Literature DB >> 24920317

The derivative discontinuity of the exchange-correlation functional.

Paula Mori-Sánchez1, Aron J Cohen.   

Abstract

The derivative discontinuity is a key concept in electronic structure theory in general and density functional theory in particular. The electronic energy of a quantum system exhibits derivative discontinuities with respect to different degrees of freedom that are a consequence of the integer nature of electrons. The classical understanding refers to the derivative discontinuity of the total energy as a function of the total number of electrons (N), but it can also manifest at constant N. Examples are shown in models including several hydrogen systems with varying numbers of electrons or nuclear charge (Z), as well as the 1-dimensional Hubbard model (1DHM). Two sides of the problem are investigated: first, the failure of currently used approximate exchange-correlation functionals in DFT and, second, the importance of the derivative discontinuity in the exact electronic structure of molecules, as revealed by full configuration interaction (FCI). Currently, all approximate functionals, including hybrids, miss the derivative discontinuity, leading to basic errors that can be seen in many ways: from the complete failure to give the total energy of H2 and H2(+), to the missing gap in Mott insulators such as stretched H2 and the thermodynamic limit of the 1DHM, or a qualitatively incorrect density in the HZ molecule with two electrons and incorrect electron transfer processes. Description of the exact particle behaviour of electrons is emphasised, which is key to many important physical processes in real systems, especially those involving electron transfer, and offers a challenge for the development of new exchange-correlation functionals.

Entities:  

Year:  2014        PMID: 24920317     DOI: 10.1039/c4cp01170h

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  3 in total

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Authors:  Stefan Vuckovic; Paola Gori-Giorgi
Journal:  J Phys Chem Lett       Date:  2017-06-09       Impact factor: 6.475

2.  Artificial neural networks for density-functional optimizations in fermionic systems.

Authors:  Caio A Custódio; Érica R Filletti; Vivian V França
Journal:  Sci Rep       Date:  2019-02-13       Impact factor: 4.379

3.  Application of two-component neural network for exchange-correlation functional interpolation.

Authors:  Alexander Ryabov; Iskander Akhatov; Petr Zhilyaev
Journal:  Sci Rep       Date:  2022-08-19       Impact factor: 4.996

  3 in total

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