A Composition-Dependent Performance Prediction Model for a Hollow-Fiber Membrane Module Equipped with Glycine-Based Facilitated Transport Membranes

A performance prediction model for a hollow-fiber membrane module equipped with a facilitated transport membrane with glycine as a carrier (glycine-FTM) was developed for CO2 separation. The model accounts for the effects of feed gas composition changes within the module on both CO2 and water vapor permeances. The model predictions exhibited good agreement with experimental data, demonstrating that the model can accurately describe complicated permeation behavior arising from the composition-dependent CO2 permeability of a glycine-FTM. Furthermore, the model provides insights into internal module behavior, enabling a detailed understanding of CO2 recovery by the glycine-FTM module. For example, the analysis clarified the importance of water vapor, which affects CO2 permeance and transmembrane CO2 partial pressure in the module. The proposed model is a practical tool for describing the composition-dependent CO2 and water vapor permeation in glycine-FTM modules, and would be useful for supporting their rational design and operational optimization.