Algorithmic Design of Geometric Data for Molecular Potential Energy Surfaces

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Quantum Chemistry

Background:

• Potential energy surfaces (PESs) are crucial for understanding molecular behavior and reactions.
• Calculating accurate PESs requires comprehensive sampling of molecular geometries.
• Existing methods can be computationally intensive, especially for complex molecules.

Purpose of the Study:

• To introduce MolecGeom, a novel code for generating molecular geometries.
• To develop an efficient method for calculating potential energy surfaces (PESs).
• To analyze the impact of incremental geometric changes on PES precision.

Main Methods:

• MolecGeom employs algorithms for stepwise distortions of bond lengths, angles, and dihedral angles.
• It calculates PESs based on the Born-Oppenheimer approximation.
• The code generates geometric data for theoretical calculations of molecular properties.

Main Results:

• MolecGeom successfully generated PESs for water and formaldehyde, yielding vibrational frequencies with high accuracy (errors < 0.8%).
• A PES for vinyl alcohol with 14 internal coordinates comprised 1458 unique geometries.
• A PES for ascorbic acid with 54 internal coordinates involved 1,899,776 points.

Conclusions:

• MolecGeom provides a robust and precise method for generating extensive PES data.
• The code facilitates accurate theoretical predictions of molecular properties, including vibrational spectra.
• This approach enables comprehensive sampling of molecular configurations for complex systems.