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

Atreyee Banerjee,David J Wales,Samuel P Niblett,Dipti Jasrasaria

doi:10.1021/acs.jpca.1c00903

Abstract

Organic molecules can be stable in distinct crystalline forms, known as polymorphs, which have significant consequences for industrial applications. Here, we predict the polymorphs of crystalline benzene computationally for an accurate anisotropic model parametrized to reproduce electronic structure calculations. We adapt the basin-hopping global optimization procedure to the case of crystalline unit cells, simultaneously optimizing the molecular coordinates and unit cell parameters to locate multiple low-energy structures from a variety of crystal space groups. We rapidly locate all the well-established experimental polymorphs of benzene, each of which corresponds to a single local energy minimum of the model. Our results show that basin-hopping can be both an efficient and effective tool for polymorphic crystal structure prediction, requiring no a priori experimental knowledge of cell parameters or symmetry.

Highlights

Molecular crystals have a variety of applications in pharmaceuticals, pigments, and organic electronics
In the early tests[3−6] it was widely assumed that the experimental crystal structure should be the one that is most thermodynamically stable, so crystal structure prediction (CSP) methods focused on finding the global minimum of the potential energy landscape (PEL) for a crystal
We model benzene using the polycyclic aromatic hydrocarbon anisotropic potential (PAHAP),[12] in which the interaction between two atoms depends on both the distance between them and the orientations of the corresponding molecules

Summary

Introduction

Molecular crystals have a variety of applications in pharmaceuticals, pigments, and organic electronics. Physical properties of polymorphs may differ significantly, with potentially dramatic consequences for the bioavailability and stability of pharmaceuticals,[7] so a good CSP protocol should identify all the low-energy polymorphs rather than the single most-favorable structure. This requirement complicates the problem significantly because identifying multiple stable structures requires exploring high-dimensional configuration space.[1] Most CSP methods use a physically motivated potential energy model to compute the lattice energy of candidate structures, which requires a search for low-energy regions of the PEL

Methods

Results

Conclusion