Abstract

Developing efficient heterogeneous catalysts plays a crucial role in solving many grand challenges humanity faces. In recent decades, first-principles modeling has been widely used to understand various catalytic systems. Still, the rational design of new solid catalysts remains elusive, mainly due to the huge gap between the highly simplified theoretical models and real catalytic systems studied experimentally. In this talk, I will present our recent efforts in developing efficient computational approaches that aim at the realistic treatment of heterogeneous catalytic materials. For catalytic surfaces with configurational disorder, such as bimetallic surfaces and transition metal carbides with significant carbon vacancies, we have developed systematic schemes that combine cluster expansion (CE) and machine-learning force field (MLFF) to model the structure and stability of configurationally disordered surfaces at finite temperature. We have also explored the utility of the large atomic model (LAM)-based MLFF for theoretical modeling of complex catalytic systems with iron carbides (FeCx) used in Fischer-Tropsch synthesis as an example.

[1] J.-Z. Xie, X.-Y. Zhou, H. Jiang, J. Chem. Phys. 157, 200901 (2022).  

[2] D. Luan, H. Jiang, J. Chem. Phys. 154, 074702 (2021).

[3] J.-Z. Xie, X.-Y Zhou, D. Luan, H. Jiang, J. Chem. Theory Comput. 18, 3795 (2022).

[4] J.-Z. Xie and H. Jiang, J. Phys. Chem. C 127, 13228 (2023).

Biography

Dr. Hong Jiang is a tenured associate professor at the College of Chemistry and Molecular Engineering at Peking University. He obtained his Bachelor's degree and Ph. D. in chemistry from Peking University in 1998 and 2003, respectively. During 2001-2004, he worked at Duke University, first as a visiting student and then as a postdoctoral researcher. During 2004-2009, he worked as a postdoctoral researcher, first at the University of Frankfurt and then at the Fritz Harber Institute of the Max Planck Society in Germany. Dr. Jiang's research interests focus on developing first-principles approaches to electronic excitations and strong correlation in materials and their applications to advanced functional materials.