Noncovalent Interactions in SIESTA Using the vdW-DF Functional: S22 Benchmark and Macrocyclic Structures.

Area of Science:

• Computational Chemistry
• Materials Science
• Quantum Mechanics

Background:

• Accurate prediction of non-covalent interactions is crucial in chemistry and materials science.
• Traditional density functional theory (DFT) methods often struggle to capture van der Waals (vdW) dispersion forces.
• The van der Waals Density Functional (vdW-DF) approach offers a promising solution for describing these interactions.

Purpose of the Study:

• To evaluate the performance of the vdW-DF functional, as implemented in the SIESTA code.
• To assess its accuracy for systems with significant vdW interactions, using the S22 dataset and calixarene host-guest complexes.
• To compare vdW-DF results with experimental data and other computational methods.

Main Methods:

• Utilized the vdW-DF functional within the SIESTA computational code.
• Applied the method to the standard S22 dataset for non-covalent interactions.
• Investigated several calixarene-based host-guest molecular structures.

Main Results:

• The vdW-DF functional demonstrated highly favorable binding energy error statistics on the S22 dataset.
• Performance was found to be competitive with, and often superior to, other dispersion correction methods and vdW-DF implementations in different codes.
• For calixarene systems, vdW-DF generally yielded more accurate structural properties and binding energies compared to previous computational studies.

Conclusions:

• The vdW-DF functional, implemented in SIESTA, is a reliable method for describing van der Waals interactions.
• It provides accurate binding energies and structural properties for molecular systems, including complex host-guest structures.
• vdW-DF represents a significant improvement over many existing DFT methods for non-covalent interactions.