神经形态工程学
记忆电阻器
可扩展性
纳米技术
计算机科学
电阻随机存取存储器
电子线路
电阻器
离子键合
材料科学
纳米尺度
制作
电压
电气工程
人工神经网络
离子
工程类
物理
人工智能
病理
数据库
医学
量子力学
替代医学
作者
Theo Emmerich,Yunfei Teng,Nathan Ronceray,Edoardo Lopriore,R. Chiesa,Andrey Chernev,В. Г. Артемов,Massimiliano Di Ventra,András Kis,Aleksandra Radenović
出处
期刊:Cornell University - arXiv
日期:2023-01-01
被引量:1
标识
DOI:10.48550/arxiv.2306.07617
摘要
While most neuromorphic systems are based on nanoscale electronic devices, nature relies on ions for energy-efficient information processing. Therefore, finding memristive nanofluidic devices is a milestone toward realizing electrolytic computers mimicking the brain down to its basic principles of operation. Here, we present a nanofluidic device designed for circuit scale in-memory processing that combines single-digit nanometric confinement and large entrance asymmetry. Our fabrication process is scalable while the device operates at the second timescale with a conductance ratio in the range 10-60. In-operando optical microscopy unveils the origin of memory, arising from the reversible formation of liquid blisters modulating the device conductance. The combination of features of these mechano-ionic memristive switches permits assembling logic circuits composed of two interactive devices and an ohmic resistor. These results open the way to design multi-component ionic machinery, such as nanofluidic neural networks, and implementing brain-inspired ionic computations.
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