IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-021-27531-x.html
   My bibliography  Save this article

Electroresistance in multipolar antiferroelectric Cu2Se semiconductor

Author

Listed:
  • Hui Bai

    (Wuhan University of Technology
    Wuhan University of Technology)

  • Jinsong Wu

    (Wuhan University of Technology
    Wuhan University of Technology)

  • Xianli Su

    (Wuhan University of Technology)

  • Haoyang Peng

    (Wuhan University of Technology
    Wuhan University of Technology)

  • Zhi Li

    (Wuhan University of Technology)

  • Dongwang Yang

    (Wuhan University of Technology)

  • Qingjie Zhang

    (Wuhan University of Technology)

  • Ctirad Uher

    (University of Michigan)

  • Xinfeng Tang

    (Wuhan University of Technology)

Abstract

Electric field-induced changes in the electrical resistance of a material are considered essential and enabling processes for future efficient large-scale computations. However, the underlying physical mechanisms of electroresistance are currently remain largely unknown. Herein, an electrically reversible resistance change has been observed in the thermoelectric α-Cu2Se. The spontaneous electric dipoles formed by Cu+ ions displaced from their positions at the centers of Se-tetrahedrons in the ordered α-Cu2Se phase are examined, and α-Cu2Se phase is identified to be a multipolar antiferroelectric semiconductor. When exposed to the applied voltage, a reversible switching of crystalline domains aligned parallel to the polar axis results in an observed reversible resistance change. The study expands on opportunities for semiconductors with localized polar symmetry as the hardware basis for future computational architectures.

Suggested Citation

  • Hui Bai & Jinsong Wu & Xianli Su & Haoyang Peng & Zhi Li & Dongwang Yang & Qingjie Zhang & Ctirad Uher & Xinfeng Tang, 2021. "Electroresistance in multipolar antiferroelectric Cu2Se semiconductor," Nature Communications, Nature, vol. 12(1), pages 1-6, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27531-x
    DOI: 10.1038/s41467-021-27531-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-021-27531-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-021-27531-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. V. Garcia & S. Fusil & K. Bouzehouane & S. Enouz-Vedrenne & N. D. Mathur & A. Barthélémy & M. Bibes, 2009. "Giant tunnel electroresistance for non-destructive readout of ferroelectric states," Nature, Nature, vol. 460(7251), pages 81-84, July.
    2. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Min, Fuhong & Zhang, Wen & Ji, Ziyi & Zhang, Lei, 2021. "Switching dynamics of a non-autonomous FitzHugh-Nagumo circuit with piecewise-linear flux-controlled memristor," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    2. Feng, Liang & Hu, Cheng & Yu, Juan & Jiang, Haijun & Wen, Shiping, 2021. "Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    3. Hu, Yongbing & Li, Qian & Ding, Dawei & Jiang, Li & Yang, Zongli & Zhang, Hongwei & Zhang, Zhixin, 2021. "Multiple coexisting analysis of a fractional-order coupled memristive system and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. Yan, Dengwei & Wang, Lidan & Duan, Shukai & Chen, Jiaojiao & Chen, Jiahao, 2021. "Chaotic Attractors Generated by a Memristor-Based Chaotic System and Julia Fractal," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    5. Luo, Mengzhuo & Cheng, Jun & Liu, Xinzhi & Zhong, Shouming, 2019. "An extended synchronization analysis for memristor-based coupled neural networks via aperiodically intermittent control," Applied Mathematics and Computation, Elsevier, vol. 344, pages 163-182.
    6. Liu, Shuxin & Yu, Yongguang & Zhang, Shuo & Zhang, Yuting, 2018. "Robust stability of fractional-order memristor-based Hopfield neural networks with parameter disturbances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 845-854.
    7. Zhang, Ge & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir & Alzahrani, Faris, 2018. "Dynamical behavior and application in Josephson Junction coupled by memristor," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 290-299.
    8. Chen, Qun & Li, Bo & Yin, Wei & Jiang, Xiaowei & Chen, Xiangyong, 2023. "Bifurcation, chaos and fixed-time synchronization of memristor cellular neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    9. Stavrinides, Stavros G. & Hanias, Michael P. & Gonzalez, Mireia B. & Campabadal, Francesca & Contoyiannis, Yiannis & Potirakis, Stelios M. & Al Chawa, Mohamad Moner & de Benito, Carol & Tetzlaff, Rona, 2022. "On the chaotic nature of random telegraph noise in unipolar RRAM memristor devices," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    10. Li, Liangchen & Xu, Rui & Lin, Jiazhe, 2020. "Lagrange stability for uncertain memristive neural networks with Lévy noise and leakage delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    11. Rohit Abraham John & Yiğit Demirağ & Yevhen Shynkarenko & Yuliia Berezovska & Natacha Ohannessian & Melika Payvand & Peng Zeng & Maryna I. Bodnarchuk & Frank Krumeich & Gökhan Kara & Ivan Shorubalko &, 2022. "Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    12. Sakthivel, R. & Anbuvithya, R. & Mathiyalagan, K. & Ma, Yong-Ki & Prakash, P., 2016. "Reliable anti-synchronization conditions for BAM memristive neural networks with different memductance functions," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 213-228.
    13. Liying Xu & Jiadi Zhu & Bing Chen & Zhen Yang & Keqin Liu & Bingjie Dang & Teng Zhang & Yuchao Yang & Ru Huang, 2022. "A distributed nanocluster based multi-agent evolutionary network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    14. Xu, Ying & Jia, Ya & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Synchronization between neurons coupled by memristor," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 435-442.
    15. Ushakov, Yury & Balanov, Alexander & Savel’ev, Sergey, 2021. "Role of noise in spiking dynamics of diffusive memristor driven by heating-cooling cycles," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    16. Qin, Xiaoli & Wang, Cong & Li, Lixiang & Peng, Haipeng & Yang, Yixian & Ye, Lu, 2018. "Finite-time modified projective synchronization of memristor-based neural network with multi-links and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 302-315.
    17. Yan Sun & Shuting Xu & Zheqi Xu & Jiamin Tian & Mengmeng Bai & Zhiying Qi & Yue Niu & Hein Htet Aung & Xiaolu Xiong & Junfeng Han & Cuicui Lu & Jianbo Yin & Sheng Wang & Qing Chen & Reshef Tenne & All, 2022. "Mesoscopic sliding ferroelectricity enabled photovoltaic random access memory for material-level artificial vision system," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    18. Yueyang Jia & Qianqian Yang & Yue-Wen Fang & Yue Lu & Maosong Xie & Jianyong Wei & Jianjun Tian & Linxing Zhang & Rui Yang, 2024. "Giant tunnelling electroresistance in atomic-scale ferroelectric tunnel junctions," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    19. Ui Yeon Won & Quoc An Vu & Sung Bum Park & Mi Hyang Park & Van Dam Do & Hyun Jun Park & Heejun Yang & Young Hee Lee & Woo Jong Yu, 2023. "Multi-neuron connection using multi-terminal floating–gate memristor for unsupervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    20. Ying, Jiajie & Liang, Yan & Wang, Junlan & Dong, Yujiao & Wang, Guangyi & Gu, Meiyuan, 2021. "A tristable locally-active memristor and its complex dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27531-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.