CAREER: Accurate, Reliable, and Routine First-Principles Prediction of the Structure and Stability of Molecular Crystal Polymorphs

Cornell University, Ithaca NY

Investigators

Abstract

Professor Robert A. DiStasio Jr. of Cornell University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop methods which enable accurate and reliable predictions of the structure and stability of molecular crystals. Molecular crystals are ubiquitous and versatile materials that are used in alternative energy and the environmental sciences, pharmaceuticals and medicine, as well as technology and industry. Of crucial importance to these applications is the fact that molecular crystals often have many accessible polymorphs—alternative structures that are nearly identical in stability yet display drastically different physical and chemical properties. When used to improve device performance or enable novel functions in alternative energy applications, these distinct properties can be very beneficial. The existence of polymorphs can also have devastating and potentially catastrophic effects, e.g., when a pharmaceutical agent unexpectedly converts into an unknown (and inactive) polymorph, and thereby reduces the amount of the disease-fighting (and potentially life-saving) form. DiStasio and his research group are developing accurate and reliable methods which use computer simulations to predict the structures and stabilities of molecular crystal polymorphs based on the laws of quantum and statistical mechanics. In doing so, DiStasio is developing a computational framework that addresses new opportunities to use molecular crystal polymorphs in novel energy solutions and pharmaceutical agents. The DiStasio research group is also developing an interactive molecular dynamics (MD) package which allows students at all levels (K-12, undergraduate, and graduate) to visualize the abstract mathematical concepts encountered in chemistry, and to build physical and chemical intuition regarding the complex interplay between observed properties and the microscopic structure of matter. By developing and utilizing state-of-the-art methods that combine quantum and statistical mechanics, numerical analysis, and high-performance computing, DiStasio and his research group are creating a theoretical and algorithmic framework which exploits sparsity to enable highly accurate ab initio molecular dynamics (AIMD) simulations of complex and large-scale condensed-phase systems of interest throughout biology, chemistry, physics, and materials science. This framework simultaneously accounts for the quantum mechanical nature of the electrons (including sophisticated exchange-correlation effects) and the nuclei, as well as realistic experimental conditions (i.e., finite temperatures and pressures), and therefore enables accurate, reliable, and routine predictions of the structures and stabilities of all thermodynamically (and kinetically) relevant molecular crystal polymorphs from first principles. These research efforts pave the way towards an enhanced fundamental understanding of complex polymorphic energy landscapes and the routine use of predictive first-principles based crystal structure prediction, both of which are crucial to accessing the vast and largely unexplored potential of molecular crystals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.