High-efficiency perovskite–polymer bulk heterostructure light-emitting diodes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-11-05

AUTHORS

Baodan Zhao, Sai Bai, Vincent Kim, Robin Lamboll, Ravichandran Shivanna, Florian Auras, Johannes M. Richter, Le Yang, Linjie Dai, Mejd Alsari, Xiao-Jian She, Lusheng Liang, Jiangbin Zhang, Samuele Lilliu, Peng Gao, Henry J. Snaith, Jianpu Wang, Neil C. Greenham, Richard H. Friend, Dawei Di

ABSTRACT

Perovskite-based optoelectronic devices are gaining much attention owing to their remarkable performance and low processing cost, particularly for solar cells. However, for perovskite light-emitting diodes, non-radiative charge recombination has limited the electroluminescence efficiency. Here we demonstrate perovskite–polymer bulk heterostructure light-emitting diodes exhibiting external quantum efficiencies of up to 20.1% (at current densities of 0.1–1 mA cm−2). The light-emitting diode emissive layer comprises quasi-two-dimensional and three-dimensional (2D/3D) perovskites and an insulating polymer. Photogenerated excitations migrate from quasi-2D to lower-energy sites within 1 ps, followed by radiative bimolecular recombination in the 3D regions. From near-unity external photoluminescence quantum efficiencies and transient kinetics of the emissive layer with and without charge-transport contacts, we find non-radiative recombination pathways to be effectively eliminated, consistent with optical models giving near 100% internal quantum efficiencies. Although the device brightness and stability (T50 = 46 h in air at peak external quantum efficiency) require further improvement, our results indicate the significant potential of perovskite-based photon sources. Near-infrared perovskite–polymer light-emitting diodes (LEDs) with external quantum efficiencies of up to 20.1% are reported. More... »

PAGES

1-7

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41566-018-0283-4

    DOI

    http://dx.doi.org/10.1038/s41566-018-0283-4

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    https://app.dimensions.ai/details/publication/pub.1107912952


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