High-Performance Modeling in the Chemical and Material Sciences

Student Research Assistants: Pavan Kumar Behara, Viswanath Pasumarthi

High-performance computational and data sciences have emerged as critical contibutions to advance and accelerate the discovery of materials that are essential to technological and economical leadership in many domain of modern society. For example, to overcome the challenges of fossil fuel-driven energy utilization, technologies that store electrical energy or convert solar and electrical energies to fuels are emerging as critical to our ability to deploy cost-effective energy equivalents from renewable and inexpensive sources, such as sun, wind, biomass, and carbon dioxide. Our research program in theory, modeling, and simulation, with emphasis on multi-scale, multi-physics, and high performance computing, focuses on key fundamental science topics that limit these technologies. It includes, among others, studies of photo-electro conversions and electrical energy storage.

Our overall research program deals with timely societal challenges in energy, water, and environment. A point of emphasis is the efficient and cost-effective conversion of solar energy to electrical and chemical energies. Current conversion efficiencies, including for solar water splitting, are far from the level needed for practical applications. Our project addresses how the flow of charge carriers in complex crystalline environments of single phase, multi-phase, and multi-materials semiconductor systems can be tailored to enhance redox reactivity in photo-electro-chemical conversion. Our approach to modeling the space-charge distribution dynamics combines first-principles atomistic computation and mesoscale simulation.

We develop unique high-performance simulation tools. We apply these tools to the discovery of materials with superior charge carrier transport and solar energy conversion efficiency. The new tools encompass massively parallel quantum chemical electronic structure computations and mesoscale kinetic simulations. Guided by the application of the mesoscale models for several classes of materials, we also aim to identify through a data science paradigm, structural and chemical descriptors for the discovery materials with superior transport and carrier separation ability and solar conversion performance.