journal article·2014-11

Enhancing the antifouling property of poly(vinylidene fluoride)/SiO2 hybrid membrane through TIPS method

Aiwen Qin, Xueliang Wu, Bomou Ma, Xinzhen Zhao, Chunju He

Journal of Materials Science· Volume 49· Issue 22
Publisher page

Abstract

PVDF/SiO2 hybrid membranes with outstanding antifouling property were prepared from PVDF/glycerol triacetate system via thermally induced phase separation method, and characterized by scanning electron microscope, energy dispersive X-ray spectrometer analyses, differential scanning calorimeter, and wide angle X-ray diffraction. Their properties such as permeability, porosity, pore size distribution, and mechanical performance were also determined. The results show that SiO2 nanoparticles modified by 3-aminopropyltriethoxysilane can be uniformly dispersed in membranes due to improved compatibility between PVDF solution and nanoparticles. The addition of SiO2 particles to PVDF/glycerol triacetate mixture has a strong effect on crystallinity of the resulting hybrid membrane, which does not affect the type of PVDF crystal structure. Water flux recovery ratio is significantly increased from 11.7 % for pure PVDF membrane to 93.8 % for PVDF/SiO2 hybrid membrane with addition of 8 wt% modified SiO2. This remarkable promotion is related to the implantation of SiO2 nanoparticles into the inner surface of membrane, which effectively restrains the adsorption of bovine serum albumin on the pore walls and improves antifouling property of the final membranes. Additionally, pure water flux of the hybrid membrane is increased by 276 %, i.e., from 85 to 320 L m−2 h−1, tensile strength is increased by 26.5 %, and elongation at break is increased by 85.4 % compared with that of pure membrane.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Membrane Separation Technologies · Advanced Sensor and Energy Harvesting Materials · Dielectric materials and actuators

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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