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arXiv 0910.3597cond-mat.mtrl-sci
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正常和非正常多铁性的混合泛函研究

Hybrid functional study of proper and improper multiferroics

A. Stroppa, S. Picozzi

摘要:

本文采用密度泛函理论(DFT)和Heyd-Scuseria-Ernzerhof杂化泛函(HSE)方法,分别对BiFeO $_{3}$和正交HoMnO $_{3}$等典型\textit{proper}和\textit{improper}多铁性(MF)体系的结构、电子、磁性和铁电性质进行了详细的研究.通过比较我们的结果与现有的实验数据,以及与国家的最先进的GW计算,我们表明,HSE形式主义是能够很好地说明这些化合物的相关属性,它出现作为一个准确的工具,预测第一性原理调查多铁性系统。我们表明,超出本地和半本地DFT方法(HSE提供)的影响是必要的一个现实的描述MF。对于电极化的强度,发现具有磁致铁电性的MF(例如HoMnO $_3$)降低,其中计算的极化从使用Perdew-Burke-Ernzerhof(PBE)的$\sim$ 6 $μ C/cm^2$改变为使用HSE的$\sim$ 2 $μ C/cm^2$。然而,对于\textit{proper} MF,例如BiFeO $_{3}$,在引入精确交换时,极化略微增加。因此,我们的研究结果表明,一个总的趋势HSE校正裸密度功能不能提取,而是一个特定的调查,必须进行每一个化合物。

英文摘要:

We present a detailed study of the structural, electronic, magnetic and ferroelectric properties of prototypical \textit{proper} and \textit{improper} multiferroic (MF) systems such as BiFeO$_{3}$ and orthorhombic HoMnO$_{3}$, respectively, within density functional theory (DFT) and using the Heyd-Scuseria-Ernzerhof hybrid functional (HSE). By comparing our results with available experimental data as well as with state-of-the-art GW calculations, we show that the HSE formalism is able to account well for the relevant properties of these compounds and it emerges as an accurate tool for predictive first-principles investigations on multiferroic systems. We show that effects beyond local and semilocal DFT approaches (as provided by HSE) are necessary for a realistic description of MFs. For the electric polarization, a decrease is found for MFs with magnetically-induced ferroelectricity, such as HoMnO$_3$, where the calculated polarization changes from $\sim$ 6 $μ C/cm^2$ using Perdew-Burke-Ernzerhof (PBE) to $\sim$ 2 $μ C/cm^2$ using HSE. However, for \textit{proper} MFs, such as BiFeO$_{3}$, the polarization slightly increases upon introduction of exact exchange. Our findings therefore suggest that a general trend for the HSE correction to bare density functional cannot be extracted; rather, a specific investigation has to be carried out on each compound.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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