The innovation engine for new materials

Structure Prediction and Discovery of Molecular Crystals with Enhanced Electronic Properties

Seminar Group: 


Professor Noa Marom


Dept. of Materials Science and Engineering
Carnegie Mellon University


Friday, November 15, 2019 - 11:00am


ESB 1001


Prof. Chris Palmstrom

Quantum mechanical simulations are combined with genetic algorithm optimization and machine learning to predict the structure of molecular crystals and to discover molecular crystals with enhanced electronic and optical properties for applications in organic electronic and photovoltaic devices.

Molecular crystals are bound by dispersion (van der Waals) interactions, whose weak nature generates potential energy landscapes with many local minima that may be extremely close in energy. This often results in polymorphism, the crystallization of the same molecule in several different structures. Crystal structure may profoundly influence the physical and chemical properties, including the electronic and optical properties relevant for device applications. We perform large scale quantum mechanical simulations to predict the structure of molecular crystals and discover molecular crystals with enhanced electronic and optical properties. 

To perform structure search, we develop the genetic algorithm (GA) code, GAtor. GAs rely on the evolutionary principle of survival of the fittest to perform global optimization. GAtor offers a variety of crossover and mutation operators, specifically designed for molecular crystals, to create offspring by combining/ modifying the structural genes of parent structures. GAtor achieves massive parallelization by spawning several GA replicas that run in parallel and only interact via a shared population of structures. Multimodal optimization is achieved by using evolutionary niching to enable the simultaneous evolution of several subpopulations. Machine learning is used for dynamic clustering of the population. A cluster-based fitness function is then employed to steer the GA to under-sampled low-energy regions of the potential energy landscape. Advantageously, the GA fitness function may be any property or combination of properties, not necessarily the energy. We rely on this to search for potential polymorphic structures with enhanced charge carrier mobility. 

An emerging application of molecular crystals is singlet fission (SF), the down-conversion of one photogenerated singlet exciton into two triplet excitons. SF has the potential to significantly increase the efficiency of organic photovoltaics beyond the Shockley-Queisser limit by harvesting two charge carriers from one photon. However, the realization of SF-based solar cells is hindered by the dearth of suitable materials. Using many-body perturbation theory in the GW approximation and Bethe-Salpeter equation (BSE), we have elucidated the effect of crystal packing on the excitonic properties of molecular crystals. To assess the likelihood of new materials to exhibit SF, we have proposed a two-dimensional descriptor based on the thermodynamic driving force for SF and the degree of singlet exciton charge transfer character. To evaluate the latter we have developed the double-Bader analysis method for exciton wave-functions from BSE calculations. We have identified several promising candidates for intermolecular SF in the solid state including monoclinic rubrene, quaterrylene, and phenylated pentacene derivatives.