Predicting An Optimal Oxide/Metal Catalytic Interface For Hydrodeoxygenation Chemistry Of Biomass Derivatives

CATALYSIS SCIENCE & TECHNOLOGY(2021)

引用 2|浏览0
暂无评分
摘要
Complex reaction pathways such as hydrodeoxygenation (HDO) of multi-oxygenated reactants like furfuryl alcohol towards 2-methylfuran can benefit from a close connection between multi-component (oxide-metal) catalytic site properties and their catalytic performance. The HDO activity can be tuned by optimizing the synergy between the individual metal oxide and metal site properties towards the HDO catalytic cycle consisting of C-O activation, C-H formation, and oxygen vacancy formation steps. Through our previously reported model of an oxide-metal interface catalyst - a TiO2 nanorod on a Pd (111) surface, we identified the following material descriptors that dictate furfuryl alcohol HDO activity: work function (phi), oxygen vacancy formation energy (Delta E-vac), metal-carbon binding energy (M-C-B.E.), and extent of metal-metal oxide interfacial charge transfer (q). The descriptors were examined over the interface with the composition altered towards closed pack metals: Ag, Au, Cu, Pd, Rh, Ru and Zn, and monolayer surfaces of Ag, Au, Co, Cu, Fe, Ir, Ni, Pt, Rh, Ru and Zn metals atop Pd (111). We identified a greater stabilization of the C-O activation transition state, the key HDO step, through electronic charge redistribution at the interface, facilitated by a higher metal work function. Stronger metal-carbon binding dictates the favorable hydrogenation of the resulting organic fragment. The role of these descriptors was further investigated under experimentally relevant hydrogenation reaction conditions of H-2 and hydrocarbons partial pressures. Such fundamental knowledge of the descriptors dictating HDO can provide opportunities for further tuning the structural, electronic, and chemical properties of a multicomponent interface to achieve optimal HDO activity.
更多
查看译文
关键词
hydrodeoxygenation chemistry,oxide/metal interface catalyst,optimal oxide/metal
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要