CO2 to dimethyl ether (DME): structural and functional insights of hybrid catalysts

The rapid and unparalleled advancement of human civilization has been made possible by the utilization of fossil feedstocks, beginning with coal, and followed by petroleum oil and natural gas. However, the accelerated burning of these resources results in substantial anthropogenic CO2 emissions, outpacing the natural carbon cycle. This is resulting in detrimental global environmental shifts, the complete consequences of which remain uncertain. Although fossil feedstocks are abundant, it is important to recognize that they are finite and will eventually be exhausted. For the transition towards a sustainable energy landscape, direct conversion of CO2 to dimethyl ether (DME) has great potential as an efficient and cost-effective way to use CO2 as a renewable and cheap carbon resource. In recent times, this process holds immense promise of interest to academia and industry as it shows a promising way to simultaneously address two important global challenges: reducing carbon emissions and developing clean-burning alternative fuel. Nevertheless, due to limitations related to kinetics and thermodynamics, the development of more efficient catalysts is needed to achieve the direct use of CO2 as the primary raw material for DME production. In this perspective, we concentrate on the recent advancements in one-step CO2 to DME. We explore the crucial role of different catalytic systems by delving into reported experimental findings and the reaction mechanism. In particular, by examining the catalytic properties of active sites, stability, activation mechanism, and behavior of CO2 molecules under relevant conditions, we aim to shed light on their significance in advancing CO2 to DME transformation in industrial implementation. This review mainly encompasses an extensive analysis of recent progress in the designing of heterogeneous hybrid/bifunctional catalysts. Furthermore, the thermodynamics aspect, process engineering, and economic and environmental analysis are elucidated in detail to overcome the limitations associated with the upscaling of this technology.