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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

This study assesses the effects of different polytetrafluoroethylene (PTFE) particle sizes and concentrations on the performance of dual-layer membranes in direct contact membrane distillation (DCMD). Specifically, particle sizes of 0.5 μm, 1 μm, and 6 μm were systematically evaluated at concentrations of 0 wt%, 2 wt%, 4 wt%, and 6 wt%. Comprehensive analyses, including scanning electron microscopy (SEM), liquid entry pressure (LEP), contact angle, thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP), atomic force microscopy (AFM), permeate flux, nitrogen gas permeation, and salt rejection, were employed to characterize the membranes. Under conditions of a feed temperature of 70 °C and a salt concentration of 8000 ppm for a 24 h duration, the results clearly indicated that a 0.5 μm PTFE particle size combined with a 6 wt% concentration exhibited the highest performance. This configuration achieved a permeate flux of 11 kg·m2/h and a salt rejection rate of 99.8%. The outcomes of this research have significant implications for the optimization of membranes used in DCMD applications, with potential benefits for sustainable water treatment and energy conservation.

Details

Title
Enhancing Hydrophobic/Hydrophilic Dual-Layer Membranes for Membrane Distillation: The Influence of Polytetrafluoroethylene (PTFE) Particle Size and Concentration
Author
Mohammed Faleh Abd Al-Ogaili 1 ; Mohd Hafiz Dzarfan Othman 1 ; Rava, Mohammad 2   VIAFID ORCID Logo  ; Zhong Sheng Tai 1 ; Mohd Hafiz Puteh 1 ; Jaafar, Juhana 1 ; Rahman, Mukhlis A 1 ; Kurniawan, Tonni Agustiono 3   VIAFID ORCID Logo  ; Ojo, Samuel 1 ; Aniqa Imtiaz 1 

 Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia; [email protected] (M.F.A.A.-O.); [email protected] (Z.S.T.); [email protected] (M.H.P.); [email protected] (J.J.); [email protected] (M.A.R.); [email protected] (O.S.); [email protected] (A.I.) 
 Software Engineering Research Group (SERG), Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia; [email protected] 
 College of the Environment and Ecology, Xiamen University, Xiamen 361102, China; [email protected] 
First page
14931
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2882816766
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.