An improved treatment of empirical dispersion and a many-body energy decomposition scheme for the explicit polarization plus symmetry-adapted perturbation theory (XSAPT) method-Reference-Cited by-同舟云学术

An improved treatment of empirical dispersion and a many-body energy decomposition scheme for the explicit polarization plus symmetry-adapted perturbation theory (XSAPT) method

Published:2013-07-21 Issue:3 Volume:139 Page:034107
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:The Journal of Chemical Physics

Author:

Lao Ka Un,Herbert John M.

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.4813523

Reference97 articles.

1. Liquid water

2. Møller-Plesset perturbation theory: from small molecule methods to methods for thousands of atoms

3. Spin-component-scaled electron correlation methods

4. Assessment of the Performance of MP2 and MP2 Variants for the Treatment of Noncovalent Interactions

5. Optimized spin-component scaled second-order Møller-Plesset perturbation theory for intermolecular interaction energies

Cited by 66 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improving second-order Møller–Plesset perturbation theory for noncovalent interactions with the machine learning-corrected ab initio dispersion potential;The Journal of Chemical Physics;2024-05-09

2. Ab initio dispersion potentials based on physics-based functional forms with machine learning;The Journal of Chemical Physics;2024-05-08

3. Energy decomposition analysis method using density matrix formulation;The Journal of Chemical Physics;2024-05-01

4. A many-body energy decomposition analysis (MB-EDA) scheme based on a target state optimization self-consistent field (TSO-SCF) method;Physical Chemistry Chemical Physics;2024

5. Accurate prediction of global-density-dependent range-separation parameters based on machine learning;The Journal of Chemical Physics;2023-07-24