Abstract
Memristors 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.
Original language | English |
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Pages (from-to) | 3842-3850 |
Number of pages | 9 |
Journal | Nano Letters |
Volume | 23 |
Issue number | 9 |
DOIs | |
Publication status | Published - 10 May 2023 |
Keywords
- BiOSe
- artificial neural network
- low power
- memristor
- synapse