In the last ~20 years computational catalysis started to significantly impact catalysis research by providing a new tool for testing experimental hypothesis and by being able to computationally screen a large number of materials in a reasonably short period of time. In this seminar, I will present a case study illustrating the strengths and challenges of computational catalysis and how some of the challenges can be overcome with the application of data science tools. In particular, I will illustrate recent progress in understanding heterogeneous catalysis at the three-phase boundary of a gas-phase, a reducible oxide surface, and a noble metal cluster or atom. I intend to illustrate the specific role of the three-phase boundary in determining the activity and selectivity of TiO2 supported Pt catalysts for the water-gas shift (CO + H2O à CO2 + H2) reaction. We find that for heterogeneously catalyzed reactions with more than one key surface intermediate, multiphase catalysts have a significant advantage over conventional monophase catalysts since each phase can potentially be adjusted independently to activate a key reaction step. Next, I illustrate a novel procedure based on Bayesian statistics for properly integrating computational models with experimental observations with the aim of identifying the active site for catalysis. Water-gas shift models obtained from density functional theory for a large Pt particle, a small Pt cluster on a TiO2 support and an isolated (positively charged) Pt atom on TiO2 will be correlated with experimental data from various research groups to determine the active site for catalysis.
Dr. Heyden received his Ph.D. in chemical engineering from Hamburg University of Technology, Germany, under the supervision of Profressor Fred Keil and Professor Alex Bell (UC Berkeley) in 2005. After a Postdoc in Minnesota in theoretical chemistry under the supervision of Professor Don Truhlar, he joined the University of South Carolina in 2007. His main research areas are computational catalysis at metal-support interfaces and at solid-liquid interfaces, high temperature electrocatalysis, and the development of novel data science and multi-scale modeling strategies and their application to (electro-) catalytic systems. For his research, he has been awarded the 2013 NSF CAREER award and USC’s Breakthrough Rising Star, Young Investigator, Research Progress, and Research Achievement awards.