Atomization Energy Calculations in 13-Atom Alkali Metal Clusters: Is There an Appropriate Exchange-Correlation Functional?

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Wagner F. D. Angelotti, Lucila C. Z. Angelotti, Roberto L. A. Haiduke
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引用次数: 0

Abstract

Density functional theory (DFT) is a treatment widely employed for exploring the electronic structure of atoms, molecules, solids, and complex systems. Despite its efficiency and popularity, the accuracy of DFT results is highly dependent on the choice of exchange–correlation (XC) functionals. This study evaluates several XC functionals for calculating atomization energies in 13-atom homo- and heteronuclear alkali metal clusters (X13 and YX12, with X, Y = Li, Na, K, Rb, and Cs), comparing these results with reference data obtained from fixed-node Diffusion Monte Carlo (DMC) simulations. Our findings emphasize the critical role of the correlation functional in achieving more accurate results. Moreover, empirical dispersion corrections are shown to be quite important for these systems. Notably, PBE and PBE0 functionals with D3-BJ dispersion seem particularly reliable for atomization energy calculations in these clusters.

Abstract Image

13原子碱金属团簇的原子化能计算:是否存在合适的交换相关泛函?
密度泛函理论(DFT)是一种广泛用于探索原子、分子、固体和复杂系统的电子结构的处理方法。尽管它的效率和普及,DFT结果的准确性高度依赖于交换相关(XC)泛函的选择。本研究评估了几种用于计算13原子同质和异核碱金属团簇(X13和YX12, X, Y = Li, Na, K, Rb和Cs)原子化能的XC函数,并将这些结果与固定节点扩散蒙特卡罗(DMC)模拟获得的参考数据进行了比较。我们的研究结果强调了相关功能在获得更准确结果中的关键作用。此外,经验色散校正对这些系统是非常重要的。值得注意的是,具有D3-BJ色散的PBE和PBE0官能团似乎特别可靠地用于这些团簇中的原子化能计算。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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