Inkjet printing on hydrophobic surfaces: Controlled pattern formation using sequential drying
Bibliographic record
Abstract
Inkjet-printed micro-patterns on hydrophobic surfaces have promising applications in the fabrication of microscale devices such as organic thin-film transistors. The low wettability of the surface prevents the inkjet-printed droplets from spreading, connecting to each other, and forming a pattern. Consequently, it is challenging to form micro-patterns on surfaces with low wettability. Here, we propose a sequential printing and drying method to form micro-patterns and control their shape. The first set of droplets is inkjet-printed at a certain spacing and dried. The second set of droplets is printed between these dry anchors on the surface with low wettability. As a result, a stable bridge on the surface with low wettability forms. This printing method is extended to more complicated shapes such as triangles. By implementing an energy minimization technique, a simple model was devised to predict the shape of the inkjet-printed micro-patterns while confirming that their equilibrium shape is mainly governed by surface tension forces. The gradient descent method was utilized with parametric boundaries to emulate droplet pinning and wettability of the anchors and to prevent convergence issues from occurring in the simulations. Finally, the energy minimization based simulations were used to predict the required ink to produce dry lines and triangles with smooth edges.
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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".