Rotate-to-bend setup for fatigue bending tests on inkjet-printed silver lines
Bibliographic record
Abstract
Abstract For the growing field of flexible electronics the performance of fabricated flexible devices during bending deformation has to be investigated in order to guarantee their resilience against small bending radii and bending fatigue. We report on a rotate-to-bend apparatus, which allows for arbitrary sequences of compressive as well as tensile bending and a wide range of selectable bending radii without applying additional strain. The electrical characterization can be conducted simultaneously with high speed measurement. We test the rotate-to-bend device on inkjet-printed conducting paths of Ag nanoparticles and Ag nanowires on various foil substrates. Fatigue bending cycles show that tensile deformation leads to a higher increase in resistance of the printed lines compared to compressive strain. This is caused by the higher tendency of microcracks to form during tensile bending. We also show the high negative impact of the substrate thickness on bending fatigue during full bending cycles. Here, Ag nanowires show superior fatigue behaviour compared to the nanoparticle lines due to their flexible, mesh-like network. The rotate-to-bend apparatus could become an efficient and inexpensive device for the testing of flexible devices.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".