Filling schemes of silver dots inkjet-printed on pixelated nanostructured surfaces
Bibliographic record
Abstract
Recently, our group demonstrated an inkjet-based technique to enable high-throughput, versatile and full-colour printing of structural colours on generic pixelated nanostructures, termed as molded ink on nanostructured surfaces. The printed colours are controlled by the area of printed silver on the pixelated red, green and blue polymer nanostructure arrays. This paper investigates the behaviour of jetted silver ink droplets on nanostructured surfaces and the microscale dot patterns implemented during printing process, for achieving accurate and consistent colours in the printed images. The surface wettability and the schemes of filling silver dots inside the subpixels are crucial to the quality of printed images. Several related concepts and definitions are introduced, such as filling ratio, full dots per subpixel (DPSP), number of printable colours, colour leaking and dot merging. In our experiments, we first chemically modified the surface to control the wettability and dot size. From each type of modified surface, various filling schemes were experimented and the printed results were evaluated with comprehensive considerations on the number of printable colours and the negative effects of colour leaking and dot merging. Rational selection of the best filling scheme resulted in a 2-line filling scheme using 20 μm dot spacing and line spacing capable of printing 9261 different colours with 121 pixel per inch display resolution, on low-wettability surface. This study is of vital importance for scaling up the printing technique in industrial applications and provides meaningful insights for inkjet-printing on nanostructures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".