journal article·2023-08

Highly Reliable Textile‐Type Memristor by Designing Aligned Nanochannels

Yue Liu, Xufeng Zhou, Hui Yan, Xiang Shi, Ke Chen, Jinyang Zhou, Jialin Meng, Tianyu Wang, Yulu Ai, Jingxia Wu, Jiaxin Chen, Kaiwen Zeng, Lin Chen, Yahui Peng, Xuemei Sun, Peining Chen, Huisheng Peng

Advanced Materials· Volume 35· Issue 32
Publisher page

Abstract

Abstract Information‐processing devices are the core components of modern electronics. Integrating them into textiles is the indispensable demand for electronic textiles to form close‐loop functional systems. Memristors with crossbar configuration are regarded as promising building blocks to design woven information‐processing devices that seamlessly unify with textiles. However, the memristors always suffer from severe temporal and spatial variations due to the random growth of conductive filaments during filamentary switching processes. Here, inspired by the ion nanochannels across synaptic membranes, a highly reliable textile‐type memristor made of Pt/CuZnS memristive fiber with aligned nanochannels, showing small set voltage variation (<5.6%) under ultralow set voltage (≈0.089 V), high on/off ratio (≈106), and low power consumption (0.1 nW), is reported. Experimental evidence indicate that nanochannels with abundant active S defects can anchor silver ions and confine their migrations to form orderly and efficient conductive filaments. Such memristive performances enable the resultant textile‐type memristor array to have high device‐to‐device uniformity and process complex physiological data like brainwave signals with high recognition accuracy (95%). The textile‐type memristor arrays are mechanically durable to withstand hundreds of bending and sliding deformations, and seamlessly unified with sensing, power‐supplying, and displaying textiles/fibers to form all‐textile integrated electronic systems for new generation human‐machine interactions.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Photoreceptor and optogenetics research · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular Science and Laboratory of Advanced Materials Fudan University Shanghai 200438 China

School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China

State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai 200433 China

Department of Materials Science Fudan University Shanghai 200433 China

Funding

Science and Technology Commission of Shanghai Municipality · National Natural Science Foundation of China

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