LEAPS-MPS: Stochastic Particle-Continuum Hybrid Simulation Method for Model Heterogeneous Catalysts under Reaction Conditions

University Of California - Merced, Merced CA

Investigators

Abstract

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). In this project, funded by the Mathematical and Physical Sciences Directorate and housed in the Chemistry Division, Professor Changho Kim and his students at the University of California, Merced (UCM) will develop an improved method for simulating complex chemical reactions on computers. Many important chemical processes, from synthesizing fuel to cleaning exhaust, involve so-called catalysts, added chemicals which make the reaction proceed faster, with fewer unwanted byproducts. Developing improved catalysts is very challenging, especially “heterogeneous catalysts” which are used in reactions combining gas, liquid, and/or solid chemicals. The outcome of the research will be computer models of heterogeneous catalysts that can help explain how they work and guide the design of improved versions. As they are developed, these computer simulations will be tested against experimental results on reactions involving heterogeneous catalysts. This project will provide research opportunities as well as extracurricular activities for undergraduate students at UCM, which is a Minority-Serving Institution. Additionally, Prof. Kim will create and lead educational activities for local K-12 teachers and students, demonstrating how math is used to understand chemistry. These efforts will contribute to improving science education in California’s ethnically and economically diverse Central Valley and help increase the regional STEM workforce. Professor Kim will develop a stochastic hybrid method that efficiently simulates gas-solid interfacial systems. To this end, this project will couple the kinetic Monte Carlo method (for an atomistic-resolution description of chemical reactions on the catalytic surface) with the fluctuating hydrodynamics method (for hydrodynamic transport at the mesoscopic scale). In this way, intrinsic thermal fluctuations present in the particle description of surface chemistry can be seamlessly coupled with the continuum description of the gas phase. Prof. Kim will develop a scalable implementation strategy that can be used efficiently on high-performance computing platforms, and he will perform theoretical and experimental validations using the example of carbon monoxide oxidation on metal surfaces. 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.