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Improved grid-based algorithm for Bader charge allocation.

Edward Sanville1, Steven D Kenny, Roger Smith

  • 1Department of Mathematical Sciences, Loughborough University, Loughborough LE11 3TU, United Kingdom. e.sanville@lboro.ac.uk

Journal of Computational Chemistry
|January 24, 2007
PubMed
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This study introduces an improved Bader analysis algorithm for calculating atomic properties, enhancing accuracy and robustness in charge density partitioning for computational chemistry. The method offers linear scaling and precise Bader surface calculations, enabling reliable energy per atom definitions.

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • The theory of Atoms in Molecules (AIM) provides a framework for understanding atomic properties within a molecule.
  • Bader analysis is a method used to partition electron charge density among atoms.
  • Existing grid-based algorithms for Bader analysis, such as that by Henkelman et al., have limitations in accuracy and computational efficiency.

Purpose of the Study:

  • To propose an improved grid-based algorithm for calculating Bader volumes.
  • To enhance the accuracy of atomic property calculations based on the theory of Atoms in Molecules.
  • To develop a more robust and efficient method for partitioning charge density.

Main Methods:

  • An improved grid-based algorithm is suggested, building upon the method of Henkelman et al.

Related Experiment Videos

  • The new algorithm corrects systematic deviations from the true Bader surface.
  • The method does not require explicit representation of interatomic surfaces, improving robustness.

    • Main Results:

    • The improved algorithm more accurately calculates atomic properties according to AIM.
    • The computational time scales linearly with the number of interatomic surfaces.
    • Systematic deviations from the true Bader surface are corrected.

    Conclusions:

    • The enhanced algorithm provides a more accurate and robust method for Bader analysis.
    • The linear scaling of CPU time makes the method efficient for larger systems.
    • The method facilitates the definition of energy per atom in ab initio calculations.