Neuromorphic device based on silicon nanosheets

Chenhao Wang, Xinyi Xu, Xiaodong Pi, Mark D. Butala, Wen Huang, Lei Yin, Wenbing Peng, Munir Ali, Srikrishna Chanakya Bodepudi, Xvsheng Qiao, Yang Xu (), Wei Sun () and Deren Yang ()
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Chenhao Wang: Zhejiang University
Xinyi Xu: ZJU-Hangzhou Global Scientific and Technological Innovation Centre
Xiaodong Pi: Zhejiang University
Mark D. Butala: Zhejiang University
Wen Huang: Nanjing University of Posts and Telecommunications
Lei Yin: Zhejiang University
Wenbing Peng: Zhejiang University
Munir Ali: ZJU-Hangzhou Global Scientific and Technological Innovation Centre
Srikrishna Chanakya Bodepudi: ZJU-Hangzhou Global Scientific and Technological Innovation Centre
Xvsheng Qiao: Zhejiang University
Yang Xu: ZJU-Hangzhou Global Scientific and Technological Innovation Centre
Wei Sun: Zhejiang University
Deren Yang: Zhejiang University

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: Abstract Silicon is vital for its high abundance, vast production, and perfect compatibility with the well-established CMOS processing industry. Recently, artificially stacked layered 2D structures have gained tremendous attention via fine-tuning properties for electronic devices. This article presents neuromorphic devices based on silicon nanosheets that are chemically exfoliated and surface-modified, enabling self-assembly into hierarchical stacking structures. The device functionality can be switched between a unipolar memristor and a feasibly reset-able synaptic device. The memory function of the device is based on the charge storage in the partially oxidized SiNS stacks followed by the discharge activated by the electric field at the Au-Si Schottky interface, as verified in both experimental and theoretical means. This work further inspired elegant neuromorphic computation models for digit recognition and noise filtration. Ultimately, it brings silicon - the most established semiconductor - back to the forefront for next-generation computations.

Date: 2022
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DOI: 10.1038/s41467-022-32884-y

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