Crystal Structure Prediction for Benzene Using Basin-Hopping Global Optimization.

Area of Science:

• Crystallography
• Computational Chemistry
• Materials Science

Background:

• Organic molecules exhibit polymorphism, existing in multiple crystalline forms.
• Polymorphism significantly impacts industrial applications and material properties.

Purpose of the Study:

• To computationally predict the polymorphic crystal structures of benzene.
• To assess the efficacy of an adapted basin-hopping global optimization method for crystal structure prediction.

Main Methods:

• Developed an accurate anisotropic model for crystalline benzene, parameterized using electronic structure calculations.
• Adapted the basin-hopping global optimization algorithm to simultaneously optimize molecular coordinates and unit cell parameters.
• Explored various crystal space groups to locate low-energy polymorphs.

Main Results:

• Successfully identified all known experimental polymorphs of benzene.
• Each experimental polymorph corresponded to a unique local energy minimum within the computational model.
• The basin-hopping method demonstrated efficiency and effectiveness in predicting polymorphic structures.

Conclusions:

• The adapted basin-hopping method is a powerful tool for polymorphic crystal structure prediction.
• This computational approach requires no prior experimental knowledge of cell parameters or symmetry.
• The findings support the use of basin-hopping for exploring the conformational landscape of crystalline materials.