Efficient Tandem Quantum‐Dot LEDs Enabled by An Inorganic Semiconductor‐Metal‐Dielectric Interconnecting Layer Stack
Bibliographic record
Abstract
Light-emitting diodes (LEDs) in a tandem configuration offer a strategy to realize high-performance, multicolor devices. Until now, though, the efficiency of tandem colloidal quantum dot LEDs (QLEDs) has been limited due to unpassivated interfaces and solvent damage originating from the materials processing requirements of interconnecting layers (ICLs). Here an ICL is reported consisting of a semiconductor-metal-dielectric stack that provides facile fabrication, materials stability, and good optoelectronic coupling. It is investigated experimentally how the ICL enables charge balance, suppresses current leakage, and prevents solvent damage to the underlying layers. As a result record efficiencies are reported for double-junction tandem QLEDs, whose emission wavelengths cover from blue to red light; i.e., external quantum efficiencies (EQEs) of 40% (average 37+/-2%) for red, 49% (average 45+/-2%) for yellow, 50% (average 46+/-2%) for green, and 24% (average 21+/-2%) for blue are achieved.
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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 | 0.001 | 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".