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Benchmarking the performance of plane-wave vs. localized orbital basis set methods in DFT modeling of metal surface: a case study for Fe-(110)

机译:在金属表面DFT建模中基准测试平面波与局部轨道基集方法的性能:以Fe-(110)为例

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Reproducing electronic structure of extended metallic systems is computationally demanding with the cost efficiency of this approach heavily dependent on both the density functional and the basis function used to approximate the electronic orbitals. It is well known that the generalized gradient approximation functional (GGA) is the most suitable and reliable approach for the description of metallic systems. As for the basis functions, two approaches dominate: the linear combination of localized basis functions (LB) such as Gaussian functions and the linear combination of plane waves (PW). Both have their own advantages and disadvantages, that may impact the efficiency and accuracy of the simulations. In this work, we use the VASP and the CRYSTAL14 suites of codes that employ plane waves and localized Gaussian basis sets, respectively, to establish a benchmark on their computational efficiency for the modeling of metal surfaces. The PW basis technique requires that the entire simulation box including the vacuum space be filled with plane waves which reduces the computational efficiency and limits the vacuum space. For its part, the LB method is based on atomic localized orbitals and does not require vacuum to model surfaces. Therefore, for calculations that require relatively large vacuum thickness such as modeling of adsorption, the LB method might be superior in terms of computational expense while providing the comparable accuracy. (C) 2018 Elsevier B.V. All rights reserved.
机译:扩展金属系统的电子结构的再现在计算上是需要的,这种方法的成本效率在很大程度上取决于用于近似电子轨道的密度函数和基函数。众所周知,广义梯度近似函数(GGA)是描述金属系统的最合适和最可靠的方法。至于基函数,主要有两种方法:局部基函数(LB)(例如高斯函数)的线性组合和平面波(PW)的线性组合。两者都有各自的优缺点,可能会影响仿真的效率和准确性。在这项工作中,我们分别使用VASP和CRYSTAL14套件的代码,这些套件分别使用平面波和局部高斯基集,以建立用于金属表面建模的计算效率基准。 PW基础技术要求整个模拟盒(包括真空空间)中要充满平面波,这会降低计算效率并限制真空空间。就其本身而言,LB方法是基于原子局部轨道,不需要真空就可以对表面进行建模。因此,对于需要相对较大真空厚度的计算(例如吸附模型),LB方法在提供可比较精度的同时,在计算费用方面可能会更好。 (C)2018 Elsevier B.V.保留所有权利。

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