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Balance between Physical Interpretability and Energetic Predictability in Widely Used Dispersion-Corrected Density

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Empirical dispersion models in density functional theory show unpredictable performance across various systems due to parameter fitting. A targeted-dispersion approach improved molecular crystal lattice energies but not structural properties.

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Area of Science:

  • Computational Chemistry
  • Materials Science

Background:

  • Noncovalent interactions are crucial in molecular systems.
  • Density functional theory (DFT) is widely used in computational sciences.
  • Accurate modeling of dispersion forces is essential for DFT accuracy.

Purpose of the Study:

  • To evaluate the performance of various dispersion models for popular density functionals.
  • To analyze the accuracy of these models across diverse noncovalent systems.
  • To identify limitations and potential improvements for dispersion modeling in DFT.

Main Methods:

  • Assessed dispersion model performance using interaction energies and energy decomposition analyses.
  • Tested models on systems ranging from molecular dimers to crystal lattices.
  • Compared empirical dispersion models with a targeted-dispersion approach (SCAN-rVV10).

Main Results:

  • Empirical dispersion models exhibit system-dependent variability and rely on error compensation.
  • The revPBE-D3 model showed accuracy in some aqueous systems due to error compensation but failed for the benzene dimer.
  • SCAN-rVV10 significantly reduced errors in molecular crystal lattice energies but had limited accuracy for structural properties.

Conclusions:

  • Parameter fitting in empirical dispersion models can obscure underlying physics.
  • Unpredictable behavior of dispersion-corrected functionals across systems necessitates careful model selection.
  • Future dispersion models should prioritize a faithful description of dispersion energy for improved accuracy in diverse systems.