CAREER: Microkinetic Modeling-Driven Discovery of Molecular Catalysts

With support from the Chemical Catalysis Program in the Division of Chemistry, Tibor Szilvási of the University of Alabama-Tuscaloosa is focusing on computational tools that empower the design of efficient molecular catalysts. Dr. Szilvási will develop computational methods to investigate catalytic reactions relevant to the chemical industry.

His research group will be using high-performance computational screening to identify optimal catalyst structures, compositions, and kinetics to increase overall activity, selectivity, and stability. Dr. Szilvási will also design a new course that is designed to provide advanced programming expertise to undergraduate students in chemical engineering.

This training will help prepare students for computationally focused jobs in the chemical sciences. Additional lesson plans will be developed for teaching programming to high school students and to help encourage underrepresented minority students to pursue advanced degrees.

This proposed work will involve electronic structure calculations and microkinetic modeling to accelerate the design of molecular catalysts, with an emphasis on obtaining quantitative agreement between experiments and simulations. The PI will develop and use microkinetic modeling to analyze reaction networks and transform computational data into a standard format often used in kinetic measurements.

This will enable direct benchmarking and verification between kinetic measurements and simulations in an easily accessible manner, which will be understandable to experimentalists who are not experts in computations. This proposal will address the mentioned challenges and focus on three systems: (i) nitrogen fixation using biomimetic organometallic complexes; (ii) hydrogen activation using main group catalysts; and (iii) light-driven carbon dioxide (CO2) reduction.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.