Computational, theoretical investigation of materials for a sustainable energy future

Over the past several decades there has been significant progress in electronic structure theory, statistical sampling algorithms and computational resources which can be leveraged to calculate fundamental properties of materials and estimate rates of relevant chemical reactions. In the following dissertation, I use computational methods to address the materials problem of a sustainable energy future.

Energy storage technologies have played a vital role in the mobile-technology revolution and the transition to utilize more sustainable energy sources; however improvements to the energy density, charge/discharge rate, and safety of rechargeable batteries are needed to realize the ambitious goals of fully electric vehicles and on-grid storage in areas with intermittent, renewable power sources. Li-ion batteries, in general, have a potential to fulfill these demands. In the following work, a new, high energy density electrode material with little capacity loss is considered. Additionally, the complex interaction between an electrode/electrolyte model system is considered in a potential dependent computational framework.

Having a sustainable energy future also means utilizing energy-efficient processing in industrial scale applications. Separation processes use roughly 12% of all energy consumed in the United States due to energy-intensive thermal separation techniques. A final study looks at an alloy catalysts for the separation of ethylene from ethane/ethylene mixtures. A unique selectivity property was discovered that may help design catalysts to replace thermal separation of gases.