polyaniline blended membranes using response surface methodology approach

Desalination 311 (2013) 182–191

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Optimisation of polyethersulfone/polyaniline blended membranes using response surface methodology approach Nor Faizah Razali a, Abdul Wahab Mohammad a,⁎, Nidal Hilal b, Choe Peng Leo c, Javed Alam d a

Scale-Up and Downstream Processing Research Group, Centre for Sustainable Process Technology (CESPRO), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia The Centre for Water Advanced Technologies and Environmental Research (CWATER), College of Engineering, Swansea University, Swansea SA2 8PP, UK c School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang, Malaysia d King Abdullah Institute for Nanotechnology, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia b

H I G H L I G H T S ► Polyaniline nanoparticles were used to produce a polyethersulfone/polyaniline blended membrane. ► Polyaniline can exist in a blend membrane stably, thus produce membranes with stable structure and performance. ► Response surface method was successfully applied for optimisation in the production of the blended membranes.

a r t i c l e

i n f o

Article history: Received 18 June 2012 Received in revised form 25 November 2012 Accepted 26 November 2012 Available online 21 December 2012 Keywords: Polyethersulfone Polyaniline Nanoparticle Blended membrane Response surface method

a b s t r a c t In the study, polyaniline (PANI) nanoparticles were used as polymeric additives in order to improve polyethersulfone (PES) structure and performance. A major role of PANI nanoparticles in PES membranes is to improve the hydrophilic properties and permeability of the substrate membrane. The central composite design (CCD) of the response surface method (RSM) was used for the optimisation of blended PES/PANI membranes. The objectives were to obtain the optimum operating variables and to observe interactions among the variables. The factors considered were the PES concentration, PANI concentration and evaporation time during the casting process, while pure water permeability, salt rejection and contact angle values were considered as the responses. The design of experiment (DoE) managed to develop models that related the responses with the operating variables which were further analysed by analysis of variance (ANOVA). The optimal conditions were 18.33 wt.% PES, 0.75 wt.% PANI and 1.34 min of evaporation time with the predicted results of water permeability, salt rejection and contact angle of 62.2 L/m2 h bar, 32.4% and 54.95°, respectively. The interaction graph shows that there was a strong interaction between the variables of PES concentration (A), PANI concentration (B) and evaporation time (C). With additional characterisation, the optimised membrane showed an improvement in the membrane structure when observed by SEM. The addition of nanoparticles evidently increased the membrane surface roughness, as observed in the AFM images. The membrane pore size distribution was also obtained from the AFM images which showed a difference between the control (1–6 nm) and blended (2–40 nm) membranes. The membrane surface charge showed that the blended membrane has the highest charge at low and high pH with iso-electric point at pH 3 while there is no iso-electric point obtained for a controlled membrane. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Polyethersulfone (PES) is one of the most common polymers used in producing ultrafiltration/nanofiltration membranes, either on the laboratory or industrial scale. PES is a polysulfone (Psf) derivative which has better chemical properties than Psf in terms of thermal stability and hydrophilicity [1]. It is a thermally stable polymer and is widely used in protein separation and purification [2]. PES is often used in high performance applications due to its toughness, good thermal resistance, ⁎ Corresponding author. Tel.: +60 389216410; fax: +60 389216148. E-mail addresses: [email protected], [email protected] (A.W. Mohammad). 0011-9164/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.desal.2012.11.033

chemical inertness and environmental endurance [3]. It also shows other good qualities such as good membrane forming properties, a high glass transition temperature, good commercial availability and a relatively low cost [4]. However, the hydrophobic properties of PES always lead to severe fouling and affect membrane applications and the usable lifetime of the membrane [5]. Considerable research has been performed in order to overcome this problem. The only way to improve PES performance is by improving the hydrophobic structure using appropriate methods. It is important to improve the hydrophilicity of the membrane without interfering with the other good characteristics of the PES membrane and to comply with industry requirements. Some of the methods used for the modification

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of PES include blending with hydrophilic polymeric additives [6], ultraviolet irradiation [7], graft polymerisation [8] and plasma grafts [9]. Some of the polymeric additives that have been used are polyvinylpyrrolidone (PVP) [10,11], polyethylene glycol (PEG) [12] and polysulphoxideamide [13]. In the present work, polyaniline (PANI) nanoparticles were used as polymeric additives in order to improve PES structure and performance. PANI is a type of conducting polymer that has major applications in chemistry, physics, material science and engineering [14]. PANI was selected because of its ease of synthesis, environmental stability [15], simple doping/dedoping chemistry, relatively inexpensive cost [16,17] and solubility in highly aprotic solvents like N-methyl2-pyrrolidone (NMP) [18]. In membrane technology, PANI has been applied for gas separation [19], pervaporation [20,21] and in semiconductor membranes [22]. A major role of PANI nanoparticles in PES membranes is to improve the hydrophilic properties and permeability of the substrate membrane. It is used to obtain superhydrophilic surfaces because of its high surface energy and hydrophilic properties [23]. Currently, membrane blending with nanoparticles has attracted research interest since the resulting membranes have excellent separation performance, convenient operation under mild conditions [24], adaptability to harsh environments and good thermal and chemical resistance [25]. The two major roles of nanoparticles in improving membranes are to enhance pore formation and interconnectivity and to also improve hydrophilicity [26]. In our previous work, we discovered an improvement in PES performance and structure after blending with polyaniline [27]. The aim of this study was to determine the optimum parameters for fabricating PES–PANI blended membranes. For this purpose, we used the response surface methodology (RSM) approach to investigate the simple effect and the interaction of different operating conditions, such as the PES–PANI composition and the evaporation time in membrane fabrication; optimisation trials were also conducted. RSM is a collection of statistical and mathematical techniques that are useful for process modelling and optimisation. This statistical method is important to understand the interaction effects between factors and to reduce the total number of experimental runs [28]. There have been a few studies using RSM for optimising membrane fabrication. Ahmad et al. applied RSM to optimise membrane performance by thermal– mechanical stretching where they considered stretching elongation, the stretching rate and the stretching temperature as their variables [29]. Ismail and Lai used RSM to develop defect-free asymmetric membranes through the manipulation of membrane fabrication variables, including the polymer concentration, solvent ratio, shear rate and evaporation time [30]. Ng et al. used RSM to optimise the incorporation of silica nanoparticles in polysulphone/poly(vinyl alcohol) membranes by varying the polymer and silica weight percentage [31]. Xiangli et al. also reported using RSM in membrane fabrication by optimising the polymer concentration, crosslinking agent concentration and dip-coating time for polydimethylsiloxane/ceramic composite pervaporation membranes [32]. So far, no one has reported on the optimisation of parameters in the fabrication of PANI/PES blended membranes using RSM.

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2.2. Membrane fabrication 2.2.1. Synthesis of polyaniline nanoparticles The chemical oxidative polymerisation method was applied during the synthesis of PANI nanoparticles. First, the aniline monomer was added to an HCl solution and stirred at room temperature. Next, an (NH4)2S2O8 solution, which acts as an oxidant, was added dropwise into the solution and the colour of the solution gradually changed from light blue to dark blue. The solution was left for 24 h with constant mechanical stirring. After 24 h, the emeraldine salt was collected, filtered and washed with distilled water (10 × 200 mL) and methanol (10 × 200 mL). However, further treatment was needed for the conversion of emeraldine salt to emeraldine base. In this research, PANI in emeraldine base form was chosen because it has good solubility in NMP. PANI in emeraldine salt form has better conductivity and hydrophilicity than emeraldine in the base form because of the protonation of the acid. However, its poor solubility in most solvents restricts its applications, especially in membrane fabrication. Emeraldine salt was deprotonated by stirring it continuously in 1 M ammonium hydroxide. The solution was continuously stirred for 24 h to make sure it completely turned into emeraldine base. The dark blue precipitate was then refiltered, washed with distilled water (10×200 mL) and methanol (10× 200 mL) and dried in a vacuum oven at 60 °C for 24 h to obtain a dark blue PANI powder. The size of the nanoparticles obtained was in the range of 22–53 nm. 2.2.2. Preparation of blended membranes For membrane preparation, a few membranes were produced via the phase inversion method based on the composition suggested by the RSM software. Generally, the suggested membrane composition consisted of PES (control membrane) and PES–PANI blended membranes. All of the polymer and nanoparticle weight percentages were calculated based on the total casting solution. For the control membrane, the solution was prepared by dissolving a certain amount of PES in NMP. Then, the solution was heated in a water bath set at 80 °C and mechanically stirred at 500 rpm for 5 h. The prepared solution was then left overnight to deaerate. For the blended membranes, the PANI solution was prepared separately before blending with the PES solution. First, 0.55 g of PANI nanoparticles was dissolved in 50 mL of NMP followed by 12 h of stirring at room temperature. Then, the PANI solution was filtered with a 0.45 μm syringe filter and sonicated in ultrasonic bath in order to reduce agglomeration. Finally, the PANI solution was mixed with the PES solution to get the blended PES–PANI solution. The blended solution was stirred for 8 h at room temperature and left overnight to deaerate. For the membrane fabrication process, a Filmographe Doctor Blade 360099003 casting knife was used where the thickness was set to 150 μm. The membranes were cast on a sterilised glass plate via the immersion precipitation process. After the casting process, the membrane was exposed to the atmosphere based on the evaporation times that had been fixed for each composition. Then, the prepared membrane was immersed in ultrapure water for 24 h at room temperature to minimise the amount of residual casting solvent in the membrane.

2. Experimental 2.3. Experimental design 2.1. Materials Aniline (ANI; Aldrich), 37% hydrochloric acid (HCl; R&M Chemicals), ammonium peroxydisulphate ((NH4)2S2O8; APS; R&M Chemicals), magnesium sulphate (MgSO4; R&M Chemicals), potassium chloride (KCl; R&M Chemicals), sodium hydroxide (NaOH; R&M Chemicals) and 30% ammonium hydroxide (R&M Chemicals) were used as received. Membranes were prepared from PES (Ultrason E1010 NAT, BASF Corporation, Mw=58,000 g/mol) and the solvent used was 1-methyl-2pyrrolidone (NMP), supplied by Merck. All aqueous solutions were prepared with ultrapure water.

This study applied the use of RSM instead of conventional experimental methods in order to determine the optimised parameters for the fabrication of blended PES/PANI membranes. RSM is a collection of mathematical and statistical techniques and is useful for developing, improving and optimising processes. It can be used to evaluate the relative significance of several affecting factors even in the presence of complex interactions. Compared to conventional methods, RSM has many advantages, including the provision of rapid and reliable experimental data, a consideration of the effects and interactions between factors, a reduction in the number of experiments and minimising

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experimental costs and time consumption [33]. RSM comes with a statistical design of experiments (DoE) where all the experimental processes are arranged based on the central composite design (CCD). The experimental design consists of factors that have been studied, a set of centre points and a set of axial points. The centre points of the experiments are normally repeated to improve the precision of experiments. Axial or star points represent the values both below and above the centre of the two factorial levels and both are outside their range. In this study, the experimental design consisted of three factors: the PES composition (wt.%), PANI composition (wt.%) and evaporation time (min), while the responses were water permeability (L/m 2 bar h), salt rejection (%) and contact angle (°) of the membrane. Even though ultrafiltration is a conventional membrane method applicable for rejection of suspended solids and high molecular compounds, salt rejection was taken into consideration in order to investigate desalting effects in the prepared membranes. Desalting refers to the process of removing salts and low molecular weight impurities from protein solutions [34]. Table 1 lists the variable ranges used in RSM with actual and coded values, while Table 2 shows the CCD experimental design for blended PES–PANI membranes that was developed by Design Expert software (version 6.0.10, Stat-Ease, Inc, MN).

Table 2 CCD experimental design for a PES–PANI blended membrane. Run

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Factors with coded levels

Responses

A: PES (wt.%)

B: PANI (wt.%)

C: evaporation time (min)

Y1 (L/m2 bar h)

Y2 (%)

Y3 (θ)

+α −1 0 +1 0 0 −α 0 0 0 +1 −1 0 −1 +1 −1 +1

0 −1 +α +1 0 0 0 0 0 0 −1 +1 −α −1 +1 +1 −1

0 +1 0 +1 0 −α 0 +α 0 0 +1 −1 0 −1 −1 1 −1

10.7 17.4 37.4 16.2 65.8 20.3 15 26.8 66.5 58.9 43.2 10.9 0.5 36.9 28.2 16.7 65.9

20.3 19 17.8 20.4 33.3 20 17.5 21.6 33.1 33.6 23.2 22.8 25.6 18.2 20.3 22 22.5

46.8 47.4 58.1 47.7 53.3 48.4 53.2 56.1 56 56.3 50.6 55.1 63 52 49 56.5 50.8

−1 = low value, 0 = centre value, +1 = high value, +/−α = star point value.

2.4. Membrane characterisation 2.4.1. Ultrafiltration test A simple ultrafiltration test was conducted in order to determine the flux and water permeability. A dead-end filtration system connected to a tank filled with ultrapure water was used as the experimental rig. The system consisted of 200 mL stirred ultrafiltration cells (model 8200) with a membrane surface area of 28.7 cm2. A nitrogen cylinder was used to pressurise the system. Before starting the experiment, the membrane was compacted for 30 min at 2 bar to minimise the compaction effects. After the steady state flux was recorded, the pressure was reduced to 0.5 bar and the pure water flux was measured. The pure water flux was calculated using the following equation: J¼

V At

ð1Þ

where J is the pure water flux (L/m2 h), V is the permeate volume (L), A is the membrane area (m2) and t is the time (h). For each membrane, five samples were tested and the water flux value was taken as the average value. The ultrafiltration test continued by replacing the ultrapure water with MgSO4 solution for the salt rejection test and stirred mechanically at 300 rpm. MgSO4 solution (2 g/L) was prepared using ultrapure water and the concentration was determined using a portable conductivity meter (Martini Instruments). Salt rejection was calculated based on Eq. (2):
 Cp R ¼ 1− Cf

ð2Þ

where Cp represents the concentration of the solute for the permeate while Cf is the concentration of the solute in the feed stream. Table 1 Variables used in the experimental design represented with actual and coded values. Variable

Polyethersulfone (wt.%) Polyaniline (wt.%) Evaporation time (min)

Symbol

+αa

Coded level

Actual

Coded

−αa

−1

0

+1

PES PANI Time

A B C

17 0 0

17.41 0.3 0.61

18 0.75 1.5

18.59 1.2 2.39

2.4.2. Contact angle measurements The hydrophilicity of the control and blended membranes was measured using a drop shape analysis system (Easydrop, KRUSS, Gmbh). The method used was the sessile drop method. In this method, the membrane was placed on a glass plate and 3 mL of water was dropped automatically onto the sample surface. The syringe used was a microsyringe with a stainless steel needle. The contact angle reading was measured using a camera connected to a video screen. In order to minimise the experimental error, five measurements were taken and the average value was calculated. 2.4.3. Scanning electron microscopy (SEM) The surface and cross-sectional morphology of the membranes were observed using scanning electron microscopy (SEM; Gemini, SUPRA 55VP-ZEISS). The samples were first dried and cut into pieces. For crosssections, the samples were immersed in liquid nitrogen, and then fractured. The samples were then put on sample stubs and sputtered with a thin layer of gold using a sputtering apparatus. Finally, the prepared samples were observed by SEM operated at 3 kV and images were taken at 5000× and 10,000× magnification. 2.4.4. Atomic force microscopy (AFM) Atomic force microscopy (AFM) analysis was performed to analyse the surface morphology and roughness of the membranes. It was conducted on a Multimode atomic force microscope (model 920-006100). Initially, the samples were immersed in ultrapure water overnight in order for them to be free of any preservative substances. Next, the samples were dried at room temperature. For these measurements, the samples were placed on a magnetic steel disc using double sided tape, and then put in the AFM sample holder for analysis. The sample was set in the AFM apparatus and tapping mode was used during the scanning process. This apparatus provides surface morphology data measurements such as roughness. In this study, the pore size distribution and porosity were also measured from the two-dimensional image using line analysis software. The porosity of the membranes was calculated using Eq. (3) [35]: ! 2 n

19 1.5 3

a α = 1.682 (star or axial point for orthogonal CCD in the case of 3 independent variables).

Porosityð% Þ ¼

πdp 4

Aimage

 100%

ð3Þ

 represents the average pore diameter of the membrane surwhere d p face while Aimage is the image surface area.

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2.4.5. Zeta potential Zeta potential measurement is important in the interpretation and prediction of filtration properties especially in a fouling study [36]. In this study, streaming potential measurements were applied where the potential was induced when an electrolyte solution flows across a stationary charged surface [37]. This method has easily measurable magnitude and it is very sensitive to change in concentration increasing for low concentrations [38]. A 0.01 M KCl solution was used and the pH was varied between 3 and 12 by adding NaOH and HCl. The membrane sample with dimensions of 30 mm × 50 mm was placed on the glass plate. After setting up the experimental rig, the electrolyte solution is pumped through the membrane cell with the applied pressure difference of 0.4 bar. This experiment comes out with the charge characteristics and iso-electric point of the exterior membrane surface.

185

until the end of the experiment. This is because the longer the evaporation time, the rougher the membrane surface, leading to membrane deterioration. Therefore, after the evaporation time reached 1.34 min, the permeability started to decrease. Based on ANOVA analysis, all the factors followed second-order effects, yielding a quadratic model for membrane permeability. In Table 3, it is obvious that there was no major interaction between the three factors (AB, BC, and AC). The models, in terms of the coded and actual factors of membrane permeability, are:   2 2 ðY1 Þ ¼ 4014:54 þ 367:21ðAÞ−297:794ðBÞ−248:85ðCÞ−1178:66 A ð4Þ     2 2 −991:83 B −1038:95 C 2

6

5

ðY1 Þ ¼ −1:09  10 þ 1:21  10 ðPESÞ þ 6813:07ðPANIÞ þ 3639:1ðTIMEÞ ð5Þ

3. Results and discussion

2

2

−3333:75ðPESÞ −4987:22ðPANIÞ −1306:04ðTIMEÞ

2

3.1. RSM and ANOVA analysis In RSM, the experimental data were analysed using ANOVA and experimental response models were achieved. The optimised conditions of the operating variable could also be obtained using the response models. 3.1.1. Permeability All the data and analysis from RSM are presented graphically in order to get a clear view of the interactions between the factors and responses. Fig. 1 shows the three-dimensional response surfaces for membrane permeability. In Fig. 1(a), at low and high concentrations of PANI, the permeability increased with the PES concentration from 17.41 wt.% to 18.1 wt.% and decreased from 18.1 wt.% to 18.59 wt.%. This occurred because the polymer density per unit volume of the membrane increased with an increase in the polymer concentration. Therefore, the membrane resistance also increased and decreased the mass transfer rates of the permeating components, resulting in decreased permeability [39]. Fig. 1(b) shows the effect of PES concentration and the evaporation time on membrane permeability. At low and high concentrations of PES, it can be seen that permeability increased with evaporation time from 0.61 to 1.34 min and decreased with further increments. The optimum permeability was observed at the PES concentration of 18.33 wt.% and 1.34 min of evaporation time. A shorter evaporation time after the casting process improved the membrane structure. Usually, the membranes that were prepared with a shorter solvent evaporation time had a smoother membrane surface than those prepared with a longer evaporation time [28]. In this case, after the membrane permeability reached a certain point, the permeability decreased

3.1.2. Salt rejection Fig. 2 shows the three-dimensional graphs that represent the effect of the three factors on salt rejection. In Fig. 2(a), at low and high concentrations of PANI, salt rejection increased when the PES concentration increased from 17.41 wt.% to 18 wt.% and then decreased when the PES concentration increased to 18.59 wt.%. The same trend occurred in the PES concentration and evaporation time threedimensional graph in Fig. 2(b). At low and high concentrations of PES, salt rejection increased in the range of evaporation time from 0.61 to 1.5 min and decreased from 1.5 to 2.39 min. In this graph, the optimum PES concentration (18.33 wt.%) and evaporation time (1.34 min) that resulted in optimum permeability were also associated with the optimum value for salt rejection.

b) 4055.33

3340.3

3336.72

(Permeabolity) 2

4060.72 2619.89

>

(Permeabolity) 2

a)

where Y1 represents permeability with six terms: PES concentration (A), PANI concentration (B), evaporation time (C) and the secondorder effects of PES concentration (A2), PANI concentration (B2) and evaporation time (C2). This model was well fitted to the experimental results based on the p value which was less than 0.05. The p-value is the probability of error that is associated with accepting the observed result as valid. Normally, a p-value of 0.05 is the borderline acceptable error level [32]. The reliability of the regression models for membrane permeability showed moderate accuracy given by the R2 value (0.6633) and standard deviation (1203.59). This result was obtained because the manual casting technique is difficult to control compared to using a casting machine. This situation led to variable casting speeds in membrane preparation, which causes variations in membrane thickness. This factor has a large influence on membrane performance, especially in terms of membrane permeability [31].

1899.47 1179.06

1.20

18.59

>

0.97 0.75

B:Polyaniline concentration 0.53

18.30 18.00 17.70 A: PES concentration 0.30 17.41

2618.1 1899.49 1180.87

18.59

2.39

18.30 18.00

A: PES concentration

1.95 1.50

17.70 17.41

1.05 0.61

C: Evaporation time

Fig. 1. 3D graph response surface plotted on: a) PANI concentration and PES concentration, and b) PES concentration and evaporation time for membrane permeability.

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Table 3 ANOVA and regression analysis for permeability.

Table 4 ANOVA and regression analysis for salt rejection.

Source

Sum of squares

DF

Mean square

F

p>F

Source

Sum of squares

DF

Mean square

F

p>F

Model A B C A2 B2 C2 Lack of fit

2.853E+007 1.842E+006 1.211E+006 8.457E+005 1.566E+007 1.109E+007 1.217E+007 1.393E+007

6 1 1 1 1 1 1 8

4.755E+006 1.842E+006 1.211E+006 8.457E+005 1.566E+007 1.109E+007 1.217E+007 1.741E+006

3.28 1.27 0.84 0.58 10.81 7.66 8.40 6.27

0.0473 0.2859 0.3821 0.4625 0.0082 0.0199 0.0159 0.1449

Model A B C A2 B2 C2 Lack of fit

1.933E+009 7.921E+006 1.908E+007 1.380E+006 1.170E+009 8.435E+008 9.997E+008 9.611E+007

6 1 1 1 1 1 1 8

3.221E+008 7.921E+006 1.908E+007 1.380E+006 1.170E+009 8.435E+008 9.997E+008 1.201E+007

33.03 0.81 1.96 0.14 119.95 86.49 102.51 17.02

b0.0001 0.3887 0.1922 0.7147 b0.0001 b0.0001 b0.0001 0.0567

For salt rejection, the empirical model provided a model with a p-value less than 0.05 and no major interactions between factors occur as shown in Table 4. The equation obtained includes PES concentration (A), PANI concentration (B), evaporation time (C) and the second-order effects of PES concentration (A2), PANI concentration (B2) and evaporation time (C2) in terms of coded and actual factors: 3

ðY2 Þ ¼ 36; 900:93 þ 761:56ðAÞ−1181:88 ðBÞ   2

þ 317:87ðCÞ−10; 186:47 A   2 þ 9416:98 C

3

6

  2 −8649:9 B ð6Þ

Y3 ¼ 56:94−1:73ðAÞ−0:054   ðBÞ 

6

ðY2 Þ ¼ −9:37  10 þ 1:04  10 ðPESÞ þ 62; 591:36ðPANIÞ 2

decreased from 1.35 to 2.39 min. This graph also shows the optimum contact angle with a similar PES concentration (18.33 wt.%) and evaporation time (1.34 min) as shown before. From the contact angle measurements, the model comes out with the equation that shows a strong interaction between factors A and B as shown in Table 5. The obtained model consisted of PES concentration (A), PANI concentration (B), evaporation time (C) and the second-order effects of PES concentration (A2) and evaporation time (C2) as well as an interaction effect of PES concentration plus PANI concentration (AB), with a p-value of less than 0.05. The equations obtained in the coded and actual factors are:

2

2

þ 35; 870:04ðTIMEÞ−28; 811:68ðPESÞ −43; 494:4ðPANIÞ

þ 0:6ðCÞ−2:88 A

ð7Þ

2

−11; 837:88ðTIMEÞ :

2

−2:08 C

 −2:11ðABÞ

ð8Þ

Y3 ¼ −2642:28 þ 296:1ðPESÞ þ 143:28ðPANIÞ 2

2

þ 8:53ðTIMEÞ−8:14ðPESÞ −2:62ðTIMEÞ −7:97ðPESÞðPANIÞ: ð9Þ 2

This equation shows a high R value (0.9520) that reflects the high reliability of the regression model for salt rejection. 3.1.3. Contact angle Fig. 3 shows the three-dimensional graphs for contact angle. In Fig. 3(a), at a low concentration of PANI, the contact angle value increased when the PES concentration increased from 17.41 wt.% to 18 wt.% and decreased when the PES concentration increased from 18 wt.% to 18.59 wt.%. However, at a high concentration of PANI, the contact angle value continuously decreased with a PES concentration of 17.41 wt.% to 18.59 wt.%. This result shows that membrane hydrophilicity improved with higher PANI concentrations. PANI contributed to the enhanced hydrophilicity by its high surface energy and the existence of hydrophilic groups (\NH\) in its structure. Fig. 3(b) shows the effect of PES concentration and evaporation time on the contact angle values. At low and high concentrations of PES, the contact angle value increased with the evaporation time from 0.61 to 1.35 min and

The reliability level of this equation showed moderate accuracy with an R2 value of 0.6601 and a standard deviation of 3.29. This situation occurred as it was difficult to be consistent in each casting process, resulting in variable membrane performance. Fig. 4 shows the interaction effect among the parameters where the effects of binary combination of combining two independent factors can be easily recognised. All of the interaction graphs show non-parallel curvatures that indicate a relatively strong interaction between the variables of PES concentration (A), PANI concentration (B) and evaporation time (C) [29]. 3.2. Optimisation and verification of the statistical model Membrane optimisation was determined by the RSM software through regression analysis. The membranes produced were targeted to achieve maximum permeability, the highest salt rejection and the

a)

b) 36900.9

33.302

31730.2 (Rejection) 3

Rejection

31.2919

<

29.2819 27.2719 25.2618

1.20 0.97

18.59 18.30 0.75

B: Polyaniline concentration 0.53

26559.5 21388.8 16218.1

18.59 2.39

18.30

18.00 18.00 17.70 A: PES concebtration A: PES concebtration 17.70 0.30 17.41 17.41 0.61

1.95 1.50 1.05

C: Evaporation time

Fig. 2. 3D graph response surface plotted on: a) PANI concentration and PES concentration, and b) PES concentration and evaporation time for salt rejection.

N.F. Razali et al. / Desalination 311 (2013) 182–191

b) 58.1709

57.244

56.1697

55.3446

54.1686

53.4453

Contract Angle

Contract Angle

a)

187

52.1674 50.1663

1.20

18.59 18.30

0.97 0.75

18.00

B: Polyaniline concentration 0.53

17.70 0.30 17.41

51.5459 49.6466

18.59 18.30

2.39 1.95

18.00

A: PES concentration 17.70

A: PES concentration

17.41 0.61

1.50 1.05 C: Evaporation time

Fig. 3. 3D graph response surface plotted on a) PANI concentration and PES concentration and b) PES concentration and evaporation time for contact angle.

lowest contact angle. The software provided the predicted values and a confirmation run was required to verify the prediction. The difference between the predicted and real values was calculated in order to determine the error percentage. The error percentages were calculated based on the following equation:
Errorð% Þ ¼

 Actual value−Predicted value  100%: Actual value

ð10Þ

The confirmation run was conducted with the optimum operating parameters of 18.33 wt.% PES, 0.75 wt.% PANI and 1.34 min of evaporation time. In Table 6, the predicted responses obtained were 62.2 L/m 2 bar h for permeability, 32.35% for salt rejection and 54.95°for the contact angle. This preliminary study shows that the optimised composition could produce membranes with the desired responses. The confirmation runs gave 65 L/m 2 bar h for permeability, 30.63% for salt rejection and 55.7° for the contact angle with percentage errors for permeability, salt rejection and contact angle of 4.3%, 1.4% and 5.6%, respectively. These results show that the errors were less than 6% for each response. These small errors show that the CCD process optimisation was able to reliably produce membranes with the desired responses with the membrane modifications suggested by the optimum parameters. Additional run was conducted with the same PES composition and evaporation time, but without the presence of PANI nanoparticles. The results come out with 0.5 L/m 2 bar h for permeability, 25% for salt rejection and 60° for the contact angle. These results show a lot of improvement in the blended membrane compared with the controlled membrane.

the improvement and difference in the performance and structure. PANI characterisations have been presented in the previous work [40]. 3.3.1. SEM analysis Fig. 5 shows the SEM images of the surface and cross-sections of the control and blended membranes. Fig. 5(a) shows the control membrane without PANI nanoparticles while Fig. 5(b) shows the PANI nanoparticles on the surface. From the figure, it can be seen that the PANI nanoparticles were stably dispersed over the surface of the membrane. Even though some agglomeration occurred, particles were still nanoparticle-sized and did not affect membrane performance. Fig. 5(d) shows an improvement in the cross-sectional membrane structure after PES was blended with PANI nanoparticles. The comparison between images in this figure indicates that the addition of PANI nanoparticles led to membranes with larger pores and higher porosity. The PANI nanoparticles produced finger-like pores through the cross section of the PES membrane that resulted in an enhancement in permeability. PANI as the emeraldine base has high solubility in NMP and is slightly soluble in water [41]. During membrane formation, watersoluble polymers act as pore formers. The pores in the membranes formed since the water-soluble polymers leached out of the flat sheet membrane and the places where the polymers came from became pores [42]. In this case, PANI nanoparticles acted as pore formers as the small amount of PANI that was soluble in water leached out from the prepared membrane together with the solvent into the coagulation bath. This phenomenon occurred during phase separation resulting in an improvement in membrane pore size and porosity.

3.3. Membrane characterisation

3.3.2. AFM results

The PES–PANI blended membrane was then characterised using SEM, and AFM and also by measuring the surface charge. The comparisons were made between the control membrane and the optimised membranes obtained from the previous analysis in order to analyse

3.3.2.1. Roughness. Fig. 6 depicts the three-dimensional images of the control and blended membranes. It can be seen that the blended PES–PANI membrane had greater roughness compared to the PES membrane where the Ra values of the modified and unmodified membranes were 4.391 and 1.192 nm, respectively. Normally, greater surface roughness is related to a higher fouling tendency. However, in this study, the presence of PANI increased the surface roughness and provided improved anti-fouling properties. Usually, fouling occurs due to contaminants that accumulate in the valleys of the rough surface. Nevertheless, hydrophilic PANI nanoparticles helped to improve membrane surface hydrophilicity with the presence of hydrophilic (\NH\) groups in the PANI structure. As a result, this material can reduce the adhesive force between contaminants and the membrane surface, leading to an improvement in the anti-fouling properties. An improvement in membrane hydrophilicity can reduce the fouling tendency even though the surface roughness is increased. The increase in

Table 5 ANOVA and regression analysis for contact angle. Source

Sum of squares

DF

Mean square

F

p>F

Model A B C A2 C2 AB Lack of fit

210.52 41 0.040 4.98 102.29 53.56 35.70 102.94

6 1 1 1 1 1 1 8

35.09 41 0.040 4.98 102.29 53.56 35.70 12.87

3.24 3.78 3.707E−003 0.46 9.44 4.94 3.29 4.71

0.0492 0.0804 0.9527 0.5131 0.0118 0.0505 0.0996 0.1868

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Interaction Graph

Interaction Graph B: Polyaniline concentration

A: PES concentration

4424.910

3271.624

(Permeability) 2

(Permeability) 2

4424.910

3272.077

<

<

2118.337

2119.244

965.050

966.411

-188.236

-186.422 17.41

17.70

18.00

18.30

0.61

18.59

1.50

1.95

2.39

C: Evaporation time

A: PES concentration Interaction Graph

Interaction Graph

B: Polyaniline concentration

33.6

1.05

A: PES concentration

37933.056

(Permeability) 3

29.575

29789.636

Rejection

<

25.55

21646.216

21.525

13502.795

17.5

5359.375 17.41

17.70

18.00

18.30

0.61

18.59

Interaction Graph

1.95

2.39

A: PES concentration

63

58.65

58.8069

Contact Angle

Contact Angle

1.50

Interaction Graph

B: Polyaniline concentration

63

1.05

C: Evaporation time

A: PES concentration

54.3

54.6137

49.9501

50.4206

45.6001

46.2274 17.41

17.70

18.00

18.30

18.59

0.61

1.05

1.50

1.95

2.39

C: Evaporation time

A: PES concentration

Fig. 4. Interaction plots of membrane permeability, salt rejection and contact angle.

Table 6 Error percentage between predicted values and actual values for the responses.

Predicted value Actual value Error (%)

Permeability (L/m2 bar h)

Salt rejection (%)

Contact angle (°)

62.2 65 4.3

32.35 30.63 1.4

54.95 55.7 5.6

the membrane surface roughness also led to a high surface area for filtration. Due to the hydrophilicity of PANI, water molecules could permeate through the nanoparticles and the accumulation of the nanoparticles on the membrane surface enhanced the effective filtration area instead of reducing it [43]. 3.3.2.2. Pore size distribution. Fig. 7 displays the pore size distributions that were measured using two-dimensional AFM images with an area

N.F. Razali et al. / Desalination 311 (2013) 182–191

a)

c)

b)

d)

189

Fig. 5. SEM images of the membranes: a) surface of the PES membrane, b) surface of the PES–PANI membrane, c) cross section of the PES membrane and d) cross section of the PES–PANI membrane.

of 5 μm × 5 μm. It is clear that the PES/PANI membrane had a larger range of pore sizes. The pore sizes were in the range of 2–40 nm with a porosity of 9%. Porosity can be used as a prediction of the percentage area of the membrane that the fluid may pass through [35]. These results were in contrast with those of the control membrane which had a smaller value for the range of pore sizes, from 1 to 6 nm, and a porosity of 0.16%. These results show that the PANI nanoparticles changed the morphology of the PES membrane by producing more pores with larger pore diameter. 3.3.3. Surface charge determination Fig. 8 shows the zeta potential as a function of pH for PES and PES– PANI blended membranes. The addition of PANI nanoparticles into the PES polymer solution obviously changed the surface charge of the PES membrane. For the PES–PANI blended membrane, the membrane is slightly positively charged at low pH and become negatively charged at high pH. For PES membrane, the membrane shows negatively charged over the entire pH range studied. The iso-electric point of the blended membrane is located at pH 3 while the controlled membrane did not have any iso-electric point.

a)

Digital Instruments Nanoscope Scan size 5.000 µm Scan rate 1.001 Hz Number of samples 512 Image Data Height 75.00 nm Data scale

1 2 3

x 1.000 µm/div z 75.000 µm/div

4 µm

Digital Instruments Nanoscope Scan size 5.000 µm Scan rate 1.001 Hz Number of samples 512 Image Data Height 50.00 nm Data scale

b)

4. Conclusions The CCD of the RSM was successfully applied for parameter optimisation in the production of blended PES–PANI membranes. From the CCD, the optimum compositions obtained were 18.33 wt.% PES, 0.75 wt.% PANI and 1.34 min of evaporation time. The predicted values for the permeability, salt rejection and contact angle were 62.2 L/m2 h bar, 32.4% and 54.95°, respectively, which were tested by analysis of variance (ANOVA). These results were confirmed experimentally where the deviations from the predicted value were less than 6% for each of the response variables. From the additional membrane characterization, it can be observed that the addition of PANI nanoparticles in PES membrane shows a lot of improvement in the blended membrane compared with the controlled membrane. From

1 2 3 4

µm

x 1.000 µm/div z 50.000 µm/div

Fig. 6. AFM images of the membranes: a) PES membrane and b) PES–PANI membrane.

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a) 50

References

% of Pores

40

30

20

10

0 1

2

3

4

5

6

Pore Radius (nm)

b) 60

% of Pores

50

40

30

20

10 0

5

10

15

20

25

30

35

40

Pore Radius (nm) Fig. 7. Pore size distribution of the membranes: a) PES membrane and b) PES–PANI membrane.

this research, PANI nanoparticles has shown its ability in improving the membrane structure and performance when deposited on the membrane surface and it can be a promising nanoparticle for future research.

Acknowledgements

Zeta potential (mV)

The financial support for this research from UKM-GUP-KPB-0832-129 is gratefully acknowledged.

2 0 -2 0 -4 -6 -8 -10 -12 -14 -16 -18 -20 -22 -24

1

2

3

4

5

6

7

8

9

10 11 12 13

pH PES-PANI

PES

Fig. 8. Zeta potential behaviour as a function of the pH for both PES and PES–PANI blended membranes.

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