A review on CO2 hydrogenation to lower olefins: Understanding the structure-property relationships in heterogeneous catalytic systems

The alarming scenario of global warming continues to drive mitigation actions to reduce the global temperature rise and keep this earth a dwelling place. In this regard, all the countries in this world have agreed upon a common agenda to take appropriate actions to reduce CO2 emission, mainly from the extensive use of fossil resources to meet the energy demand. In the past decade, an immense amount of work has been done in this regard, focusing on CO2 sequestration and CO2 utilization to valuable end products i.e. methanol, DME, formic acid, lower olefins, etc. A combination of both may not only utilize alternative carbon sources compared to the fossil sources but also imposes a carbon-neutral pathway, thereby aiding the reduction of CO2 accumulation in the atmosphere. CO2 transformation to lower olefins (C2-C4=) has the utmost demand to have an alternative environmental-friendly raw material for the polymer industries, but the majority of catalysts sought for this process are suffering from low selectivity (must possess low CH4, CO, and higher hydrocarbons, paraffin, and aromatic selectivity), which has driven increased interest in the design of an efficient hydrogenation catalyst. A detailed understanding of the structural-property relationships is vital towards designing scalable, efficient, economical, and intrinsically stable catalysts for the process. Therefore, this review focuses on the advances in heterogeneous catalyst design for CO2 hydrogenation to lower olefins, focusing on structure-property correlation via various influencing parameters, describing modified Fischer-Tropsch pathway and methanol mediated pathway with the influence of different types of zeolite and tandem catalysts. Also, mechanisms over these catalysts are discussed. Finally, future research strategies are proposed that would guide the design of novel CO2 hydrogenation catalysts incorporating a combination of core-shell tandem technology, machine learning, advanced DFT, and spectroscopic (in situ, ex situ) understanding of the reaction mechanism.