Enhancement of localization phenomena driven by covalency in the SrBiMn_1.75Ti_0.25O₆ manganite

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• 作者：E. Asensio de Lucas^a ; I. &#193 ; lvarez-Serrano^a ; G.J. Cuello^b ; M. Garcí ; a-Herná ; ndez^c ; M.L. Ló ; pez^a ; ^{marisal@quim.ucm.es} ; C. Pico^a ; M.L. Veiga^a
• 关键词：Manganites ; Bismuth ; Charge ordering ; Orbital ordering ; Neutron diffraction
• 刊名：Journal of Alloys and Compounds
• 出版年：2012
• 期刊代码：45_09258388
• 类别：ms
• 出版时间：5 May, 2012
• 卷：522
• 期：Complete
• 页码：123-129
• 文件大小：500 K

摘要

Manganites are materials that show remarkable phenomena related to charge orbital ordering (CO/OO) and it is extremely important to understand the fundamental nature of this behaviour. This paper reports on the structural, electronic and magnetic behaviour of the new SrBiMn_1.75Ti_0.25O₆ manganite and the dependence of these properties with temperature. A detailed structural analysis has been carried out by electron, X-ray, neutron diffraction between 4 and 700 K. The electron diffraction patterns obtained at room temperature (RT) evidence that the average structure ( and m>cm> 鈭?#xA0;2m>am>_m>pm>) presents a modulation that doubles the m>am> and m>cm> lattice parameters. A very high charge ordering (CO) transition temperature of 510 K, similar to that found for the non-doped material, SrBiMn₂O₆, is observed. Above this temperature the symmetry changes from orthorhombic to tetragonal. The conductivity and susceptibility data show a strong interdependence with the structural transition. The activation energy decreases from 0.24 eV to 0.12 eV below and above 510 K, respectively. On the other hand, the high value of the magnetic moment (m>渭m>_eff = 9.34 m>渭m>_B), observed between 300 and 500 K, is interpreted in terms of the existence of Mn₄ magnetic clusters. Finally, extra maxima appearing in neutron diffraction patterns at lower temperatures are interpreted considering the stabilization of AFM interactions, consistent with an A-type magnetic ordering. The results are discussed in the framework of charge ordering/orbital ordering and cluster models.