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Reconfigurable memristor based on SrTiO3 thin-film for neuromorphic computing

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Abstract

Neuromorphic computing aims to achieve artificial intelligence by mimicking the mechanisms of biological neurons and synapses that make up the human brain. However, the possibility of using one reconfigurable memristor as both artificial neuron and synapse still requires intensive research in detail. In this work, Ag/SrTiO3(STO)/Pt memristor with low operating voltage is manufactured and reconfigurable as both neuron and synapse for neuromorphic computing chip. By modulating the compliance current, two types of resistance switching, volatile and nonvolatile, can be obtained in amorphous STO thin film. This is attributed to the manipulation of the Ag conductive filament. Furthermore, through regulating electrical pulses and designing bionic circuits, the neuronal functions of leaky integrate and fire, as well as synaptic biomimicry with spike-timing-dependent plasticity and paired-pulse facilitation neural regulation, are successfully realized. This study shows that the reconfigurable devices based on STO thin film are promising for the application of neuromorphic computing systems.

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Acknowledgements

This work was financially supported by the National Key R&D Program of China (Grant No. 2018AAA0103300), the National Key R&D Plan “Nano Frontier” Key Special Project (Grant No. 2021YFA1200502), the Cultivation Projects of National Major R&D Project (Grant No. 92164109), the National Natural Science Foundation of China (Grant Nos. 61874158, 62004056, and 62104058), the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences (Grant No. XDB44000000-7), Hebei Basic Research Special Key Project (Grant No. F2021201045), the Support Program for the Top Young Talents of Hebei Province (Grant No. 70280011807), the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province (Grant No. SLRC2019018), the Interdisciplinary Research Program of Natural Science of Hebei University (No. DXK202101), Institute of Life Sciences and Green Development (No. 521100311), the Natural Science Foundation of Hebei Province (Nos. F2022201054 and F2021201022), the Outstanding Young Scientific Research and Innovation team of Hebei University (Grant No. 605020521001), Special Support Funds for National High Level Talents (Grant No. 041500120001), High-level Talent Research Startup Project of Hebei University (Grant No. 521000981426), the Science and Technology Project of Hebei Education Department (Grant Nos. QN2020178 and QN2021026), and Baoding Science and Technology Plan Project (Nos. 2172P011 and 2272P014).

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  1. These authors contributed equally to the work.

Authors and Affiliations

  1. Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding, 071002, China

    Xiaobing Yan, Xu Han, Ziliang Fang, Zhen Zhao, Zixuan Zhang, Jiameng Sun, Yiduo Shao, Yinxing Zhang, Lulu Wang, Shiqing Sun, Zhenqiang Guo, Xiaotong Jia, Yupeng Zhang & Zhiyuan Guan

  2. Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China

    Tuo Shi

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  1. Xiaobing Yan
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  2. Xu Han
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Correspondence to Xiaobing Yan or Tuo Shi.

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Yan, X., Han, X., Fang, Z. et al. Reconfigurable memristor based on SrTiO3 thin-film for neuromorphic computing. Front. Phys. 18, 63301 (2023). https://doi.org/10.1007/s11467-023-1308-0

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