Synaptic Feature of Quantum Dot Light-Emitting Diodes for Visualization of Learning Process

Menglin Li, Jia Peng, Yuyu Jing, Yiran Yan, Cheng Wang, Wenjun Hou, Weiran Cao, Shuangpeng Wang, Haizheng Zhong*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Brain-inspired electronics with synaptic functions hold significant promise for advancing artificial intelligent applications. In this study, we demonstrate the synaptic feature of quantum-dot light-emitting diodes (QLEDs), which can convert electrical pulses into synapse-like light signals (the brightness gradually increases as the electrical pulses are prolonged). These features are analogous to learning and forgetting in biological synapses. The enhancement of brightness can be attributed to the reduction of charge transfer from the quantum dots to ZnO electron transport layer and resistive switching effect. With an integrated complementary metal-oxide-semiconductor (CMOS) drive, arrayed synaptic QLEDs can simulate the visualization of brain-like learning processes, which can reduce the noise toward high image recognition rate (>95.0%) by deep neural networks. Our findings introduce a novel brain-inspired optoelectronic approach with potential applications in optical neuromorphic systems.

Original languageEnglish
Pages (from-to)10334-10340
Number of pages7
JournalJournal of Physical Chemistry Letters
Volume15
Issue number41
DOIs
Publication statusPublished - 17 Oct 2024
Externally publishedYes

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