Towards fully green printed device with environmental perspectives
Bibliographic record
Abstract
Abstract Printed electronics (PE) is growing rapidly through innovation in several pathways: ink formulation, substrate improvement, printing and drying process optimization. All these developments are combining to enable the production of a new generation of PE devices that reduce e-waste. However, the main question of the recyclability of these devices is critical. This article is focused on (1) the industrial fabrication of recyclable substrates prepared by roll-to-roll printing using flexographic printing units to cover paper with shellac solution and (2) the environmental impact assessment of new development of PE. To investigate the performance of the produced substrate, a battery-less near-field communication antenna was printed with a flatbed screen printing using silver ink. The print quality, electrical resistance and the basic functional characterization of these paper-based antennas were investigated and reported. To validate the functionality of printed devices, a 2.5 × 2.5 mm2 electronic chip was integrated onto the printed device. In order to predict the future perspectives and development of the PE, environmental challenges of the ink and substrates, during the production and end-of-life phases, are explored and discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".