CAREER: Develop a Hybrid Adaptive Particle-Field Simulation Method for Solutions of Macromolecules and a New Computational Chemistry Course for Lower-Division Undergraduates

Harvey Mudd College, Claremont CA

Investigators

Abstract

With support from the Chemical Theory, Models and Computational Methods (CTMC) program in the Division of Chemistry, Dr. Bilin Zhuang of Harvey Mudd College is developing a hybrid simulation method to simulate large molecules in solution. All-atom simulations have become an indispensable tool for studying interactions between molecules, but they are very costly for systems of large molecules in solution, such as polymers and protein assemblies. To enable these simulations, Dr. Zhuang and her research group will work to develop a simulation method that can greatly reduce the number of solvent molecules described with molecular detail while capturing the correct solute-solvent interactions and dynamics. This method is expected to provide a convenient and accelerated tool for simulating large molecules in solution ranging from simple ions to proteins. Achieving these goals will also involve training undergraduates and high school students in computational research and developing a new computational chemistry course for first-year undergraduate students. The new course will 1) introduce the broad usage of computation in chemistry from molecular modeling to data sciences, 2) engage students in active discovery through collaborative research-oriented projects, and 3) create introductory-level teaching resources that use computation to facilitate student learning. This is seen as filling a need as such courses are still scarce in the chemistry teaching community. The new hybrid adaptive particle-field simulation method being developed in this research is expected to make a meaningful contribution to the toolbox of available computational chemistry tools for chemists in all subdisciplines. The simulation method will exploit the equivalence between particle-based and field-based representations in statistical mechanics, allowing one to treat molecules in selected regions of space with more molecular detail (particle-like) and in other regions with fewer molecular details (field-like). The particle-like and field-like regions may adapt to the conformation of the large molecule on the fly, with no abrupt boundary between the regions. The PI has derived the partition function for the proposed method and will achieve the research objectives by implementing and validating the simulation scheme and applying the method to investigate polyelectrolyte brushes and peptide hydrogels. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.