神经形态工程学
可扩展性
材料科学
计算机科学
冯·诺依曼建筑
瓶颈
人工神经网络
突触
记忆电阻器
MNIST数据库
晶体管
长时程增强
抑制性突触后电位
突触后电位
计算
人工智能
能量(信号处理)
高效能源利用
尖峰神经网络
光电子学
等离子体子
CMOS芯片
计算机体系结构
内存处理
纳米技术
神经科学
突触重量
光电流
混合动力系统
纳米电子学
电子工程
突触可塑性
自然计算
对偶(语法数字)
生物电子学
作者
Kun Lv,Ping Chen,Yanjie Kong,Yuehua Chen,Ni Zhang,Haowen Tang,Xiaofeng Liu,Yanqi Gu,Xi Zhang,Caofeng Pan
标识
DOI:10.1002/adfm.202531919
摘要
ABSTRACT As the bottleneck of energy efficiency associated with the separation of storage and computation in the von Neumann architecture becomes increasingly restrictive, brain‐inspired electronic devices based on 2D materials are emerging as promising candidates for next‐generation information processing. Here, a top‐gate tri‐terminal optoelectronic synapse based on 2D NbOI 2 is demonstrated. Stable inhibitory postsynaptic current (IPSC) modulation and paired‐pulse depression (PPD) behaviors are successfully emulated for the first time in NbOI 2 devices. The device achieves an ultralow single‐spike energy consumption, comparable to that of natural biological synapses (∼10 fJ). Under hybrid optical‐electrical stimulation, it exhibits long‐term potentiation and depression (LTP/LTD), showing versatile synaptic plasticity. An artificial neural network constructed using its synaptic properties achieves classification accuracies of 93.61% and 84.57% on the MNIST and Fashion‐MNIST datasets, respectively. Furthermore, a closed‐loop human‐machine interaction system inspired by the vision‐neural‐motor pathway is established by exploiting the accumulative photocurrent memory of NbOI 2 synapses. Multi‐channel robotic arm control is also realized, highlighting the scalability of NbOI 2 optoelectronic synapses for complex collaborative tasks. This work demonstrates the dual potential of NbOI 2 optoelectronic synapses in neuromorphic computing and intelligent human‐machine interaction, offering insights for the development of energy‐efficient brain‐inspired electronics.
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