Structural and energetic properties of cluster models of anatase-supported single late transition metal atoms: a density functional theory benchmark study

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2024-10-22 DOI:10.1007/s00894-024-06173-y
Xavier Deraet, Umut Çilesiz, Viktorya Aviyente, Frank De Proft
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Abstract

Context

Single-atom catalytic systems constitute an intriguing research topic due to their inherently different chemical behavior as compared to classic heterogeneous catalysts. In this study, cluster systems representing single late transition metal atoms adsorbed on anatase were constructed starting from previously generated periodic models and subjected to a density functional theory (DFT) benchmark study. The ability of different density functional approximations representing all rungs of the Jacob’s Ladder classification to accurately describe bond lengths and adsorption energies was assessed for these clusters with the aim of revealing the functional that allows to retain the structural characteristics of the initial periodic system, while also delivering reliable energetics. In this regard, our results indicate that optimisation of the clusters with the meta-GGA functionals TPSS or RevTPSS provides the lowest mean unsigned error and root-mean-square deviations with respect to the periodic models. Moreover, these functionals and, to a slightly lesser degree, PW91 were also found to provide adsorption energies that are statistically the least deviating from the CCSD(T) reference data. More complex hybrid functionals appear to be performing less well.

Methods

Cluster geometries were determined at the Kohn–Sham DFT level using the LANL2DZ basis set for the transition metals and the Pople 6-31G(d) basis set for O and H. The density functional approximations considered were SVWN, PBE, BP86, BLYP, PW91, TPSS, RevTPSS, M06L, M11L, B3LYP, PBE0, M06, M06-2X, MN15, ωB97X-D, CAM-B3LYP, M11, and MN12-SX. Reference adsorption energies of the metals on the support cluster were obtained at the CCSD(T)/LANL2TZ (transition metals)/6–311 +  + G(d,p)//RevTPSS/LANLD2DZ (transition metals)/6-31G*. Besides the above-mentioned functionals, energy calculations using the double-hybrid functionals, DSDPBEP86, PBE0-DH, and B2PLYP, were also performed. All adsorption energy calculations were carried out on the RevTPSS geometries.

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锐钛矿支持的单个晚过渡金属原子簇模型的结构和能量特性:密度泛函理论基准研究
背景单原子催化体系是一个引人入胜的研究课题,因为与传统的异相催化剂相比,它们的化学行为有着本质的不同。本研究从先前生成的周期模型出发,构建了代表吸附在锐钛矿上的单个晚期过渡金属原子的团簇系统,并对其进行了密度泛函理论(DFT)基准研究。我们对代表雅各布阶梯分类所有梯级的不同密度泛函近似值准确描述键长和吸附能的能力进行了评估,目的是揭示既能保留初始周期系统的结构特征,又能提供可靠能量的泛函。在这方面,我们的研究结果表明,使用元 GGA 函数 TPSS 或 RevTPSS 对簇进行优化,与周期模型相比,平均无符号误差和均方根偏差最小。此外,我们还发现这些函数和 PW91(程度稍低)提供的吸附能与 CCSD(T) 参考数据的统计偏差最小。方法在 Kohn-Sham DFT 水平上,使用 LANL2DZ 基集确定过渡金属的簇几何图形,使用 Pople 6-31G(d) 基集确定 O 和 H 的簇几何图形。考虑的密度泛函近似为 SVWN、PBE、BP86、BLYP、PW91、TPSS、RevTPSS、M06L、M11L、B3LYP、PBE0、M06、M06-2X、MN15、ωB97X-D、CAM-B3LYP、M11 和 MN12-SX。金属在支持物团簇上的参考吸附能是在 CCSD(T)/LANL2TZ (过渡金属)/6-311 + + G(d,p)//RevTPSS/LANLD2DZ (过渡金属)/6-31G* 得到的。除上述函数外,还使用双杂交函数 DSDPBEP86、PBE0-DH 和 B2PLYP 进行了能量计算。所有吸附能计算都是在 RevTPSS 几何结构上进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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