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.

Automated summary

A new knowledge-based assessment platform was developed for early-stage screening of CO2 direct hydrogenation catalysts, using surrogate models to simulate a new methanol production process. Evaluation criteria were applied to assess technical, economic, and environmental capabilities, and the platform was used to analyze 38 CO2 hydrogenation catalysts to establish R&D goals in catalyst discovery.