Process Optimization Based Selection of Adsorbents for Post-combustion CO2 Capture

Abstract

Recent interest in carbon capture has led to development of 100s of adsorbents. The selection of the adsorbents and analyzing their performance for a given process is a challenging task. Usually, the expected performances of these adsorbents are evaluated by inspecting the isotherms and using simple screening metrics (selectivities, working capacities, figures of merit), whereas very few claims are made based on process-scale studies. In this work, we present a systematic approach to screen adsorbents for post-combustion CO2 capture which accounts for the complexities associated with the process and gives an overall picture of the adsorbent performance for the chosen process using a pressure swing adsorption (PSA) cycle model coupled with a genetic algorithm based optimization with an objective to maximize purity/recovery and maximize productivity/minimize energy. Simulation experiments have been set up using Zeolite 13X as the base case and hypothetical adsorbents with constant henry selectivity and fixed CO2/N2 isotherms. It was found for adsorbents with a selectivity of 365 (corresponding to 13X), for 90% CO2 recovery, the weakly and strongly adsorbing adsorbents are able to achieve a purity of 95% and 80%, respectively. For adsorbents with a selectivity of 365 satisfying the purity/recovery constraint, the weakly and strongly adsorbing adsorbent utilizes 120 and 180 kWh/tonne CO2 captured, respectively. For the experiments set up in this work we show that post-combustion CO2 capture is not a CO2 capture problem, but a N2 removal problem.