(147t) Computational Exploration of Single Atom Catalysts Supported on Metal Oxides for Sustainable Hydrogenation Reactions | AIChE

(147t) Computational Exploration of Single Atom Catalysts Supported on Metal Oxides for Sustainable Hydrogenation Reactions

Authors 

Hu, J. - Presenter, Penn State University
My research experience is in heterogeneous catalyst discovery and evaluation using computational tools such as density functional theory (DFT), kinetic modeling, and high-throughput screening. My research focuses on the investigation of single atom transition metal catalysts (SACs) supported on metal oxides, specifically targeting their potential application in selective hydrogenation reactions. I use computational tools to screen for plausible reaction mechanisms and apply rational design principles to optimize these systems. Initially, my work with SACs started due to recent experimental breakthroughs that highlighted their promising activity and selectivity. Despite conventional wisdom dismissing Ag as a poor hydrogenation metal, I helped identify its activity for hydrogen activation and spillover as single atoms supported on anatase TiO2. My research suggests that the vast majority of C-H bond formation on these SACs occurs on the metal oxide rather than the metal. Thus, my work revisits catalysis on bare metal oxides, a field largely popular up until the 1990s, in the context of SACs to evaluate mechanisms and performance using computational tools.

My research studies the feasibility of these catalysts in the context of catalytic upgrading of plastic waste to value-added products. By utilizing DFT, I screen and identify plausible reaction mechanisms for the hydrodeoxygenation of plastic waste-derived aromatics. My research identifies a hydride-facilitated mechanism that guides our fundamental understanding of how C-H bonds form on reducible metal oxide-based SACs. To optimize the performance of these catalysts under realistic reaction conditions, I have developed microkinetic models that evaluate their activity and selectivity. I have also started implementing high-throughput methods to identify suitable transition-metal dopants into our system to enhance its performance. Lastly, I am extending our mechanistic knowledge to propose generalized mechanisms and rational design principles for a diverse range of hydrogenation reactions involved in the production of platform chemicals.

Research Interests

Catalysis and reaction engineering, materials and drug discovery, energy, machine learning, artificial intelligence, process systems engineering.

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