Roughness Effects on Continuous and Discrete Flows in Superhydrophobic Microchannels
Bibliographic record
Abstract
The dynamic behaviors of continuous and discrete flows in superhydrophobic microchannels are investigated with a lattice Boltzmann model. Typical characters of the superhydrophobic phenomenon are well observed from our simulations, including air trapped in the surface microstructures, high contact angles, low contact angle hysteresis, and reduced friction to fluid motions. Increasing the roughness of a hydrophobic surface can produce a large flow rate through the channel due to the trapped air, implying less friction or large apparent slip. The apparent slip length appears to be independent to the channel width and could be considered as a surface property. For a moving droplet, its behavior is affected by the surface roughness from two aspects: the contact angle difference between its two ends and the surface-liquid interfacial friction. As a consequence, the resulting droplet velocity changes with the surface roughness as firstly decreasing and then increasing. Simulation results are also compared with experimental observations and better agreement has been obtained than that from other numerical method. The information from this study could be valuable for 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".