Dr. Peng Xu, Ames Lab

Many interesting phenomena occurring in condensed phase or at the interface require good description of both local and long-range effects. High-level quantum mechanical methodologies, which can provide accurate descriptions of both intra- and intermolecular interactions, are often out of reach for such large systems due to very high computational demands. Quantum mechanics-based fragmentation approaches offer a viable alternative to probe such large systems, balancing accuracy and computational efficiency. In this talk, three fragmentation approaches will be discussed, highlighting their capabilities to capture many-body effects, higher order dispersion, as well as flexibilities of treating both chemically bonded systems and intermolecular interactions. Computational scalability can be achieved by taking advantage of inherent parallelism of fragmentation, as well as efficient parallel implementation of component calculations. Given good accuracy and scalability, we aim to combine the fragmentation approaches with simulation techniques such as Monte Carlo to probe the complex, coupled processes occurring at interfaces in the carbon dioxide removal processes.

Peng Xu is an associate scientist at Ames Laboratory, Ames, Iowa. Her research interests lie broadly in the development of efficient and accurate methods for intermolecular interactions, study of solvent effects in chemical and biological systems, development of computational tools for study of protein−ligand and host−guest systems, and high-performance algorithms on novel computing architectures. Peng Xu earned her Bachelor of Science degree in chemistry and Biochemistry from University of Sydney in 2007 and her Ph.D. in 2014 from Iowa State University under the supervision of Dr. Mark S. Gordon. For her postdoctoral studies at Cornell University from 2014 to 2016, she was co-supervised by Dr. Roald Hoffmann and Dr. Neil Ashcroft for the study of diradicals and extended systems under high pressure. From 2016−2018, for her second postdoctoral studies, she developed interests in high performance computing under the supervision of Dr. Mark S. Gordon. Now she is developing computational tools for modeling carbon capture processes.

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