De Novo Catalyst Design for Biopolymer Upgrading

mech fig

The overarching goal underpinning the next phase of this work is to develop fundamental mechanistic studies into a blueprint for the extraction of sustainable chemicals from plants. This will focus on the discovery of enzymatic, heterogeneous, and homogeneous catalysts to selectively activate lignocellulosic biomass (lignin, hemicellulose, and cellulose). Our research first focuses on designing mechanism-driven catalysts for more selective and functionalized structures through biomass upgrading. A graph neural network development will be added to predict the energetics of homolytic bond cleavage in biomass, by training against QM studies of model compounds. This will enable automated mechanistic exploration of possible routes for thermochemical conversion of biomass using realistic models for the first time.

Related Publications

Chemical kinetic basis of synergistic blending for research octane number, Gina M. Fioroni, Mohammed J. Rahimi, Charles K. Westbrook, Scott W. Wagnon, William J. Pitz, Seonah Kim and Robert L. McCormick, Fuel, 307, 121865 (2022)

Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects, Yeonjoon Kim, Ashutosh Mittal, David J. Robichaud, Heidi M. Pilath, Brian D. Etz, Peter C. St. John, David K. Johnson, and Seonah Kim, ACS Catalysis, 10, 24, 14707-14721 (2020).

Different Behaviors of a Substrate in P450 Decarboxylase and Hydroxylase Reveal Reactivity-Enabling Actors, Vivek S. Bharadwaj, Seonah Kim, Michael T. Guarnieri, Michael F. Crowley, Scientific Reports, 8, 12826 (2018).

Quantum Mechanical Calculations suggest that Lytic Polysaccharide Monooxygenases employ a Copper-oxyl, Oxygen-rebound Mechanism, Seonah Kim, Mats Sandgren, Jerry Ståhlberg, Robert S. Paton, Gregg T. Beckham, PNAS, 111, 149-154 (2014)