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Reproducibility of density functional approximations (DFAs) is crucial for chemistry and materials science. This study proposes a framework for verifying DFAs using reliable reference data to prevent errors and ensure accurate computational results.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Quantum Mechanics

Background:

  • Density functional theory (DFT) is a cornerstone in computational chemistry and materials science, with frequent development of new density functional approximations (DFAs).
  • Implementing novel DFAs into software packages is hampered by a lack of reliable reference data for verification.
  • This deficiency has led to inconsistent implementations of established functionals, resulting in varying total energies across different software packages.

Purpose of the Study:

  • To address the critical issue of reproducibility for density functional approximations (DFAs).
  • To establish a common framework for the verification and testing of DFAs, preventing errors and incompatibilities.
  • To ensure the accuracy and reliability of computational chemistry and materials science research.

Main Methods:

  • Proposing methods for generating reference energies using free and open-source software.
  • Utilizing non-self-consistent calculations with tabulated atomic densities for reference energy generation.
  • Employing self-consistent calculations across various program packages for verification.

Main Results:

  • Identified numerous issues with incorrect functional forms in recently published DFAs.
  • Demonstrated the existence of non-equivalent implementations for widely used functionals (e.g., Perdew-Burke-Ernzerhof), leading to differing total energies.
  • Highlighted the necessity of converged numerical parameters, particularly quadrature grids, for achieving high precision (≲0.1 μEh) in total energy calculations.

Conclusions:

  • A standardized verification framework is essential for the reliable implementation of DFAs.
  • Achieving sub-μEh precision requires equivalent DFA implementations and the availability of reference source code.
  • Ensuring DFA reproducibility is vital for the advancement of chemistry and materials science.