Pressure-driven membrane desalination

被引:0
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作者
Weifan Liu
Joshua L. Livingston
Li Wang
Zhangxin Wang
Martina del Cerro
Saad A. Younssi
Razi Epsztein
Menachem Elimelech
Shihong Lin
机构
[1] Vanderbilt University,Department of Civil and Environmental Engineering
[2] Tongji University,State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, Tongji Advanced Membrane Technology Center, School of Environmental Science and Engineering
[3] Guangdong University of Technology,School of Ecology, Environment and Resources
[4] Guangzhou,Department of Chemical and Environmental Engineering
[5] Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Laboratory of Materials, Membranes and Environment, Faculty of Sciences and Technologies
[6] Yale University,Faculty of Civil and Environmental Engineering
[7] Hassan II University of Casablanca,Department of Chemical and Bimolecular Engineering
[8] Technion — Israel Institute of Technology,undefined
[9] Vanderbilt University,undefined
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摘要
Pressure-driven membrane desalination (PMD), such as reverse osmosis or nanofiltration, is an energy-efficient technology that addresses water shortages by using saline waters to augment freshwater supplies. This Primer describes several key methodological aspects of PMD, including membrane fabrication, characterization and performance evaluation; system modelling; process configurations; and applications. Thin-film composite polyamide membranes represent the state of the art in reverse osmosis and nanofiltration membranes and are the focus of the membrane development discussion. First, thin-film composite polyamide membrane fabrication using interfacial polymerization and alternative methods is discussed, followed by an exploration of techniques for characterizing the morphological, structural and interfacial properties. Experimental procedures and model frameworks for evaluating membrane performance are introduced, noting caveats in data collection, interpretation and reproducibility, with best practices recommended. Additionally, the general method for modelling the module-scale behaviour of PMD processes is introduced, alongside process configurations for existing and emerging applications. Finally, an outlook for the development of PMD is provided, highlighting the most meaningful directions for future research to further advance PMD beyond the current state of the art.
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