Over 30% External Quantum Efficiency Light‐Emitting Diodes by Engineering Quantum Dot‐Assisted Energy Level Match for Hole Transport Layer
Abstract
In the study of hybrid quantum dot light‐emitting diodes (QLEDs), even for state‐of‐the‐art achievement, there still exists a long‐standing charge balance problem, i.e., sufficient electron injection versus inefficient hole injection due to the large valence band offset of quantum dots (QDs) with respect to the adjacent carrier transport layer. Here the dedicated design and synthesis of high luminescence Zn1−x CdxSe/ZnSe/ZnS QDs is reported by precisely controlled shell growth, which have matched energy level with the adjacent hole transport layer in QLEDs. As emitters, such Zn1−xCdxSe‐ based QLEDs exhibit peak external quantum efficiencies (EQE) of up to 30.9%, maximum brightness of over 334 000 cd m−2, very low efficiency roll‐off at high current density (EQE ≈25% @ current density of 150 mA cm−2), and operational lifetime extended to ≈1 800 000 h at 100 cd m−2. These extraordinary performances make this work the best among all solution‐processed QLEDs reported in literature so far by achieving simultaneously high luminescence and balanced charge injection. These major advances are attributed to the combination of an intermediate ZnSe layer with an ultrathin ZnS outer layer as the shell materials and surface modification with 2‐ethylhexane‐1‐thiol, which can dramatically improve hole injection efficiency and thus lead to more balanced charge injection.
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.