Color‐Tunable 3D InGaN/GaN Multi‐Quantum‐Well Light‐Emitting‐Diode Based on Microfacet Emission and Programmable Driving Power Supply
Bibliographic record
Abstract
Abstract Color‐tunable InGaN/GaN multi‐quantum‐well (MQW) light‐emitting diodes (LEDs) are reported based on GaN microfacet structure directly grown on c‐plane patterned sapphire substrate by metal organic vapor phase epitaxy (MOVPE) through promoting 3D growth. By adjusting GaN growth temperature and pattern arrangement, a GaN microfacet with almost pure {101} semipolar facets is obtained. The multifacetted InGaN/GaN MQW LED chip evolves three distinct emission peaks around 630, 530, and 450 nm in electroluminescence (EL) as injection current increases from 1 to 100 mA. The EL behavior originates from locally different facets of the complex 3D structure: MQWs grown on c‐planes and semipolar facets, respectively, which is confirmed by cathodoluminescence characterization in a scanning transmission electron microscope (STEM‐CL). Considering the dependence of emission wavelength and intensity on injection currents, a programmable power supply is designed to drive the LED. The specific color of the LED is tuned by time‐shared driving of the currents based on three channels with controllable magnitudes and duty cycle from the power supply, covering red, yellow, green, cyan, blue, and purple. Furthermore, white LEDs with high color rendering index (CRI) up to 96.1 and correlated color temperature (CCT) between 4000 and 10 000 K are achieved.
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 | 0.000 | 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 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".