New parameterization scheme of DFT-D for graphitic materials.

Area of Science:

• Computational Chemistry
• Materials Science
• Quantum Chemistry

Background:

• Density-Functional Theory (DFT) with empirical dispersion correction (DFT-D) is widely used for materials modeling.
• Accurate prediction of binding energies and geometries is crucial for understanding graphitic materials.
• Existing DFT-D parametrization schemes may not adequately capture the nuances of graphitic systems.

Purpose of the Study:

• To develop a novel DFT-D parametrization scheme specifically for graphitic materials.
• To incorporate geometry optimization directly within the parametrization fitting process.
• To improve the accuracy of binding energy and structural predictions for graphitic systems.

Main Methods:

• A new DFT-D parametrization scheme was developed.
• The scheme includes an integrated geometry optimization step.
• Parameters were fitted using the benzene dimer as a model system, referencing highly accurate Coupled Cluster Singles Doubles with Perturbation Theory (CCSD(T)) data.

Main Results:

• The new scheme accurately reproduces CCSD(T) binding energies for the benzene dimer, even with small basis sets.
• Geometry optimization within the fitting scheme significantly improves performance compared to other methods.
• The method yields accurate geometries and binding energies, demonstrating its potential for larger graphitic systems.

Conclusions:

• The proposed DFT-D parametrization scheme offers a robust methodology for studying graphitic materials.
• The integration of geometry optimization enhances predictive accuracy for binding energies and structures.
• This approach is expected to provide reliable results for larger and more complex graphitic systems.