Structural colour printing from a reusable generic nanosubstrate masked for the target image
Bibliographic record
Abstract
Structural colour printing has advantages over traditional pigment-based colour printing. However, the high fabrication cost has hindered its applications in printing large-area images because each image requires patterning structural pixels in nanoscale resolution. In this work, we present a novel strategy to print structural colour images from a pixelated substrate which is called a nanosubstrate. The nanosubstrate is fabricated only once using nanofabrication tools and can be reused for printing a large quantity of structural colour images. It contains closely packed arrays of nanostructures from which red, green, blue and infrared structural pixels can be imprinted. To print a target colour image, the nanosubstrate is first covered with a mask layer to block all the structural pixels. The mask layer is subsequently patterned according to the target colour image to make apertures of controllable sizes on top of the wanted primary colour pixels. The masked nanosubstrate is then used as a stamp to imprint the colour image onto a separate substrate surface using nanoimprint lithography. Different visual colours are achieved by properly mixing the red, green and blue primary colours into appropriate ratios controlled by the aperture sizes on the patterned mask layer. Such a strategy significantly reduces the cost and complexity of printing a structural colour image from lengthy nanoscale patterning into high throughput micro-patterning and makes it possible to apply structural colour printing in personalized security features and data storage. In this paper, nanocone array grating pixels were used as the structural pixels and the nanosubstrate contains structures to imprint the nanocone arrays. Laser lithography was implemented to pattern the mask layer with submicron resolution. The optical properties of the nanocone array gratings are studied in detail. Multiple printed structural colour images with embedded covert information are demonstrated.
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 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".