Our future energy needs mandate shifting from an economy based on non-renewable chemicals and fuels to one that utilizes entirely renewable feedstocks. Utilizing biomass is one promising route to achieving this goal. In this work computational materials science is used to solve problems in the use of biomass as a renewable feedstock. Liquid fuels and chemicals from biomass can be an important part of a renewable energy future, and integration of biomass-derived pyrolysis oil into a standard refinery is a potential first step in the integration of renewable feedstocks with existing infrastructure. Currently biomass-derived pyrolysis oil exhibits significant differences from standard petroleum, especially in its characteristic high oxygen content. The technology used in standard refineries is geared towards low-oxygen inputs. No infrastructure currently exists for the deoxygenation of the refinery input stream, warranting the development of deoxygenation technologies. In this work we explore catalytic hydrodeoxygenation of biomass-derived pyrolysis oil using computational materials science. Known catalysts for this process require high hydrogen pressures rendering the process unfeasible for pyrolysis oil. Recent experimental work suggests a possible pathway for direct deoxygenation at low hydrogen pressure and high temperature over noble metal and metal phosphide catalysts. To understand these catalysts, a model of the guaiacol hydrodeoxygenation mechanism over the platinum and nickel phosphide surfaces was constructed. The deoxygenation mechanism is then proposed and compared to experimental data. These results indicate a possible direct deoxygenation pathway for guaiacol.

Computational materials science for applications in renewable energy: Catalytic upgrading biomass pyrolysis oil

248th National Meeting (2014)

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