神经形态工程学
记忆电阻器
离子
选择性
纳米技术
材料科学
计算机科学
化学
物理
人工智能
电子工程
人工神经网络
工程类
量子力学
生物化学
催化作用
作者
Boyang Xie,Tianyi Xiong,Guang-Can Guo,Cong Pan,Wenjie Ma,Ping Yu
标识
DOI:10.1073/pnas.2417040122
摘要
The fluidic memristor has attracted growing attention as a promising candidate for neuromorphic computing and brain-computer interfaces. However, a fluidic memristor with ion selectivity as that of natural ion channels remains a key challenge. Herein, inspired by the structure of natural biomembranes, we developed an ion-shuttling memristor (ISM) by utilizing organic solvents and artificial carriers to emulate ion channels embedded in biomembranes, which exhibited both neuromorphic functions and ion selectivity. Pinched hysteresis I-V loop curve, scan rate dependency, and distinctive impedance spectra confirmed the memristive characteristics of the as-prepared device. Moreover, the memory mechanism was discussed theoretically and validated by finite-element modeling. The ISM features multiple neuromorphic functions, such as paired-pulse facilitation, paired-pulse depression, and learning-experience behavior. More importantly, the ion selectivity of the ISM was observed, which allowed further emulation of ion-selective neural functions like resting membrane potential. Benefiting from the structural similarity to membrane-embedded ion channels, the ISM opens the door for ion-based neuromorphic computing and sophisticated chemical regulation by manipulating multifarious ions with neuromorphic functions.
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