Optically invariant InGaN nanowire light-emitting diodes on flexible substrates under mechanical manipulation
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The integration of GaN-based light-emitting diodes (LEDs) onto flexible platforms provides opportunities for conformal lighting, wearable electronics, and bendable displays. While this technology may enhance the functionality of the light source, the development of flexible GaN LEDs suffers from performance degradation, when mechanical bending is applied during operation. A unique approach to eliminate the degradation employs dot-in-wire structures, using cylindrical light-emitting heterostructures that protrude above the flexible platform, separating the active light-emitting region from the bending substrate. Here, we demonstrate the optical enhancement of nanowire light emitters by changing the geometric orientation within a 1 × 1 mm 2 array of nanowires on a flexible platform through bending of the substrate platform. The flexible structures were achieved by transferring GaN nanowire LEDs from sapphire substrates onto flexible polyethylene terephthalate (PET) using a “paste-and-cut” integration process. The I–V characteristics of the nanowire LEDs showed negligible change after integration onto the PET, with a turn-on voltage of 2.5 V and a forward current of 400 μA at 4 V. A significant advantage for the nanowire devices on PET was demonstrated by tilting the LEDs through substrate bending that increased the electroluminescence (EL) intensity, while the I–V characteristics and the EL peak position remained constant. Through finite-element analysis and three-dimensional finite-difference time-domain modeling, it was determined that tilting the protruding devices changed the effective distance between the structures, enhancing their electromagnetic coupling to increase light output without affecting the electrical properties or peak emission wavelength of the LEDs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 it