CAREER: First Principles Modeling of Solvothermal and Coverage Effects for Selective Deoxygenation on Transition Metal Catalysts

Mississippi State University, Mississippi State MS

Investigators

Abstract

The conversion of biomass into fuels or chemicals often involves catalytic treatment of the bio-derived oil to produce high-value products. Catalyst selection involves a complicated juggling act to identify materials that selectively promote desired chemical reactions while avoiding undesired side reactions. Typically, catalysts are selected through tedious trial-and-error screening of many combinations of materials. In contrast, this project seeks to accelerate the catalyst discovery process through mathematical and computer models that relate the properties of prospective catalytic materials to their ability to carry out the desired reactions under a wide range of conditions. The improved catalyst designs resulting from the project will promote broader utilization of biomass as a carbon-neutral source of energy, directly addressing the nation's energy security while minimizing environmental impact. Training of graduate and undergraduate students in computational research will provide a future workforce for the emerging areas of computational and data-enabled science and engineering. The project will focus on an integrated research and education program that provides molecular insights into the selective catalytic deoxygenation activity of transition metal catalysts (TMCs), particularly those based on bimetallic phosphide and carbide materials as the active components. From a technical standpoint, the primary objectives will be to understand the effects of solvent, temperature, and pressure on the binding modes of aromatic oxygenates while revealing mechanistic insights into C-O bond cleavage and competitive pathways for undesired products in the presence of solvents and high surface coverages of adsorbed species. The objectives will be accomplished by developing advanced first-principles Monte Carlo (FPMC) and molecular dynamics (FPMD) algorithms. These novel sampling algorithms will be used to investigate catalytic activity for the cleavage of carbon oxygen bonds including the beta-O-4 linkage by considering model compounds containing a phenolic hydroxyl group. In all these calculations, solvent molecules will be explicitly represented to determine their effect on reactants, transition states, products, and catalytic sites. Composition of model phosphide and carbide catalysts will be systematically varied to understand the structure-composition-property relationship for catalytic activity. More broadly, the FPMC and FPMD simulations will significantly advance the state-of-the-art in computational modeling, and provide advanced simulation tools to model catalytic processes under relevant thermodynamic constraints. The fundamental knowledge thus generated will provide a rational framework for designing efficient and effective catalysts for converting lignocellulosic biomass into fuels and chemicals. The algorithmic developments will be implemented in a widely distributed software suite, CP2K, enabling modeling of a wide range of heterogeneous catalytic processes, including zeolite-based catalysis and electrocatalysis. Beyond the graduate and undergraduate educational components, the project will provide K-12 educational outreach to economically disadvantaged communities. In addition, professional development of middle school teachers, through workshops targeted at inquiry-based learning, will lead to higher retention of underrepresented groups in STEM disciplines. 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.