Location：Meeting Room on 3rd Foor of SKLC
Pacific Northwest National Laboratory
Developing multi-scale computational modeling capability that enables us to improve the performances of the catalysts, and invent new catalytic processes and technologies is vital for economically converting coal- and biomass-derived resources to low-carbon energy platforms such as synthetic natural gas, transportation fuels, and other valuable chemicals. Since heterogeneous catalytic phenomena span a wide range of time and length scales, a full description of a practical heterogeneous catalytic system from the microscopic to the macroscopic level needs multi-scale computational modeling. On each scale the computational model deals with different time and length regime by using different computational chemistry theories and statistical mechanical simulation models. In particular, first-principles density functional theory (DFT) calculations are used for exploring unbiased reaction mechanisms and determining the thermodynamics and the kinetics of elementary reaction steps over the well-defined catalyst surfaces; kinetic Monte Carlo (KMC) simulations with DFT-determined kinetic information are then used predicting the macroscopic reaction kinetics over supported catalyst materials under operating reaction conditions. Finally, by integrating DFT-based KMC with stochastic partial differential equation theory (SPDE), which is used for describing mass and heat transfer around the catalyst surface, a multi-scale multiphase reactor model is developed to predict the global catalytic performance in industrial reactors. In this talk, we will discuss the above computational model via specific reaction systems such as methanol synthesis from CO2 hydrogenation on Cu(111) surface, reaction kinetics of nitric oxide on the three-dimensional platinum nanoparticles under lean-burn conditions, and CO oxidation on the RuO2(110) surface with mass and heat transfer.
Dr. Donghai Mei obtained his bachelor degree in chemical engineering from Northwest University (Xi An city, Shaanxi province) in china in 1986. After graduation, he worked as an engineer in a chemical factory for four years. He obtained his master and Ph. D degrees from Beijing University of Chemical Technology (1993) and University of Petroleum China (1996), all in chemical engineering. Before He holds the current scientist position at Pacific Northwest National Laboratory in 2006, he did his postdoctoral research in Tsinghua University and University of Virginia. Dr. Mei’s major research expertise focuses on the quantitative understanding of molecular-level reaction mechanisms underlying the macroscopic phenomena in chemical transformation processes, envisioning rational design of novel catalysts and improvement of renewable energy production and storage technologies. Of particular relevance are hierarchically multi-scale modeling and simulations across all relevant time and length scales. He had published 68 papers on the peer-reviewed journals including Science, JACS, Nano Letters, and Journal of Catalysis, etc.