Laterally Coupled 2D MoS<sub>2</sub> Synaptic Transistor With Ion Gating

Wang, Yarong; Yang, Yafen; He, Zhenyu; Zhu, Hao; Chen, Lin; Sun, Qizhen; Zhang, David Wei

doi:10.1109/led.2020.3008728

Cited by 21 publications

(16 citation statements)

References 19 publications

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“…A magnified EPSC at the pulse frequency of 100 Hz is presented in the inset of Fig. 4 d. So, TiN-NP inserted HfAlO x switching layer properties can mimic synaptic dynamic high-pass filtering characteristics, which is very important for neuromorphic computing [ 44 ]. The measurement details and data processing method for EPSC variation under different spike number and frequency scheme are described in Additional file 1 : Fig.…”

Section: Resultsmentioning

confidence: 99%

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

et al. 2022

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Controlled conductive filament formation in the resistive random access memory device is an essential requirement for analog resistive switching to develop artificial synapses. In this work, we have studied Au/Ti/HfAlOx/TiN-NP/HfAlOx/ITO RRAM device to demonstrate conductance quantization behavior to achieve the high-density memory application. Stepwise change in conductance under DC and pulse voltage confirms the quantized conductance states with integer and half-integer multiples of G0. Reactive TiN-NPs inside the switching layer helps to form and rupture the atomic scale conductive filaments due to enhancing the local electric field inside. Bipolar resistive switching characteristics at low SET/RESET voltage were obtained with memory window > 10 and stable endurance of 103 cycles. Short-term and long-term plasticities are successfully demonstrated by modulating the pre-spike number, magnitude, and frequency. The quantized conductance behavior with promising synaptic properties obtained in the experiments suggests HfAlOx/TiN-NP/HfAlOx switching layer is suitable for multilevel high-density storage RRAM devices.

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Section: Resultsmentioning

confidence: 99%

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

et al. 2022

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“…ANN-based neuromorphic computing can be simulated, and the recognition accuracy of the Modified National Institute of Standards and Technology (MNIST) data set reaches 90%. Different from previous MoS 2 synaptic devices based on thermally unstable organic electrolytes or 1T′-MoS 2 , − our device based on stable inorganic materials is more suitable for high-temperature applications. In addition, the MoS 2 synaptic transistors with a retention time of only seconds at room temperature cannot achieve long-term plasticity at high temperatures. ,, Our work provides a promising way to fabricate synaptic transistors for high-temperature neuromorphic computing.…”

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confidence: 93%

“…In addition, the MoS 2 synaptic transistors with a retention time of only seconds at room temperature cannot achieve long-term plasticity at high temperatures. 35,36,38 Our work provides a promising way to fabricate synaptic transistors for hightemperature neuromorphic computing.…”

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confidence: 99%

Monolayer MoS₂ Synaptic Transistors for High-Temperature Neuromorphic Applications

Wang

et al. 2021

Nano Lett.

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As essential units in an artificial neural network (ANN), artificial synapses have to adapt to various environments. In particular, the development of synaptic transistors that can work above 125 °C is desirable. However, it is challenging due to the failure of materials or mechanisms at high temperatures. Here, we report a synaptic transistor working at hundreds of degrees Celsius. It employs monolayer MoS 2 as the channel and Na + -diffused SiO 2 as the ionic gate medium. A large on/off ratio of 10 6 can be achieved at 350 °C, 5 orders of magnitude higher than that of a normal MoS 2 transistor in the same range of gate voltage. The short-term plasticity has a synaptic transistor function as an excellent low-pass dynamic filter. Long-term potentiation/depression and spike-timing-dependent plasticity are demonstrated at 150 °C. An ANN can be simulated, with the recognition accuracy reaching 90%. Our work provides promising strategies for high-temperature neuromorphic applications.

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“…Therefore, researchers are trying to solve this problem by increasing crystallinity, [ 17 ] utilizing ferroelectric ion gels, [ 18,19 ] and developing new composite materials. [ 20a ] The majority of available publications focused on excitatory stimulatory responses evoked by the accumulated cation ions and electronics at the electrolyte/semiconductor channel layer, [ 21 ] while inhibitory stimulatory reactions induced by anionic ions and holes that were rarely reported. At present, the main channel materials for ionic liquid EGST are indium‐based metal oxide systems, such as InGaZnO, [ 20b ] InGaO, [ 20c ] and InZnO.…”

Section: Introductionmentioning

confidence: 99%

“…At present, the main channel materials for ionic liquid EGST are indium‐based metal oxide systems, such as InGaZnO, [ 20b ] InGaO, [ 20c ] and InZnO. [ 21c ] Unfortunately, indium is an expensive and rare metal. The tin dioxide is considered a promising candidate to replace the indium‐based oxide semiconductor.…”

Section: Introductionmentioning

confidence: 99%

Low‐Cost Fabricated MgSnO Electrolyte‐Gated Synaptic Transistor with Dual Modulation of Excitation and Inhibition

Chen

Sun

Fan

et al. 2022

Adv Elect Materials

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challenges in terms of speed and power usage, while neural algorithms show the potential to bypass the Von Neumann bottleneck and exceed Moore's Limitation. [1] Compared to traditional computers, the biological brain excels in learning, generalization, abstraction, and applicability. [2] Scientists have created a range of synaptic devices inspired by the structure and function of the human brain, using physical processes, and functional materials. [3] Due to their cost-effectiveness, scalability, integrated density, and low power consumption, emerging two-terminal meristem devices are potential possibilities. [4] However, low on/off current ratios, nonlinear, and asymmetric conductance changes lead to low numbers of synaptic weight and inferior linearity of synaptic weight changes. [5] Furthermore, an additional selector component is needed to select the target cell. In comparison, threeterminal synaptic transistors can exhibit low read/write currents, parallel write and read operations, low power consumption, and quasi-linear weight change, which can improve the controllability of prominent weight thereby avoiding the crosstalk problems. [6] Moreover, the post-synaptic received signal cannot be easily disrupted by the pre-synaptic input signal in the three-terminal device, which is crucial to the design of multi-input devices. [7a] Three-terminal synaptic device can control synaptic weights more easily than two-terminal synaptic device because of its structural properties of independent terminals in both training and testing phases. The gate is used for training, and the source-drain and channel are used in the test phase. [5] This structural feature prevents synaptic weights from being destroyed during the testing phase. [7b] As a promising candidate for neuromorphic applications, three-terminal electrolyte-gated synaptic transistors (EGSTs) have drawn considerable attention owe to their low operation voltages, similarity to actual biological systems through the evolutionary structural design of synaptic transistor functions. [6a,b,8] The neural networks of the brain are built on the contributions of excitatory and inhibitory neurons. Presynaptic impulses can activate or inhibit post-synaptic neurons in signal processing, memory, and learning. [6e] Specifically, excitatory postsynaptic potentials cause postsynaptic neurons to produce action potentials. In contrast, inhibitory postsynaptic potentials counterbalance excitatory effects, making postsynaptic neurons less Artificial synapses have attracted extensive attention due to their capacity to circumvent the inherent restrictions of Von Neumann computing architecture. Although electrolyte-gated synaptic transistors (EGSTs) have been enabled to emulate the essential synaptic plasticity, the corresponding neurological applications have been restricted by the lack of inhibitory synaptic response and the subsequent low asymmetric non-linearity factor. Here, Mg-doped SnO 2 (Mg:SnO 2 ) EGSTs via a low-cost and facile solution method are fabricated. With ...

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Laterally Coupled 2D MoS₂ Synaptic Transistor With Ion Gating

Cited by 21 publications

References 19 publications

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Monolayer MoS₂ Synaptic Transistors for High-Temperature Neuromorphic Applications

Low‐Cost Fabricated MgSnO Electrolyte‐Gated Synaptic Transistor with Dual Modulation of Excitation and Inhibition

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Laterally Coupled 2D MoS2 Synaptic Transistor With Ion Gating

Cited by 21 publications

References 19 publications

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Monolayer MoS2 Synaptic Transistors for High-Temperature Neuromorphic Applications

Low‐Cost Fabricated MgSnO Electrolyte‐Gated Synaptic Transistor with Dual Modulation of Excitation and Inhibition

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Product

Resources

About

Laterally Coupled 2D MoS₂ Synaptic Transistor With Ion Gating

Monolayer MoS₂ Synaptic Transistors for High-Temperature Neuromorphic Applications