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 CO 2 separation. The model accounts for the effects of feed gas composition changes within the module on both CO 2 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 CO 2 permeability of a glycine-FTM. Furthermore, the model provides insights into internal module behavior, enabling a detailed understanding of CO 2 recovery by the glycine-FTM module. For example, the analysis clarified the importance of water vapor, which affects CO 2 permeance and transmembrane CO 2 partial pressure in the module. The proposed model is a practical tool for describing the composition-dependent CO 2 and water vapor permeation in glycine-FTM modules, and would be useful for supporting their rational design and operational optimization.