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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/43293
Title: Perovskite energy funnels for efficient light-emitting diodes
Authors: Mingjian Yuan
Li Na Quan
Riccardo Comin
Grant Walters
Randy Sabatini
Oleksandr Voznyy
Sjoerd Hoogland
Yongbiao Zhao
Eric M. Beauregard
Pongsakorn Kanjanaboos
Zhenghong Lu
Dong Ha Kim
Edward H. Sargent
University of Toronto
Ewha Womans University
Mahidol University
Keywords: Chemical Engineering;Engineering;Materials Science
Issue Date: 1-Oct-2016
Citation: Nature Nanotechnology. Vol.11, No.10 (2016), 872-877
Abstract: © 2016 Macmillan Publishers Limited, part of Springer Nature. Organometal halide perovskites exhibit large bulk crystal domain sizes, rare traps, excellent mobilities and carriers that are free at room temperature - properties that support their excellent performance in charge-separating devices. In devices that rely on the forward injection of electrons and holes, such as light-emitting diodes (LEDs), excellent mobilities contribute to the efficient capture of non-equilibrium charge carriers by rare non-radiative centres. Moreover, the lack of bound excitons weakens the competition of desired radiative (over undesired non-radiative) recombination. Here we report a perovskite mixed material comprising a series of differently quantum-size-tuned grains that funnels photoexcitations to the lowest-bandgap light-emitter in the mixture. The materials function as charge carrier concentrators, ensuring that radiative recombination successfully outcompetes trapping and hence non-radiative recombination. We use the new material to build devices that exhibit an external quantum efficiency (EQE) of 8.8% and a radiance of 80W sr-1m-2. These represent the brightest and most efficient solution-processed near-infrared LEDs to date.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84976293881&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/43293
ISSN: 17483395
17483387
Appears in Collections:Scopus 2016-2017

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