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      A Trip to the Density Functional Theory Zoo: Warnings and Recommendations for the User

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      Australian Journal of Chemistry
      CSIRO Publishing

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          Abstract

          This account is written for general users of density functional theory (DFT) methods as well as experimental researchers who are new to the field and would like to conduct such calculations. Its main emphasis lies on how to find a way through the confusing ‘zoo’ of DFT by addressing common misconceptions and highlighting those modern methods that should ideally be used in calculations of energetic properties and geometries. A particular focus is on highly popular methods and the important fact that popularity does not imply accuracy. In this context, we present a new analysis of the openly available data published in Swart and co-workers’ famous annual ‘DFT poll’ (http://www.marcelswart.eu/dft-poll/) to demonstrate the existing communication gap between the DFT user and developer communities. We show that despite considerable methodological advances in the field, the perception of some parts of the user community regarding their favourite approaches has changed little. It is hoped that this account makes a contribution towards changing this status and that users are inspired to adjust their current computational protocols to accommodate strategies that are based on proven robustness, accuracy, and efficiency rather than popularity.

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          Generalized Gradient Approximation Made Simple

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            Toward reliable density functional methods without adjustable parameters: The PBE0 model

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              A new mixing of Hartree–Fock and local density-functional theories

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                Author and article information

                Journal
                Australian Journal of Chemistry
                Aust. J. Chem.
                CSIRO Publishing
                0004-9425
                2019
                2019
                : 72
                : 8
                : 563
                Article
                10.1071/CH19023
                7ebfc612-531d-450f-92ad-33cef6f47599
                © 2019
                History

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