Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”-Reference-Cited by-同舟云学术

Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”

Published:2022-08-05 Issue:6606 Volume:377 Page:
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Gerasimov Igor S.¹,Losev Timofey V.²³^ORCID,Epifanov Evgeny Yu.²⁴^ORCID,Rudenko Irina⁵⁶^ORCID,Bushmarinov Ivan S.⁵^ORCID,Ryabov Alexander A.⁶⁷^ORCID,Zhilyaev Petr A.⁷^ORCID,Medvedev Michael G.²⁴^ORCID

Affiliation:

1. Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea.

2. N. D. Zelinsky Institute of Organic Chemistry of Russian Academy of Sciences, 119991 Moscow, Russian Federation.

3. Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russian Federation.

4. National Research University Higher School of Economics, 101000 Moscow, Russian Federation.

5. Yandex, 119021 Moscow, Russian Federation.

6. Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region 141700, Russian Federation.

7. Center for Materials Technologies, Skolkovo Institute of Science and Technology, Moscow 143026, Russian Federation.

Abstract

Kirkpatrick et al . (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference15 articles.

1. Pushing the frontiers of density functionals by solving the fractional electron problem

2. Strongly Constrained and Appropriately Normed Semilocal Density Functional

3. Accurate first-principles structures and energies of diversely bonded systems from an efficient density functional

4. ωB97X-V: A 10-parameter, range-separated hybrid, generalized gradient approximation density functional with nonlocal correlation, designed by a survival-of-the-fittest strategy

5. The M06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four M06-class functionals and 12 other functionals

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