Recent innovations in spinel oxide-based catalysts for CO2 hydrogenation to olefins

Abstract

With the increased urgency for reducing CO₂ emissions, CO₂ capture and hydrogenation into hydrocarbons stands out as a promising approach. This review highlights recent advancements in the evaluation of spinel oxide-based catalysts for CO₂ hydrogenation into olefins, covering un-doped, doped, and bi-functional spinel oxide-based catalysts. The effect of catalyst composition and promotion on catalytic performance is thoroughly discussed. Among the various spinel oxides, Fe₃O₄ and K-ZnFe₂O₄ have shown promising performance, exhibiting 43 % and 46.7 % CO₂ conversion, respectively, and 41.5 % and 68.9 % selectivity towards olefins, respectively. Bi-functional catalysts combining spinel oxides with SAPO-34 have shown enhanced olefins selectivity up to 87 % and low methane formation. Bi-functional zinc-based spinel catalysts were shown to outperform bi-functional magnesium-based spinel catalysts, due to their better ability to activate hydrogen and the balance between basicity and reducibility. However, despite improved olefins selectivity, CO₂ conversion remains low (13–14 %), highlighting the need for further optimization. This review also provides a comprehensive analysis of the active sites responsible for catalysis, and the proposed mechanisms for CO₂ hydrogenation. The mechanism of CO₂ hydrogenation over spinel oxide catalysts is strongly influenced by the catalyst composition. The two main proposed pathways are: i) the redox mechanism (such as on ZnFe₂O₄), and ii) the formate mechanism (such as on ZnAl₂O₄/SAPO-34). In this review, challenges such as achieving higher CO₂ conversion and olefins selectivity, enhancing catalyst stability, and understanding the underlying reaction mechanisms are discussed. Finally, future research opportunities, including enhanced catalyst design, exploring multi-component systems, developing underutilized promoters like cesium, and utilizing advanced in-situ characterization techniques and computational modeling, are proposed to advance the field of CO₂ hydrogenation.