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Efficient perovskite LEDs with tailored atomic layer number emission at fixed wavelengths.

Accepted version
Peer-reviewed

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Abstract

Colloidal quantum dots (QDs) have illuminated computer monitors and television screens due to their fascinating color-tunable properties depending on the size. Here, the electroluminescence (EL) wavelength of perovskite LEDs was tuned via the atomic layer number (ALN) of nanoplates (NPs) instead of the "size" in conventional QDs. We demonstrated efficient LEDs with controllably tailored emission from n = 3, 4, 5, and ≥7 ALN perovskite NPs with specific and discrete major peaks at 607, 638, 669, and 728 nanometers. These LEDs demonstrated peak external quantum efficiency (EQE) of 26.8% and high wavelength reproducibility with less than 1 to 2 nm difference between batches. High color stability without observable EL spectral change and operating stability with the best T50 of 267 minutes at 1.0 milliampere per square centimeter was also achieved. This work demonstrates a concept of tailoring specific ALN emission with fixed wavelengths, shedding light on efficient, emission-discrete, and color-stable LEDs for next-generation display.

Description

Journal Title

Sci Adv

Conference Name

Journal ISSN

2375-2548
2375-2548

Volume Title

Publisher

American Association for the Advancement of Science (AAAS)

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Except where otherwised noted, this item's license is described as Attribution 4.0 International
Sponsorship
Engineering and Physical Sciences Research Council (EP/M000524/1)
EPSRC (EP/V06164X/1)
Simons Foundation (601946)
European Research Council (756962)
Engineering and Physical Sciences Research Council (EP/R023980/1)
Engineering and Physical Sciences Research Council (EP/S030638/1)
European Commission Horizon 2020 (H2020) ERC (957513)
EPSRC (EP/T022159/1)
UK Research and Innovation (EP/Y029429/1)
L.W. received funding from the Royal Society (RS) of the United Kingdom under the Newton International Fellowship 2019 program (grant agreement No. NIF\R1\192347) hosted by the University of Cambridge. L.W. and R.H.F. acknowledge funding from EPSRC (grant No. EP/V06164X/1). We acknowledge support from the National Key Research and Development Program of China (Grant No. 2020YFB1506400, 2017YFA0206701), the National Natural Science Foundation of China (Grant No. 52125206, 51972004), and the Tencent Foundation through the XPLORER PRIZE. This work was also supported by the National Natural Science Foundation of China (Grant No. 22031002, 21771005, 21931001, and 21927901) and the Ministry of Science and Technology of China (2017YFA0205101 and 2017YFA0205104). L.D. acknowledges support from the European Research Council (ERC, European Union's Horizon 2020, PEROVSCI 957513). Yun Liu acknowledges the funding from the Simons Foundation (Grant 601946) and A*STAR under its Young Achiever Award. The calculations were performed using resources provided by the Cambridge Service for Data-Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the EPSRC (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). C.Z., B.Z. and D.D acknowledge the Zhejiang University Education Foundation Global Partnership Fund for support.

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