Optoelectronic dynamic memristor systems based on two-dimensional crystals

Panin, G. N.

doi:10.1016/j.chaos.2020.110523

Cited by 14 publications

(7 citation statements)

References 48 publications

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“…The device can be modulated by local QD excitation and shows the resistive switching in an electric field, as shown in figures 5(c)-(e). The Raman spectra demonstrate reversible photo-induced phase transition from 2H to 1T phase [56,211]. Furthermore, the phase change, controlled by the charges and temperature, generates tunable periodic oscillations with a chaotic behavior similar to what occurs in a biological neuron network [211], as reported by Panin et al They claimed the potential of their devices for further artificial neural networks.…”

Section: Two-terminal Devicessupporting

confidence: 53%

2D materials and van der Waals heterojunctions for neuromorphic computing

Zhang

Yang

et al. 2022

Neuromorph. Comput. Eng.

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Neuromorphic computing systems employing artificial synapses and neurons are expected to overcome the limitations of the present von Neumann computing architecture in terms of efficiency and bandwidth limits. Traditional neuromorphic devices have used 3D bulk materials, and thus, the resulting device size is difficult to be further scaled down for high density integration, which is required for highly integrated parallel computing. The emergence of two-dimensional (2D) materials offers a promising solution, as evidenced by the surge of reported 2D materials functioning as neuromorphic devices for next-generation computing. In this review, we summarize the 2D materials and their heterostructures to be used for neuromorphic computing devices, which could be classified by the working mechanism and device geometry. Then, we survey neuromorphic device arrays and their applications including artificial visual, tactile, and auditory functions. Finally, we discuss the current challenges of 2D materials to achieve practical neuromorphic devices, providing a perspective on the improved device performance, and integration level of the system. This will deepen our understanding of 2D materials and their heterojunctions and provide a guide to design highly performing memristors. At the same time, the challenges encountered in the industry are discussed, which provides a guide for the development direction of memristors.

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Section: Two-terminal Devicessupporting

confidence: 53%

2D materials and van der Waals heterojunctions for neuromorphic computing

Zhang

Yang

et al. 2022

Neuromorph. Comput. Eng.

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“…Recent research illustrated that the memristor was sensitive to visible light, possibly providing a chance to mimic the function of the biological visual system. , For instance, Hu et al reported that the free charges at the CuPc/Au interface were extracted to generate a light-sensitive molecular ferroelectric memristor . Gennady et al found a unique structural phase transition triggered under light stimulation for the graphene/MoS 2 quantum dot nanosheet (QDNS), which led to an obvious photoresistive switching effect . In fact, our previous work demonstrated that the photocoupling process between electrons, ions, and quantum dots at the interface could induce a tunability of the negative photoconductivity .…”

mentioning

confidence: 99%

Multiphotoconductance Levels of the Organic Semiconductor of Polyimide-Based Memristor Induced by Interface Charges

Wang

Zhou

Wang

et al. 2022

J. Phys. Chem. Lett.

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A memristor with Au/polyimide (PI)/Au structure is prepared by magnetron sputtering to investigate the multiphotoconductance resistive switching (RS) memory behavior. The PI-based memristor presents stable bipolar RS memory and is sensitive to visible light. Four discrete conductance states in both high-resistance state (HRS) and low-resistance state (LRS) are obtained when illuminating by 365, 550, 590, and 780 nm light. Electron trapping and detrapping from the defects distributed at interfaces and the PI switching layer are responsible for the observed RS memory behavior. The enhanced trapping and detrapping process by light illumination is responsible for the multiconductance states. This work provides the possibility for further development of neuromorphic vision sensors using an organic semiconductor-based memristor.

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“…Compared with the previous, a single resistive device can simulate synapses, which can greatly improve the efficiency of simulation and reduce the power consumption of simulation. In addition, GO film also possesses several unique properties, including the growth conditions at room temperature, which are suitable for the preparation of highly flexible devices, and the electrical properties can be modulated by oxidative functional groups, which are indeed suitable for simulating the learning function of neural protrusions, demonstrating the great application prospects [40,113,141,188,[206][207][208][209][210]. The simulations of various functions of neural synapses by GO memristors are summarized below.…”

Section: Neuromorphic Hardwarementioning

confidence: 99%

Graphene oxide-based random access memory: from mechanism, optimization to application

Xiu²,

Jiang³

et al. 2022

J. Phys. D: Appl. Phys.

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According to Moore's Law's development law, traditional floating gate memory is constrained by charge tunneling, and its size has approached the physical limit, which is insufficient to meet the requirements of large data storage. The introduction of new information storage devices may be the key to overcoming the bottleneck. Resistive random access memory (RRAM) has garnered interest due to its fast switching speed, low power consumption, and high integration density. Generally, the resistive switching (RS) behaviors can be explained by the formation/rupture of nanoscale conductive filaments (CFs) in many materials, including transition metal oxides, perovskite oxides and organic matter, etc.. Among these materials, graphene oxide (GO) with its unique physical, chemical properties and excellent mechanical properties is attracting significant attention for use in RRAM owing to its RS operation and potential for integration with other graphene-based electronics. The stoichiometry of sp2 to sp3 bonds determines the electrical properties of GO films. The random formation of CFs is usually attributed to the migration of oxygen functional groups driven by electricity field and transition from sp3 to sp2 bonds at the nanoscale. However, there is unacceptable variability in RS reliability, including retention and endurance, which is the key factor that affects the development of memristors. In this article, we discuss systematically several typical models of the switching mechanism of GO-based RRAM and a summary of methods for improving the device's RS performance. This article concludes by discussing the applications of GO-RRAM in artificial neural networks, flexible devices, and biological monitoring.

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Optoelectronic dynamic memristor systems based on two-dimensional crystals

Cited by 14 publications

References 48 publications

2D materials and van der Waals heterojunctions for neuromorphic computing

2D materials and van der Waals heterojunctions for neuromorphic computing

Multiphotoconductance Levels of the Organic Semiconductor of Polyimide-Based Memristor Induced by Interface Charges

Graphene oxide-based random access memory: from mechanism, optimization to application

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