Dislocation and indium droplet related emission inhomogeneities in InGaN LEDs
Bibliographic record
Abstract
Abstract This report classifies emission inhomogeneities that manifest in InGaN quantum well blue light-emitting diodes grown by plasma-assisted molecular beam epitaxy on free-standing GaN substrates. By a combination of spatially resolved electroluminescence and cathodoluminescence measurements, atomic force microscopy, scanning electron microscopy and hot wet potassium hydroxide etching, the identified inhomogeneities are found to fall in four categories. Labeled here as type I through IV, they are distinguishable by their size, density, energy, intensity, radiative and electronic characteristics and chemical etch pits which correlates them with dislocations. Type I exhibits a blueshift of about 120 meV for the InGaN quantum well emission attributed to a perturbation of the active region, which is related to indium droplets that form on the surface in the metal-rich InGaN growth condition. Specifically, we attribute the blueshift to a decreased growth rate of and indium incorporation in the InGaN quantum wells underneath the droplet which is postulated to be the result of reduced incorporated N species due to increased N2 formation. The location of droplets are correlated with mixed type dislocations for type I defects. Types II through IV are due to screw dislocations, edge dislocations, and dislocation bunching, respectively, and form dark spots due to leakage current and nonradiative recombination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".