铁（II）卟啉电子相关的NOF近似
Electron correlation in the Iron(II) Porphyrin by NOF approximations
摘要：
铁卟啉（FeP）单重态、三重态和五重态自旋态的相对稳定性是电子结构方法的一个挑战性问题。虽然它是目前公认的基态是一个三重态，多组态波函数为基础的方法预测一个五重态，密度泛函近似三重态和五重态之间的变化，导致预测高度依赖于所采用的方法的功能。最近提出的全球自然轨道泛函（GNOF）旨在提供静态和动态相关性之间的平衡处理，并与以前的Piris自然轨道泛函（PNOF）一起，使我们能够探索每种类型的相关性在FeP状态的稳定性顺序中的重要性，并保持系统的自旋。值得注意的是，对于给定的基组，GNOF关联了所有可用轨道中的所有电子;在本工作中使用的具有双zeta基组的FeP的情况下;这意味着GNOF可以正确关联465个轨道中的186个电子，显着增加了适合多构型处理的系统的大小。结果表明，PNOF 5、PNOF 7s和PNOF 7预测五重态的能量低于三重态;然而，通过二阶Moller-Plesset修正（NOF-MP2）增加的动态相关性使三重态的能量低于五重态，GNOF也重现了这一预测，它比以前的预测包含了更多的动态相关性。
英文摘要：
The relative stability of the singlet, triplet, and quintet spin states of Iron(II) porphyrin (FeP) represents a challenging problem for electronic structure methods. While it is currently accepted that the ground state is a triplet, multiconfigurational wavefunction-based methods predict a quintet, and density functional approximations vary between triplet and quintet states, leading to a prediction that highly depends on the features of the method employed. The recently proposed Global Natural Orbital Functional (GNOF) aims to provide a balanced treatment between static and dynamic correlation, and together with the previous Piris Natural Orbital Functionals (PNOFs), allowed us to explore the importance of each type of correlation in the stability order of the states of FeP with a method that conserves the spin of the system. It is noteworthy that GNOF correlates all electrons in all available orbitals for a given basis set; in the case of the FeP with a double zeta basis set as used in this work; this means that GNOF can properly correlate 186 electrons in 465 orbitals, significantly increasing the sizes of systems amenable to multiconfigurational treatment. Results show that PNOF5, PNOF7s and PNOF7 predict the quintet to have a lower energy than the triplet state; however, the addition of dynamic correlation via second-order Moller-Plesset corrections (NOF-MP2) turns the triplet state to be lower than the quintet state, a prediction also reproduced by GNOF that incorporates much more dynamic correlation than its predecessors.
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