Boosting Efficiency and Curtailing the Efficiency Roll-Off in Green Perovskite Light-Emitting Diodes via Incorporating Ytterbium as Cathode Interface Layer
Bibliographic record
Abstract
Perovskite light-emitting diodes (PeLEDs) exhibit high external quantum efficiencies (EQEs), emerging as a next-generation lighting and display technology. Nevertheless, they suffer from severe efficiency roll-off at high luminance, particularly in the case of blue and green emissions, which is one of the major bottlenecks in their industrial applications. Here, we attack this problem using a rare-earth metal, Yb, as cathode interface layer (CIL) for green PeLEDs. By adopting a new device configuration of ITO/TFB/FA-based quasi-2D perovskite/TPBi/Yb/Ag, we achieved a peak current efficiency (CE) of 22.3 cd/A with a corresponding EQE of 5.28% and a high maximum luminance of 19 160 cd/m2. Importantly, the maximum CE of 22.0 cd/A at 2000 cd/m2 slightly decreased to 16.8 cd/A at 5000 cd/m2 and maintained a still-decent value of 12.0 cd/A at a high luminance of 10 000 cd/m2, exhibiting a remarkably low efficiency roll-off. Our Yb-incorporated devices significantly outperformed the PeLEDs containing conventional CILs, including Mg and Liq, in terms of peak efficiency, efficiency roll-off, and operational lifetime. We attribute this encouraging performance to barrier-free, efficient electron injection enabled by the low work function of Yb (2.6 eV), which led to a high electron current, nearly approaching the hole current in hole-dominant PeLEDs, as confirmed by the single-carrier device measurements. In addition, we also present Yb-incorporated PeLEDs containing Cs-based quasi-2D perovskite as the emissive layer, which displayed an impressive CE of 51.3 cd/A with a corresponding EQE of 16.4% and a maximum luminance of 14 240 cd/m2, and still demonstrated a reduced efficiency roll-off comparing to that of the Liq-based equivalent. These results unveil the inspiring prospects of Yb as an efficient CIL for PeLEDs toward high efficiency with curtailed roll-off.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".