Preparation and characterization of HEMA-co-VAm/PDA@GO/PSf membrane with enhanced CO2 separation.

Autor: Zhang, Beibei, Zhang, Lihua, Li, Jin, Qiang, Qi
Předmět:
Zdroj: Polymer Bulletin; Aug2024, Vol. 81 Issue 13, p11459-11479, 21p
Abstrakt: Carbon emission reduction has been accepted as a common concern all over the world. Currently, CO2 emission is mainly derived from the consumption of fossil fuels. To solve this issue, there is an urgent need to develop technologies for CO2 capture. The utilization of membrane technology to remove CO2 from a mixture gas attracts great interest. In the present work, poly(2-hydroxyethyl methacrylate-co-vinylamine) was synthesized by polymerization (n-vinyl formamide and 2-hydroxyethyl methacrylate), hydrolysis, and ion exchange. The surface function of graphene oxide was carried out by aerobic self-polymerization of dopamine. The mixed matrix membranes were fabricated by adding the nanofiller (before and after modification) into the polymeric matrix. The membrane properties and its structure were characterized by FTIR, TGA, XRD, and SEM. The effect of nanofiller content and operation conditions on membrane performance was investigated. Results showed that the additions of nanofiller could decrease the crystallization of these membranes and effectively improve gas permeance. Remarkably, for the addition of 2.0 wt% dopamine-modified graphene oxide, the CO2 permeance of the membrane was increased by 30.9% while achieving a CO2/N2 selectivity of 83.5. The CO2 permeation for CO2/CH4 was also increased by 16.77%. These were surpassed over the 2008 Robeson's upper bound. These resultant membranes demonstrated attractive potential for low-pressure post-combustion CO2 capture. Besides, the stability of longtime tests on membranes was studied, and it was observed that membranes exhibited excellent stabilization with continuously operated for 220 h. The excellent properties of these membranes provide new opportunities for gas separation applications. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index