Computational Screening of Metal Oxide Support Materials for CO₂ Conversion Catalysts: Stability and Interaction Analysis

The catalytic performance of heterogeneous catalysts for CO₂ conversion is critically governed by the nature and strength of metal–support interactions (MSI), which influence active phase dispersion, reducibility, surface basicity, and resistance to sintering under reaction conditions. This study presents a systematic computational screening of metal oxide support materials — including Al₂O₃, TiO₂, CeO₂, ZrO₂, MgO, and SiO₂ for application in CO₂ conversion catalysts, with particular focus on methanation and reverse water-gas shift (RWGS) reactions using Ni and Cu as active metals. The screening methodology integrates semi-empirical quantum mechanical calculations and density functional theory (DFT)-derived descriptors sourced from validated literature and materials databases (Materials Project, NIST) to evaluate key surface properties including oxygen vacancy formation energy, surface hydroxyl density, Lewis acid site strength, and metal adhesion energy. A multi-criteria scoring framework is developed to rank support materials based on their combined thermal stability, metal–support interaction strength, CO₂ adsorption capacity, and predicted resistance to active phase agglomeration. Results indicate that CeO₂ and ZrO₂ exhibit superior bifunctional characteristics owing to their high oxygen storage capacity and favorable MSI with Ni, while MgO demonstrates enhanced CO₂ basicity beneficial for RWGS selectivity. The computational framework is further extended to evaluate binary oxide supports (e.g., CeO₂-ZrO₂, Al₂O₃-TiO₂), revealing synergistic effects on surface properties not achievable with single-component supports. This resource-efficient computational approach provides actionable material selection guidance for the rational design and manufacturing of next-generation CO₂ conversion catalysts, reducing reliance on trial-and-error experimental synthesis.