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对于依赖密度的色散校正(dDsC)而言,自洽性有多重要?

How important is self-consistency for the dDsC density dependent dispersion correction?

作者信息

Brémond Éric, Golubev Nikolay, Steinmann Stephan N, Corminboeuf Clémence

机构信息

Laboratory for Computational Molecular Design, Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.

出版信息

J Chem Phys. 2014 May 14;140(18):18A516. doi: 10.1063/1.4867195.

DOI:10.1063/1.4867195
PMID:24832324
Abstract

The treatment of dispersion interactions is ubiquitous but computationally demanding for seamless ab initio approaches. A highly popular and simple remedy consists in correcting for the missing interactions a posteriori by adding an attractive energy term summed over all atom pairs to standard density functional approximations. These corrections were originally based on atom pairwise parameters and, hence, had a strong touch of empiricism. To overcome such limitations, we recently proposed a robust system-dependent dispersion correction, dDsC, that is computed from the electron density and that provides a balanced description of both weak inter- and intramolecular interactions. From the theoretical point of view and for the sake of increasing reliability, we here verify if the self-consistent implementation of dDsC impacts ground-state properties such as interaction energies, electron density, dipole moments, geometries, and harmonic frequencies. In addition, we investigate the suitability of the a posteriori scheme for molecular dynamics simulations, for which the analysis of the energy conservation constitutes a challenging tests. Our study demonstrates that the post-SCF approach in an excellent approximation.

摘要

色散相互作用的处理无处不在,但对于无缝从头算方法而言计算量很大。一种非常流行且简单的补救方法是通过在标准密度泛函近似中添加一个对所有原子对求和的吸引能项来事后校正缺失的相互作用。这些校正最初基于原子对参数,因此带有很强的经验主义色彩。为克服此类限制,我们最近提出了一种稳健的、依赖于体系的色散校正方法dDsC,它根据电子密度计算得出,能对分子间和分子内的弱相互作用提供平衡的描述。从理论角度以及为了提高可靠性,我们在此验证dDsC的自洽实现是否会影响诸如相互作用能、电子密度、偶极矩、几何结构和谐波频率等基态性质。此外,我们研究了事后方案对分子动力学模拟的适用性,对此能量守恒分析构成一项具有挑战性的测试。我们的研究表明,自洽场后的方法是一种极佳的近似。

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