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渐近成对色散校正能够准确描述层状材料。

Asymptotic Pairwise Dispersion Corrections Can Describe Layered Materials Accurately.

作者信息

Otero-de-la-Roza A, LeBlanc Luc M, Johnson Erin R

机构信息

Departamento de Química Física y Analítica, Facultad de Química, Universidad de Oviedo, 33006 Oviedo, Spain.

Department of Chemistry, Dalhousie University, 6274 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada.

出版信息

J Phys Chem Lett. 2020 Mar 19;11(6):2298-2302. doi: 10.1021/acs.jpclett.0c00348. Epub 2020 Mar 9.

DOI:10.1021/acs.jpclett.0c00348
PMID:32118447
Abstract

A recent study by Tawfik et al. [ 2018, 2, 034005] found that few density functionals, none of which are asymptotic pairwise dispersion methods, describe the geometry and binding of layered materials accurately. Here, we show that the exchange-hole dipole moment (XDM) dispersion model attains excellent results for graphite, hexagonal BN, and transition-metal dichalcogenides. Contrary to what has been argued, successful modeling of layered materials does not necessitate meta-GGA exchange, nonlocal correlation functionals, or the inclusion of three-body dispersion terms. Rather, a GGA functional, combined with a simple asymptotic pairwise dispersion correction, can be reliably used, provided that it properly accounts for the geometric dependence of the dispersion coefficients. The overwhelming contribution to the variation of the pairwise dispersion coefficients comes from the immediate vicinity of an atom and is already present for single layers. Longer-range and interlayer effects are examined in detail for graphite.

摘要

陶菲克等人[2018, 2, 034005]最近的一项研究发现,很少有密度泛函(其中没有一个是渐近成对色散方法)能够准确描述层状材料的几何结构和结合情况。在此,我们表明交换空穴偶极矩(XDM)色散模型在石墨、六方氮化硼和过渡金属二硫属化物方面取得了优异的结果。与之前所主张的观点相反,对层状材料进行成功建模并不需要meta - GGA交换、非局部相关泛函或包含三体色散项。相反,只要能恰当地考虑色散系数的几何依赖性,一个GGA泛函与一个简单的渐近成对色散校正相结合就可以可靠地使用。成对色散系数变化的主要贡献来自原子的紧邻区域,并且单层中就已经存在这种贡献。我们对石墨的长程和层间效应进行了详细研究。

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引用本文的文献

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XDM-corrected hybrid DFT with numerical atomic orbitals predicts molecular crystal lattice energies with unprecedented accuracy.采用数值原子轨道的XDM校正混合密度泛函理论以前所未有的精度预测分子晶体晶格能。
Chem Sci. 2022 Dec 15;14(5):1252-1262. doi: 10.1039/d2sc05997e. eCollection 2023 Feb 1.