Floating-gate memristor based on a MoS/h-BN/AuNPs mixed-dimensional heterostructure.

Nanotechnology

Zhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou 310058, People's Republic of China.

Published: August 2024


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Article Abstract

Memristors have recently received substantial attention because of their promising and unique emerging applications in neuromorphic computing, which can achieve gains in computation speed by mimicking the topology of the brain in electronic circuits. Traditional memristors made of bulk MoOand HfO, for example, suffer from a low switching ratio and poor durability and stability. In this work, a floating-gate memristor is developed based on a mixed-dimensional heterostructure comprising two-dimensional (2D) molybdenum disulfide (MoS) and zero-dimensional (0D) Au nanoparticles (AuNPs) separated by an insulating hexagonal boron nitride (h-BN) layer (MoS/h-BN/AuNPs). We find that under the modulation of back-gate voltages, the MoS/h-BN/AuNPs device operates reliably between a high-resistance state (HRS) and a low-resistance state (LRS) and shows multiple stable LRS states, demonstrating the excellent potential of our memristor in multibit storage applications. The modulation effect can be attributed to electron quantum tunneling between the AuNP charge-trapping layer and the MoSchannel. Our memristor exhibits excellent durability and stability: the HRS and LRS are retained for more than 10s without obvious degradation and the on/off ratio is >10after more than 3000 switching cycles. We also demonstrate frequency-dependent memory properties upon stimulation with electrical and optical pulses.

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http://dx.doi.org/10.1088/1361-6528/ad5cfcDOI Listing

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Floating-gate memristor based on a MoS/h-BN/AuNPs mixed-dimensional heterostructure.

Nanotechnology

August 2024

Zhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou 310058, People's Republic of China.

Memristors have recently received substantial attention because of their promising and unique emerging applications in neuromorphic computing, which can achieve gains in computation speed by mimicking the topology of the brain in electronic circuits. Traditional memristors made of bulk MoOand HfO, for example, suffer from a low switching ratio and poor durability and stability. In this work, a floating-gate memristor is developed based on a mixed-dimensional heterostructure comprising two-dimensional (2D) molybdenum disulfide (MoS) and zero-dimensional (0D) Au nanoparticles (AuNPs) separated by an insulating hexagonal boron nitride (h-BN) layer (MoS/h-BN/AuNPs).

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Multi-terminal memristor and memtransistor (MT-MEMs) has successfully performed complex functions of heterosynaptic plasticity in synapse. However, theses MT-MEMs lack the ability to emulate membrane potential of neuron in multiple neuronal connections. Here, we demonstrate multi-neuron connection using a multi-terminal floating-gate memristor (MT-FGMEM).

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Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level.

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Contribution of Polymers to Electronic Memory Devices and Applications.

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Department of Electronic Engineering, Gachon University, Seongnam 1342, Korea.

Electronic memory devices, such as memristors, charge trap memory, and floating-gate memory, have been developed over the last decade. The use of polymers in electronic memory devices enables new opportunities, including easy-to-fabricate processes, mechanical flexibility, and neuromorphic applications. This review revisits recent efforts on polymer-based electronic memory developments.

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