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Get Free AccessMemristors that emulate synaptic plasticity are building blocks for opening a new era of energy-efficient neuromorphic computing architecture, which will overcome the limitation of the von Neumann bottleneck. Layered two-dimensional (2D) Bi2O2Se, as an emerging material for next-generation electronics, is of great significance in improving the efficiency and performance of memristive devices. Herein, high-quality Bi2O2Se nanosheets are grown by configuring mica substrates face-down on the Bi2O2Se powder. Then, bipolar Bi2O2Se memristors are fabricated with excellent performance including ultrafast switching speed (<5 ns) and low-power consumption (<3.02 pJ). Moreover, synaptic plasticity, such as long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-timing-dependent plasticity (STDP), are demonstrated in the Bi2O2Se memristor. Furthermore, MNIST recognition with simulated artificial neural networks (ANN) based on conductance modification could reach a high accuracy of 91%. Notably, the 2D Bi2O2Se enables the memristor to possess ultrafast and low-power attributes, showing great potential in neuromorphic computing applications.
Zilong Dong, Qilin Hua, Jianguo Xi, Yuanhong Shi, Tianci Huang, Xinhuan Dai, Jianan Niu, Bingjun Wang, Zhong Lin Wang, Weiguo Hu (2023). Ultrafast and Low-Power 2D Bi<sub>2</sub>O<sub>2</sub>Se Memristors for Neuromorphic Computing Applications. , 23(9), DOI: https://doi.org/10.1021/acs.nanolett.3c00322.
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Type
Article
Year
2023
Authors
10
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1021/acs.nanolett.3c00322
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