Simulation for light power distribution of 3D InGaN/GaN MQW LED with textured surface
Bibliographic record
Abstract
In this paper, we introduce a full 3D simulation for light power distribution of an InGaN/GaN MQW LED with textured surface. Device simulation was performed by APSYS software to get power distribution of light source inside the LED. Based on this, ray tracing simulation was carried out to get light power distribution outside the LED. During the process of ray tracing, the textured surface was treated as a special boundary which means its reflectivity, transmittance and refraction angle are not calculated according to Fresnel equations, but obtained from data extracted from Finite-difference time-domain(FDTD) method. By comparing ray tracing result with and without textured surface, we found that textured surface not only smoothed transmitted power distribution, but also greatly improved power extraction efficiency which can be further improved by changing texture geometry.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".