CO₂ hydrogenation to methanol has attracted considerable attention as a promising catalytic route for both reducing CO₂ emissions and producing valuable chemical intermediates. Among various catalysts, Cu–ZnO-based systems are the most widely studied; however, their performance remains constrained by limited methanol selectivity and stability, highlighting the need for improved catalytic strategies. In this work, liquid metal gallium (Ga) was incorporated into Cu–ZnO catalysts as an additive for CO₂ hydrogenation to methanol. Owing to its high dispersibility and fluidity, Ga helps maintain long-term catalyst stability. We investigated different introduction methods for Ga promoters and found that the physical mixing approach generated the strongest alkaline sites, thereby enhancing CO₂ activation and increasing the CO₂ conversion to methanol. Moreover, this catalyst effectively suppressed carbon deposition, further improving its stability. These findings offer new insights into the use of liquid metal Ga in CO₂ hydrogenation and provide fresh perspectives for the rational design of efficient methanol synthesis catalysts.

CO₂ hydrogenation to methanol is a key route for carbon recycling within the carbon capture, utilization, and storage (CCUS) framework. Cu-based catalysts are widely employed because of their low cost and high methanol selectivity, yet monometallic Cu suffers from sintering, limited CO₂ activation, and competing reverse water-gas shift (RWGS) reactions. This review systematically summarizes recent advances in Cu-based bimetallic catalysts, categorized as Cu-p-block, Cu-noble metal, Cu-transition metal, and Cu-rare-earth metal systems. Throughout this review, the term “bimetallic catalysts” broadly refers to Cu-based systems containing a second metallic element, which may be present as a metallic alloy, an intermetallic compound, an atomically dispersed promoter species, or an oxide promoter or support component that forms Cu-M or Cu-MO_x interfacial structures. Experimental findings and density functional theory calculations are integrated to clarify how second metals regulate electronic structures, interfacial sites, oxygen vacancies, and hydrogen activation, thereby governing the competition between the formate pathway and RWGS. The dynamic evolution of active sites and the concentration-dependent role of reaction-generated water are also discussed. Finally, current challenges in machine learning-assisted catalyst development are assessed, and future directions involving operando characterization, hydrophobic interface engineering, reactor-level water management, and interpretable data-driven catalyst design are proposed to guide catalyst optimization and practical implementation.