神经形态工程学
电压
磁滞
材料科学
纳米技术
记忆电阻器
光电子学
能源景观
物理
凝聚态物理
计算机科学
人工神经网络
量子力学
热力学
机器学习
作者
De-Li Shi,Wenhui Wang,Yan Liang,Libing Duan,Guohao Du,Yanbo Xie
出处
期刊:Nano Letters
[American Chemical Society]
日期:2023-12-08
卷期号:23 (24): 11662-11668
标识
DOI:10.1021/acs.nanolett.3c03518
摘要
The emergence of nanofluidic memristors has made a giant leap to mimic the neuromorphic functions of biological neurons. Here, we report neuromorphic signaling using Angstrom-scale funnel-shaped channels with poly-l-lysine (PLL) assembled at nano-openings. We found frequency-dependent current–voltage characteristics under sweeping voltage, which represents a diode in low frequencies, but it showed pinched current hysteresis as frequency increases. The current hysteresis is strongly dependent on pH values but weakly dependent on salt concentration. We attributed the current hysteresis to the entropy barrier of PLL molecules entering and exiting the Angstrom channels, resulting in reversible voltage-gated open-close state transitions. We successfully emulated the synaptic adaptation of Hebbian learning using voltage spikes and obtained a minimum energy consumption of 2–23 fJ in each spike per channel. Our findings pave a new way to mimic neuronal functions by Angstrom channels in low energy consumption.
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