Cong Liu

Argonne National Laboratory

Hosted by: Dr. Wenyu Huang

**Physical/Inorganic**

Abstract:

"Understanding the Heterogeneity and Dynamic Evolution of Supported Catalysts via Combined XANES Simulations and First-principle Mechanistic Studies."

Single-site heterogeneous catalysts (e.g., single-atom catalysts, supported organometallics and metal hydrides, etc.) have gained increasing attention in both industry and academia, integrating crucial aspects of homogeneous catalysis (high activity and selectivity) with the stability of heterogeneous catalysts. Because high-surface-area supports are usually preferred in synthesizing these catalysts, a lot of these catalysts often present high heterogeneity in the catalytic sites, resulting in a distribution of active-site structures and site-specific activities. Meanwhile, some of these catalysts may not be stable under reaction condition and can experience dynamic evolution during catalysis. In situ spectroscopic characterization (e.g., X-ray absorption spectroscopy (XAS)) is an effective technique to characterize supported catalysts under reaction conditions. In XAS, X-ray Absorption Near Edge Spectroscopy (XANES) spectra contains key information on the local coordination environment of the metal atom(s), and thus the analysis of which is more challenging. Some key characteristics of the metal centers and their coordination environment can be directly extracted from the experimental XAS, such as average oxidation state and coordination number. However, certain bonding interactions that are key to catalysis, such as metal-hydride, often present only subtle features in XANES spectra, and these are challenging to interpret directly from experimental spectra. In addition, interpreting XANES spectra of supported catalysts with high site heterogeneity is particularly difficult. This is because XAS measures all the catalytic sites, and the response from this technique is dominated by the sites with the highest volumetric density. However, the overall activity is dominated by the sites with the highest turnover frequencies, not necessarily those with the highest density. Computational XANES simulations offer a powerful technique for interpreting experimental spectra, providing a one-to-one correspondence between the molecular structure and spectral features. In this talk, we will discuss about our recent work on a supported organovanadium catalyst and a supported single-atom Cu catalyst to demonstrate that when integrated in situ and computational XANES analyses are combined with systematic mechanistic simulations, the most active catalytic site in dynamic and disordered catalytic systems can be identified. 

Bio:

Cong Liu is a Chemist in Chemical Sciences and Engineering (CSE) Division at Argonne National Laboratory. She received her Ph.D. degree in Physical Chemistry at University of North Texas in 2013. She was then awarded the Argonne Director’s Fellowship in Materials Science Division (MSD) at Argonne. She became Assistant Chemist of CSE in 2016, and Chemist in 2021. She is also a Consortium for Advanced Science and Engineering (CASE) Fellow at University of Chicago, as well as Courtesy Faculty in Department of Chemistry at Oregon State University. She is currently a PI of an FECM-funded Consortium for CO2 Capture and Utilization, and a co-PI of various BES funded programs, including Catalysis Science Program, Selective Interface Reaction Program, Computational Chemical Science (CCS) Program, and Clean Energy Technologies and Low-Carbon Manufacturing Program. Her research focuses on computational materials and catalyst design, and development and application of computational methods for excited states simulations. Her interests cover fundamental perspectives of in catalytic C-H activation, C-C activation/formation, atomic layer deposition reactions, fuel cell reactions, and CO2 reduction, as well as development of battery materials. Her research has resulted in over 60 publications with nearly 6000 citations, including some of the most prestigious journals like Science and Nature, etc.