Structural optimization of molecular clusters with density functional theory combined with basin hopping

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Physical Chemistry

Background:

• Determining the lowest energy configurations of molecular clusters is computationally intensive.
• Traditional methods rely on empirical force fields, which may lack accuracy or applicability for certain systems.

Purpose of the Study:

• To develop and validate a novel computational approach for molecular cluster optimization.
• To eliminate the need for empirical force fields in exploring cluster energy landscapes.

Main Methods:

• Implementation of a basin hopping search algorithm.
• Integration with density functional theory (DFT) calculations.
• Application to neutral and protonated water and methanol clusters using B3LYP+D/6-31+G*.

Main Results:

• Successfully optimized molecular clusters without empirical force fields.
• Predicted a new lowest energy structure for protonated water cluster H(+)(H(2)O)(7).
• Demonstrated that protonated methanol is favored over water in mixed clusters.

Conclusions:

• The combined basin hopping and DFT method offers a robust alternative to empirical force fields.
• This approach enhances the accuracy and scope of molecular cluster energy minimization.
• Protonation strongly influences the aggregation behavior of mixed water-methanol systems.