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Multiobjective optimization based on "distance-to-target" approach of membrane units for separation of CO2/CH4

Abstract: The effective separation of CO2 and CH4 mixtures is essential for many applications, such as biogas upgrading, natural gas sweetening or enhanced oil recovery. Membrane separations can contribute greatly in these tasks, and innovative membrane materials are being developed for this gas separation. The aim of this work is the evaluation of the potential of two types of highly CO2-permeable membranes (modified commercial polydimethylsiloxane and non-commercial ionic liquid-chitosan composite membranes) whose selective layers possess different hydrophobic and hydrophilic characteristics for the separation of CO2/CH4 mixtures. The study of the technical performance of the selected membranes can provide a better understanding of their potentiality. The optimization of the performance of hollow fiber modules for both types of membranes was carried out by a "distance-to-target" approach that considered multiple objectives related to the purities and recovery of both gases. The results demonstrated that the ionic liquid?chitosan composite membranes improved the performance of other innovative membranes, with purity and recovery percentage values of 86 and 95%, respectively, for CO2 in the permeate stream, and 97 and 92% for CH4 in the retentate stream. The developed multiobjective optimization allowed for the determination of the optimal process design and performance parameters, such as the membrane area, pressure ratio and stage cut required to achieve maximum values for component separation in terms of purity and recovery. Since the purities and recoveries obtained were not enough to fulfill the requirements imposed on CO2 and CH4 streams to be directly valorized, the design of more complex multi-stage separation systems was also proposed by the application of this optimization methodology, which is considered as a useful tool to advance the implementation of the membrane separation processes.

 Fuente: Processes, 2021, 9(11), 1871

Editorial: MDPI

 Fecha de publicación: 21/10/2021

Nº de páginas: 25

Tipo de publicación: Artículo de Revista

 DOI: 10.3390/pr9111871

ISSN: 2227-9717

Proyecto español: PID2019- 108136RB-C31