Fig. 1.
(Color online) (a) The fabrication process for the rCGO memristor. (b) The schematic images of the rCGO memristor structure.
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| Citation: |
Bo Chen, Baojie Zhu, Yifan Wu, Pengpeng Sang, Jixuan Wu, Xuepeng Zhan, Jiezhi Chen. Laser processing induced nonvolatile memory in chaotic graphene oxide films for flexible reservoir computing applications[J]. Journal of Semiconductors, 2024, 45(12): 122403. doi: 10.1088/1674-4926/24080045
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B Chen, B J Zhu, Y F Wu, P P Sang, J X Wu, X P Zhan, and J Z Chen, Laser processing induced nonvolatile memory in chaotic graphene oxide films for flexible reservoir computing applications[J]. J. Semicond., 2024, 45(12), 122403 doi: 10.1088/1674-4926/24080045
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Laser processing induced nonvolatile memory in chaotic graphene oxide films for flexible reservoir computing applications
DOI: 10.1088/1674-4926/24080045
More Information
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Bo Chen is a PhD student at Shandong University under the supervision of Prof. Xuepeng Zhan and Prof. Jiezhi Chen. Her research includes memristors, ferroelectric capacitors and their network implementations -
Baojie Zhu is a senior student, entered Shandong University in 2021 pursuing her bachelor's degree. Her research focuses on memristor fabrication and application -
Xuepeng Zhan received the bachelor’s degree and the PhD degree from Jilin University, China, in 2012 and 2017, respectively. He was a Postdoctoral Fellow with Shandong University, China, and Liverpool John Moores University, Liverpool, U.K. He is currently working as a Professor with the School of Information Science and Engineering, Shandong University. His research interests focus on emerging non-volatile memory, hardware neural network, and femtosecond laser processing - Corresponding author: zhanxuepeng@sdu.edu.cn
- Revised Date: 2024-09-24 Available Online: 2024-10-15
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Abstract
Graphene oxide, as a 2D material with nanometer thickness, offers ultra-high mobility, chaotic properties, and low cost. These make graphene oxide memristors beneficial for reservoir computing (RC) networks. In this study, continuous-wave (CW) laser processing is used to reduce chaotic graphene oxide (CGO) films, resulting in the non-volatile storage capability based on the reduced chaotic graphene oxide (rCGO) films. Laser power significantly impacts the characteristics of the rCGO memristor. Material characterization indicates that laser radiation can effectively reduce the oxygen content in CGO films. With optimized laser power, the rCGO memristor achieves a large ratio at 18 mW laser power. Benefiting from the short-term memory characteristics, distinct conductive states are achieved, which are further utilized to construct RC networks. With a third control probe, the rCGO memristor can express rich reservoir states, demonstrating accuracy in predicting the Hénon map with an NRMSE below 0.3. These findings provide the potential for developing flexible RC networks based on graphene oxide memristors via laser processing. -
References
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Proportional views
§Bo Chen and Baojie Zhu contributed equally to this work and should be considered as co-first authors.
