Numerical Study of Capillary Flow in Microchannels With Alternate Hydrophilic-Hydrophobic Bottom Wall
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Bibliographic record
Abstract
A two-dimensional numerical simulation of flow in patterned microchannel with alternate layers of different sizes of hydrophilic and hydrophobic surfaces at the bottom wall is conducted here. The effect of specified contact angle and working fluid (de-ionized (DI) water and ethanol) on capillary phenomena is observed here. The volume of fluid method is used for simulating the free surface flow in the microchannel. Meniscus profiles with varying amplitude and shapes are obtained under the different specified surface conditions. Nonsymmetric meniscus profiles are obtained by changing the contact angles of the hydrophilic and hydrophobic surfaces. A meniscus stretching parameter is defined here and its relation to the capillary phenomena in the microchannel is discussed. Flow variation increases as the fluid traverses alternately between the hydrophilic and hydrophobic regions. The pattern size and the surface tension of the fluid are found to have significant influence on the capillary phenomena in the patterned microchannel. Smaller pattern size produces enhanced capillary effect with DI water, whereas no appreciable gain is observed for ethanol. The magnitude of maximum velocity along the channel height varies considerably with the pattern size and the contact angle. Also, the rms velocity is found to be higher for smaller alternate patterned microchannel. The meniscus average velocity difference at the top and bottom walls increases for a dimensionless pattern size of 0.6 and thereafter it decreases with the increase in pattern size in the case of DI water with hydrophilic-hydrophobic pattern. Using such patterned microchannel, it is possible to manipulate and optimize fluid flow in microfluidic devices, which require enhanced mixing for performing biological reactions.
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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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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