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Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

Yuan Ye Tian Bo-Bo Duan Chun-Gang

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Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

Yuan Ye, Tian Bo-Bo, Duan Chun-Gang
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  • Perovskite BiMnO3 with ferroelectric and ferromagnetic ordering simultaneously, as a kind of multiferroics, can be expected to have the coupling between the magnetic and dielectric properties as well as their control by the application of electric fields. This advantage can make BiMnO3 a good candidate for an artificial synapse material. Under the framework of the density functional theory, in this paper we adopt the generalized gradient approximation (GGA+U) plane wave pseudopotential method to calculate the ferroelectricity double-well potential curves and magnetic moments of Mn of tetragonal BiMnO3, with 0.18% and 4% strain exerted in its x-y plane. The results show that the magnetic moment of Mn monotonically increases from paraelectric state to ferroelectric state. It means that the ferromagnetic property of tetragonal BiMnO3 can be controlled by the intensity of polarization. The greater the stress, the greater the range of magnetic moment is. This would imply that the multiferroic artificial synapse device based on BiMnO3 can bring another degree of freedom into designing the complex cognitive systems of artificial intelligence in the future.
      Corresponding author: Tian Bo-Bo, bbtian@ee.ecnu.edu.cn
    • Funds: Project supported by the Shanghai Science and Technology Innovation Action Plan, China (Grant No. 17JC1402500), the Shanghai Sailing Program, China (Grant No. 17YF1404200), and the National Postdoctoral Program for Innovative Talents, China (Grant No. BX201600052).
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    [19]

    Plov L, Chandra P, Rabe K M 2010 Phys. Rev. B 82 075432

    [20]

    Chanthbouala A, Matsumoto R, Grollier J, Cros V, Anane A, Fert A, Khvalkovskiy A V, Zvezdin K A, Nishimura K, Nagamine Y, Maehara H, Tsunekawa K, Fukushima A, Yuasa S 2011 Nat. Phys. 7 626

    [21]

    Lequeux S, Sampaio J, Cros V, Yakushiji K, Fukushima A, Matsumoto R, Kubota H, Yuasa S, Grollier J 2016 Sci. Rep. 6 31510

    [22]

    Biswas A K, Atulasimha J, Bandyopadhyay S 2015 Nanotechnology 26 285201

    [23]

    Perdew J P, Burke K, Ernzerhof M 1996 Phys. Rev. Lett. 77 3865

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    Kresse G, Furthmuller J 1996 Comput. Mater. Sci. 6 15

    [25]

    Kresse G, Joubert D 1999 Phys. Rev. B 59 1758

    [26]

    Kresse G, Furthmuller J 1996 Phys. Rev. B 54 11169

    [27]

    Blchl P E, Jepsen O, Andersen O K 1994 Phys. Rev. B 49 16223

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    Dudarev S L, Dudarev S L, Botton G A, Savrasov S Y, Humphreys C J, Sutton A P 1998 Phys. Rev. B 57 1505

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  • [1]

    Yang J J, Strukov D B, Stewart D R 2013 Nat. Nanotechnol. 8 13

    [2]

    Yang Y, Wen J, Guo L, Wan X, Du P, Feng P, Shi Y, Wan Q 2016 ACS Appl. Mater. Interfaces 8 30281

    [3]

    Hebb D O 1949 The Organization of Behavior: A Neuropsychological Theory (New York: John Wiley and Sons, Inc.)

    [4]

    Kandel E R 2001 Science 294 1030

    [5]

    Burke S N, Barnes C A 2006 Nat. Rev. Neurosci. 7 30

    [6]

    Merolla P A, Arthur J V, Alvarez-Icaza R 2014 Science 345 668

    [7]

    Versace M, Chandler B 2010 IEEE Spectrum 47 30

    [8]

    Smith L S 2006 Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies (New York: Springer) pp433-475

    [9]

    Indiveri G, Chicca E, Douglas R 2006 IEEE Trans. Neural Networks 17 211

    [10]

    Song S, Miller K D, Abbott L F 2000 Nature Neurosci. 3 919

    [11]

    Bi G Q, Poo M M 1998 J. Neurosci. 18 10464

    [12]

    Douglas R, Mahowald M, Mead C 1995 Annu. Rev. Neurosci. 18 255

    [13]

    Jo S H, Chang T, Ebong I, Bhadviya B B, Mazumder P, Lu W 2010 Nano Lett. 10 1297

    [14]

    Boyn S, Grollier J, Lecerf G, Xu B, Locatelli N, Fusil S, Girod S, Carretero C, Garcia K, Xavier S, Tomas J, Bellaiche L, Bibes M, Barthlmy A, Saghi S, Garcia V 2017 Nat. Commun. 8 14736

    [15]

    Chanthbouala A, Garcia V, Cherifi R O, Bouzehouane K, Fusil S, Moya X, Xavier S, Yamada H, Deranlot C, Mathur N D, Bibes M, Barthlmy A, Grollier J 2012 Nat. Mater. 11 860

    [16]

    Kim D J, Lu H, Ryu S, Bark C W, Eom C B, Tsymbal E Y, Gruverman A 2012 Nano Lett. 12 5697

    [17]

    Hill N A, Rabe K M 1999 Phys. Rev. B 59 8759

    [18]

    Seshadri R, Hill N A 2001 Chem. Mater. 13 2892

    [19]

    Plov L, Chandra P, Rabe K M 2010 Phys. Rev. B 82 075432

    [20]

    Chanthbouala A, Matsumoto R, Grollier J, Cros V, Anane A, Fert A, Khvalkovskiy A V, Zvezdin K A, Nishimura K, Nagamine Y, Maehara H, Tsunekawa K, Fukushima A, Yuasa S 2011 Nat. Phys. 7 626

    [21]

    Lequeux S, Sampaio J, Cros V, Yakushiji K, Fukushima A, Matsumoto R, Kubota H, Yuasa S, Grollier J 2016 Sci. Rep. 6 31510

    [22]

    Biswas A K, Atulasimha J, Bandyopadhyay S 2015 Nanotechnology 26 285201

    [23]

    Perdew J P, Burke K, Ernzerhof M 1996 Phys. Rev. Lett. 77 3865

    [24]

    Kresse G, Furthmuller J 1996 Comput. Mater. Sci. 6 15

    [25]

    Kresse G, Joubert D 1999 Phys. Rev. B 59 1758

    [26]

    Kresse G, Furthmuller J 1996 Phys. Rev. B 54 11169

    [27]

    Blchl P E, Jepsen O, Andersen O K 1994 Phys. Rev. B 49 16223

    [28]

    Dudarev S L, Dudarev S L, Botton G A, Savrasov S Y, Humphreys C J, Sutton A P 1998 Phys. Rev. B 57 1505

    [29]

    Gao Y C, Duan C G, Tang X D, Hu Z G, Yang P, Zhu Z, Chu J 2013 J. Phys.: Condens. Matter 25 165901

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Publishing process
  • Received Date:  12 May 2018
  • Accepted Date:  15 June 2018
  • Published Online:  05 August 2018

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