Reducing density-driven error without exact exchange

Literature Information

Publication Date 2017-01-30
DOI 10.1039/C6CP08108H
Impact Factor 3.676
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Abstract

The errors in density functional theory (DFT) calculations can be decomposed into contributions from the exchange–correlation density functional approximation (DFA), and contributions from the approximate electron density generated by that DFA. Standard “semilocal” DFAs have large density-driven delocalization errors for dissociating bonds, radical complexes, metal–ligand complexes, reaction intermediates, and reaction barriers. Several recent studies use Hartree–Fock exchange to reduce these density-driven errors. However, Hartree–Fock calculations can be formally and computationally problematic in periodic systems. I show that Rung 3.5 DFAs, which project the Kohn–Sham one-particle density matrix onto a localized model density matrix at each point in space, can provide a practical alternative. Rung 3.5 densities reduce the aforementioned density-driven errors without empirical parametrization, without the orbital rotation dependence of self-interaction corrections, and without any exact exchange whatsoever. While existing Rung 3.5 DFAs cannot reduce density-driven errors as much as Hartree–Fock exchange, these results offer new prospects for broadening the reach of density-corrected DFT.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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