Gregory Beran of the University of California at Riverside is supported by an award from the Chemical Theory, Models and Computational Methods program to develop a computational method that enables the efficient and reliable prediction of molecular crystal structures and properties. The model will combine a quantum mechanical treatment of individual molecules and their dominant interactions with a classical treatment, while weaker interactions are being approximated using a computationally inexpensive classical polarizable force field. This project has three principle objectives: to develop the model into a practical computational tool, to benchmark the performance of the model on a set of well-studied molecular crystals, and to apply this model to several challenging crystal structure prediction problems.
This research will help make it possible to predict, before any experiments are performed, how molecules pack together in solid-state crystals. Crystal packing affects useful properties such as the solubility of pharmaceuticals in the body, the charge-carrier performance of organic semi-conductor materials, the detonation of energetic materials, and efficiency of solid-state chemical reactions. The research will provide new insights into the physical interactions that govern crystal packing and into how these can be controlled to design new high-performance molecular materials.
