Our group leverages data science, statistical mechanics, molecular modeling, and machine learning tools to design and discover new materials and address some of society’s most pressing technological needs. We also collaborate with other groups in the United States and around the world to develop and deploy new technologies.
Materials Discovery, Design, and Characterization
Though new materials may be identified computationally, predicting the conditions that will lead to their realization remains a challenge. We model the self-assembly processes of materials to aid synthetic chemists realize novel materials and morphologies necessary in various applications. We also characterize the physical, mechanical, and chemical properties of materials like zeolites, metal-organic frameworks (MOFs), soft porous coordination polymers, ionic liquids, etc.
Gas Adsorption and Separations
Porous materials have the capacity to store significant amounts of gas in their pores. Interactions in the pores can also be tailored to attract certain gases over others and can thus also be used as a platform to perform separations. We use molecular simulations to characterize and design the interactions for applications in hydrogen storage, methane storage, water harvesting, and gas separations.
Navigating Material and Thermodynamic Landscapes
The number of possible materials for any given application is virtually limitless. In addition, applications of interest like sensing, quantum technologies, separations, etc. require studies at multiple conditions or expensive calculations. We develop algorithms and strategies to efficiently navigate the material and condition space to provide structure-property relationships and identify promising synthetic candidates.