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Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

Yuan Ye Tian Bo-Bo Duan Chun-Gang

Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

Yuan Ye, Tian Bo-Bo, Duan Chun-Gang
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  • Received Date:  12 May 2018
  • Accepted Date:  15 June 2018
  • Published Online:  05 August 2018

Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

    Corresponding author: Tian Bo-Bo, bbtian@ee.ecnu.edu.cn
  • 1. Key Laboratory of Polar Materials and Devices, Ministry of Education, School of Information Science Technology, East China Normal University, Shanghai 200241, China
Fund Project:  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).

Abstract: 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.

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