Controlling Electron Overflow in Phosphor-Free InGaN/GaN Nanowire White Light-Emitting Diodes
Bibliographic record
Abstract
We have investigated for the first time the impact of electron overflow on the performance of nanowire light-emitting diodes (LEDs) operating in the entire visible spectral range, wherein intrinsic white light emission is achieved from self-organized InGaN quantum dots embedded in defect-free GaN nanowires on a single chip. Through detailed temperature-dependent electroluminescence and simulation studies, it is revealed that electron leakage out of the device active region is primarily responsible for efficiency degradation in such nanowire devices, which in conjunction with the presence of nonradiative surface recombination largely determines the unique emission characteristics of nanowire light-emitting diodes. We have further demonstrated that electron overflow in nanowire LEDs can be effectively prevented with the incorporation of a p-doped AlGaN electron blocking layer, leading to the achievement of phosphor-free white light-emitting diodes that can exhibit for the first time virtually zero efficiency droop for injection currents up to ~2200 A/cm(2). This study also provides unambiguous evidence that Auger recombination is not the primary mechanism responsible for efficiency droop in GaN-based nanowire light-emitting diodes.
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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 | 0.001 |
| 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".