Optimization of Doping Concentration to Obtain High Internal Quantum Efficiency and Wavelength Stability in An InGaN/GaN Blue Light-Emitting Diode
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Bibliographic record
Abstract
We conduct a comprehensive study to investigate the feasibility of achieving high internal quantum efficiency (IQE) and wavelength stability in an InGaN/GaN blue light-emitting diode (LED) through numerical simulations with different doping concentrations. To ensure accurate calculations, we emulated the structure of an LED, fabricated on freestanding GaN with low defect density, abrupt interfaces, and high-performing characteristics, which resemble ideal conditions. Our objective is to determine the optimal doping concentration of the claddings using the Quantum Drift-Diffusion (QDD) model. We tested three concentrations ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="italic">low</mml:mi> </mml:mrow> </mml:msub> <mml:mo>,</mml:mo> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="italic">middle</mml:mi> </mml:mrow> </mml:msub> <mml:mo>,</mml:mo> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>h</mml:mi> <mml:mi mathvariant="italic">ig</mml:mi> <mml:mi>h</mml:mi> </mml:mrow> </mml:msub> </mml:math> ), and found that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="italic">middle</mml:mi> </mml:mrow> </mml:msub> </mml:math> produced the highest IQE of 82.5%, the most stable wavelength <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mrow> <mml:mi>λ</mml:mi> </mml:mrow> <mml:mo>ˆ</mml:mo> </mml:mover> <mml:mo>=</mml:mo> <mml:mrow> <mml:mfenced close=")" open="("> <mml:mrow> <mml:mn>457.0</mml:mn> <mml:mo>±</mml:mo> <mml:mn>1.2</mml:mn> </mml:mrow> </mml:mfenced> </mml:mrow> <mml:mspace width="1em"/> <mml:mi mathvariant="normal">nm</mml:mi> </mml:math> in the range of (0.08–63.25) mA, an optical power of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="double-struck">P</mml:mi> <mml:mo>=</mml:mo> <mml:mn>14.76</mml:mn> </mml:math> mWs −1 , and a forward voltage of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>V</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="italic">middle</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:mn>3.81</mml:mn> </mml:math> V at 20 mA. We suggest that using this concentration leads to the parameters closest to those of the reference device.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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