Effect of Superhydrophobic Surfaces for Wetting in Micro-Systems
Bibliographic record
Abstract
To develop energy efficient microfluidic systems it is important to minimize the adhesion of the liquid to the surfaces in the system. One of the proposed methods in the literature is to use superhydrophobic surfaces, i.e. surfaces with contact angles above 150 degrees (for water). However, the issue that is not generally considered in depth in literature is the role of contact angle hysteresis (the difference between advancing and receding contact angles). In other words, to have an energy efficient droplet actuation system for microfluidics it is not sufficient to use surfaces that have large contact angles, but they also should have low contact angle hysteresis (CAH). Contact angle hysteresis is a common phenomenon in wetting. It is important but difficult to theoretically investigate CAR to optimally design superhydrophobic surfaces for micro-systems. We will present a universal approach to calculate CAR based on a free energy analysis for micro-textured surfaces. Thermodynamic status of contact angles and calculation of free the energy barrier are significantly simplified by using a representative 2D model instead of a 3D model with minimum loss of generality. A pillar surface structure is chosen as a typical example (see Figure 1). It is demonstrated that this approach can predict CAR and equilibrium contact angles that are consistent with predictions of Wenzel's and Cassie's equations. This approach can also provide a criterion for transition between noncomposite and composite structures (i.e. free spreading of liquids on a surface or achieving minimum contact area between a liquid drop and surfaces in a channel). Recent experimental results for wetting of superhydrophobic surfaces will also be discussed.
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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 | 0.001 | 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".