Dual‐Phase Regulation for High‐Efficiency Perovskite Light‐Emitting Diodes
Bibliographic record
Abstract
Abstract Perovskite light‐emitting diodes (Pero‐LEDs) have attracted significant attention due to their high color purity and solution processing, presenting potential applications for next‐generation solid‐state lighting and displays. Continued materials development has shown that passivating non‐radiative defects can improve device performance. In theory, CsPbBr3&Cs4PbBr6 should be a model emitter for Pero‐LEDs, as its lattice matching provides ideal passivation and efficient exciton confinement. However, the low charge transport of Cs4PbBr6 has so far hindered device performance. Herein, a dual‐phase regulation method to grow a CsPbBr3&Cs4PbBr6 perovskite layer that enables efficient electrical injection is developed. This leads to the realization that Pero‐LEDs with a maximum EQE of 22.3% with a luminance of 10,050 cd m−2, and the devices show a T50 of 59 h at 130 cd m−2.
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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".