A novel strategy for enhancing the performance of membranes for dyes separation: Embedding PAA@UiO-66-NH2 between graphene oxide sheets

By Haojie Zeng, Zongxue Yu, Liangyan Shao, Xiuhui Li, Meng Zhu, Yuchuan Liu, Xiaofang Feng, Ximei Zhu. Chemical Engineering Journal, 2021

196 citations recorded by the source corpus.

Abstract A composite membrane based on a novel strategy was prepared which using graphene oxide (GO), UiO-66-NH2 and polyacrylic acid (PAA) as basic materials on the surface of nylon membrane by vacuum filtration self-assembly. The structure of the composite membrane was made of graphene oxide as vertical separation layer, the PAA@UiO-66-NH2 (PAA@UiO) embedding between GO as horizontal capture material. The PAA@UiO-66-NH2/GO (PAA@UiO/GO) membrane was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and atomic force microscopy (AFM). Compared with the GO membrane, PAA@UiO/GO membrane combined the effects of GO, UiO-66-NH2 and PAA, which significantly enhances the separation performance of dye wastewater. In particular, the PAA@UiO/GO membrane can achieve complete removal of MB, RB and CR while the fluxes during filtration process can reach about 100  L ∙ m - 2 ∙ h - 1 . At the same time, PAA@UiO/GO membrane almost retained stable removal rate on all dyes under extreme pH and ionic strength conditions. In addition, after 10 cycles of experiments, PAA@UiO/GO membrane retained a removal rate and a flux more than 95% and 85  L ∙ m - 2 ∙ h - 1 for all dyes, respectively. Compared to a composite membrane based on intercalation, the unique structure of PAA@UiO/GO membrane with a large number of adsorption sites and screening structures, resulting a better removal rate for dyes. Furthermore, PAA@UiO/GO membrane has a great potential in practical applications and a solution to balance trade-off effect.

Subfields: Biomedical Engineering, Materials Chemistry, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/d9a37932d0c71785ec0985ef703e25e1808b1bf6