神经形态工程学
机制(生物学)
计算机科学
光电效应
对偶(语法数字)
突触
铅(地质)
材料科学
纳米技术
视网膜
神经科学
光电子学
人工神经网络
人工智能
物理
生物
古生物学
艺术
文学类
量子力学
作者
Zhenpeng Cheng,Tianle Wang,Junyan Zhu,Yaqi He,Shijie Liu,Mingyu Li,Haifei Lu,Xiaoyan Wen,Jihoon Lee,Sisi Liu,Mao Sui
出处
期刊:Small
[Wiley]
日期:2025-02-02
被引量:3
标识
DOI:10.1002/smll.202411129
摘要
Adaptive learning capability of optoelectronic synaptic hardware holds promising application prospects in next generation artificial intelligence, and the development of biometric retina perception is sternly hampered by three crucial issues, including well-balance between excitatory and inhibitory, non-volatile multi-state storage, and optimal energy consumption. In this work, a novel Cs2AgBiBr6/ZnO non-volatile optoelectronic synapse is proposed and successfully programmed with optical excitatory and electronic inhibitory in the light of dual-mechanism: Lead-free perovskite Cs2AgBiBr6 guarantees abundant photogenerated carrier concentration, and the process of carrier capture and release occurs in ZnO layer, which can collaboratively modulate various synaptic plasticity behaviors depending on distinct stimulus. Consequently, multi-bit storage is attained with the dual-mechanism non-volatile memory (DNVM) as a function of consecutive light spikes. The energy consumption of the DNVM is 1.85 nJ at a single light spike, and an ultra-low one of 13.8 fJ is triggered with a single electrical pulse, which approximatively meets the requirement of the biological synaptic event energy consumption. The performance of the DNVM is further evaluated with the Pavlov's classical conditioning experiment and visual hardware system, offering an exciting paradigm for implementing on-chip adaptive visual perception and neuromorphic computing.
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