Professor of Department of Chemical & Biomolecular Engineering; Professor of Department of Chemistry
Energy-efficient chemical transformations and separations are key to solving our society’s many issues toward substantiality. The long-term goal of the Jiang Research Group is to achieve data-driven design and discovery of functional materials and molecules for a sustainable society. By leveraging great advances in computing hardware and software as well as in machine learning and artificial intelligence, we hope to discover new materials and molecules that help solve our society’s issues in energy and the environment. More specifically, the Jiang Group conducts research in the following areas: (a) computational nanocatalysis for transformations of alkanes and oxygenates; (b) simulations of molecular and ionic separations including carbon capture and rare-earth separations; (c) design of electrode materials and understanding of solid/liquid interfaces for anion-storage batteries. We employ a suite of methods, from first principles density functional theory, to atomistic molecular dynamics and Monte Carlo simulations, to machine learning and data-driven discovery.
“One of my research goals and interests is to achieve nano with atomic precision,” said Jiang. “I believe this is going to be important in the coming decade, as the semiconductor industry is approaching 1 nm in manufacturing. Joining VINSE allows me to share my research and vision in nano with the VINSE colleagues and students.”
Learn more about De-en and his research group