Browse by author
Lookup NU author(s): Dr Peng Liu, Professor David XieORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Nowadays, oil contamination has become a major reason for water pollution, and presents a global environmental challenge. Although many efforts have been devoted to the fabrication of oil/water separation materials, their practical applications are still hindered by their weak durability, poor chemical tolerance, environmental resistance, and potential negative impact on health and the environment. To overcome these drawbacks, this work offers a facile method to fabricate the eco-friendly and durable oil/water separation membrane fabrics by alkaline hydrolysis and silicon polyurethane coating. The X-ray photoelectron spectroscopy, scanning electron microscopy, and atomic force microscopy results demonstrate that silicon polyurethane membrane could be coated onto the surface of hydrolyzed polyester fabric and form a micro-/nano-scaled hierarchical structure. Based on this, the modified fabric could have a stable superhydrophobic property with a water contact angle higher than 150°, even after repeated washing and mechanical abrasion 800 times, as well as chemical corrosion. Moreover, the modified fabrics show excellent oil/water separation efficiency of up to 99% for various types of oil–water mixture. Therefore, this durable, eco-friendly and cost-efficient superhydrophobic fabric has great potential in large-scale oil/water separation.
Author(s): Mao T, Xiao R, Liu P, Chen J, Luo J, Luo S, Xie F, Zheng C
Publication type: Article
Publication status: Published
Journal: Chinese Journal of Chemical Engineering
Year: 2023
Volume: 55
Pages: 73-83
Print publication date: 01/03/2023
Online publication date: 21/05/2022
Acceptance date: 16/05/2022
Date deposited: 22/09/2022
ISSN (print): 1004-9541
ISSN (electronic): 2210-321X
Publisher: Elsevier
URL: https://doi.org/10.1016/j.cjche.2022.05.003
DOI: 10.1016/j.cjche.2022.05.003
Altmetrics provided by Altmetric