Transparent superhydrophobic surfaces for applications of controlled reflectance
Bibliographic record
Abstract
This work involves a new optical application for transparent superhydrophobic materials, which enables low-energy optical contact between a liquid and solid surface. The new technique described here uses this surface property to control the reflectance of a surface using frustration of total internal reflection. Surface chemistry and appropriate micro-scale and nano-scale geometries are combined to produce interfaces with low adhesion to water and the degree to which incident light is reflected at this interface is controlled by the movement of water, thereby modifying the optical characteristics at the interface. The low adhesion of water to superhydrophobic surfaces is particularly advantageous in imaging applications where power use must be minimized. This paper describes the general approach, as well as a proof-of-principle experiment in which the reflectance was controlled by moving a water drop into and out of contact with a superhydrophobic surface by variation of applied electrostatic pressure.
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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".