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离子共价材料的极性表面能:基于对Li2FeSiO4表面测试的电荷转移模型的启示

Polar surface energies of iono-covalent materials: implications of a charge-transfer model tested on Li2FeSiO4 surfaces.

作者信息

Hörmann Nicolas G, Groß Axel

机构信息

Helmholtz Institute Ulm Electrochemical Energy Storage, Albert-Einstein-Allee 11, 89069 Ulm (Germany); Universität Ulm, Institut für Theoretische Chemie, Albert-Einstein-Allee 11, 89069 Ulm (Germany).

出版信息

Chemphyschem. 2014 Jul 21;15(10):2058-69. doi: 10.1002/cphc.201400012. Epub 2014 May 27.

Abstract

The ionic compounds that are used as electrode materials in Li-based rechargeable batteries can exhibit polar surfaces that in general have high surface energies. We derive an analytical estimate for the surface energy of such polar surfaces assuming charge redistribution as a polarity compensating mechanism. The polar contribution to the converged surface energy is found to be proportional to the bandgap multiplied by the surface charge necessary to compensate for the depolarization field, and some higher order correction terms that depend on the specific surface. Other features, such as convergence behavior, coincide with published results. General conclusions are drawn on how to perform polar surface energy calculations in a slab configuration and upper boundaries of "purely" polar surface energies are estimated. Furthermore, we compare these findings with results obtained in a density functional theory study of Li(2)FeSiO(4) surfaces. We show that typical polar features are observed and provide a decomposition of surface energies into polar and local bond-cutting contributions for 29 different surfaces. We show that the model is able to explain subtle differences of GGA and GGA+U surface energy calculations.

摘要

在锂基可充电电池中用作电极材料的离子化合物,其极性表面通常具有较高的表面能。我们假设电荷重新分布作为一种极性补偿机制,推导出此类极性表面表面能的解析估计值。发现对收敛表面能的极性贡献与带隙乘以补偿去极化场所需的表面电荷成正比,以及一些取决于特定表面的高阶校正项。其他特征,如收敛行为,与已发表的结果一致。得出了关于如何在平板构型中进行极性表面能计算的一般结论,并估计了“纯”极性表面能的上限。此外,我们将这些发现与对Li(2)FeSiO(4)表面进行密度泛函理论研究所获得的结果进行了比较。我们表明观察到了典型的极性特征,并给出了29个不同表面的表面能分解为极性和局部断键贡献的结果。我们表明该模型能够解释广义梯度近似(GGA)和GGA+U表面能计算的细微差异。

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