Model-Based Approach for the Evaluation of Materials and Processes for Post-Combustion Carbon Dioxide Capture from Flue Gas by PSA/VSA Processes

This work presents a mathematical modeling framework for the simulation and optimization of PSA/VSA processes for postcombustion CO2 capture from dry flue gas (85% N-2, 15% CO2). The modeling framework is first validated against literature data, illustrating good agreement in terms of several process performance indicators. Accordingly, the model is used to evaluate three available potential adsorbents for CO2 capture, namely, zeolite 13X, activated carbon and metal organic framework (MOP), Mg-MOP-74. A two-bed configuration (six-step VSA cycle) with light product pressurization has been employed in all simulations. The results from systematic comparative simulations demonstrate that zeolite 13X has the best process performance among the three adsorbents, in terms of CO2 purity and CO2 recovery. On the other hand, Mg-MOF-74 appears to be a promising adsorbent for CO2 capture, as it has considerably higher CO2 productivity compared to the other two adsorbents. Furthermore, process optimization studies using zeolite 13X and Mg-MOE-74, have been performed to minimize energy consumption for specified minimum requirements in CO2 purity and in CO2 recovery at nearly atmospheric feed pressures. The optimization results indicate that the minimum target of 90% in CO2 purity and 90% in CO2 recovery is met for the VSA process under consideration for both adsorbents at different operating conditions resulting in different energy requirements. Thus, there is a complex relationship between optimal process performance indicators and operating conditions that varies among the different adsorbents and cannot be quantified by simple comparison of CO2/N-2 adsorption isotherms and selectivity data. Evidently, detailed process modeling, simulation and optimization strategies, provide the most reliable way to evaluate both qualitatively and quantitatively potential adsorbents for CO2 capture.