Method Calibration or Data Fitting?

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Density functional methods are widely used in computational chemistry.
• Basis sets are crucial for the accuracy of these calculations.
• Understanding error compensation is vital for reliable predictions.

Purpose of the Study:

• To investigate error compensation in density functional methods using polarized double-ζ basis sets.
• To determine the impact of basis set parameterization on method performance.
• To assess if basis set choices can mask underlying method deficiencies.

Main Methods:

• Explicit parameter optimization of basis sets.
• Evaluation across five different density functional methods.
• Testing on nuclear magnetic shielding constants, isomerization energies, barrier heights, and noncovalent interactions.

Main Results:

• Minor adjustments in basis set contraction coefficients significantly impact performance.
• Different density functional methods achieve comparable results due to basis set compensation.
• Errors from vibrational and solvent effects can be absorbed by method/basis set combinations.

Conclusions:

• The practice of selecting method-basis set combinations may function as data fitting.
• Basis set flexibility can obscure true method performance.
• Re-evaluation of standard benchmarking practices is warranted.