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 10⁶ and a retention time exceeding 2.0 × 10⁵ 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.

Keywords

covalent organic frameworks / high-performance / memristors / neuromorphic computing / one-dimensional nanochannels

References

[1] Z. Lv, Y. Wang, J. Chen, J. Wang, Y. Zhou, and S. T. Han, “Semiconductor Quantum Dots for Memories and Neuromorphic Computing Systems,” Chemical Reviews 120, no. 9 (2020): 3941-4006.

[2] S. Gao, X. Yi, J. Shang, G. Liu, and R. W. Li, “Organic and Hybrid Resistive Switching Materials and Devices,” Chemical Society Reviews 48, no. 6 (2019): 1531-1565.

[3] A. Sebastian, M. Le Gallo, R. Khaddam-Aljameh, and E. Eleftheriou, “Memory Devices and Applications for In-Memory Computing,” Nature Nanotechnology 15, no. 7 (2020): 529-544.

[4] H. Bian, Y. Y. Goh, Y. Liu, H. Ling, L. Xie, and X. Liu, “Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing,” Advanced Materials 33, no. 46 (2021): 2006469.

[5] P. Yao, H. Wu, B. Gao, et al., “Fully Hardware-Implemented Memristor Convolutional Neural Network,” Nature 577, no. 7792 (2020): 641-646.

[6] K. Roy, A. Jaiswal, and P. Panda, “Towards Spike-Based Machine Intelligence With Neuromorphic Computing,” Nature 575, no. 7784 (2019): 607-617.

[7] L. Q. Zhu, C. J. Wan, L. Q. Guo, Y. Shi, and Q. Wan, “Artificial Synapse Network on Inorganic Proton Conductor for Neuromorphic Systems,” Nature Communications 5, no. 1 (2014): 3158.

[8] L. Chua, “Memristor-the Missing Circuit Element,” IEEE Transactions on Circuit Theory 18, no. 5 (1971): 507-519.

[9] D. B. Strukov, G. S. Snider, D. R. Stewart, and R. S. Williams, “The Missing Memristor Found,” Nature 453, no. 7191 (2008): 80-83.

[10] M. Prezioso, F. Merrikh-Bayat, B. D. Hoskins, G. C. Adam, K. K. Likharev, and D. B. Strukov, “Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors,” Nature 521, no. 7550 (2015): 61-64.

[11] K. Sun, J. Chen, and X. Yan, “The Future of Memristors: Materials Engineering and Neural Networks,” Advanced Functional Materials 31, no. 8 (2021): 2006773.

[12] Y. Li, Y. Xiong, B. Zhai, et al., “Ag-Doped Non-Imperfection-Enabled Uniform Memristive Neuromorphic Device Based on van der Waals Indium Phosphorus Sulfide,” Science Advances 10, no. 11 (2024): eadk9474.

[13] M. Li, H. Liu, R. Zhao, et al., “Imperfection-Enabled Memristive Switching in van der Waals Materials,” Nature Electronics 6, no. 7 (2023): 491-505.

[14] Z. Li, Z. Li, W. Tang, et al., “Crossmodal Sensory Neurons Based on High-Performance Flexible Memristors for Human-Machine In-Sensor Computing System,” Nature Communications 15, no. 1 (2024): 7275.

[15] W. Zhang, P. Yao, B. Gao, et al., “Edge Learning Using a Fully Integrated Neuro-Inspired Memristor Chip,” Science 381, no. 6663 (2023): 1205-1211.

[16] T. Zhang, L. Wang, W. Ding, et al., “Rationally Designing High-Performance Versatile Organic Memristors Through Molecule-Mediated Ion Movements,” Advanced Materials 35, no. 40 (2023): 2302863.

[17] P. K. Zhou, Y. Li, T. Zeng, et al., “One-Dimensional Covalent Organic Framework-Based Multilevel Memristors for Neuromorphic Computing,” Angewandte Chemie International Edition 63, no. 20 (2024): e202402911.

[18] K. Zhou, Z. Jia, Y. Zhou, et al., “Covalent Organic Frameworks for Neuromorphic Devices,” Journal of Physical Chemistry Letters 14, no. 32 (2023): 7173-7192.

[19] P. K. Zhou, X. L. Lin, M. Y. Chee, et al., “Switching the Memory Behaviour From Binary to Ternary by Triggering S₆^2- Relaxation in Polysulfide-Bearing Zinc-Organic Complex Molecular Memories,” Materials Horizons 10, no. 7 (2023): 2535-2541.

[20] P. K. Zhou, H. Yu, W. Huang, et al., “Photoelectric Multilevel Memory Device Based on Covalent Organic Polymer Film With Keto-Enol Tautomerism for Harsh Environments Applications,” Advanced Functional Materials 34, no. 1 (2024): 2306593.

[21] A. P. Côté, A. I. Benin, N. W. Ockwig, M. O'Keeffe, A. J. Matzger, and O. M. Yaghi, “Porous, Crystalline, Covalent Organic Frameworks,” Science 310, no. 5751 (2005): 1166-1170.

[22] Y. Liu, X. Liu, A. Su, et al., “Revolutionizing the Structural Design and Determination of Covalent-Organic Frameworks: Principles, Methods, and Techniques,” Chemical Society Reviews 53, no. 1 (2024): 502-544.

[23] K. T. Tan, S. Ghosh, Z. Wang, et al., “Covalent Organic Frameworks,” Nature Reviews Methods Primers 3, no. 1 (2023): 1.

[24] D. N. Ampong, E. Effah, E. A. Tsiwah, et al., “Advances and Challenges in Covalent Organic Frameworks as an Emerging Class of Materials for Energy and Environmental Concerns,” Coordination Chemistry Reviews 519 (2024): 216121.

[25] R. Liu, K. T. Tan, Y. Gong, et al., “Covalent Organic Frameworks: An Ideal Platform for Designing Ordered Materials and Advanced Applications,” Chemical Society Reviews 50, no. 1 (2021): 120-242.

[26] T. Li, H. Yu, Z. Xiong, Z. Gao, Y. Zhou, and S. T. Han, “2D Oriented Covalent Organic Frameworks for Alcohol-Sensory Synapses,” Materials Horizons 8, no. 7 (2021): 2041-2049.

[27] J. Liu, F. Yang, L. Cao, et al., “A Robust Nonvolatile Resistive Memory Device Based on a Freestanding Ultrathin 2D Imine Polymer Film,” Advanced Materials 31, no. 28 (2019): 1902264.

[28] L. Liu, B. Geng, W. Ji, L. Wu, S. Lei, and W. Hu, “A Highly Crystalline Single Layer 2D Polymer for Low Variability and Excellent Scalability Molecular Memristors,” Advanced Materials 35, no. 6 (2023): 2208377.

[29] B. Sun, X. Li, T. Feng, et al., “Resistive Switching Memory Performance of Two-Dimensional Polyimide Covalent Organic Framework Films,” ACS Applied Materials & Interfaces 12, no. 46 (2020): 51837-51845.

[30] Z. Zhao, M. E. El-Khouly, Q. Che, et al., “Redox-Active Azulene-Based 2D Conjugated Covalent Organic Framework for Organic Memristors,” Angewandte Chemie International Edition 62, no. 7 (2023): e202217249.

[31] C. Li, D. Li, W. Zhang, H. Li, and G. Yu, “Towards High-Performance Resistive Switching Behavior Through Embedding a D-A System Into 2D Imine-Linked Covalent Organic Frameworks,” Angewandte Chemie 133, no. 52 (2021): 27341-27349.

[32] D. Wu, Q. Zhang, N. Gu, et al., “Improved Resistive Switching Performance Through Donor-Acceptor Structure Construction in Memristors Based on Covalent Organic Framework Films,” Journal of Materials Chemistry C 11, no. 47 (2023): 16672-16678.

[33] D. Wu, Q. Che, H. He, et al., “Room-Temperature Interfacial Synthesis of Vinylene-Bridged Two-Dimensional Covalent Organic Framework Thin Film for Nonvolatile Memory,” ACS Materials Letters 5, no. 3 (2023): 874-883.

[34] Z. Xu, Y. Li, Y. Xia, et al., “Organic Frameworks Memristor: An Emerging Candidate for Data Storage, Artificial Synapse, and Neuromorphic Device,” Advanced Functional Materials 34, no. 16 (2024): 2312658.

[35] K. Wang, H. Yang, Z. Liao, et al., “Monolayer-Assisted Surface-Initiated Schiff-Base-Mediated Aldol Polycondensation for the Synthesis of Crystalline Sp² Carbon-Conjugated Covalent Organic Framework Thin Films,” Journal of the American Chemical Society 145, no. 9 (2023): 5203-5210.

[36] L. Liu, L. Yin, D. Cheng, et al., “Surface-Mediated Construction of an Ultrathin Free-Standing Covalent Organic Framework Membrane for Efficient Proton Conduction,” Angewandte Chemie 133, no. 27 (2021): 15001-15006.

[37] T. Liu, Y. Zhang, Z. Shan, et al., “Covalent Organic Framework Membrane for Efficient Removal of Emerging Trace Organic Contaminants From Water,” Nature Water 1, no. 12 (2023): 1059-1067.

[38] Q. Hao, Z. J. Li, C. Lu, et al., “Oriented Two-Dimensional Covalent Organic Framework Films for Near-Infrared Electrochromic Application,” Journal of the American Chemical Society 141, no. 50 (2019): 19831-19838.

[39] Y. Liu, Y. Wu, B. Wang, et al., “Versatile Memristor Implemented in van der Waals CuInP₂S₆,” Nano Research 16, no. 7 (2023): 10191-10197.

[40] S. S. Teja Nibhanupudi, A. Roy, D. Veksler, et al., “Ultra-Fast Switching Memristors Based on Two-Dimensional Materials,” Nature Communications 15, no. 1 (2024): 2334.

[41] G. Zhang, J. Qin, Y. Zhang, et al., “Functional Materials for Memristor-Based Reservoir Computing: Dynamics and Applications,” Advanced Functional Materials 33, no. 42 (2023): 2302929.

[42] X. F. Lu, Y. Zhang, N. Wang, et al., “Exploring Low Power and Ultrafast Memristor on p-Type van der Waals SnS,” Nano Letters 21, no. 20 (2021): 8800-8807.

[43] Z. Wang, S. Joshi, S. Savel'Ev, et al., “Fully Memristive Neural Networks for Pattern Classification With Unsupervised Learning,” Nature Electronics 1, no. 2 (2018): 137-145.

[44] H. Tian, Q. Guo, Y. Xie, et al. Anisotropic Black Phosphorus Synaptic Device for Neuromorphic Applications, ahead of print, March 13, 2016, https://doi.org/10.48550/arXiv.1603.03988.

[45] J. Bian, Z. Cao, and P. Zhou, “Neuromorphic Computing: Devices, Hardware, and System Application Facilitated by Two-Dimensional Materials,” Applied Physics Reviews 8, no. 4 (2021): 041313.

[46] D. M. Bannerman, R. Sprengel, D. J. Sanderson, et al., “Hippocampal Synaptic Plasticity, Spatial Memory and Anxiety,” Nature Reviews Neuroscience 15, no. 3 (2014): 181-192.

[47] L. Gao, P. Y. Chen, and S. Yu, “Programming Protocol Optimization for Analog Weight Tuning in Resistive Memories,” IEEE Electron Device Letters 36, no. 11 (2015): 1157-1159.

[48] S. Yu, “Neuro-Inspired Computing With Emerging Nonvolatile Memorys,” Proceedings of the IEEE 106, no. 2 (2018): 260-285.

RIGHTS & PERMISSIONS

2025 The Author(s). Interdisciplinary Materials published by Wuhan University of Technology and John Wiley & Sons Australia, Ltd.