Exchange-correlation kernel for perturbation dependent auxiliary functions in auxiliary density perturbation theory

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Luis I. Hernández-Segura, Flor A. Olvera-Rubalcava, Roberto Flores-Moreno, Patrizia Calaminici, Andreas M. Köster
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引用次数: 0

Abstract

Context

Analytic exchange-correlation kernel formulations are of the outermost importance for density functional theory (DFT) perturbation calculations. In this paper, the working equation for the exchange-correlation kernel of the generalized gradient approximation (GGA) for perturbation dependent auxiliary functions is derived and discussed in the framework of auxiliary density functional theory (ADFT). The presented new formulation is extended to the unrestricted approach, too. A comprehensive discussion of the implementation of the GGA ADFT kernel, using either the native exchange-correlation functional implementations in deMon2k or the ones from the LibXC library, is given. Calculations with analytic exchange-correlation kernels are compared to their finite difference counterparts. The obtained results are in quantitative agreement. Nevertheless, analytic GGA ADFT kernel implementations show substantial improvement in the computational performance. Similar results are reported for analytic second derivatives of effective core potential (ECP) and model core potential (MCP) matrix elements when compared to their finite difference counterparts in molecular frequency analyses.

Method

All calculations are performed in the framework of ADFT as implemented in deMon2k. In the ADFT analytic frequency calculations, auxiliary density perturbation theory was used. The underlying two-center exchange-correlation kernel matrix elements are calculated by numerical integration either with analytic or finite difference kernel expressions. Validation calculations are performed with the VWN and PBE functionals employing DFT-optimized DZVP basis sets in conjunction with automatically generated GEN-A2 auxiliary density function sets. In the (Pt3Cu)n cluster benchmark calculations, the RPBE functional was used. For Pt atoms, the quasi-relativistic LANL2DZ effective core potential with the corresponding valence basis set was employed, whereas for Cu atoms, the all-electron DFT-optimized TZVP basis was applied. The auxiliary density was expanded by the automatically generated GEN-A2* auxiliary function set. We run all benchmark calculations in parallel on 24 cores.

Abstract Image

辅助密度扰动理论中扰动相关辅助函数的交换相关核。
背景:分析交换相关核公式对于密度泛函理论(DFT)扰动计算至关重要。本文在辅助密度泛函理论(ADFT)框架内,推导并讨论了扰动相关辅助函数广义梯度近似(GGA)交换相关核的工作方程。提出的新公式也扩展到了无限制方法。文中全面讨论了如何使用 deMon2k 中的本地交换相关函数实现或 LibXC 库中的交换相关函数实现 GGA ADFT 内核。分析交换相关核的计算结果与有限差分核的计算结果进行了比较。得到的结果在数量上是一致的。然而,解析 GGA ADFT 内核的实现大大提高了计算性能。在分子频率分析中,有效核心势能(ECP)和模型核心势能(MCP)矩阵元素的解析二阶导数与有限差分对应元素相比,也得到了类似的结果:所有计算均在 deMon2k 实现的 ADFT 框架内进行。在 ADFT 分析频率计算中,使用了辅助密度扰动理论。基本的双中心交换相关核矩阵元素是通过数值积分计算得出的,可以使用解析核表达式或有限差分核表达式。验证计算采用 VWN 和 PBE 函数,使用 DFT 优化的 DZVP 基集和自动生成的 GEN-A2 辅助密度函数集。在 (Pt3Cu)n 簇基准计算中,使用了 RPBE 函数。对于铂原子,采用了具有相应价基集的准相对论 LANL2DZ 有效核心势,而对于铜原子,则采用了全电子 DFT 优化的 TZVP 基。辅助密度由自动生成的 GEN-A2* 辅助函数集扩展。我们在 24 个内核上并行运行所有基准计算。
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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