into a stratified flow pattern. Interestingly, the simulations uncovered a non‐monotonic and nonlinear reduction in pressure drop with the decrease in interfacial tension. The change in the pressure drop was correlated to the variation in the slug, plug, or droplet frequency of water at the outlet. The variations in the pressure drop were also associated with the transition from dripping to jetting of water droplet ejection near the channel inlet. Apart from the interfacial tension, the viscosity stratification across the phases was also found to play an important role in converting the slug flow patterns into smaller plugs or droplets. The study also reports the parametric space in which the droplet flow patterns could be obtained inside a microchannel tuning the flow and viscosity ratios of the phases alongside the interfacial tension. The reported transitions of flow patterns and the pressure drop characteristics can be of significance in improving the efficiency of future microfluidic devices.
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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 | 0.000 |
| 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".