Suppr超能文献

二茂铁鎓与三甲基膦反应的密度泛函理论(DFT)、密度拟合局部二阶微扰理论(DLPNO-CCSD(T))和核-电子振动-转动微扰理论(NEVPT2)基准研究

DFT, DLPNO-CCSD(T), and NEVPT2 benchmark study of the reaction between ferrocenium and trimethylphosphine.

作者信息

Chamkin Aleksandr A, Serkova Elena S

机构信息

A.N. Nesmeyanov Institute of Organoelement Compounds of Russian Academy of Sciences, Moscow, Russia.

出版信息

J Comput Chem. 2020 Oct 30;41(28):2388-2397. doi: 10.1002/jcc.26398. Epub 2020 Aug 19.

Abstract

The reaction between ferrocenium and trimethylphosphine was studied using density functional theory (DFT), domain-based local pair natural orbital coupled cluster theory with single-, double-, and perturbative triple excitations (DLPNO-CCSD(T)), and N-electron valence state perturbation theory (NEVPT2). The accuracy of the DFT functionals decreases compared to the DLPNO-CCSD(T) level in the following order: M06-L > TPSS > M06, BLYP > PBE, PBE0, B3LYP > > PWPB95 > > DSD-BLYP. The roles of thermochemical, continuum solvation (SMD), and counterpoise corrections were evaluated. Grimme's D3 empirical dispersion correction is essential for all functionals studied except M06 and M06-L. The reliability of the frequency calculations performed directly within the SMD was confirmed. The systems showed no significant multireference character according to T and T diagnostics and the fractional occupation number (FOD) weighted electron density analysis. The multireference NEVPT2 calculations gave qualitatively valid conclusions about the reaction mechanism. However, a multireference approach is generally not recommended because it requires arbitrary chosen active spaces.

摘要

采用密度泛函理论(DFT)、含单、双及微扰三激发的基于域的定域对自然轨道耦合簇理论(DLPNO-CCSD(T))和N电子价态微扰理论(NEVPT2)研究了二茂铁鎓与三甲基膦之间的反应。与DLPNO-CCSD(T)水平相比,DFT泛函的精度按以下顺序降低:M06-L>TPSS>M06,BLYP>PBE,PBE0,B3LYP>>PWPB95>>DSD-BLYP。评估了热化学、连续介质溶剂化(SMD)和平衡校正的作用。除M06和M06-L外,Grimme的D3经验色散校正对所有研究的泛函都是必不可少的。证实了直接在SMD内进行频率计算的可靠性。根据T和T诊断以及分数占据数(FOD)加权电子密度分析,这些体系没有显著的多参考特征。多参考NEVPT2计算给出了关于反应机理的定性有效结论。然而,一般不推荐使用多参考方法,因为它需要任意选择活性空间。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验