Yudan Liu

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Year
2020-2021

Research Description
Charge transfer dynamics via mapping methods and generalized quantum master equation

Mentor
Prof. Eitan Geva, Chemistry

Dominika Zgid

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Dominika Zgid is an Associate Professor in the Department of Chemistry and in the Department of Physics. Her group bridges the fields of chemistry, physics and material sciences seeking to explain and predict the electronic movement in finite molecular systems and infinite crystalline materials. They develop new theoretical approaches that will advance current theoretical tools in chemistry that can be applied to a variety of industrial applications.

Paul Zimmerman

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From elementary chemical reactions to exciton dynamics in solar cells, chemistry is a particularly rich field for atomistic simulation. Research in the Zimmerman group develops and employs a broad spectrum of computational techniques to chemical problems. Special emphasis is taken on creating new, practical computational methods for application to problems that are considered out-of-reach to standard simulation methodologies. For instance, automated prediction of chemical reactions has long been considered impossible using quantum chemical simulation. To break this limitation, the Zimmerman group is creating new techniques for locating reaction paths and products of catalytic reactions, with the goal of predicting the outcome of reactions prior to experiment. These tools use a combination of chemical intuition, applied mathematics, and massively parallel computation to achieve an impressive level of automation and predictive value.

Automatically generated growth pattern of a chemical reaction network involving a hydrogen storage material, NH3BH3.

Automatically generated growth pattern of a chemical reaction network involving a hydrogen storage material, NH3BH3.

Aaron Frank

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In order to understand the relationship between molecular structure and dynamics and biological function, the Frank research group seeks to develop and deploy integrative modeling tools to elucidate the structure and dynamics of biologically relevant molecules. Our methods will utilize readily accessible experimental observables from a variety of sources to first guide structure prediction efforts and then guide atomistic simulations to map the entire conformational landscape of these molecules. We are primarily interested in using our methods to understand how functional ribonucleic acids, either by themselves or in concert with other molecules, achieve specific cellular functions. Our research makes heavy use of advanced machine learning  and  optimization techniques.

Integrative modeling and simulations of biomolecules

Integrative modeling and simulations of biomolecules

Charles Brooks

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Charles L. Brooks III is the Warner-Lambert/Parke-Davis Professor of Chemistry and a Professor of Biophysics. He is affiliated with the department of Chemistry, Biophysics Program, program in Applied Physics, Molecular Biophysics Training Program (Director), program in Chemical Biology, Bioinformatics Graduate Program, Center for Computational Medicine and Bioinformatics and the Medicinal Chemistry Interdepartmental Graduate Program. The research in the group of Charles L. Brooks III is focused on the application of statistical mechanics, quantum chemistry and computational methods to chemically and physically oriented problems in biology. The group develops and applies computational models to studies of the dynamics of proteins, nucleic acids and their complexes, including virus structure and assembly. They specifically develop novel computational methods for the inclusion of pH effects in modeling biological systems. Significant focus is in the development of a large, world-wide distributed software package for molecular simulations, CHARMM. Efforts are ongoing to explore new means of parallel and accelerated computation utilizing scalable parallel algorithms for molecular dynamics and integrated CPU/GPU computational models.