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This study evaluates 59 exchange-correlation functionals for molecular structures. Recently developed double hybrids and global hybrids show high reliability, with M06-L being a notable semilocal exception.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Accurate prediction of molecular structures is crucial in chemistry and materials science.
  • Exchange-correlation functionals are key components of density functional theory (DFT) methods.
  • Evaluating functional performance across different molecular systems is essential for method selection.

Purpose of the Study:

  • To conduct an error analysis of 59 exchange-correlation functionals.
  • To assess their performance in predicting structural parameters of organic molecules.
  • To compare their accuracy with energetic properties.

Main Methods:

  • Systematic evaluation of 59 exchange-correlation functionals.
  • Analysis of structural parameters for small- and medium-sized organic molecules.
  • Comparison of structural errors with errors on energetic databases.

Main Results:

  • Double hybrid functionals (e.g., xDH-PBE0) demonstrated the highest reliability for structural predictions.
  • Global hybrid functionals maintained robust performance in reproducing molecular structures.
  • The M06-L density functional was the only semilocal method achieving hybrid-level accuracy.
  • Most functionals exhibited consistent performance across both structural and energetic evaluations.

Conclusions:

  • Advanced functionals like double hybrids offer superior accuracy for molecular structure prediction.
  • Global hybrids remain a reliable choice for structural calculations.
  • M06-L presents a promising semilocal alternative.
  • Functional performance is generally coherent between structural and energetic properties.