搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

四方相多铁BiMnO3电控磁性的理论研究

袁野 田博博 段纯刚

引用本文:
Citation:

四方相多铁BiMnO3电控磁性的理论研究

袁野, 田博博, 段纯刚

Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3

Yuan Ye, Tian Bo-Bo, Duan Chun-Gang
PDF
导出引用
  • 钙钛矿结构BiMnO3作为同时具有铁电性与铁磁性的多铁材料,在人工神经网络方面可以作为一种潜在的人工突触材料,从而设计出新型多铁人工突触器件.本文使用第一性原理计算的方法,分别研究了四方相BiMnO3在xy面内施加0.18%与4%应力条件下的铁电情况,以及Mn原子磁矩随着铁电极化强度变化的曲线.结果表明,在四方相多铁BiMnO3中,Mn原子磁矩会随着极化强度的增强而增大,表示其铁磁性可以在一定程度上由其铁电极化来进行调控,并且应力越大,其磁矩变化范围就越大.这一结果使得多铁BiMnO3在人工突触器件设计方面拥有潜在的应用价值,多铁性使其在作为人工突触器件材料中具有更多可调控的自由度,从而可用于模拟多突触连接.这可为将来构造类脑芯片打下一定的理论基础.
    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.
      通信作者: 田博博, bbtian@ee.ecnu.edu.cn
    • 基金项目: 上海科技创新基础研究项目(批准号:17JC1402500)、上海扬帆科技人才项目(批准号:17YF1404200)和中国博士后创新人才项目(批准号:BX201600052)资助的课题.
      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).
    [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

  • [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

  • [1] 陈开辉, 樊贞, 董帅, 李文杰, 陈奕宏, 田国, 陈德杨, 秦明辉, 曾敏, 陆旭兵, 周国富, 高兴森, 刘俊明. 钙钛矿相界面插层对SrFeOx基忆阻器的性能提升. 物理学报, 2023, 72(9): 097301. doi: 10.7498/aps.72.20221934
    [2] 温新宇, 王亚赛, 何毓辉, 缪向水. 忆阻类脑计算. 物理学报, 2022, 71(14): 140501. doi: 10.7498/aps.71.20220666
    [3] 张宇琦, 王俊杰, 吕子玉, 韩素婷. 应用于感存算一体化系统的多模调控忆阻器. 物理学报, 2022, 71(14): 148502. doi: 10.7498/aps.71.20220226
    [4] 郭科鑫, 于海洋, 韩弘, 卫欢欢, 龚江东, 刘璐, 黄茜, 高清运, 徐文涛. 基于水热法制备三氧化钼纳米片的人工突触器件. 物理学报, 2020, 69(23): 238501. doi: 10.7498/aps.69.20200928
    [5] 徐威, 王钰琪, 李岳峰, 高斐, 张缪城, 连晓娟, 万相, 肖建, 童祎. 新型忆阻器神经形态电路的设计及其在条件反射行为中的应用. 物理学报, 2019, 68(23): 238501. doi: 10.7498/aps.68.20191023
    [6] 刘恩华, 陈钊, 温晓莉, 陈长乐. 顺磁性La2/3Sr1/3MnO3层对Bi0.8Ba0.2FeO3薄膜多铁性能的影响. 物理学报, 2016, 65(11): 117701. doi: 10.7498/aps.65.117701
    [7] 毛翔宇, 邹保文, 孙慧, 陈春燕, 陈小兵. Co含量对Bi6Fe2-xCoxTi3O18样品多铁性的影响. 物理学报, 2015, 64(21): 217701. doi: 10.7498/aps.64.217701
    [8] 李永超, 周航, 潘丹峰, 张浩, 万建国. Co/Co3O4/PZT多铁复合薄膜的交换偏置效应及其磁电耦合特性. 物理学报, 2015, 64(9): 097701. doi: 10.7498/aps.64.097701
    [9] 宋桂林, 苏健, 张娜, 常方高. 多铁材料Bi1-xCaxFeO3的介电、铁磁特性和高温磁相变. 物理学报, 2015, 64(24): 247502. doi: 10.7498/aps.64.247502
    [10] 陈延彬, 张帆, 张伦勇, 周健, 张善涛, 陈延峰. 探索基于人工超晶格LaFeO3-YMnO3和自然超晶格n-LaFeO3-Bi4Ti3O12薄膜多铁性. 物理学报, 2015, 64(9): 097502. doi: 10.7498/aps.64.097502
    [11] 陈强, 仲崇贵, 袁国秋, 董正超, 方靖淮. 多铁材料HoMnO3中光学吸收和畸变驱动的第一性原理研究. 物理学报, 2013, 62(12): 127502. doi: 10.7498/aps.62.127502
    [12] 王怀强, 杨运友, 鞠艳, 盛利, 邢定钰. 铁磁绝缘体间的极薄Bi2Se3薄膜的相变研究. 物理学报, 2013, 62(3): 037202. doi: 10.7498/aps.62.037202
    [13] 王美娜, 李英, 王天兴, 刘国栋. 正交多铁性材料DyMnO3的磁性质研究. 物理学报, 2013, 62(22): 227101. doi: 10.7498/aps.62.227101
    [14] 魏杰, 陈彦均, 徐卓. 多铁性BiFeO3纳米颗粒的尺寸依赖磁性能研究. 物理学报, 2012, 61(5): 057502. doi: 10.7498/aps.61.057502
    [15] 郭冬云, 李超, 王传彬, 沈强, 张联盟, Tu Rong, Goto Takashi. Sol-gel法制备Bi0.85Nd0.15FeO3多铁性薄膜. 物理学报, 2010, 59(8): 5772-5776. doi: 10.7498/aps.59.5772
    [16] 胡星, 王伟, 毛翔宇, 陈小兵. Co掺杂Bi5Ti3FeO15多铁陶瓷的磁电性能. 物理学报, 2010, 59(11): 8160-8166. doi: 10.7498/aps.59.8160
    [17] 姚长达, 巩江峰, 耿芳芳, 高虹, 徐云玲, 张爱梅, 唐春梅, 朱卫华. 常温常压下BiMnO3纳米粉末的制备与物性分析. 物理学报, 2010, 59(8): 5332-5337. doi: 10.7498/aps.59.5332
    [18] 罗炳成, 周超超, 陈长乐, 金克新. 单相Bi0.9Ba0.1Fe0.85Mn0.15O3陶瓷中的多铁性. 物理学报, 2009, 58(7): 4563-4566. doi: 10.7498/aps.58.4563
    [19] 仲崇贵, 蒋青, 方靖淮, 葛存旺. 单相ABO3型多铁材料的磁电耦合及磁电性质研究. 物理学报, 2009, 58(5): 3491-3496. doi: 10.7498/aps.58.3491
    [20] 仲崇贵, 蒋青, 方靖淮, 江学范, 罗礼进. 1-3型纳米多铁复合薄膜中电场诱导的磁化研究. 物理学报, 2009, 58(10): 7227-7234. doi: 10.7498/aps.58.7227
计量
  • 文章访问数:  6437
  • PDF下载量:  339
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-05-12
  • 修回日期:  2018-06-15
  • 刊出日期:  2018-08-05

/

返回文章
返回