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REAlgo:用于估计大分子簇的MP2/CCSD能量梯度的快速高效算法。

REAlgo: Rapid and efficient algorithm for estimating MP2/CCSD energy gradients for large molecular clusters.

作者信息

Khire Subodh S, Nakajima Takahito, Gadre Shridhar R

机构信息

RIKEN Center for Computational Science, Kobe 6500047, Japan.

Department of Scientific Computing, Modelling and Simulation, Savitribai Phule Pune University, Pune 411007, India.

出版信息

J Chem Phys. 2023 Nov 14;159(18). doi: 10.1063/5.0174726.

Abstract

This work reports the development of an algorithm for rapid and efficient evaluation of energy gradients for large molecular clusters employing correlated methods viz. second-order Møller-Plesset perturbation theory (MP2) theory and couple cluster singles and doubles (CCSD). The procedure segregates the estimation of Hartree-Fock (HF) and correlation components. The HF energy and gradients are obtained by performing a full calculation. The correlation energy is approximated as the corresponding two-body interaction energy. Correlation gradients for each monomer are approximated from the respective monomer-centric fragments comprising its immediate neighbours. The programmed algorithm is explored for the geometry optimization of large molecular clusters using the BERNY optimizer as implemented in the Gaussian suite of software. The accuracy and efficacy of the method are critically probed for a variety of large molecular clusters containing up to 3000 basis functions, in particular large water clusters. The CCSD level geometry optimization of molecular clusters containing ∼800 basis functions employing a modest hardware is also reported.

摘要

这项工作报告了一种算法的开发,该算法用于使用相关方法(即二阶莫勒-普列斯特定则微扰理论(MP2)理论和耦合簇单双激发(CCSD))对大分子簇的能量梯度进行快速有效的评估。该程序将哈特里-福克(HF)和相关分量的估计区分开来。HF能量和梯度通过进行全计算获得。相关能近似为相应的两体相互作用能。每个单体的相关梯度从包含其紧邻原子的以单体为中心的片段近似得出。使用高斯软件套件中实现的BERNY优化器,对该编程算法进行了大分子簇几何优化的探索。针对各种包含多达3000个基函数的大分子簇,特别是大的水簇,对该方法的准确性和有效性进行了严格探究。还报告了使用适度硬件对包含约800个基函数的分子簇进行CCSD水平几何优化的情况。

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