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Low-power memristors based on layered 2D SnSe/graphene materials

基于层状硒化锡/石墨烯材料的低功耗忆阻器件

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Abstract

The emerging two-terminal memristor with a conductance-adjustable function under external stimulation is considered a strong candidate for use in artificial memory and electronic synapses. However, the stability, uniformity, and power consumption of memristors are still challenging in neuromorphic computing. Here an Au/SnSe/graphene/SiO2/Si memristor was fabricated, incorporating two-dimensional graphene with high thermal conductivity. The device not only exhibits excellent electrical characteristics (e.g., high stability, good uniformity and a high ROFF/RON ratio), but also can implement biological synaptic functions such as paired-pulse facilitation, short-term plasticity and long-term plasticity. Its set and reset power values can be as low as 16.7 and 2.3 nW, respectively. Meanwhile, the resistance switching mechanism for the device, which might be associated with the formation and rupture of a filamentary conducting path consisting of Sn vacancies, was confirmed by high-resolution transmission electron microscopy observations. The proposed device is an excellent candidate for use in high-density storage and low-power neuromorphic computing applications.

摘要

在外部刺激下具有电导可调功能的新兴两端忆阻器被认为在记忆和电子突触功能方面颇具潜力. 但是, 目前忆阻器的稳定性、 均匀性和功耗在神经形态计算中仍然具有一定挑战性. 本文中, 我们利用具有高导热性的层状二维石墨烯制造了Au/SnSe/石墨烯/SiO2/Si忆阻器. 该器件不仅具有压倒性的电性能(高稳定性、 均匀性和ROFF/RON比), 而且还可以实现生物突触功能, 例如双脉冲促进、 短期可塑性和长期可塑性. 其开关功率值分别可降低至16.7 和2.3 nW. 同时, 高分辨透射电子显微镜图证实了该器件的电阻转换机制, 可能归因于由锡空位组成的丝状导电路径的形成和破裂. 该设备有望应用于高密度存储和低功率神经形态计算领域.

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (51972094, 61674050 and 61874158), the Outstanding Youth Project of Hebei Province (F2016201220), the Project of Science and Technology Activities for Overseas Researcher (CL201602), the Project of Distinguished Youth of Hebei Province (A2018201231), the Support Program for the Top Young Talents of Hebei Province (70280011807), and the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province (SLRC2019018).

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  1. These authors contributed equally to this paper.

Authors and Affiliations

  1. Key Laboratory of Brain-like Neuromorphic Devices and Systems of Hebei Province, Key Laboratory of Optoelectronic Information Materials of Hebei Province, Hebei University, Baoding, 071002, China

    Hong Wang  (王宏), Tianqi Yu  (于天奇), Jianhui Zhao  (赵建辉), Shufang Wang  (王淑芳) & Xiaobing Yan  (闫小兵)

  2. Department of Materials Science and Engineering, National University of Singapore, Singapore, 117576, Singapore

    Xiaobing Yan  (闫小兵)

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  1. Hong Wang  (王宏)
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  2. Tianqi Yu  (于天奇)
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  3. Jianhui Zhao  (赵建辉)
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  4. Shufang Wang  (王淑芳)
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  5. Xiaobing Yan  (闫小兵)
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Contributions

Author contributions Yan X designed the samples and revised the paper. Wang H conducted the performance test of the device and prepared the manuscript. Yu T analyzed the data. Zhao J assisted in writing the response. All authors contributed to the general discussion of the manuscript.

Corresponding authors

Correspondence to Shufang Wang  (王淑芳) or Xiaobing Yan  (闫小兵).

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Conflict of interest The authors declare no conflict of interest.

Additional information

Hong Wang received her MSc degree from Hebei University in 2018. She is currently pursuing a PhD degree at the Department of Physics, Hebei University. Her research interests include the design and application of 2D-material-based devices.

Tianqi Yu received his Bachelor’s degree from Henan University of Science and Technology in 2018. He is a graduate student at the College of Electronic and Information Engineering, Hebei University. His current research focuses on memristors.

Shufang Wang received her PhD degree in optics from the Institute of Physics, Chinese Academy of Sciences in 2004. She then joined the group of Professor D. Rémiens at IEMN-CNRS, France and the group of Professor Xiaoxing Xi at Pennsylvania State University as a postdoctoral fellow. Her research focuses on photoelectric/ thermalelectric materials and devices.

Xiaobing Yan received his PhD degree from Nanjing University in 2011. He is currently a professor at the College of Electron Information and Engineering, Hebei University. His current research interests include the study of emerging memories, such as charge-trapping memory, phase-change memory, resistive switching memory, and brain-inspired neuromorphic devices.

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Wang, H., Yu, T., Zhao, J. et al. Low-power memristors based on layered 2D SnSe/graphene materials. Sci. China Mater. 64, 1989–1996 (2021). https://doi.org/10.1007/s40843-020-1586-x

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  • DOI: https://doi.org/10.1007/s40843-020-1586-x

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