材料科学
神经形态工程学
记忆电阻器
信号(编程语言)
人工神经网络
电压
偏压
离子键合
纳米技术
计算机科学
光电子学
电子工程
生物系统
离子
人工智能
电气工程
物理
生物
工程类
量子力学
程序设计语言
作者
Zhiyong Wang,Laiyuan Wang,Y. H. Wu,Linyi Bian,Masaru Nagai,Ruolin Jv,Linghai Xie,Haifeng Ling,Qi Li,Hongyu Bian,Moonsuk Yi,Nai Shi,Xiaogang Liu,Wei Huang
标识
DOI:10.1002/adma.202104370
摘要
Neural systems can selectively filter and memorize spatiotemporal information, thus enabling high-efficient information processing. Emulating such an exquisite biological process in electronic devices is of fundamental importance for developing neuromorphic architectures with efficient in situ edge/parallel computing, and probabilistic inference. Here a novel multifunctional memristor is proposed and demonstrated based on metalloporphyrin/oxide hybrid heterojunction, in which the metalloporphyrin layer allows for dual electronic/ionic transport. Benefiting from the coordination-assisted ionic diffusion, the device exhibits smooth, gradual conductive transitions. It is shown that the memristive characteristics of this hybrid system can be modulated by altering the metal center for desired metal-oxygen bonding energy and oxygen ions migration dynamics. The spike voltage-dependent plasticity stemming from the local/extended movement of oxygen ions under low/high voltage is identified, which permits potentiation and depression under unipolar different positive voltages. As a proof-of-concept demonstration, memristive arrays are further built to emulate the signal filtering function of the biological visual system. This work demonstrates the ionic intelligence feature of metalloporphyrin and paves the way for implementing efficient neural-signal analysis in neuromorphic hardware.
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