Gravure-printed electronics: recent progress in tooling development, understanding of printing physics, and realization of printed devices
Bibliographic record
Abstract
Abstract Printed electronics promises the realization of low-cost electronic systems on flexible substrates over large areas. In order to achieve this, high quality patterns need to be printed at high speeds. Gravure printing is a particularly promising technique that is both scalable and offers micron-scale resolution. Here, we review the tremendous progress that has recently been made to push gravure printing beyond its traditional limitations in the graphic arts. Rolls with far greater precision than traditional rolls and with sub-5 μ m resolution can be fabricated utilizing techniques leveraging the precision of silicon microfabrication. Physical understanding of the sub-processes that constitute the gravure process is required to fully utilize the potential of gravure. We review the state-of-the-art of this understanding both for single cells and patterns of multiple cells to print high-resolution features as well as highly-uniform layers. Finally, we review recent progress on gravure printed transistors as an important technology driver. Fully high-speed printed transistors with sub-5 μ m channel length and sub-5 V operation can be printed with gravure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".