Based on our recently published range-separated random phase approximation (RPA) functional [Kreppel et al., “Range-separated density-functional theory in combination with the random phase approximation: An accuracy benchmark,” J. Chem. Theory Comput. 16, 2985–2994 (2020)], we introduce self-consistent minimization with respect to the one-particle density matrix. In contrast to the range-separated RPA methods presented so far, the new method includes a long-range nonlocal RPA correlation potential in the orbital optimization process, making it a full-featured variational generalized Kohn–Sham (GKS) method. The new method not only improves upon all other tested RPA schemes including the standard post-GKS range-separated RPA for the investigated test cases covering general main group thermochemistry, kinetics, and noncovalent interactions but also significantly outperforms the popular G0W0 method in estimating the ionization potentials and fundamental gaps considered in this work using the eigenvalue spectra obtained from the GKS Hamiltonian.
Skip Nav Destination
Article navigation
28 December 2020
Research Article|
December 29 2020
A range-separated generalized Kohn–Sham method including a long-range nonlocal random phase approximation correlation potential
Daniel Graf
;
Daniel Graf
Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU)
, D-81377 Munich, Germany
Search for other works by this author on:
Christian Ochsenfeld
Christian Ochsenfeld
a)
Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU)
, D-81377 Munich, Germany
a)Author to whom correspondence should be addressed: [email protected]
Search for other works by this author on:
a)Author to whom correspondence should be addressed: [email protected]
J. Chem. Phys. 153, 244118 (2020)
Article history
Received:
September 29 2020
Accepted:
November 29 2020
Citation
Daniel Graf, Christian Ochsenfeld; A range-separated generalized Kohn–Sham method including a long-range nonlocal random phase approximation correlation potential. J. Chem. Phys. 28 December 2020; 153 (24): 244118. https://doi.org/10.1063/5.0031310
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
DeePMD-kit v2: A software package for deep potential models
Jinzhe Zeng, Duo Zhang, et al.
CREST—A program for the exploration of low-energy molecular chemical space
Philipp Pracht, Stefan Grimme, et al.
Dielectric profile at the Pt(111)/water interface
Jia-Xin Zhu, Jun Cheng, et al.
Related Content
Double-hybrid density-functional theory made rigorous
J. Chem. Phys. (February 2011)
Range-separated double-hybrid density-functional theory applied to periodic systems
J. Chem. Phys. (July 2015)
Chemical accuracy with σ-functionals for the Kohn–Sham correlation energy optimized for different input orbitals and eigenvalues
J. Chem. Phys. (October 2021)
Energies, structures, and harmonic frequencies of small water clusters from the direct random phase approximation
J. Chem. Phys. (August 2021)