Bright high-colour-purity deep-blue carbon dot light-emitting diodes via efficient edge amination

Fanglong Yuan, Ya-Kun Wang, Geetu Sharma, Yitong Dong, Xiaopeng Zheng, Peicheng Li, Andrew K. Johnston, Golam Bappi, James Z. Fan, Hao Kung, Bin Chen, Makhsud I. Saidaminov, Kamalpreet Singh, Oleksandr Voznyy, Osman Bakr, Zhenghong Lu, E. Sargent

Research output: Contribution to journalArticlepeer-review

316 Scopus citations


Deep-blue light-emitting diodes (LEDs) (emitting at wavelengths of less than 450 nm) are important for solid-state lighting, vivid displays and high-density information storage. Colloidal quantum dots, typically based on heavy metals such as cadmium and lead, are promising candidates for deep-blue LEDs, but these have so far had external quantum efficiencies lower than 1.7%. Here we present deep-blue light-emitting materials and devices based on carbon dots. The carbon dots produce emission with a narrow full-width at half-maximum (about 35 nm) with high photoluminescence quantum yield (70% ± 10%) and a colour coordinate (0.15, 0.05) closely approaching the standard colour Rec. 2020 (0.131, 0.046) specification. Structural and optical characterization, together with computational studies, reveal that amine-based passivation accounts for the efficient and high-colour-purity emission. Deep-blue LEDs based on these carbon dots display high performance with a maximum luminance of 5,240 cd m−2 and an external quantum efficiency of 4%, notably exceeding that of previously reported quantum-tuned solution-processed deep-blue LEDs.
Original languageEnglish (US)
Pages (from-to)171-176
Number of pages6
JournalNature Photonics
Issue number3
StatePublished - Dec 9 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work is supported by Tier 1 Canada Research Chair in Organic Optoelectronics (grant number 950-220944), the Natural Sciences and Engineering Research Council of Canada (NSERC, grant number 216956-12), and the National Natural Science Foundation of China (grant number 11774304). E.H.S. and all coauthors from the Department of Electrical and Computer Engineering at the University of Toronto acknowledge financial support from the Ontario Research Fund−Research Excellence Program and from the Natural Sciences and Engineering Research Council of Canada (NSERC). M.I.S. acknowledges the support of the Banting Postdoctoral Fellowship Program, administered by the Government of Canada. Computations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by the Canada Foundation for Innovation; the Government of Ontario; Ontario Research Fund-Research Excellence; and the University of Toronto.


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