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arXiv 2301.01945cond-mat.mtrl-sci
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二维金属的密度泛函模拟优化

Optimizing density-functional simulations for two-dimensional metals

Kameyab Raza Abidi, Pekka Koskinen

摘要:

与共价二维(2D)材料(如石墨烯)不同,2D金属由于其非定向金属键合而具有非分层结构。虽然二维金属的实验仍然稀少且具有挑战性,但密度泛函理论(DFT)提供了一种理想的方法来预测其基本性质并协助其设计。然而,DFT方法很少在低维度下对金属键合进行基准测试。因此,为了确定所需精度的最佳DFT属性,我们系统地基准交换相关泛函从LDA到混合动力车和基组从平面波到本地基础与不同的赝势。与一维链,二维蜂窝,二维正方形,二维六边形,和三维大块金属系统,我们比较DFT属性使用键长,结合能,弹性常数,状态密度,和计算成本。虽然今天大多数二维金属的DFT研究使用平面波,我们的比较表明,经常使用的PBE交换相关的本地基础是足够的,对于大多数目的,而平面波和混合泛函带来有限的改善相比,大大增加了计算成本。这些结果缓解了生成DFT数据的需求,以便更好地与实验进行交互,并结合机器学习算法进行2D金属的数据驱动发现。

英文摘要:

Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory (DFT) provides an ideal approach to predict their basic properties and assist in their design. However, DFT methods have been rarely benchmarked against metallic bonding at low dimensions. Therefore, to identify optimal DFT attributes for a desired accuracy, we systematically benchmark exchange-correlation functionals from LDA to hybrids and basis sets from plane waves to local basis with different pseudopotentials. With 1D chain, 2D honeycomb, 2D square, 2D hexagonal, and 3D bulk metallic systems, we compare the DFT attributes using bond lengths, cohesive energies, elastic constants, densities of states, and computational costs. Although today most DFT studies on 2D metals use plane waves, our comparisons reveal that local basis with often-used PBE exchange-correlation is well sufficient for most purposes, while plane waves and hybrid functionals bring limited improvement compared to the greatly increased computational cost. These results ease the demands for generating DFT data for better interaction with experiments and for data-driven discoveries of 2D metals incorporating machine learning algorithms.

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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