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用于神经形态器件的共价有机框架

Covalent Organic Frameworks for Neuromorphic Devices.

作者信息

Zhou Kui, Jia Ziqi, Zhou Yao, Ding Guanglong, Ma Xin-Qi, Niu Wenbiao, Han Su-Ting, Zhao Jiyu, Zhou Ye

机构信息

Institute for Advanced Study, Shenzhen University, 3688 Nanhai Avenue, Shenzhen 518060, P. R. China.

College of Materials Science and Engineering, Shenzhen University, 3688 Nanhai Avenue, Shenzhen 518060, P. R. China.

出版信息

J Phys Chem Lett. 2023 Aug 17;14(32):7173-7192. doi: 10.1021/acs.jpclett.3c01711. Epub 2023 Aug 4.

Abstract

Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices. Covalent organic frameworks (COFs), as crystalline porous polymers, have tailorable skeletons and pores, providing unique platforms for the interplay with photons, excitons, electrons, holes, ions, spins, and molecules. Such features encourage the rising research interest in COF materials in neuromorphic electronics. To develop high-performance COF-based neuromorphic memory devices, it is necessary to comprehensively understand materials, devices, and applications. Therefore, this Perspective focuses on discussing the use of COF materials for neuromorphic memory devices in terms of molecular design, thin-film processing, and neuromorphic applications. Finally, we provide an outlook for future directions and potential applications of COF-based neuromorphic electronics.

摘要

神经形态计算有可能突破传统冯·诺依曼架构的固有局限,这引发了人们对开发新型神经形态存储器件(如忆阻器和受生物启发的人工突触器件)的广泛研究兴趣。共价有机框架(COF)作为结晶多孔聚合物,具有可定制的骨架和孔隙,为与光子、激子、电子、空穴、离子、自旋和分子的相互作用提供了独特平台。这些特性激发了神经形态电子学领域对COF材料日益增长的研究兴趣。为了开发高性能的基于COF的神经形态存储器件,有必要全面了解材料、器件和应用。因此,本综述着重从分子设计、薄膜加工和神经形态应用等方面讨论COF材料在神经形态存储器件中的应用。最后,我们展望了基于COF的神经形态电子学的未来发展方向和潜在应用。

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