Realization of Artificial Neuron Using MXene Bi-Directional Threshold Switching Memristors

Chen, Yi-Hao; Wang, Yu; Luo, Yuhao; Li, Xinwei; Wang, Yuqi; Gao, Fei; Xu, Jianguang; Hu, Ertao; Samanta, Subhranu; Wan, Xiang; Lian, Xiaojuan; Xiao, Jianguo; Tong, Yi

doi:10.1109/led.2019.2936261

Cited by 75 publications

(44 citation statements)

References 27 publications

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“…reported TS‐based memristor for the artificial neuron device application. [ 39 ] However, the use of MXene material as a diffusive memristor has not been explored yet. On the other hand, the sliced oxidized MXene material to nanosheets (NS) possesses highly insulating properties due to precursor oxidation, which is related to the influence of surface functional groups such as F, OH, and O as well as an increased amount of TiX bonds.…”

Section: Introductionmentioning

confidence: 99%

Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Соколов

Ali

et al. 2020

Adv Elect Materials

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Transition metal carbides, called MXenes, can be used for MXene‐based unique electronic devices such as new types of batteries, energy storage devices, and supercapacitors, where MXene is used as an electrode. The unique surface properties of MXene and 2D structure can be further applied to the new electronic devices. In this paper, the unique insulating properties of partially oxidized MXene (Ti3C2Tx) sheets are utilized for memory storage and electronic synapse applications. The device exhibits threshold resistive switching characteristics based on Ag+ migration dynamics. It is found that this Ag+ cation migration is similar to Ca2+ ion dynamics of a biological synapse, and thus, biological synapse functions such as intrusion/extrusion of Ag+ cation, paired‐pulse facilitation (PPF), post‐tetanic potentiation (PTP), short‐term potentiation (STP), and transition of STP to long‐term potentiation (LTP) are well‐emulated. It is believed that this device development can be potentially used in the next‐generation hardware‐based artificial intelligence systems.

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Section: Introductionmentioning

confidence: 99%

Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Соколов

Ali

et al. 2020

Adv Elect Materials

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“…In 2019, Chen et al simulated various neural properties using RRAM with the Cu/MXene/Cu structure ( Figure a). [ 62 ] In this report, the simulation of neurons did not require auxiliary circuits, and all the simulations were completed by a single MXene RS layer‐based RRAM. Figure 12d shows the simulation of biological integration‐and‐fire.…”

Section: Applicationsmentioning

confidence: 99%

Emerging MXenes for Functional Memories

et al. 2021

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MXenes are a rapidly growing family of 2D materials. The composition, morphology, structure, surface chemistry, and structural configuration of MXenes directly affect their electrochemical performance. For example, when used as the source and drain electrodes in a transistor, MXenes provide increased chemically active interfaces, reduced ion diffusion length, and improved inplane carrier/charge transport kinetics, thus improving the storage performance of the transistor significantly. The work function and bandgap of MXenes can be controlled by tailoring their structure and surface functional groups. This makes MXenes as the first choice for several storage applications. Herein, the latest progress in the synthesis and properties of MXenes is summarized, and it is aimed to boost the motivation of researchers for developing novel MXenes and improving their applications. It emphasizes on the importance of MXenes in high‐density data storage applications, such as flash memories and memristors. The applications of MXenes in artificial synapses, neurons, and logic circuits are also discussed. A future roadmap is outlined for realizing the storage applications of MXenes.

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“…Although this model presents some advantages over the IF and LIF such as neuron-like precision control of the spiking rate, its realization generally demands very complex circuits. Up-to-date developments of 2D materials-based artificial neurons can be classified into two categories: some reports demonstrated artificial neurons with 2D materials-based TSMs ( Chen et al., 2019b ; Dev et al., 2020 ; Hao et al., 2020 ; Kalita et al., 2019 ), whereas others employed 2D materials-based FETs ( Bao et al., 2019 ; Beck et al., 2020 ; Das et al., 2019 ; Hu et al., 2017 ).…”

Section: D Materials-based Neuromorphic Device Applicationsmentioning

confidence: 99%

“…Chen et al. made another demonstration of LIF neuron without an external circuit by using a 2D MXene (Ti 3 C 2 )-based TSM device ( Chen et al., 2019b ). The Cu/MXene/Cu memristor device showed bidirectional volatile switching with a threshold voltage of 0.68 V. The OFF-state current was high (∼10 μA), and it lost the volatile characteristics only after 3 consecutive cycles.…”

Section: D Materials-based Neuromorphic Device Applicationsmentioning

confidence: 99%

Two-Dimensional Near-Atom-Thickness Materials for Emerging Neuromorphic Devices and Applications

Mofid

et al. 2020

iScience

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Summary Two-dimensional (2D) layered materials and their heterostructures have recently been recognized as promising building blocks for futuristic brain-like neuromorphic computing devices. They exhibit unique properties such as near-atomic thickness, dangling-bond-free surfaces, high mechanical robustness, and electrical/optical tunability. Such attributes unattainable with traditional electronic materials are particularly promising for high-performance artificial neurons and synapses, enabling energy-efficient operation, high integration density, and excellent scalability. In this review, diverse 2D materials explored for neuromorphic applications, including graphene, transition metal dichalcogenides, hexagonal boron nitride, and black phosphorous, are comprehensively overviewed. Their promise for neuromorphic applications are fully discussed in terms of material property suitability and device operation principles. Furthermore, up-to-date demonstrations of neuromorphic devices based on 2D materials or their heterostructures are presented. Lastly, the challenges associated with the successful implementation of 2D materials into large-scale devices and their material quality control will be outlined along with the future prospect of these emergent materials.

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Realization of Artificial Neuron Using MXene Bi-Directional Threshold Switching Memristors

Cited by 75 publications

References 27 publications

Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Emerging MXenes for Functional Memories

Two-Dimensional Near-Atom-Thickness Materials for Emerging Neuromorphic Devices and Applications

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Realization of Artificial Neuron Using MXene Bi-Directional Threshold Switching Memristors

Cited by 75 publications

References 27 publications

Partially Oxidized MXene Ti3C2Tx Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Partially Oxidized MXene Ti3C2Tx Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Emerging MXenes for Functional Memories

Two-Dimensional Near-Atom-Thickness Materials for Emerging Neuromorphic Devices and Applications

Contact Info

Product

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Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics

Partially Oxidized MXene Ti₃C₂T_x Sheets for Memristor having Synapse and Threshold Resistive Switching Characteristics