Computational catalysis on the conversion of CO2 to methane-an update

The reliance on fossil fuels intensifies CO2 emissions, worsening political and environmental challenges. CO2 capture and conversion present a promising solution, influenced by industrialization and urbanization. In recent times, catalytic conversion of CO2 into fuels and chemical precursors, particularly methane, are gaining traction for establishing a sustainable, carbon-neutral economy due to methane's advantages in renewable energy applications. Though homogeneous and heterogeneous catalysts are available for the conversion of CO2 to methane, the efficiency is found to be higher in heterogeneous catalysts. Therefore, this review focuses only on the heterogeneous catalysts. In this context, the efficient heterogeneous catalysts with optimum utility are yet to be obtained. Therefore, the quest for suitable catalyst for the catalytic conversion of CO2 to CH4 is still continuing and designing efficient catalysts requires assessing their synthetic feasibility, often achieved through computational methods like density functional theory simulations, providing insights into reaction mechanisms, rate-limiting steps, catalytic cycle, activation of C=O bonds and enhancing understanding while lowering costs. In this context, this review examines the conversion of CO2 to CH4 using seven distinct types of catalysts, including single and double atom catalysts, metal organic frameworks, metalloporphyrins, graphdiyne and graphitic carbon nitrite and alloys with some case studies. The main focus of this review is to offer a detailed and extensive examination of diverse catalyst design approaches and their utilization in CH4 production, with a specific emphasis on computational aspects. It explores the array of design methodologies used to identify reaction pathways and investigates the critical role of computational tools in their refinement and enhancement. We believe this review will help budding researchers to explore the possibilities of designing catalysts for the CO2 to CH4 conversion from computational framework.