Significant Lifetime Enhancement in QLEDs by Reducing Interfacial Charge Accumulation via Fluorine Incorporation in the ZnO Electron Transport Layer
Bibliographic record
Abstract
Abstract ZnO nanoparticles are widely used for the electron transport layers (ETLs) of quantum dots light emitting devices (QLEDs). In this work we show that incorporating fluorine (F) into the ZnO ETL results in significant enhancement in device electroluminescence stability, leading to LT50 at 100 cd m−2 of 2,370,000 h in red QLED, 47X longer than the control devices. X-ray photo-electron spectroscopy, time-of-flight secondary ion mass spectroscopy, photoluminescence and electrical measurements show that the F passivates oxygen vacancies and reduces electron traps in ZnO. Transient photoluminescence versus bias measurements and capacitance–voltage-luminance measurements reveal that the CF4 plasma-treated ETLs lead to increased electron concentration in the QD and the QD/hole transport layer interface, subsequently decreasing hole accumulation, and hence the higher stability. The findings provide new insights into the critical roles that optimizing charge distribution across the layers play in influencing stability and present a novel and simple approach for extending QLED lifetimes.
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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".