Using High-Performance Computing
to Intelligently Design Nanomaterials
Designing Stable Heterogeneous Catalysts
The deactivation of catalysts under reaction conditions is inevitable; however, great economic impacts could be realized by improving catalyst lifetime. We seek to design materials with improved resistance to deactivation through combining DFT calculations with kinetic Monte Carlo simulations in a structure-sensitive approach, focusing our efforts on catalytic ethane dehydrogenation to ethylene. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support of this research.
Selective Catalytic Conversion of Biologically-Derived Molecules
Sustainable feedstocks in energy applications and consumer products can be made more economically viable by developing frameworks for selective transformations of biologically-derived material, thereby reducing dependence on fossil fuel feedstocks. The multifunctional nature of biomass products motivates the development of computational approaches to selective transformations of these complex molecules. DFT calculations provide a fundamental understanding into the surface chemistry of various conversion reactions, enabling the design of novel catalytic materials with tailor-made surface structures and compositions toward the selective production of high-value chemical products.