Living hinges for resilient and recyclable paper-based flexible printed electronics
Bibliographic record
Abstract
Abstract The ability to fabricate electronics by printing has enabled an array of technologies that can create intelligent or smart packaging; however, this can come at the cost of recyclability. Selection of materials compatible with recycling streams is possible, such as paperboard and carbon inks, but there is a trade-off in terms of performance, flexibility and reliability. A major challenge for the use of paperboard is delamination and deformation when subject to small bend radii. The substrate has a tendency to crease when bent beyond a critical radius, which can fracture the surface and any traces printed onto it, causing device failure. We have demonstrated that the use of kerf cuts to form a living hinge, similar to that used in woodworking, can increase the flexibility of paperboard and allow reliable bending of conductive traces. We have identified the key design parameters of such a living hinge and evaluated their effect on the flexibility of a typical paperboard used in packaging. We then demonstrated that conductive traces of silver or carbon can withstand repeated bending with 100% reliability, compared to a worst case of 16% of control sample traces surviving the same test. Additionally, we demonstrated that the hinges improve the consistency of the trace resistance when subject to repeat bending. The behaviour of the resistance change as a function of bending was seen to be dependent upon the ink material, likely due to differing morphologies. We demonstrate the applicability of this technique in a smart device for medication adherence packaging.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".