神经形态工程学
离子通道
记忆电阻器
材料科学
突触
纳米技术
可扩展性
频道(广播)
膜
短杆菌肽
计算机科学
内容寻址存储器
离子
信息处理
能量(信号处理)
脂质双层
人工神经网络
突触重量
仿生学
膜计算
超大规模集成
Spike(软件开发)
计算机体系结构
纳米器件
高效能源利用
作者
Zhongwu Li,Jiachen Feng,Jingyi Xiao,Anton Leuski,Aleksandr Noy
标识
DOI:10.1002/adma.202519525
摘要
The human brain performs complex memory and computational tasks with high energy efficiency by regulating ion transport through membrane channels. These signaling mechanisms have been inspiring the development of nanofluidic memristors that emulate synaptic behavior. Here, we describe a membrane ion channel synapse (MICS), constructed from aqueous droplets linked by gramicidin A channels, that achieves neuromorphic functionality. MICS exhibits memristive ion transport with hysteretic current-voltage behavior arising from voltage-dependent channel formation and ion transport dynamics. MICS emulates a range of synaptic behaviors including associative learning. We further demonstrate its application in reservoir computing by performing handwritten digit classification and tic-tac-toe game and explore the system parameters that improve the computational performance. This droplet-based biomimetic synapse offers a potentially scalable and energy-efficient platform for next-generation neuromorphic computing systems.
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