RT Book, Section
T1 Membrane optimization and process condition investigation for enhancing the CO2 separation from natural gas
A1 Llosa Tanco, Margot A.
A1 Medrano, Jose A.
A1 Gallucci, Fausto
A1 Pacheco Tanaka, David A.
AB This chapter provides an overview of both conventional membrane process technologies and optimization of membrane process technologies for CO2 separation from natural gas. Among other natural gas processing operations, removal of CO2 is required to meet gas specification, typically 2% CO2 for pipeline quality gas. The use of CO2-selective membrane technologies for bulk separation of methane is increasing in the natural gas industry. CO2-selective membranes represent a more efficient alternative for CO2 separation, as in this case the separation does not undergo any phase change. The economics of the process, simple operation, and the use of compact modules have led to an increasing exploration of membrane technology for CO2 separation in the natural gas industry over competing separation technologies. This chapter presents an overview of different CO2-selective membranes for the separation of CO2 from natural gas. In particular, the recent significant advances (from 2010) reported in the literature on various CO2-selective membranes, their stability, the effect of different parameters on the performance of the membranes, the relationships between structure and permeation properties, and the transport mechanism applied in different CO2-selective membranes are summarized. Finally, the future direction for CO2-selective membranes is suggested.
PB Elsevier
SN 9780128136461
SN 9780128136454
YR 2018
FD 2018-01-01
LK https://hdl.handle.net/11556/2107
UL https://hdl.handle.net/11556/2107
LA eng
NO Llosa Tanco , M A , Medrano , J A , Gallucci , F & Pacheco Tanaka , D A 2018 , Membrane optimization and process condition investigation for enhancing the CO 2 separation from natural gas . in Current Trends and Future Developments on (Bio-) Membranes : Carbon Dioxide Separation/Capture by Using Membranes . Elsevier , pp. 469-509 . https://doi.org/10.1016/B978-0-12-813645-4.00017-9
NO Publisher Copyright: © 2018 Elsevier Inc. All rights reserved.
DS TECNALIA Publications
RD 31 jul 2024