(723a) Computational Modeling of Electrochemical Bio-Oil Upgrading

Electrochemical hydrogenation (ECH) reactions are needed in the post-pyrolysis treatment of bio-oil to convert biomass into biofuels. A computational approach is taken to find the optimal catalyst material, and the conditions at which the concentration of species to react surrounding the catalyst is best. This is done to provide testable hypotheses regarding catalyst activity and selectivity for experimental work. Despite extensive research done in electrochemical reactions, the complex solvent/catalyst environment has hindered a rigorous understanding of electrocatalyst surface chemistry. Density functional theory calculations of species binding and ECH reaction energies were done as a function of voltage on the surface of numerous catalysts. Initial results show that Au, Cu, and C catalysts are best suited because they preferably bind organic molecules over hydrogen, and show a large applied potential for H₂ formation and low one for organic hydrogenation. Since only the species at the cathode vicinity are susceptible to undergo electron transfer, classical molecular dynamics simulations of solvent mixtures in an electrolytic cell were performed to assess how species concentrations differ between the solid/liquid interface and bulk regions. Simulations were performed at varying temperatures, cathode surfaces and charge. Energetic and entropic contributions were analyzed to understand competing surface binding and solvation effects. Initial results show a decrease in organic and increase in water mol fractions at the solid/liquid interface as the cathode charge in the electrolytic cell increases. This can only be compensated by a strong adhesion of the organic molecule to the cathode surface. Results are compared with concurrent experiments and implications on catalyst choice are discussed.