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Research Article | Open Access

Organic-2D composite material-based RRAM with high reliability for mimicking synaptic behavior

Tangyou Suna, Fantao Yua, Xiaosheng Tangb, Haiou Lia, Fabi Zhanga, Zhimou Xuc, Qing Liaoa, Zhiqiang Yud, Xingpeng Liua, Peihua Wangyanga, Hezhang Lie( ), Ying Penga( )
Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin, 541004, China
College of Optoelectronic Engineering, Chongqing University, Chongqing, 400044, China
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, 430074, China
School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou, 545006, China
Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
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Abstract

The field of artificial intelligence and neural computing has been rapidly expanding due to the implementation of resistive random-access memory (RRAM) based artificial synaptic. However, the low flexibility of conventional RRAM materials hinders their ability to mimic synaptic behavior accurately. To overcome such limitation, organic-2D composites with high mechanical properties are proposed as the active layer of RRAM. Moreover, we enhance the reliability of the device by ZrO2 insertion layer, resulting in stable synaptic performance. The Ag/PVA:h-BN/ZrO2/ITO devices show stable bipolar resistive switching behavior with an ON/OFF ratio of over 5 × 102, a ~2400 cycles endurance and a long retention time (>6 × 103s), which are essential for the development of high-performance RRAMs. We also study the possible synaptic mechanism and dynamic plasticity of the memory device, observing the transition from short-term potentiation (STP) to long-term potentiation (LTP) under the effect of continuous voltage pulses. Moreover, the device exhibits both long-term depression (LTD) and paired-pulse facilitation (PPF) properties, which have significant implications for the design of organic-2D composite material RRAMs that aim to mimic biological synapses, representing promising avenues for the development of advanced neuromorphic computing systems.

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Journal of Materiomics
Pages 440-447

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Cite this article:
Sun T, Yu F, Tang X, et al. Organic-2D composite material-based RRAM with high reliability for mimicking synaptic behavior. Journal of Materiomics, 2024, 10(2): 440-447. https://doi.org/10.1016/j.jmat.2023.07.005

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Received: 08 June 2023
Revised: 06 July 2023
Accepted: 21 July 2023
Published: 02 August 2023
© 2023 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).