polyethylene hybrid membranes for collagen separation

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Chemical Engineering Research and Design journal homepage: www.elsevier.com/locate/cherd

Preparation, characterization and fouling analysis of ZnO/polyethylene hybrid membranes for collagen separation Y. Jafarzadeh a,b , R. Yegani a,b,∗ , M. Sedaghat a,b a b

Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran Membrane Technology Research Center, Sahand University of Technology, Tabriz, Iran

a b s t r a c t In this study, high density polyethylene (HDPE) membranes embedded with ZnO nanoparticles were fabricated via thermally induced phase separation (TIPS) method. A series of tests including FESEM, XRD, TGA, AFM, contact angle measurement, pure water flux, porosity and mean pore radius were performed for characterization of membranes. FESEM images showed that the membranes had leafy structure indicating solid–liquid phase separation mechanism. The results of XRD and TGA analysis confirmed the presence of ZnO nanoparticles in the polymer matrix. AFM images showed that the surface roughness of ZnO embedded membranes were higher than that of neat HDPE membrane. Pure water flux as well as surface hydrophilicity of membranes improved as the ZnO content increased. In addition, the fouling behavior of membranes was investigated by filtration of collagen protein solution. The governing fouling mechanisms of membranes were also investigated using classic models as well as combined fouling models. The results showed that for all membranes the best fit of the data occurred with the cake filtration-complete blockage model (CFCBM). Moreover, the deviation between experimental data and CFCBM prediction decreased by increasing the content of ZnO. © 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Keywords: ZnO; Polyethylene; Thermally induced phase separation (TIPS); Membrane; Fouling; Collagen

1.

Introduction

Polyethylene (PE) membranes are widely used in different membrane processes such as membrane distillation, membrane extraction and microfiltration due to its excellent mechanical strength, chemical resistance and thermal stability (Li et al., 2003; Zhang et al., 2010). Moreover, the low cost of PE membrane makes it possible to attract much attention of researchers. PE membranes are usually fabricated via thermally induced phase separation (TIPS) method (Lloyd et al., 1990; Matsuyama et al., 2002). This method is one of the most popular ways of making microporous membranes in which a polymer is dissolved in a diluent at an elevated temperature and by removing thermal energy from the solution, the phase separation is induced (Lloyd et al., 1990,

1991; Matsuyama et al., 1999, 2002). Generally, membranes formed by TIPS method possess higher porosity and mechanical strength because the microstructure of membranes can be easily controlled via TIPS method, thus they have attracted much attention in the last decades (Park and Kim, 2014; Roh et al., 2012). PE membranes, however, suffer from non-wettability and poor biocompatibility due to the characteristics of PE molecular chains, which limits their application in separation of aqueous solutions, biomedical fields and water treatment (Liu et al., 1999; Zhang et al., 2010). In other word, PE membranes are very susceptible to fouling because of their inherent hydrophobicity. It has been shown that hydrophilic polymer membranes are more fouling-resistant than hydrophobic ones (Rahimpour et al., 2008; Teli et al., 2012). Thus, increasing

∗

Corresponding author at: Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran. Tel.: +98 914 416 1424; fax: +98 41 3344 4355. E-mail address: [email protected] (R. Yegani). http://dx.doi.org/10.1016/j.cherd.2014.08.017 0263-8762/© 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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hydrophilicity could be a reasonable approach to mitigate fouling of the hydrophobic membranes. Many efforts have been devoted to reduce fouling in hydrophobic polymer membranes via surface modification of membranes using different methods such as grafting methods (Azari and Zou, 2013), plasma technique for surface treatment (Ulbricht and Belfort, 1996), ozone treatment (Gao et al., 2011) and dip-coating (Rahimpour et al., 2008). In surface modification, however, surface property of internal pores is barely concerned. Incorporation of inorganic nanoparticles into polymer matrix of membranes is another method to improve membrane antifouling properties and has recently attracted great interests in membrane technology due to unique physicchemical properties of these nanoparticles (Balta et al., 2012; Liang et al., 2012). In this method, nanoparticles with appropriate properties are dispersed through the membrane bulk and therefore, internal pores of membrane could also be concerned. These particles also elevate the mechanical strength of polymeric membranes, which is necessary due to the need for higher operational pressure in fouled membranes. Nanoparticles which have been widely used in polymer-inorganic membranes include carbon nanotubes (CNT) (Kumar and Ulbricht, 2014), TiO2 (Shi et al., 2012), SiO2 (Cui et al., 2010), ZrO2 (Bottino et al., 2002), Al2 O3 (Yan et al., 2005) and ZnO (Balta et al., 2012; Liang et al., 2012). ZnO is a multifunctional semiconductor which due to its desirable properties such as hydrophilicity, antifouling abilities, photocatalytic activities, stability and availability has been recently used in inorganic particle-embedded polymer membranes (Balta et al., 2012; Leo et al., 2010; Shen et al., 2012). Several studies have investigated the incorporation of ZnO nanoparticles into different polymers including PES (Balta et al., 2012; Shen et al., 2012), PVDF (Liang et al., 2012) and PSf (Leo et al., 2010). However, to the best of our knowledge, ZnO/polyethylene membranes have not been yet studied. In addition, fouling mechanisms of ZnO embedded polymeric membranes have not been investigated to elucidate the effect of ZnO content on the fouling mechanism. In the present work, a novel ZnO/PE membrane was successfully fabricated using the TIPS method. A set of analyses including field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), atomic force microscopy (AFM), thermogravimetric analysis (TGA), contact angle measurement, pure water flux, porosity and mean pore radius were carried out for characterization of membranes. Furthermore, the fouling characteristics of the membranes were investigated using collagen protein solution. Finally, fouling mechanism of membranes was analyzed using classic and combined models to investigate the effect of nanoparticles on the fouling mechanism of polyethylene membrane.

1.1.

Theory

The governing mechanisms of fouling are usually explained by fouling models. Classically, there are four different models used to describe membrane fouling, including standard blockage, intermediate blockage, complete blockage and cake filtration (Charfi et al., 2012). In the standard blockage or pore constriction model, foulants accumulate on the walls of inner pores and constrict their radius. In the intermediate blockage model, a portion of the particles seal off some pores and the rest of them settle on each other. Foulants seal off pore entrances completely in the complete blockage model. Finally,

in the cake formation model, a layer of particles and foulants is formed on the surface of membrane (Bolton et al., 2006; Rezaei et al., 2011). These models have been used individually or in combinations to investigate the fouling behavior of membranes in different filtration processes. For a constant pressure filtration system, the flux decline can be expressed in the following mathematical form (Charfi et al., 2012):



d2 t dt =k dV dV 2

m (1)

where t is filtration time, V is the filtrate volume, k is resistance coefficient and m is a constant which characterizes the fouling model. The values of m for cake filtration, intermediate blockage, standard blockage and complete blockage models are 0, 1, 1.5 and 2, respectively (Bolton et al., 2006; Charfi et al., 2012). Having the flux equation on the hand: J=

1 dV A dt

(2)

Eq. (1) can be written as: dJ 2−m = −kJ(AJ) dt

(3)

The analytical solutions to Eq. (3) for each m value (0, 1, 1.5 and 2) as well as the linear forms of flux expressions are listed in Table 1. These are classic models for membrane fouling. In addition to the classic models, some combined models have been developed to predict flux behavior in membrane filtration processes. Ho and Zydney (2000) developed a combined model consisted of a two-stage mechanism. This mathematically complex model accounts for initial fouling due to the pore blockage and subsequent fouling due to the cake formation. Based on Darcy’s law, Bolton et al. (2006) developed some combined models describing fouling mechanisms with two fitted parameters. These models are mathematically simpler than the model developed by Ho and Zydney, therefore have attracted much attention recently. A summary of pressure constant combined fouling models are listed in Table 2.

2.

Experimental

2.1.

Materials

Commercial grade of high density polyethylene (weight average molecular weight of ca. 119,500 g/mol) was provided by Amirkabir Petrochemical Company and used as polymer. ZnO nanoparticles (particle size less than 100 nm) were purchased from Sigma Aldrich. Mineral oil (MO) as diluent and acetone as extractant were purchased from Acros Organics and Merck, respectively. Collagen from calf skin was purchased from Sigma–Aldrich. All materials were used as received.

2.2.

Preparation of membranes

Thermally induced phase separation method was applied to prepare neat and ZnO embedded membranes. Different amounts of ZnO nanoparticles 0.25, 0.50, 0.75 and 1.00 g were dispersed into 79.75, 79.50, 79.25 and 79.00 g of MO, respectively using sonication by probe system (Sonopuls HD 3200, Bandelin) for 15 min. Then 20 g polyethylene was added to the diluent-nanoparticle suspension and melt-blended at 160 ◦ C

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Table 1 – Solutions to Eq. (3) for different m values (Jafarzadeh and Yegani, 2014; Razi et al., 2012). Fouling model

m

Flux expression

Cake filtration

0

J=

Intermediate blockage

1

J=

1.5

J=

Complete blockage

2

J = J0 exp(− kt)

2.3.

Membrane characterization

2.3.1.

SEM

2.3.5.

1 J

= ln

1 J0

+ kt

Atomic force microscopy

2.3.6.

Pure water flux

Pure water flux of membranes was determined using an inhouse fabricated dead-end filtration system having 5 cm2 of membrane area. To minimize compaction effects, the prewetted membranes were compacted for 30 min at 2 bar. Then the pressure was reduced to 1.4 bar and after reaching steady state, water flux was calculated using following equation: J0 =

M A·t

(4)

where J0 is pure water flux, M is collected mass of water (kg), A is membrane area (m2 ), and t is the time (h).

XRD analysis 2.3.7.

Porosity and mean pore radius

The overall porosity of membranes (ε) was determined based on the density measurement method using following equation adopted from Ref. Mansourizadeh et al. (2010): m p

ε=1−

Thermal analysis

The quality of dispersion of ZnO nanoparticles in the fabricated membranes was investigated using a PerkinElmer Pyris Diamond TGA system at a heating rate of 10 ◦ C/min under nitrogen atmosphere. Samples were taken from three different areas of each membrane and the amount of residue was reported as averaged of three tests.

(5)

where m and p are the densities of membrane and polyethylene, respectively. It should be noted that in Eq. (1) the effect of ZnO was neglected due to its low percent in the casting solution (ZnO wt.% ≤1%). Thus, the density of membrane was calculated as follow: M V

m =

2.3.4.

ln

Atomic force microscopy studies were conducted in tapping mode using Nanosurf Mobile S. Samples were prepared by cutting the membranes longitudinally in very narrow ribbons of less than 1 mm width and 5 mm length. The surface roughness of membranes (Ra ) was calculated using a method mentioned elsewhere (Cui et al., 2010).

XRD study of membranes was conducted with a diffractometer (D8 Advance, Bruker) equipped with monochromatic Cu-K␣ radiation ( = 0.154 nm) under a voltage of 40 kV and a current of 40 mA. All samples were analyzed in continues scan mode with the 2 ranging from 10◦ to 80◦ .

2.3.3.

1 + kt J2 0 1 1 J = J0 + kt 1 √ = √1J + kt J 0

=

using a contact angle goniometer (PGX, Thwing-Albert Instrument Co.). The average of 5 measurements was reported.

The morphology of the membranes was characterized by FESEM (MIRA3 FEG-SEM, Tescan). Cross-section samples were prepared by fracturing the membranes in liquid nitrogen. All samples were coated with gold by sputtering before observation to make them conductive.

2.3.2.

1 J2

1/2 (1+J2 kt) 0 J0 1+J0 kt J0 1/2 2 (1+J kt) 0

Standard blockage

and 450 rpm for 90 min in a sealed glass vessel kept in a silicon oil bath. The solution was then allowed to degas for 30 min and cast on a preheated glass sheet using a doctor blade. The plate was immediately quenched in the water bath (27 ◦ C ± 3) to induce phase separation. The membrane was then immersed in acetone for 24 h to extract its diluent. Finally, it was dried at room temperature to remove acetone. The results of DSC analysis (data are not shown) revealed that the acetone in the membranes was removed during drying at room temperature. In the case of neat polyethylene membrane, MO and polyethylene was melt-blended at 160 ◦ C for 90 min in a sealed glass vessel kept in a silicon oil bath. The other procedures were same to the ZnO embedded membranes preparation.

Linear form

J0

Contact angle measurement

The hydrophilicity of membranes was evaluated by measuring contact angle between membrane surface and water droplet

(6)

where M and V are the mass and the volume of the membrane, respectively. Membrane mean pore radius was determined

Table 2 – Some of the combined fouling models at constant pressure (Bolton et al., 2006). Models Cake filtration-complete blockage (CFCBM)

V=

J0 Kb

Cake filtration-intermediate blockage (CFIBM)

V=

1 Ki

V=

2 Ks

Cake filtration-standard blockage (CFSBM)

˛= ˇ=

Expressions





1 − exp

 ln



1+

Ki K J

c20

−Kb Kc J2 0

(



(





1 + 2Kc J02 t − 1)



1 + 2Kc J02 t − 1)



ˇ cos 3 − 13 arccos(˛) 4K2 t 8 s + 4K − 3s 27ˇ3 3ˇ3 Kc J0 3ˇ Kc 2Ks2 t 4Ks 4 9 + 3Kc J0 + 3Kc

+

1 3



Fitted parameters Kc (s/m2 ), Kb (s−1 ) Kc (s/m2 ), Ki (m−1 ) Kc (s/m2 ), Ks (m−1 )



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by filtration velocity method using Guerout–Elford–Ferry (GEF) equation as follow (Li et al., 2009; Vatanpour et al., 2012):

 rm =

elsewhere (Lareu et al., 2010). The rejection of the collagen was calculated as follow:

8lQ(2.9 − 1.75ε) εAP

(7)

R (%) =

Cp 1− Cf

× 100

(12)

where  is water viscosity, l is membrane thickness, Q is the volume of the permeated pure water, ε is membrane overall porosity, A is membrane area and P is trans-membrane pressure.

where Cp and Cf permeate and feed concentration of collage, respectively.

2.4.

Fouling mechanisms of fabricated membranes can be determined using flux expressions in Table 1 as follows. Experimental data were substituted in linear forms of flux equations for different fouling models and the value of k was determined using the least square method. The best expression obtained by the experimental data predicts the most probable fouling mechanism responsible for the flux decline observed. In the case of combined fouling models, the permeate volume versus filtration time (see Table 2) were fit using the aforementioned models and the best fit was determined by minimizing the sum of squared residuals (SSR) or sum of square errors (SSE) where the residual was equal to the difference between a data point and the model prediction (Bolton et al., 2006).

Filtration experiments

In order to study the effect of ZnO on the membranes fouling, the membranes were tested in a dead-end filtration system filled with collagen protein solution as the model protein solution. The solution was prepared by dissolving 1.00 g of collagen powder in 1 L of standard (0.1 M) phosphate buffer saline (PBS) solution at pH of 7.2. The system consisted of a cup connected to a pressure balloon and equipped with a stirrer. After measuring pure water flux (as mentioned earlier), the membrane holder was connected to the protein filtration system and the system was pressurized. All the filtration experiments were conducted at trans-membrane pressure of 1.4 bar. After about 300 min filtration, the membrane cell was again connected to the pure water filtration system and pure water flux after fouling (J1 ) was measured using Eq. (1). Then the cake layer on the membrane was gently removed mechanically by a sponge and the membrane was rinsed with deionized water. Finally the membrane was held in the holder and connected to the pure water filtration system and pure water flux after rinsing (J2 ) was measured using Eq. (1). Comparison between J0 , J1 and J2 gives useful information about flux behavior and variety of fouling resistance of membranes. The total fouling ratio (TFR) of a membrane is defined as follow: TFR =

J − J  1 0 J0

× 100

(8)

TFR is a degree of total flux loss caused by total fouling and the less TFR value is, the better the antifouling performance of membrane is. Moreover, two other important fouling ratios are reversible fouling ratio (RFR) and irreversible fouling ratio (IFR) which can be defined by following equations: RFR =

IFR =

J − J  1 2 J0

J − J  0 2 J0

× 100

× 100

(9)

(10)

Obviously TFR = RFR + IFR. Finally, having J0 and J2 on the hand, the flux recovery (FR) can be calculated   easily as follow: (11)FR = JJ2 × 100 0 The flux recovery is an index of antifouling property of membranes. Generally, higher FR indicates that the membrane is more fouling-resistant.

2.5.

Membrane performance

The retention of collagen protein was investigated for the prepared membranes by measuring the concentration of the collagen in the permeate using a method mentioned

2.6.

Analysis of fouling mechanisms

3.

Results and discussion

3.1.

Morphology studies, XRD and TGA analysis

The SEM images of surface and cross-section of neat and ZnO embedded HDPE membranes were shown in Fig. 1. It can be seen that all membranes have leafy structures characterized by randomly oriented connected polyethylene leaves. Lloyd has shown that HDPE/mineral oil casting solutions with compositions in the range of 15–50 wt.% HDPE undergo solid–liquid phase separation and therefore, they are capable of producing membranes with leafy structures (Lloyd et al., 1990). The presence of ZnO particles in the membranes structure especially in higher content of ZnO is clear. These structures are quite similar to that of TiO2 /HDPE membranes reported by Jafarzadeh and Yegani (2014). Fig. 1 shows that increasing the dosage of ZnO from 0 to 1 wt.% increased number of pores in the surface of membranes. This may be due to the heterogeneous nucleation effect of ZnO nanoparticles. When the casting solution of HDPE/MO/ZnO is quenched in water bath, ZnO nanoparticles act as crystal nuclei and therefore, polymer chains are crystallized around them. As a result, clusters of ZnO embedded polyethylene are formed, resulting in finer pores in the surface and the bulk of membranes (see cross section SEM images). On the other hand, the crystallization of polymer chains in the HDPE/MO solution is somewhat different. In this case, there are no heterogeneous nucleation effect and polyethylene lamellae form more uniformly. Therefore, fewer pores are formed in comparison with ZnO embedded membranes. The presence of ZnO nanoparticles was confirmed by XRD analysis. XRD diffraction patterns of ZnO nanoparticles, HDPE and 1 wt.% ZnO embedded HDPE membranes were presented in Fig. 2. The XRD pattern of utilized ZnO nanoparticles showed four crystalline characteristic peaks at 2 of 31.9◦ , 34.6◦ , 36.5◦ and 56.8◦ which is in agreement with the literature (Shen et al., 2012). Two sharp peaks at 2 of 21.6◦ and 24◦ are characteristic peaks of HDPE (Han et al., 2008). The diffraction curve of ZnO embedded HDPE membrane showed the peaks

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Fig. 1 – FESEM images of neat and ZnO embedded HDPE membranes. Upper surfaces: (a) 0.0 wt.% ZnO, (b) 0.25 wt.% ZnO, (c) 0.50 wt.% ZnO, (d) 0.75 wt.% ZnO, (e) 1.0 wt.% ZnO. Cross sections: (f) 0.0 wt.% ZnO, (g) 0.25 wt.% ZnO, (h) 0.50 wt.% ZnO, (i) 0.75 wt.% ZnO, (j) 1.0 wt.% ZnO.

at 2 of 21.6◦ , 24◦ , 31.9◦ , 34.6◦ and 36.5◦ indicating that ZnO nanoparticles have been distributed to the membrane matrix. It also shows that the addition of nanoparticles did not affect the crystalline phase of ZnO embedded HDPE membrane. The same results were observed for 0.25, 0.50 and 0.75 wt.% ZnO embedded HDPE membranes and are not shown here. To examine if ZnO nanoparticles are dispersed well in the membrane matrix, TGA test was done on the neat and ZnO embedded HDPE membranes. For each membrane three different pieces from different parts of flat sheet membrane were cut and used. Fig. 3 shows the results for neat and ZnO embedded HDPE membranes. It can be seen that the residue of, for example, 1.00 wt.% ZnO embedded HDPE membrane is 4.18% which indicates that ZnO nanoparticles were well dispersed throughout the membrane. The casting solution of 1.00 wt.% ZnO embedded HDPE membrane contained 1.00 g ZnO, 20 g HDPE and 79.00 g MO. Therefore, the final amount of ZnO in the membrane should be 4.76% which is close to the obtained result of 4.18% taking into account the fact that some amounts of particles may leached out during membrane fabrication process. Obtained results confirm that in addition to well dispersion of ZnO nanoparticles, the loss of nanoparticles during fabrication process is also negligible.

Fig. 2 – XRD patterns of (a) ZnO nanoparticles, (b) HDPE membrane and (c) 1.0 wt.% ZnO embedded HDPE membrane.

Fig. 3 – TGA for neat and ZnO embedded HDPE membranes.

3.2.

Contact angle and AFM

The effect of ZnO nanoparticles on the contact angle between water drop and prepared membranes was shown in Fig. 4. It can be seen that the contact angle decreased from 118◦ for neat HDPE membranes to 110◦ for 1 wt.% ZnO embedded membrane. As a result of the high affinity of nanoparticles to water, the addition of ZnO can increase the hydrophilicity of the membrane (Balta et al., 2012). However, an 8◦ decrease in contact angle seems not to be so discernable change after embedding hydrophilic ZnO nanoparticles. It

Fig. 4 – Contact angle versus ZnO content of membranes.

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Fig. 5 – AFM images prepared membranes: (a) neat HDPE, (b) 0.25 wt.% ZnO, (c) 0.50 wt.% ZnO, (d) 0.75 wt.% ZnO and (e) 1.0 wt.% ZnO embedded HDPE membranes. may be due to the fact that nanoparticles were coated by polyethylene though they were not in direct contact with the water drop. However, it must be noted that the contact angle between a water drop and a surface depends not only on the surface chemistry, but also on the surface roughness. There is evidence showing that incorporation of nanoparticles into polymer membranes increases the membrane roughness (Cui et al., 2010; Razmjou et al., 2012). According to the Wenzel model, the degree of roughness should be such to amplify the wettability of the surface toward its intrinsic tendency of either roll-up or film formation of the liquid (Jafarzadeh and Yegani, 2014; Razmjou et al., 2012). This means that for a surface like polyethylene which its contact angle is greater than 90◦ , roughening will increase the contact angle. On the other hand, incorporation of hydrophilic ZnO nanoparticles is expected to increase the hydrophilicity and decrease the contact angle. In order to confirm this point, AFM test was performed for the membranes. Fig. 5 shows three-dimensional AFM images of the membrane outer surfaces. Images show that the surface roughness is more pronounced for the membranes containing ZnO nanoparticles. In fact, the rougher surfaces created by ZnO particles were achieved. In the range of scan area of 8 ␮m × 8 ␮m, the surface roughness of the neat, 0.25, 0.50, 0.75 and 1.00 wt.% ZnO embedded HDPE membranes were 59.79, 74.09, 84.21, 109.84 and 131.00 nm, respectively. As mentioned earlier, morphology of the ZnO embedded HDPE membrane can have an influence on the hydrophilicity of the surface; since the water wettability strongly depends on the surface roughness of the films. These images confirmed that the presence of ZnO nanoparticles in the PE membranes increases the membrane roughness. Thus, the two aforementioned contrary factors controlling the final contact angle (hydrophilicity and roughness) compensate each other and therefore no discernable change is achieved in the contact angle.

3.3.

Pure water flux and mean pore radius

The effect of ZnO nanoparticles on pure water flux of membranes is depicted in Fig. 6. Generally, it can be seen that addition of ZnO nanoparticles in the casting solution increased pure water flux of membranes. The pure water flux of membranes increased from 10 kg/m2 h for neat HDPE membrane to 23.2 kg/m2 h for 1.0 wt.% ZnO embedded membrane. It should be noted that the data in Fig. 6 were obtained at relatively low pressure of 1.4 bar to get stable results without membranes tearing. Fig. 7 shows that mean pore radius of membranes increased from ca. 120 nm in the neat HDPE membrane to 162 nm in the 1.0 wt.% ZnO embedded membrane. It confirms that all of the ZnO embedded membranes had larger mean pore radius than neat HDPE membrane. The obtained results were in good agreement with the SEM images shown in Fig. 1 in which, the number of pores in the surface of membranes increased with the addition of ZnO nanoparticles.

Fig. 6 – Pure water flux of neat and ZnO embedded HDPE membranes.

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Table 3 – Rejection performance of neat and ZnO embedded HDPE membranes. ZnO content (wt.%) 0.00 0.25 0.50 0.75 1.00

Fig. 7 – Mean pore radius of neat and ZnO embedded HDPE membranes estimated by using GEF equation.

Fig. 8 – Flux–time behavior of neat and ZnO embedded HDPE membranes in the filtration process of 1 g/L collagen solution.

3.4.

Fouling analysis and membranes performance

In order to explore the fouling mechanisms of membranes, filtration experiments were performed using collagen protein as an organic foulant in aqueous solutions. Fig. 8 shows the results of these experiments. It can be seen that the initial flux of hybrid membranes was higher than that of neat HDPE membrane. This may be attributed to the higher pure water flux of hybrid membranes. Moreover, addition of ZnO nanoparticles in casting solution improved the fouling resistance of membranes. Additional information about membranes fouling including total fouling ratio (TFR), reversible fouling ratio (RFR), irreversible fouling ratio (IFR) and flux recovery (FR) were depicted in Fig. 9. It can be seen that neat HDPE membrane

Fig. 9 – Fouling parameters of neat and ZnO embedded HDPE membranes.

Rejection (%) 88.8 91.0 94.3 90.6 89.1

± ± ± ± ±

1.2 0.9 1.1 1.2 1.0

showed the highest TFR, indicating that this membrane was fouled easily by collagen molecules. Incorporation of ZnO nanoparticles decreased TFR from 88% for neat membrane to 54% for 1.0 wt.% ZnO embedded membrane. Moreover, IFR of membranes decreased from 43.2% for neat membrane to 12% for 1.0 wt.% ZnO embedded membrane. This indicates that incorporation of ZnO nanoparticles into polyethylene membranes not only increased fouling resistance, but also decreased irreversible fouling. Another comparison of antifouling properties of membranes could be obtained by considering the FR values. From Fig. 9 it can be seen that the FR of hybrid membranes were higher than that of neat HDPE membrane. The increase in flux recovery may be attributed to the presence of ZnO nanoparticles on the surface of membranes which increased hydrophilicity (Liang et al., 2012). As mentioned earlier, the presence of ZnO particles in the matrix of membranes improved surface hydrophilicity. In general, it has been shown that hydrophilic polymer membranes are more fouling-resistant than hydrophobic ones (Rahimpour et al., 2008; Teli et al., 2012). In addition, incorporation of ZnO particles increases the surface roughness of membranes which consequently leads to two changes in the membranes; first, an increase in efficient filtration area and second, a decrease of antifouling performance (Cui et al., 2010; Yan et al., 2006). The higher the efficient membrane area would increase the membrane flux. However, the membrane-fouling trend increases with roughness owing to contaminants accumulating in the “valleys” of the rough membrane surface (Yan et al., 2006). Thus, increasing the surface roughness of membranes does not have a negative effect on membrane performance; rather, it effectively improves the flux and antifouling properties of membranes. The rejections of prepared membranes were evaluated by measuring the concentration of collagen protein in the feed and permeate streams and results were summarized in Table 3. The results show that the rejection of collagen increased slightly by increasing the content of ZnO to 0.50 wt.%, then decreased with addition of more ZnO particles in the casting solution. This may be attributed to the surface pore size of membranes. As mentioned earlier, the number of pore as well as mean pore radius increased by increasing the content of ZnO. At higher contents, e.g. 0.75 and 1.0 wt.%, more collagen molecules may pass the membranes which results in low rejection. However, it should be noted that the variation of rejection is not discernable and all the hybrid membranes possess higher rejection in comparison with neat HDPE membrane. In general, the presence of particles increased the reversible portion of fouling and flux recovery which means that lower amounts of collagen molecules can enter the pores of membranes and consequently, lower amounts of collagen molecules can pass the membranes. Therefore, incorporation of ZnO nanoparticles into the HDPE membranes increases the separation performance.

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Fig. 10 – Classic fouling models in separation of collagen solution by prepared membranes. (a) HDPE, (b) 0.25 wt.% ZnO, (c) 0.50 wt.% ZnO, (d) 0.75 wt.% ZnO and (e) 1.00 wt.% ZnO membranes. In order to find the best model describing fouling in membranes, the values of k factor for different values of m and for each filtration test of different ZnO embedded membranes were found using the least square method. The experimental data were substituted in the linearized equations in Table 1 and k was obtained as the slope of the line. After that, with obtained k values on the hand, flux equations in Table 1 were plotted for each filtration test and compared with experimental data. The best fouling model was selected based on the best fitted equation with the highest value of R2 in linear regression method. Comparison between experimental data and fouling models for each membrane was shown in Fig. 10. The resultant

values of k and R2 are presented in Table 4. Based on the data in Table 4 and as shown in Fig. 10, it can be seen that none of the classic models fit the experimental data for fabricated membranes. Many studies have shown the inability of individual classic models to explain the flux decline during membrane processes because membrane fouling is an extremely complicated physic-chemical phenomenon. It seems that more than one fouling mechanism is needed to explain the experimental data. Therefore, to investigate fouling behavior of fabricated membranes, combined models developed by Bolton et al. (2006) were considered. Three combined models including cake filtration-complete blockage model (CFCBM), cake filtration-intermediate

Table 4 – Values of k in classic fouling models and correlation coefficient R2 for different ZnO embedded HDPE membranes. ZnO content (wt.%)

0.00 0.25 0.50 0.75 1.00

m=0

m=1

m = 1.5

m=2

k

R2

k

R2

k

R2

k

R2

0.0013 0.0013 0.0006 0.0004 0.0004

0.6896 0.9257 0.8877 0.9807 0.9480

0.0013 0.0018 0.0011 0.0011 0.0010

0.6750 0.8386 0.8099 0.9587 0.9694

0.0009 0.0016 0.0011 0.0012 0.0013

0.6554 0.7682 0.7478 0.9275 0.9394

0.0012 0.0025 0.0021 0.0026 0.0030

0.6274 0.6815 0.6732 0.8789 0.8750

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Fig. 11 – Experimental filtrated volume data and combined fouling models for prepared membranes in separation of collagen solution. (a) Flux data, (b) HDPE, (c) 0.25 wt.% ZnO, (d) 0.50 wt.% ZnO, (e) 0.75 wt.% ZnO and (f) 1.00 wt.% ZnO membranes. CFCBM: cake filtration-complete blockage model, CFIBM: cake filtration-intermediate blockage model, CFSBM: cake filtration-standard blockage model.

Table 5 – Model parameters, regression coefficient and error of fit for prepared membranes. CFCBM: cake filtration-complete blockage, CFIBM: cake filtration-intermediate blockage and CFSBM: cake filtration-standard blockage models. ZnO content (wt.%)

Models

R2

SSE

Fitted parameters

0.00

CFCBM CFIBM CFSBM

0.9512 0.7687 0.9227

1.32E−5 6.25E−5 2.21E−5

Kc = 3.83E+6 min/m2 , Kb = 2.22E−6 min−1 Kc = 1.26E+5 min/m2 , Ki = 70.0 m−1 Kc = 2.80E+6 min/m2 , Ks = 138.0 m−1

0.25

CFCBM CFIBM CFSBM

0.9691 0.7967 0.8731

3.17E−6 5.73E−6 2.17E−5

Kc = 5.15E+6 min/m2 , Kb = 6.57E−4 min−1 Kc = 1.92E+5 min/m2 , Ki = 95.0 m−1 Kc = 4.600E+6 min/m2 , Ks = 215.0 m−1

0.50

CFCBM CFIBM CFSBM

0.9804 0.8106 0.9147

3.76E−6 1.35E−4 4.28E−5

Kc = 6.74E+6 min/m2 , Kb = 7.13E−5 min−1 Kc = 9.50E+5 min/m2 , Ki = 196.2 m−1 Kc = 2.73E+6 min/m2 , Ks = 261.0 m−1

0.75

CFCBM CFIBM CFSBM

0.9910 0.8639 0.9075

1.54E−6 3.62E−5 6.29E−5

Kc = 5.96E+6 min/m2 , Kb = 9.51E−4 min−1 Kc = 7.38E+4 min/m2 , Ki = 174.0 m−1 Kc = 2.42E+5 min/m2 , Ks = 106.0 m−1

1.00

CFCBM CFIBM CFSBM

0.9974 0.8428 0.8702

1.05E−6 8.58E−5 6.25E−5

Kc = 6.12E+6 min/m2 , Kb = 3.61E−4 min−1 Kc = 2.34E+5 min/m2 , Ki = 204.0 m−1 Kc = 3.62E+6 min/m2 , Ks = 157.0 m−1

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blockage model (CFIBM) and cake filtration-standard blockage model (CFSBM) were applied to the filtration of collagen protein solution in order to clarify the fouling mechanism of prepared membranes. The permeate volume versus filtration time was fit using the aforementioned models and the best fit was determined by minimizing the sum of squared residuals (SSR) or sum of square errors (SSE) where the residual was equal to the difference between a data point and the model prediction (Bolton et al., 2006). The experimental data and model predictions were shown in Fig. 11 and Table 5. It can be seen that for all membranes the best fit of the data occurred with the cake filtration-complete blockage model. In cake filtration-complete blockage model, it is assumed that cake formation and complete pore blockage occur simultaneously; the former is formed on the membrane area that is not blocked and the latter can occur on the portions of the membrane area where a cake layer has been already formed. Obtained results were in good agreements with the data reported in the literature (Bolton et al., 2006; Golbandi et al., 2013). Comparing the results shown in Fig. 11 and Table 5 implies that the CFCBM model fit very well the experimental data as the content of ZnO nanoparticles in the casting solution increased. In other words, the deviation between experimental data and CFCBM model prediction decreased by increasing the content of ZnO. Comparison between R2 values of CFCBM model for different membranes shows that the accuracy of this model increased as the content of ZnO particles increased.

4.

Conclusion

HDPE/ZnO membranes were fabricated via thermally induced phase separation method. The results from this study showed that ZnO nanoparticles enhanced the antifouling properties of the membranes. It was shown that HDPE/ZnO membranes showed higher water flux and lower flux decline during filtration of collagen solution compared to neat HDPE membranes. These findings were attributed to the hydrophilicity of ZnO nanoparticles as well as increment in surface roughness of membranes due to the presence of ZnO. In addition, fouling mechanisms of membranes were analyzed and the results showed that for all membranes the best fit of the data occurred with the cake filtration-complete blockage model (CFCBM). Moreover, the deviation between experimental data and CFCBM prediction decreased by increasing the content of ZnO.

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Please cite this article in press as: Jafarzadeh, Y., et al., Preparation, characterization and fouling analysis of ZnO/polyethylene hybrid membranes for collagen separation. Chem. Eng. Res. Des. (2014), http://dx.doi.org/10.1016/j.cherd.2014.08.017