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完全活性空间线性化对密度泛函理论的解析核梯度

Analytic Nuclear Gradients for Complete Active Space Linearized Pair-Density Functional Theory.

作者信息

Hennefarth Matthew R, Hermes Matthew R, Truhlar Donald G, Gagliardi Laura

机构信息

Department of Chemistry and Chicago Center for Theoretical Chemistry, University of Chicago, Chicago, Illinois 60637, United States.

Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States.

出版信息

J Chem Theory Comput. 2024 May 14;20(9):3637-3658. doi: 10.1021/acs.jctc.4c00095. Epub 2024 Apr 19.

Abstract

Accurately modeling photochemical reactions is difficult due to the presence of conical intersections and locally avoided crossings, as well as the inherently multiconfigurational character of excited states. As such, one needs a multistate method that incorporates state interaction in order to accurately model the potential energy surface at all nuclear coordinates. The recently developed linearized pair-density functional theory (L-PDFT) is a multistate extension of multiconfiguration PDFT, and it has been shown to be a cost-effective post-MCSCF method (as compared to more traditional and expensive multireference many-body perturbation methods or multireference configuration interaction methods) that can accurately model potential energy surfaces in regions of strong nuclear-electronic coupling in addition to accurately predicting Franck-Condon vertical excitations. In this paper, we report the derivation of analytic gradients for L-PDFT and their implementation in the PySCF-forge software, and we illustrate the utility of these gradients for predicting ground- and excited-state equilibrium geometries and adiabatic excitation energies for formaldehyde, --butadiene, phenol, and cytosine.

摘要

由于存在锥形交叉点和局部避免交叉,以及激发态固有的多组态特性,准确模拟光化学反应具有一定难度。因此,需要一种包含态相互作用的多态方法,以便在所有核坐标下准确模拟势能面。最近发展的线性化对密度泛函理论(L-PDFT)是多组态PDFT的一种多态扩展,并且已被证明是一种经济高效的后MCSCF方法(与更传统且昂贵的多参考多体微扰方法或多参考组态相互作用方法相比),它不仅能够准确预测弗兰克-康登垂直激发,还能在强核-电子耦合区域准确模拟势能面。在本文中,我们报告了L-PDFT解析梯度的推导及其在PySCF-forge软件中的实现,并展示了这些梯度在预测甲醛、1,3-丁二烯、苯酚和胞嘧啶的基态和激发态平衡几何结构以及绝热激发能方面的效用。

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