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Improving Results by Improving Densities: Density-Corrected Density Functional Theory

期刊

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
卷 144, 期 15, 页码 6625-6639

出版社

AMER CHEMICAL SOC
DOI: 10.1021/jacs.1c11506

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资金

  1. National Research Foundation of Korea [NRF-2020R1A2C2007468, NRF-2020R1A4A1017737]
  2. NSF [CHEM 1856165]
  3. Marie Sklodowska-Curie grant [101033630]
  4. Marie Curie Actions (MSCA) [101033630] Funding Source: Marie Curie Actions (MSCA)

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Density functional theory (DFT) has been widely used in the fields of chemistry and materials science, providing useful accuracy by approximating the unknown exchange-correlation energy. Density-corrected DFT studies the relative contributions to total energy error and can significantly improve performance in certain cases.
Density functional theory (DFT) calculations have become widespread in both chemistry and materials, because they usually provide useful accuracy at much lower computational cost than wavefunction-based methods. All practical DFT calculations require an approximation to the unknown exchange-correlation energy, which is then used self-consistently in the Kohn-Sham scheme to produce an approximate energy from an approximate density. Density-corrected DFT is simply the study of the relative contributions to the total energy error. In the vast majority of DFT calculations, the error due to the approximate density is negligible. But with certain classes of functionals applied to certain classes of problems, the density error is sufficiently large as to contribute to the energy noticeably, and its removal leads to much better results. These problems include reaction barriers, torsional barriers involving p-conjugation, halogen bonds, radicals and anions, most stretched bonds, etc. In all such cases, use of a more accurate density significantly improves performance, and often the simple expedient of using the Hartree-Fock density is enough. This Perspective explains what DC-DFT is, where it is likely to improve results, and how DC-DFT can produce more accurate functionals. We also outline challenges and prospects for the field.

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