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Demonstration of Nonvolatile Storage and Synaptic Functions in All-Two-Dimensional Floating-Gate Transistors Based on MoS2 Channels Demonstration of Nonvolatile Storage and Synaptic Functions in All-Two-Dimensional Floating-Gate Transistors Based on MoS2 Channels AITranslate

Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University; Northwestern Polytechnical University
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Publisher: ACS
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Abstract AITranslate

With the advent of post-Moore era, the development of memory devices based on bulk materials gradually entered the bottleneck period. Two-dimensional (2D) materials have received much attention due to their excellent optoelectronic and mechanical properties. Also, floating-gate devices based on 2D van der Waals heterostructures have drawn widespread attention in virtue of their great potential for nonvolatile memory. In this paper, a floating-gate device based on a MoS2/BN/graphene heterostructure was fabricated and its electrical storage performance and synaptic function were investigated. Finally, the device obtains a switching ratio of close to ∼105, a large storage window of 107.8 V under a sweeping range of ±60 V, good endurance after 1000 cycles, and charge retention capability above 1500 s. In addition, the device can be used as an artificial synapse to simulate a basic synaptic function and achieve a more linear and symmetrical long-term potentiation and long-term depression profiles. At the same time, the constructed convolutional neural network using this device reaches a high recognition accuracy of 95.5% for handwritten numerals after 1000 times training. These results demonstrate the great potential of 2D material floating-gate devices for nonvolatile memory and neuromorphic computing, which pave the way for the development of next-generation memory devices.

KeyWords AITranslate

2D materials floatinggate nonvolatile storage synaptic device neuromorphic handwritten numeral recognition
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Basic Information:

DOI:https://doi.org/10.1021/acsaelm.3c00595

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Citation Information:

With the advent of post-Moore era, the development of memory devices based on bulk materials gradually entered the bottleneck period. Two-dimensional (2D) materials have received much attention due to their excellent optoelectronic and mechanical properties. Also, floating-gate devices based on 2D van der Waals heterostructures have drawn widespread attention in virtue of their great potential for nonvolatile memory. In this paper, a floating-gate device based on a MoS2/BN/graphene heterostructure was fabricated and its electrical storage performance and synaptic function were investigated. Finally, the device obtains a switching ratio of close to ∼105, a large storage window of 107.8 V under a sweeping range of ±60 V, good endurance after 1000 cycles, and charge retention capability above 1500 s. In addition, the device can be used as an artificial synapse to simulate a basic synaptic function and achieve a more linear and symmetrical long-term potentiation and long-term depression profiles. At the same time, the constructed convolutional neural network using this device reaches a high recognition accuracy of 95.5% for handwritten numerals after 1000 times training. These results demonstrate the great potential of 2D material floating-gate devices for nonvolatile memory and neuromorphic computing, which pave the way for the development of next-generation memory devices.

quote

GB/T 7714-2015 [1] Wei Li, Jiaying Li, Yuhua Chen, et al. ACS Applied Electronic Materials, 2023(5). DOI:10.1021/acsaelm.3c00595.
MLA [1] Wei Li, et al., ACS Applied Electronic Materials, no. 5, 2023, https://doi.org/10.1021/acsaelm.3c00595.
APA [1] Wei Li, Jiaying Li, Yuhua Chen, Zhanzi Chen, Weilin Li, Zhuowen Wang, Tianhui Mu, Zhao Chen, Ruijing Yang, Ziqian Meng, Yucheng Wang, Feng Li, & Shaoxi Wang. (2023). ACS Applied Electronic Materials(5). https://doi.org/10.1021/acsaelm.3c00595
IEEE [1] Wei Li, Jiaying Li, Yuhua Chen, Zhanzi Chen, Weilin Li, Zhuowen Wang, Tianhui Mu, Zhao Chen, Ruijing Yang, Ziqian Meng, Yucheng Wang, Feng Li, and Shaoxi Wang, ACS Applied Electronic Materials, no. 5, 2023, doi: 10.1021/acsaelm.3c00595. keywords: {2D materials floatinggate nonvolatile storage synaptic device neuromorphic handwritten numeral recognition}