Dispersion-Corrected Spin-Component-Scaled Double-Hybrid Density Functional Theory: Implementation and Performance...

Area of Science:

• Computational chemistry
• Quantum chemistry
• Materials science

Background:

• Accurate prediction of interaction energies is crucial for understanding molecular behavior.
• Existing density functional theory (DFT) methods face challenges in precisely calculating these energies.
• Developing cost-effective and accurate computational methods remains a significant challenge.

Purpose of the Study:

• To implement and assess 300 combinations of dispersion-corrected spin-component-scaled double-hybrid (DSD) DFT methods.
• To extend the DSD-DFT framework with the resolution of identity (RI) approximation for improved cost-effectiveness.
• To evaluate the performance of these new methods, termed RI-DSD-DFTs, across diverse non-covalent interactions.

Main Methods:

• Implementation of 300 generalized gradient approximation/local density approximation exchange-correlation DSD-DFT methods.
• Incorporation of the resolution of identity (RI) approximation to reduce computational cost.
• Validation using seven data sets covering a wide spectrum of non-covalent interactions.

Main Results:

• The DSD-DFT methods achieved root-mean-square deviations and mean absolute errors within 0.5 kcal/mol for interaction energies.
• The cost-effective RI-DSD-DFT methods showed minimal deviation (less than 0.18 kcal/mol on average) while using only 2% of the computational cost.
• Perturbative treatment of correlation effects significantly enhanced the description of weak interactions.

Conclusions:

• The developed RI-DSD-DFT methods offer a highly accurate and computationally efficient approach for predicting interaction energies.
• These methods represent a significant advancement in computational chemistry, particularly for studying non-covalent interactions.
• The flexibility of the RI-DSD-DFT framework allows for further development and application in various chemical and materials science fields.