量子点
可视化
光电子学
特征(语言学)
过程(计算)
发光二极管
计算机科学
二极管
材料科学
量子
人工智能
物理
量子力学
语言学
操作系统
哲学
作者
Menglin Li,Peng Jia,Yuyu Jing,Yiran Yan,Cheng Wang,Wenjun Hou,Weiran Cao,Shuangpeng Wang,Haizheng Zhong
标识
DOI:10.1021/acs.jpclett.4c02446
摘要
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.
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