神经形态工程学
计算机科学
纳米技术
信号(编程语言)
电压
材料科学
漏斗
人工神经网络
磁滞
人工智能
电气工程
物理
机械工程
工程类
量子力学
程序设计语言
作者
Peiyue Li,Junjie Liu,Jun‐Hui Yuan,Yechang Guo,Shaofeng Wang,Pan Zhang,Wei Wang
出处
期刊:Nano Letters
[American Chemical Society]
日期:2024-04-26
卷期号:24 (20): 6192-6200
被引量:4
标识
DOI:10.1021/acs.nanolett.3c05079
摘要
Creating artificial synapses that can interact with biological neural systems is critical for developing advanced intelligent systems. However, there are still many difficulties, including device morphology and fluid selection. Based on Micro-Electro-Mechanical System technologies, we utilized two immiscible electrolytes to form a liquid/liquid interface at the tip of a funnel nanochannel, effectively enabling a wafer-level fabrication, interactions between multiple information carriers, and electron-to-chemical signal transitions. The distinctive ionic transport properties successfully achieved a hysteresis in ionic transport, resulting in adjustable multistage conductance gradient and synaptic functions. Notably, the device is similar to biological systems in terms of structure and signal carriers, especially for the low operating voltage (200 mV), which matches the biological neural potential (∼110 mV). This work lays the foundation for realizing the function of iontronics neuromorphic computing at ultralow operating voltages and in-memory computing, which can break the limits of information barriers for brain–machine interfaces.
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