Modeling of the Sorption Enhanced CO ₂ Conversion to Methanol and Process Optimization Strategies

One strategy to intensify equilibrium-limited CO 2 hydrogenation to methanol is the use of a solid sorbent that selectively removes reaction products, thereby shifting the equilibrium toward the desired products in accordance with Le Chatelier’s principle. This concept, known as the sorption-enhanced reaction process (SERP), introduces additional design and operating variables compared to conventional catalytic processes operated in fixed-bed cyclic reactors. These include the spatial arrangement of catalyst and sorbent within the reactor, their mass ratio, the optimal duration of the different process steps, the purge strategy, etc. Evaluating the impact and optimizing these parameters is essential to maximizing process performance. Based on a prior experimental campaign at laboratory scale, a dynamic model is developed to describe the coupled heat and mass transfer, catalytic reaction, and adsorption phenomena occurring within the reactor. The model is then used to simulate different process configurations and operating scenarios. Finally, parametric studies are performed to optimize key variables in terms of methanol yield and productivity, to assess the potential of the SERP concept for industrial-scale applications.