Author
Listed:
- Feng-Shou Yang
(National Chung Hsing University
National Tsing Hua University)
- Mengjiao Li
(National Chung Hsing University)
- Mu-Pai Lee
(National Chung Hsing University
National Chiao Tung University)
- I-Ying Ho
(National Chung Hsing University
National Tsing Hua University)
- Jiann-Yeu Chen
(National Chung Hsing University)
- Haifeng Ling
(Nanjing University of Posts&Telecommunications)
- Yuanzhe Li
(Nanjing University of Posts&Telecommunications)
- Jen-Kuei Chang
(National Chung Hsing University)
- Shih-Hsien Yang
(National Chung Hsing University)
- Yuan-Ming Chang
(National Chung Hsing University)
- Ko-Chun Lee
(National Chung Hsing University)
- Yi-Chia Chou
(National Chiao Tung University)
- Ching-Hwa Ho
(National Taiwan University of Science and Technology)
- Wenwu Li
(National Chung Hsing University
East China Normal University)
- Chen-Hsin Lien
(National Tsing Hua University)
- Yen-Fu Lin
(National Chung Hsing University
National Chung Hsing University
National Chung Hsing University)
Abstract
Exploitation of the oxidation behaviour in an environmentally sensitive semiconductor is significant to modulate its electronic properties and develop unique applications. Here, we demonstrate a native oxidation-inspired InSe field-effect transistor as an artificial synapse in device level that benefits from the boosted charge trapping under ambient conditions. A thin InOx layer is confirmed under the InSe channel, which can serve as an effective charge trapping layer for information storage. The dynamic characteristic measurement is further performed to reveal the corresponding uniform charge trapping and releasing process, which coincides with its surface-effect-governed carrier fluctuations. As a result, the oxide-decorated InSe device exhibits nonvolatile memory characteristics with flexible programming/erasing operations. Furthermore, an InSe-based artificial synapse is implemented to emulate the essential synaptic functions. The pattern recognition capability of the designed artificial neural network is believed to provide an excellent paradigm for ultra-sensitive van der Waals materials to develop electric-modulated neuromorphic computation architectures.
Suggested Citation
Feng-Shou Yang & Mengjiao Li & Mu-Pai Lee & I-Ying Ho & Jiann-Yeu Chen & Haifeng Ling & Yuanzhe Li & Jen-Kuei Chang & Shih-Hsien Yang & Yuan-Ming Chang & Ko-Chun Lee & Yi-Chia Chou & Ching-Hwa Ho & We, 2020.
"Oxidation-boosted charge trapping in ultra-sensitive van der Waals materials for artificial synaptic features,"
Nature Communications, Nature, vol. 11(1), pages 1-11, December.
Handle:
RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16766-9
DOI: 10.1038/s41467-020-16766-9
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