Suppr超能文献

高效无镉倒置红色量子点发光二极管。

Efficient Cadmium-Free Inverted Red Quantum Dot Light-Emitting Diodes.

机构信息

Department of Information Display , Kyung Hee University , 26, Kyungheedae-ro , Dongdaemoon-gu, Seoul 02447 , Republic of Korea.

Research and Development Team, Visual Display , Samsung Electronics Co., Ltd , 129, Samsung-ro , Yeongtong-gu, Suwon 16677 , Republic of Korea.

出版信息

ACS Appl Mater Interfaces. 2019 Oct 9;11(40):36917-36924. doi: 10.1021/acsami.9b12514. Epub 2019 Sep 27.

Abstract

Here, we report an efficient inverted red indium phosphide (InP) comprising QD (InP/ZnSe/ZnS, core/shell structure) light-emitting diode (QLED) by modulating an interfacial contact between the electron transport layer and emissive InP-QDs and applying self-aging approach. The red InP-QLED with optimized interfacial contact exhibits a significant improvement in maximum external quantum efficiency and current efficiency from 4.42 to 10.2% and 4.70 to 10.8 cd/A, respectively, after 69 days of self-aging, which is an almost 2.3-fold improvement compared to the fresh device. The analysis indicates the consecutive reduction in electron injection and accumulation in the emissive QD due to changes in the conduction band minimum of ZnMgO (0.1 eV after 10 days of storage) through a downward vacuum-level shift according to the aging times. During the device aging periods, the oxygen vacancy of ZnMgO reduces, which leads to lower the conductivity of ZnMgO. As a result, charge balance of the device is improved with the suppression of exciton quenching at the interface of ZnMgO and InP-QD.

摘要

在这里,我们通过调节电子传输层和发射 InP-QD 之间的界面接触,并采用自老化方法,报道了一种高效的倒置红色铟磷(InP),包括量子点(InP/ZnSe/ZnS,核/壳结构)发光二极管(QLED)。经过 69 天的自老化,优化了界面接触的红色 InP-QLED 在最大外量子效率和电流效率方面分别从 4.42%和 4.70 cd/A 显著提高到 10.2%和 10.8 cd/A,与新鲜器件相比,提高了近 2.3 倍。分析表明,由于根据老化时间的不同,导带最小值(储存 10 天后为 0.1 eV)的向下真空能级移动,导致电子在发射量子点中的注入和积累连续减少。在器件老化过程中,ZnMgO 的氧空位减少,导致 ZnMgO 的电导率降低。因此,随着 ZnMgO 和 InP-QD 界面处激子猝灭的抑制,器件的电荷平衡得到改善。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验