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  5. Optimization of Polysulfone / Graphene Oxide / Polyethylene Glycol / Triaminopyrimidine by Using Response Surface Methodology
 
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Optimization of Polysulfone / Graphene Oxide / Polyethylene Glycol / Triaminopyrimidine by Using Response Surface Methodology

Journal
IOP Conference Series: Materials Science and Engineering
ISSN
17578981
Date Issued
2018-03-19
Author(s)
Jamalludin M.R.
Harun Z.
Hubadillah S.K.
Dzarfan Othman M.H.
Kamarudin N.H.
Yunos M.Z.
Ismail R.I.
Lailina N.M.
DOI
10.1088/1757-899X/318/1/012064
Handle (URI)
https://hdl.handle.net/20.500.14170/11995
Abstract
The addition of polyethylene glycol (PEG), graphene oxide (GO) and triaminopyrimidine (TAP) into polysulfone membranes was used to modify the membrane morphology and increase membrane performance. The central composite design of the response surface methodology was used to predict the maximum permeability and rejection of the PSf membrane. The parameter chosen for this study were PEG (7-14 wt%), GO (0-2.5wt%) and TAP (0-0.5 wt%) concentration. The flat sheet membrane was prepared via phase inversion technique where polysulfone (PSf) was used as base polymer. Various concentration of GO, PEG and TAP were added into the casting solution to produce different membrane composition. PEG was added as pore forming agent for the PSf membrane while inorganic additive such as GO was used to increase the hydrophilicity of the membrane. Besides that, the addition of TAP as a compatibilizer to enhance the physical interaction between GO and PEG. The characterization and surface morphology of produced membrane were analysed via scanning electron microscope, SEM and X-ray diffraction, XRD. The optimization of membrane performance was carried out by using response surface methodology (RSM). The performance of the membrane was analysed by using distilled water for pure water flux test and humic acid for rejection test. The optimized responses, membrane permeability and rejection obtained experimentally were 301.562 Lm-2h-1 and 91.562% respectively, with deviation from the predicted value of 7.884 and 0.4381 %, respectively.
Funding(s)
Universiti Tun Hussein Onn Malaysia
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