Novel method for geometry optimization of molecular clusters: application to benzene clusters

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Physical Chemistry

Background:

• Determining the optimal geometry of molecular clusters is crucial for understanding their properties.
• Nonspherical molecules present unique challenges in predicting stable cluster configurations.
• Existing methods often struggle with efficiency and thoroughness in exploring the conformational space.

Purpose of the Study:

• To develop a heuristic and unbiased computational method for identifying optimal geometries of nonspherical molecular clusters.
• To adapt and apply an existing algorithm for atomic clusters to the more complex case of molecular clusters.
• To investigate the global minima of benzene clusters using the newly developed method.

Main Methods:

• Construction of a novel heuristic and unbiased search method based on an algorithm for Lennard-Jones atomic clusters.
• Utilization of three operators: interior (perturbing central molecules), surface (optimizing surface molecule positions), and orientation (randomizing molecular orientations).
• Selection of molecules for perturbation based on their contribution to the cluster's potential energy.

Main Results:

• Successful application of the method to benzene clusters ((C6H6)n).
• Identification of new global minima for (C6H6)11, (C6H6)14, and (C6H6)15 clusters.
• Reporting of the first-ever determined global minima for (C6H6)16 to (C6H6)30 clusters.

Conclusions:

• The developed method is effective for searching optimal geometries of nonspherical molecular clusters.
• The approach provides new insights into the structural landscape of benzene clusters.
• This work establishes a foundation for exploring larger and more complex molecular systems.