One-step tailoring surface roughness and surface chemistry to prepare superhydrophobic polyvinylidene fluoride (PVDF) membranes for enhanced membrane distillation performances

Weihua Qing, Jianqiang Wang, Xiaohua Ma, Zhikan Yao, Yong Feng, Xiaonan Shi, Fu Liu, Peng Wang, Chuyang Y. Tang

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

Superhydrophobic polyvinylidene fluoride (PVDF) membrane is a promising material for membrane distillation. Existing approaches for preparing superhydrophobic PVDF membrane often involve separate manipulation of surface roughness and surface chemistry. Here we report a one-step approach to simultaneously manipulate both the surface roughness and surface chemistry of PVDF nanofibrous membranes for enhanced direct-contact membrane distillation (DCMD) performances. The manipulation was realized in a unique solvent-thermal treatment process, during which a treatment solution containing alcohols was involved. We demonstrate that by using different chain-length alcohols in the treatment solvent, surface roughness can be promoted by creating nanofin structures on the PVDF nanofibers using an alcohol which has moderate affinity with PVDF. Meanwhile, surface chemistry can be tuned by adjusting the fraction distribution of crystal phases (nonpolar α phase and polar β phase) in the membrane using different alcohols. PVDF membranes with different surface wettabilities were used to evaluate the effects of surface roughness and surface energy on the DCMD performances. Combining both low surface energy and multi-scale surface roughness, pentanol-treated PVDF membrane achieved best anti-water property (water contact angle of 164.1° and sliding angle of 8.1°), and exhibited superior water flux and enhanced anti-wetting ability to low-surface-tension feed in the DCMD application.
Original languageEnglish (US)
Pages (from-to)99-107
Number of pages9
JournalJournal of Colloid and Interface Science
Volume553
DOIs
StatePublished - Jun 5 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2017-CPF-3320
Acknowledgements: We thank the financial support from the Office of Sponsored Research, King Abdullah University of Science and Technology (No. OSR-2017-CPF-3320), and partial funding support by Joint Research Scheme (National Natural Science Foundation of China and Research Grants Council of Hong Kong) (N_HKU706/16).

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