记忆电阻器
神经形态工程学
仿真
纳米技术
材料科学
计算机科学
平面的
张拉整体
人工神经网络
电气工程
工程类
人工智能
计算机图形学(图像)
土木工程
经济增长
经济
作者
Ziyu Lv,Xuechao Xing,Shenming Huang,Yan Wang,Zhonghui Chen,Yue Gong,Ye Zhou,Su‐Ting Han
出处
期刊:Matter
[Elsevier BV]
日期:2021-03-23
卷期号:4 (5): 1702-1719
被引量:41
标识
DOI:10.1016/j.matt.2021.02.018
摘要
Summary Memristive devices offer desirable voltage-regulated conductance switching and promise to address zettabyte storage challenges in the big-data era. Generally, most of these reported devices use amorphous solids, where the structural and compositional inhomogeneity is regarded as the origin of stochastic variability. Self-assembling peptide crystals with solution-processed fabrication, controllable morphologies, and structural stability are therefore a promising candidate to address the reliability issues. Here we report a planar diffusive memristor that possesses reliable switching characteristics based on a quasi-one-dimensional crystallized material: diphenylalanine (FF) microrod (MR). This element offers a preferential ion migration path, confining conductive filaments in a defined crystalline surface and therefore reducing programming stochasticity. Ion transport confinement along FF MR was observed via in situ electrostatic force microscopy technique. Additionally, FF MR memristor with high switching uniformity and reproducible relaxation dynamic provides an ideal hardware platform for reliable nociceptor emulation and hardware identification of four-bit decimal numbers.
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