High‐Performance Memristors Based on Ordered Imine‐Linked Two‐Dimensional Covalent Organic Frameworks for Neuromorphic Computing

ABSTRACT Covalent organic frameworks (COFs) have emerged as highly promising materials for high‐performance memristors due to their exceptional stability, molecular design flexibility, and tunable pore structures. However, the development of COF memristors faces persistent challenges stemming from the structural disorder and quality control of COF films, which hinder the effective regulation of active metal ion migration during resistive switching. Herein, we report the synthesis of high‐quality, long‐range ordered, imine‐linked two‐dimensional (2D) COF TP‐TD film via the innovative surface‐initiated polymerization (SIP) strategy. The long‐range ordered one‐dimensional (1D) nanochannels within 2D COF TP‐TD film facilitate the stable and directed growth of conductive filaments (CFs), further enhanced by imine–CFs coordination effects. As a result, the fabricated memristor devices exhibit exceptional multilevel nonvolatile memory performance, achieving an ON/OFF ratio of up to 10 6 and a retention time exceeding 2.0 × 10 5 s, marking a significant breakthrough in porous organic polymer (POP) memristors. Furthermore, the memristors demonstrate high‐precision waveform data recognition with an accuracy of 92.17%, comparable to software‐based recognition systems, highlighting its potential in advanced signal processing tasks. This study establishes a robust foundation for the development of high‐performance COF memristors and significantly broadens their application potential in neuromorphic computing.

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Publication Details

Journal
Interdisciplinary materials
Published
2025-04-07
DOI
https://doi.org/10.1002/idm2.12244
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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High‐Performance Memristors Based on Ordered Imine‐Linked Two‐Dimensional Covalent Organic Frameworks for Neuromorphic Computing

Shikun Xiao, Jinsong Wu, Zhangjie Gu, Mengqi Wang et al.
2 citations
Interdisciplinary materials
Advanced Memory and Neural Computing
1.46
article

High‐Performance Memristors Based on Ordered Imine‐Linked Two‐Dimensional Covalent Organic Frameworks for Neuromorphic Computing

Shikun Xiao, Jinsong Wu, Zhangjie Gu, Mengqi Wang, Tianyou Zhai, L. Q. Qin, Yimeng Yu, Xiaodong Chi, Bailing Song, Decai Ouyang, Da Huo, Yuan Li, Huicong Li, Wenhua Hu
article en
2 citations

Abstract

ABSTRACT Covalent organic frameworks (COFs) have emerged as highly promising materials for high‐performance memristors due to their exceptional stability, molecular design flexibility, and tunable pore structures. However, the development of COF memristors faces persistent challenges stemming from the structural disorder and quality control of COF films, which hinder the effective regulation of active metal ion migration during resistive switching. Herein, we report the synthesis of high‐quality, long‐range ordered, imine‐linked two‐dimensional (2D) COF TP‐TD film via the innovative surface‐initiated polymerization (SIP) strategy. The long‐range ordered one‐dimensional (1D) nanochannels within 2D COF TP‐TD film facilitate the stable and directed growth of conductive filaments (CFs), further enhanced by imine–CFs coordination effects. As a result, the fabricated memristor devices exhibit exceptional multilevel nonvolatile memory performance, achieving an ON/OFF ratio of up to 10 6 and a retention time exceeding 2.0 × 10 5 s, marking a significant breakthrough in porous organic polymer (POP) memristors. Furthermore, the memristors demonstrate high‐precision waveform data recognition with an accuracy of 92.17%, comparable to software‐based recognition systems, highlighting its potential in advanced signal processing tasks. This study establishes a robust foundation for the development of high‐performance COF memristors and significantly broadens their application potential in neuromorphic computing.

Interdisciplinary materialsVol. 4(3)
Wuhan University of Technology (CN), Huazhong University of Science and Technology Hospital (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, Huazhong University of Science and Technology, Shenzhen Science and Technology Innovation Program
Openalex Percentile: Top 18%
Advanced Memory and Neural Computing
1.46
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