Enhanced Performance of AlGaN-Based Deep Ultraviolet Light-Emitting Diodes with Chirped Superlattice Electron Deceleration Layer
Bibliographic record
Abstract
Abstract AlGaN-based deep ultraviolet (DUV) light-emitting diodes (LEDs) suffer from electron overflow and insufficient hole injection. In this paper, novel DUV LED structures with superlattice electron deceleration layer (SEDL) is proposed to decelerate the electrons injected to the active region and improve radiative recombination. The effects of several chirped SEDLs on the performance of DUV LEDs have been studied experimentally and numerically. The DUV LEDs have been grown by metal-organic chemical vapor deposition (MOCVD) and fabricated into 762 × 762 μm2chips, exhibiting single peak emission at 275 nm. The external quantum efficiency of 3.43% and operating voltage of 6.4 V are measured at a forward current of 40 mA, indicating that the wall-plug efficiency is 2.41% of the DUV LEDs with ascending Al-content chirped SEDL. The mechanism responsible for this improvement is investigated by theoretical simulations. The lifetime of the DUV LED with ascending Al-content chirped SEDL is measured to be over 10,000 h at L50, due to the carrier injection promotion.
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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 | 0.000 | 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".