Covalent Organic Frameworks for Neuromorphic Devices

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.

Photoelectric Multilevel Memory Device based on Covalent Organic Polymer Film with Keto–Enol Tautomerism for Harsh Environments Applications

“…Moreover, the C═O peaks at ≈1617 cm −1 were merged with the C═C stretching band and appeared as a shoulder, indicating the coexistence of the two kinds of tautomers. [23,24] The formation of the Py-COP-3 was also unraveled by 13 C CP-MAS NMR (Figure 1b). Py-COP-3 showed distinctive signals at ≈184.6, 146.5, and 107.0 ppm, corresponding to the carbonyl (─C═O), the imine carbon (─C═N), and the enamine carbon (─C═C─N─), respectively, which is consistent with the reported 𝛽-ketoenamine-linked COFs.…”

“…The Py-COP-3 film was fabricated on a conductive ITO glass substrate in a mixed solvent of N,N-dimethylacetamide (DMAc) and o-dichlorobenzene (o-DCB) at 120 °C for 3 days (Scheme 1, for details, see the Supporting Information). These as-prepared films and bulk powders were then characterized by Fourier transform infrared (FT-IR), solid-state 13 C cross-polarization magic angle spinning NMR ( 13 C CP-MAS NMR), UV-visible (UV-vis) spectroscopy, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), powder X-ray diffraction (PXRD), transmission electron microscopy (TEM), N 2 sorption isotherms, scanning electron microscopy (SEM), and contact angle tests (Figure 1 and Figures S1-S10, Supporting Information). Features originating from the imine bonds (C═N) (1622 cm −1 ) in the FT-IR spectrum for Py-COP-0 evidence the occurrence of the Schiff base reaction (Figure S1, Supporting Information), which was further confirmed by the disappearance of the aldehyde (1664 cm −1 ) and amine (3352 cm −1 ) stretching signals.…”

“…Covalent organic polymers (COPs) thin films are promising memory materials owing to their excellent solution processability, light weight, outstanding uniformity, good stability, and mechanical flexibility. [12][13][14][15][16] COPs feature a well-defined structure through rational molecular design and can attain a clearer understanding of the switching mechanism through theoretical simulations, which have led to a widespread research boom in the field of resistive switch memory. In particular, the adjustment in the molecular skeleton or substituents can significantly alter the storage performance.…”

COF-Based Photocatalysts for Enhanced Synthesis of Hydrogen Peroxide

“…To date, reported linkages include boroxine [ 50 ], boronate-ester [ 51 , 52 , 53 ], imine [ 54 , 55 , 56 , 57 ], hydrazone [ 58 , 59 ], squaraine [ 60 , 61 , 62 ], azine [ 63 , 64 , 65 ], imide [ 66 , 67 ], C=C [ 68 , 69 , 70 , 71 ], 1,4-dioxin linkage [ 72 , 73 ], among others. The COFs synthesized by these methods have shown great potential in applications such as sensing [ 74 , 75 , 76 ], catalysis [ 5 , 77 , 78 , 79 ], energy storage and conversion, [ 6 , 80 , 81 , 82 , 83 ] organic electronic devices [ 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 ], etc. [ 6 , 80 , 81 , 82 , 83 , 93 , 94 , 95 …”

Definition of a Localized Conducting Path via Suppressed Charge Injection in Oxide Memristors for Stable Practical Hardware Neural Networks

“…Therefore, it is essential to develop a promising memory device with high integration density to achieve practical neural networks. , The mechanisms and applications of a resistive switching device known as a memristor have been studied using physical models and simulations . Such a device has been demonstrated as an ideal memory component for hardware neural networks from the perspectives of integration density and electrical characteristics. − Various types of memristors, such as a photonic memristor based on the phosphorene nanoparticles, an organic memristor, − a 2D material-based memristor, and an oxide-based memristor, , have been utilized as memory components in the neuromorphic systems. In particular, the oxide memristor has been evaluated as a promising option for artificial synapses in hardware neural networks due to its large scalability and high compatibility with the complementary metal oxide semiconductor. − For the oxide-based memristor, through the application of electric stimuli, a conducting filament (CF) composed of oxygen vacancies forms within an oxide-insulating film, leading to its resistive switching characteristics.…”