Techno-economic assessment and early-stage screening of CO₂ direct hydrogenation catalysts for methanol production using knowledge-based surrogate modeling

We herein report the development of a new knowledge-based assessment platform for the early-stage screening of carbon dioxide (CO₂) direct hydrogenation catalysts. To accomplish this goal, a new methanol production process was simulated via CO₂ direct hydrogenation by employing knowledge-based surrogate models. In the proposed platform, the sizing and costing information, as well as the mass and energy balances, were determined based on selected key variables, including the CO₂ feed amount, the conversion and selectivity of the catalyst, the temperature and pressure of the reaction, and the vent-out fraction. Four evaluation criteria, including the unit production cost, the carbon and energy efficiencies, and the reduction of CO₂, were applied to assess the technical, economic, and environmental capabilities of the methanol production process. As a motivating example, we analyzed the energy efficiency and economics of the methanol production process using a Cu/Zn/Al/Zr catalyst at different operating temperatures and pressures. We then applied the assessment platform to 38 CO₂ hydrogenation catalysts reported in the literature to analyze the technical and economic merits and barriers that are required to establish R&D goals and directions in the early R&D stages of catalyst discovery.