The catalytic hydrodeoxygenation
(HDO) reaction is of considerable
interest for biomass conversion to valuable chemicals and fuels, where
one of the critical bottlenecks is the lack of cost-effective and
efficient catalysts. To discover cost-efficient catalysts for the
HDO reaction, we employed a density functional theory-based hierarchical
catalyst design strategy based on catalytic descriptors, reaction
energy profiles, and microkinetic modeling (MKM). We focused on the
carbide and nitride catalyst space, for which we calculated 121 catalyst
surfaces of Mo2C, MoC, Mo2N, W2C,
NbC, VC, VN, and NbN catalysts. Based on the computed surface energies,
reaction energies of oxygen removal, carbon binding strength, and
the surface area of nanoparticles, the likely active facets are the
Mo2C(111), MoC(011), VN(100), Mo2N(001), Mo2N(011), and Mo2N(100) surfaces. Further, detailed
energy profiles were obtained, and MKM was performed for a model reaction
(glycolaldehyde + 2H2 → ethylene + 2H2O) on the Mo2C(111), VN(100), and MoC(100) surfaces. Based
on the computed volcano map obtained from MKM, the predicted active
facets for this HDO reaction are the Mo2C(111), MoC(011),
VN(011), Mo2N(001), Mo2N(011), and Mo2N(100) surfaces. Additionally, none of the carbide and nitride catalyst
surfaces are located in the optimal catalytic activity part. Therefore,
it is essential to modify the catalyst via adding
dopants or alloying to improve the catalytic activity. Catalytic modifications
that can destabilize the surface adsorption of O*/H2O*
and decrease the energy barriers of O–H bond formation are
recommended to facilitate the HDO on the carbide and nitride catalysts.
These a priori investigations provide guidelines for future low-cost
HDO catalyst development.