神经形态工程学
材料科学
记忆电阻器
光电效应
光电子学
计算机科学
人工神经网络
锐化
光学计算
兴奋剂
逻辑门
冯·诺依曼建筑
纳米技术
电子工程
人工智能
工程类
算法
操作系统
作者
Mingjun Ma,Chaoning Huang,Jianghai Yang,Dong He,Yongfeng Pei,Yufan Kang,Wenqing Li,Cheng Lei,Xiang Xiao
出处
期刊:Small
[Wiley]
日期:2024-10-21
标识
DOI:10.1002/smll.202406402
摘要
Abstract Capitalizing on the extensive spectral capacity and minimal crosstalk properties inherent in optical signals, photoelectric synapses are poised to assume a pivotal stance in the realm of neuromorphic computation. Herein, a photoelectric synapse based on Lewis acid‐doped semiconducting tungsten diselenide (WSe 2 ) is introduced, exhibiting tunable short‐term and long‐term plasticity. The device consumes a mere 0.1 fJ per synaptic operation, which is lower than the energy required by a single synaptic event observed in the human brain. Furthermore, these devices demonstrate high‐pass filtering capabilities, highlighting their potential in image‐sharpening applications. In particular, by synergistically modulating the photoconductivity and electrical gate bias, versatile logic capabilities are demonstrated within a single device, enabling it to flexibly perform both Boolean AND and OR gate operations. This work demonstrates a viable approach for Lewis acid‐treated TMDs to realize multifunctional photoelectric synapses for neuromorphic computing.
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