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Influence of conductive surface on adsorption behavior of ultrafiltration membrane
Applied Surface Science 256 (2010) 3010–3017
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Influence of conductive surface on adsorption behavior of ultrafiltration membrane E. Salehi, S.S. Madaeni * Membrane Research Center, Chemical Engineering Department, Razi University, Tagh Bostan, Kermanshah 67149, Iran
A R T I C L E I N F O
A B S T R A C T
Article history: Received 28 July 2009 Received in revised form 20 October 2009 Accepted 22 November 2009 Available online 3 December 2009
In this research the influence of conductivity on adsorptive behavior of PM30 ultrafiltration membrane was investigated using BSA solution as the feed. The conductive membrane was prepared from the originally nonconductive membrane by chemical polymerization of pyrrole as the conducting media on the membrane surface. Both Langmuir and Redlich–Peterson isotherms properly describe the quasiequilibrium adsorption data which are produced using experimental results of flux and rejection. Higher capacity of protein adsorption was achieved using nonconductive in comparison with conductive membrane. Using nonconductive membrane, an excessive feasibility and spontaneity of BSA adsorption was observed based on the greater negative value of Gibbs free energy change (DG ) which is a criterion for spontaneity of adsorption. Determination of filtration mechanism was conducted for elucidation the dominant adsorption region within the membranes i.e. membrane surface or internal pores. The filtration mechanisms for BSA solution using nonconductive and conductive membranes were surface cake deposition and intermediate (partial) blocking, respectively. First-order-kinetic model versus second-order-kinetic model indicated a superior interpretation of adsorption kinetics for both membranes; however, the required time to reach to the equilibrium for nonconductive membrane was slightly higher. All the distinctions in adsorption behavior of the conductive membrane originate from the repulsive potential field appears on the surface of the membrane during preparation. This electrostatic field acts as a barrier against the passage of the negatively charged proteins. Moreover, the partial coverage of membrane surface and internal pores with poly(pyrrole) may reduce the quantity of the active adsorptive sites on the membrane surface and matrix or presumably deactivates a part of the sites. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Adsorption Conductive membrane Isotherm Filtration mechanism
1. Introduction The benefits of membrane technologies include smaller footprint, less operating complexity, saving in energy consumption and requirement of fewer chemicals. Adsorptive membranes offer advantages over conventional processes for separation of biomolecules, heavy metal ions and proteins from solutions [1,2]. Fouling is an important limitation for wide application of membrane technology [3–6]. Fouling mechanism of charged membranes with charged species may be described on the basis of sieving and adsorption [3]. Regeneration of fouled membranes and control of fouling are mainly established via chemical cleaning [7], backwashing and preparation of conductive membrane [8,9]. In the recent years, interest in application of conducting membranes is growing due to the elevated rejection without noticeable fouling. The basic reason for this behavior is the appearance of electrical potential field on the membrane surface * Corresponding author. Tel.: +98 831 4274530; fax: +98 831 4274542. E-mail address: [email protected] (S.S. Madaeni). 0169-4332/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2009.11.065
due to the presence of conductive media. Many polymers have been employed for preparation of conductive layer on the surface of membranes including poly(vinylidene fluoride/polyaniline) blends [10], sulfonated poly(phenylsulfone) [11] and a mixture of poly(carbonate)–poly(pyrrole) [12]. Among conducting polymers, polypyrrole is one of the most promising materials for multifunctionalized applications due to the good environmental stability and higher conductivity compared to other conducting polymers [13]. Polypyrrole has a tight, rigid structure with weakly basic anion-exchangeable groups, which is easily polymerized by chemical or electrochemical oxidation. The conducting layer pushes back the charged particles due to the electrostatic effect i.e. membrane surface acts as a barrier against the passage of charged particles [10]. Adsorption is an important fouling mechanism for the membranes [14–16]. Metal ion adsorption onto the nanofiltration membrane was investigated by the current authors using Langmuir, Freundlich and Redlich–Peterson equilibrium isotherms [17–19]. There is a strong motivation to have a technique that will allow in situ measurement of the adsorption properties of the
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Nomenclature a b c0 csi cei cp cf F D G h i k, m K1 K2 K0 Qm Qsi Qei R rej T
R–P isotherm constant affinity parameter of Langmuir and R–P isotherms initial concentration of BSA-protein in the solution (g/l) equilibrium BSA concentration in any adsorption stage (g/l) residual BSA in the solution contacting with the adsorbed phase from the process initiation (g/l) permeate concentration of BSA (g/l) feed concentration of BSA (g/l) permeate flux (l/m2 h) Gibbs free energy change of adsorption (kJ/mol) a constant reflecting heterogeneity of adsorbent surface stage counter Freundlich isotherm equilibrium constant rate constant of the first-order-kinetic model (min1) rate constant of the second-order-kinetic model (m2/min g) thermodynamic equilibrium constant Langmuir final adsorption quantity (g/m2) quantity of BSA adsorbed by membrane per any adsorption stage (g/m2) equilibrium quantity of BSA adsorbed by membrane from the process initiation (g/m2) universal gas constant (8.314 J/mol K) BSA rejection by the membrane temperature (K)
membranes [16]. As a novel presented method for in situ measurement of adsorption equilibrium data, the quasi-equilibrium adsorption data were generated on the basis of flux and rejection data in our previous (and present) works [17,18]. The influences of conductivity on membranes performances have been adequately discussed in the literatures [8–10]; however, the effect of surface conductivity on adsorption behavior of membranes has not been tackled yet. By study of adsorption properties (as the most important fouling mechanism) of conductive membranes, it may be further clarified why conductive membranes possess a superior performance (flux and rejection) with less fouling potential compared to nonconductive. Various factors affect the adsorption properties of a membrane i.e. membrane material and morphology, surface charge, hydrophilicity, surface roughness, etc. This study focuses on the effect of ‘conductivity’ on adsorptive characteristics of an ultrafiltration membranes challenged with BSA solution and in comparison with nonconductive membrane. Separation mechanisms of BSA by both membranes are illustrated using blocking laws. Moreover crucial adsorptive parameters including adsorption favorability, Gibbs free energy change due to adsorption and adsorption kinetics are compared for both membranes. 2. Experimental 2.1. Chemicals Pyrrole, ferric chloride, NaH2PO4, Na2HPO4 all from Merck, crystalline BSA (A-2934, Lot93H0291) from Sigma were used in the
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experiments. BSA is an ellipsoid charged protein (negatively charged in the solution pH 7) with dimensions of 14 4 nm and the molecular weight of 67 kDa [9]. Freshly distilled pyrrole was employed for each trial. 2.2. Conductive and nonconductive membranes Amicon PM30 (MWCO = 30 kDa) membrane was employed. This is a commercially available nonconductive ultrafiltration membrane. The characteristic of the membrane is presented in Table 1. This ultrafilter was converted to conductive membrane by applying a thin layer of conductive polymer (polypyrrole) on the surface by chemical polymerization. The nonconductive membrane was soaked in 25 ml pyrrole solution (0.2 M) for 60 min. After that the membrane was taken out and immersed in 25 ml ferric chloride solution (0.2 M) without drying. When the support was soaked in the oxidant medium, chemical polymerization occurred at the interface leading to formation of a thin layer on the membrane surface. After 60 min, the membrane was taken out from FeCl3 solution and then washed with water to remove the excess monomer and the adhered oxidizing agent. At the final stage, the membrane was dried by placing between two sheets of filter paper. A perfect investigation of conductive membrane preparation is presented in Ref. [9] of the current author. 2.3. Apparatus All experiments were carried out in an 110 ml capacity batch dead end cell with a membrane area of 15.2 cm2. The cell consisted of a cylindrical vessel containing the test solution; two circular end pieces made from Perspex and a porous medium to support the membrane (Fig. 1). The top end piece of the cell contained a feed and a gas inlet and a pressure relief valve. Stirring was achieved by an internal magnetic bar (25.4 mm long, 6.4 mm diameter) suspended 2 mm above the membrane. Nitrogen gas was used to pressurize the cell to the operating pressures. A reservoir was connected to the cell to replenish the permeate. 2.4. Filtration procedure The performances of the prepared membranes were characterized by filtration of BSA solution through the membrane. The experiments were started after 100 ml of BSA solution was poured into the cell. The experiments were carried out at ambient temperature (24 1 8C) and operating pressure of 100 kPa. The system was run for 30 min to reach to steady state. The magnetic stirrer was started with a stirring speed of 400 rpm prior to the filtration. The concentration of feed was 0.15 g/l of BSA at neutral pH (pH 7). The flux (F) was measured gravimetrically with a Mettler PJ 6000 electronic balance by continuously weighing the permeate. The rejection of BSA was determined as: R% ¼ 100½1 ðC p =C f Þ where Cp and Cf are BSA concentrations in permeate and feed, respectively. Table 1 Characteristic of PM30 ultrafiltration membrane. Manufacturer Material Hydrophobicity MW cut-off (kDa) Water fluxa (l m2 h1) Permeability (109 m Pa1 s1) Membrane resistance (1011 m1) a
DP = 100 kPa.
Amicon Polysulphone Hydrophobic 30 640–1130 1.7–3.1 3.5–4.0
E. Salehi, S.S. Madaeni / Applied Surface Science 256 (2010) 3010–3017
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Fig. 1. Schematic of dead end system.
2.5. Determination of BSA concentration The rejection of protein was estimated by measuring the BSA in permeate. The absorption of each sample was measured at 280 nm using spectrophotometer (JASCO, FP6200). 3. Results and discussion The rejection and water flux of BSA solution using conductive and nonconductive PM30 ultrafiltration membranes are depicted in Figs. 2 and 3, respectively. Rejection was increased and flux was decreased during the trials as expected in conventional ultrafiltration processes. Lower flux observed for conductive membrane can be attributed to the partial blocking of the membrane pores with polypyrrole used for preparation of conductive membrane. 3.1. Isotherm confirmation BSA molecules in the solution passing through the membrane are assumed to be in equilibrium with BSA molecules in the adsorbed phase which is formed onto the membrane (surface and/ or internal pores) during the filtration process. There was adequate contact time between two phases to reach to quasi-equilibrium due to low applied operating pressure (1 bar) as the driving force in the system. A very long term is required to establish a real thermodynamic equilibrium in the system. Adsorption isotherms are commonly used for modeling the equilibrium adsorption processes. The Langmuir adsorption isotherm [20] explains monolayer adsorption of substances from liquid solution on homogeneous adsorbent surface. There is no interaction between molecules adsorbed on neighboring sites. This is represented as: Q ¼ Q max
bc 1 þ bc
(1)
Fig. 2. Rejection versus time for BSA solution using conductive and nonconductive membranes (1 bar, 24 8C, 0.15 g/l, 400 rpm).
where Q is equilibrium adsorbed amount per dry adsorbent unit area (g/m2), Q max is the final adsorbed quantity (g/m2), c is the adsorbate equilibrium concentration in solution (g/l) and b is a constant reflecting the affinity of the membrane for adsorbate. The empirical Freundlich isotherm [21] describes multilayer adsorption with interaction between molecules on heterogeneous adsorbent surface as: Q ¼ k cm
(2)
where Q is sorption at equilibrium (g/m2), c is the residual concentration of adsorbate at equilibrium (g/l), k is the relative sorption capacity and m is an indicator of sorption intensity or surface heterogeneity. Redlich–Peterson [20,21] is a three parameters empirical equation which may be used to represent adsorption equilibria over a wide range of concentrations. This can be applied either in homogeneous or heterogeneous systems. This isotherm considers the lateral interactions between adsorbing species and is represented by: Q¼
abc 1 þ b ch
(3)
where a and b are isotherm constants, c is solute (BSA) concentration in the solution and h is an exponent which indicates the heterogeneity of the adsorption surface. Three equilibrium adsorption isotherms i.e. Langmuir, Freundlich and Redlich–Peterson were applied to fit to the quasiequilibrium adsorption data. Using a new method for in situ measurement of equilibrium adsorption data [17,18], the quasiequilibrium adsorption data were generated on the basis of the flux and rejection of the filtration process. Every 15 min portion of the process time (Dt) was assumed to be an ‘adsorption stage’. The amount of BSA adsorbed per unit area
Fig. 3. Flux versus time for BSA solution using conductive and nonconductive membrane (1 bar, 24 8C, 0.15 g/l, 400 rpm).
E. Salehi, S.S. Madaeni / Applied Surface Science 256 (2010) 3010–3017
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Fig. 4. Langmuir isotherm for adsorption of BSA using conductive PM30 membrane at 1 bar and 24 8C.
Fig. 6. Redlich–Peterson isotherm for adsorption of BSA using conductive PM30 membrane at 1 bar and 24 8C.
of the membrane in one stage was defined as Qsi (g/m2):
Fitting results for conductive and nonconductive case studies show that both two-parameter Langmuir isotherm (Figs. 4 and 5) and three-parameter Redlich–Peterson (R–P) isotherm (Figs. 6 and 7) are adequately fitted to the evaluated equilibrium data. Rsquares and equilibrium parameters are presented in Table 2. The Freundlich isotherm is not fitted to the equilibrium data desirably (results are not shown). A comparison between final adsorbed quantities (Qmax) of BSA onto the conductive and nonconductive membranes using Langmuir isotherm (Table 2), indicates that the adsorptive capacity of the conductive membrane is considerably lower. Chemical polymerization of pyrrole on the surface of the nonconductive ultrafiltration membrane leads to a repulsive electrical potential field develops on the membrane’s surface. The negatively charged membrane surface acts as a barrier against the negatively charged BSA molecules and decreases the final adsorption quantity. Higher negative ionic charge for polypyrrole-coated polysulfone membranes results in superior electrostatic repulsion of ions from the surface [22] leading to elevated rejection. This observation can be
Q si ¼ re ji c0 F i Dt
ði ¼ 1; 2; 3; . . .Þ
(4) 2
where i is the stage counter, Fi is the permeate flux (l/m h), c0 is the initial BSA concentration in the feed (g/l) and reji is the rejection. The equilibrium amount of protein adsorbed from the beginning to the ith stage was defined as Qei (g/m2): Q ei ¼ Q eði1Þ þ Q si
ðQ e0 ¼ 0; i ¼ 1; 2; 3; . . .Þ
(5)
The approximate BSA concentration in any adsorption stage which is in equilibrium with the adsorbed phase is defined as Csi (g/ l): C si ¼ ð1 re jÞ c0
(6)
The residual BSA concentration in the solution in equilibrium with the adsorbed phase which is accumulated from the beginning of the process is represented as Cei (g/l): C ei ¼ C eði1Þ þ C si
ðC e0 ¼ 0; i ¼ 1; 2; 3; . . .Þ
(7)
Fig. 5. Langmuir isotherm for adsorption of BSA using nonconductive PM30 membrane at 1 bar and 24 8C.
Fig. 7. Redlich–Peterson isotherm for adsorption of BSA using nonconductive PM30 membrane at 1 bar and 24 8C.
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Table 2 The isotherms fitting results and equilibrium parameters for BSA adsorption on conductive and nonconductive PM30 membranes. Membrane
R-square
Equilibrium parameters
Conductive PM30
Langmuir: 0.9955 R–P: 0.9988
Qmax = 19.17 (g/m2), b = 0.9419 a = 8.9, b = 1.58, h = 3.83
Nonconductive PM30
Langmuir: 0.9999 R–P: 0.9999
Qmax = 139.9 (g/m2), b = 0.9419 a = 141, b = 0.293, h = 1.25
attributed to the partial blocking of the membrane adsorptive sites with polypyrrole which reduces the adsorption capability. 3.2. Gibbs free energy change of adsorption Gibbs free energy change (DG ) is the fundamental criterion of spontaneity. Adsorption occurs spontaneously at a given temperature if DG has a negative value. This thermodynamic parameter is calculated using following equation:
DG ¼ RT ln K 0
(8)
where R is universal gas constant (8.314 J/mol K) and T is the absolute temperature in K. K0 is the thermodynamic equilibrium constant, which defines as the ratio of adsorption rate constant to desorption one when adsorption–desorption cycle reaches to an equilibrium. This parameter may be evaluated from the intercept of ln(Q/C) versus Q [23]. The plots for conductive and nonconductive membranes are presented in Figs. 8 and 9, respectively. The negative values of DG as 2.601 kJ/mol for conductive and as 3.233 kJ/mol for nonconductive membranes confirm the feasibility of the process and the spontaneous nature of BSA adsorption on the membranes. The negative value of DG for BSA adsorption on nonconductive membrane is greater compared to conductive membrane indicating that the adsorption process is more feasible and comfortable in the case of nonconductive membrane.
Fig. 10. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (t=v versus v).
This observation may be justified on the basis of the presence of repulsive electrical field on conductive surface which pushes back the BSA molecules from the surface. Consequently for adsorption of BSA on the conductive surface, further activation energy is required compared with the nonconductive membrane. 3.3. Filtration mechanism Determination of filtration mechanism was conducted for elucidation of the occurrence of adsorption i.e. membrane surface or internal pores. Adsorption may occur throughout the membrane; however, the dominant adsorption region can be elucidated as the most promising part of the membrane involves in equilibrium adsorption cycle. Furthermore, the modality of adsorption and the spatial distribution of adsorbed species which foul the membrane may be estimated on the basis of separation (filtration) mechanisms. Filtration mechanism can be elucidated using blocking laws [24]. For a mechanism of pore blocking the plot of exp(t) versus v (permeate volume) should be linear. Fore intermediate blocking
Fig. 8. The plot of ln(Q/C) versus Q for adsorption of BSA on conductive PM30 membrane (T = 24 8C).
Fig. 9. The plot of ln(Q/C) versus Q for adsorption of BSA on the nonconductive PM30 membrane (T = 24 8C).
Fig. 11. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (t=v versus t).
E. Salehi, S.S. Madaeni / Applied Surface Science 256 (2010) 3010–3017
ln(t) versus v is linear. Fore cake (gel) deposition t=v versus v is linear and for internal pore-closure t=v versus t should be linear. The generated plots are depicted in Figs. 10–13. The linearity of the plots is the criterion for interpretation of filtration behavior. However this should be coupled with other evidences for elucidation of the mechanism. The R-squares of Hermia curves are listed in Table 3. On the basis of the linearity, t=v versus t with the highest R-square value for nonconductive membrane provides a basis for selection of internal pore-closure mechanism. This means BSA molecules must enter into the membrane’s pores and deposit on the pores’ walls. The molecular weigh cut off of the PM30 membrane is 30 kDa (Table 1) which is less than molecular weight of BSA molecules (67 kDa) [9]. Therefore, it seems that BSA molecules are not able to enter into the membrane’s pores i.e. internal blocking is not the dominant mechanism. The t=v versus v i.e. cake formation is the second mechanism of choice (Table 3) for nonconductive membrane. Protein molecules may be adsorbed and deposited on the membrane surface due to electrostatic forces, Van Der Waals interactions, sieving mechanism and inertia effects.
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Table 3 Hermia tests’ R-squares for filtration of BSA solution using conductive and nonconductive PM30 membranes. Hermia test
Conductive membrane R-square
Nonconductive membrane R-square
t=v versus t t=v versus v exp(t) versus v ln(t) versus v
0.678 0.889 0.970 0.991
0.991 0.980 0.951 0.861
For conductive membrane ln(t) versus v is linear with the highest R-square. Intermediate blocking means that surface pores of the membrane are partially covered (blocked) with the adsorbing species. The surface pores and adsorption sites of the PM30 membrane may be partially blocked or deactivated during the conducting process by chemical polymerization of pyrrole on the membrane surface. Moreover, repulsive electrostatic field on the surface of conductive membrane repels back the BSA molecules leading to less occupation of the membrane surface with the molecules. In other words the surface of the conductive membrane is partially (and not completely) covered by the protein molecules. In summary, the cake formation and intermediate blocking may be the separation mechanisms for ultrafiltration of BSA using nonconductive and conductive PM30 membranes respectively. In other words, the surface of the membranes is the main section involved in adsorption and fouling; however, for conductive membrane the adsorptive sites on the surface are not entirely involved in equilibrium adsorption cycle and fouling of surface pores is better controlled and decreased consequently. 3.4. Kinetic study The kinetic of adsorption describes the rate of BSA movement towards the membrane surface. This controls the required equilibrium time. The kinetic parameters are helpful for the prediction of adsorption rate, which provides significant information for designing and modeling the process. The kinetic of the adsorption data were analyzed using two different kinetic models: the pseudo-first-order and pseudo-second-order.
Fig. 12. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (ln(t) versus v).
3.4.1. Pseudo-first-order kinetic model The pseudo-first-order model [25] is widely used to predict sorption kinetics. The model is defined as: dQ ¼ K 1 ðQ e Q Þ dT
(9)
Integrating form of Eq. (9) is represented as: logðQ e Q Þ ¼ log Q e
Fig. 13. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (exp(t) versus v).
K 1t 2:303
(10)
where Qe and Q (g/m2) are the amounts of adsorbate (BSA) adsorbed at equilibrium and at time t (min), respectively and K1 (min1) is the adsorption rate constant. However, to fit Eq. (10) to the experimental data, the Qe value must be pre-estimated. The final adsorbed quantities (Qmax) obtained from the Langmuir isotherm (Table 2) were used as the first estimation. For conductive membrane after the third try and for nonconductive membrane at the first try a proper value for Qe was adjusted. The plots of firstorder kinetic model (Eq. (10)) for kinetic of BSA adsorption onto the conductive and nonconductive membranes are depicted in Figs. 14 and 15, respectively. Using Eq. (10), values of K1 and Qe were determined from the slope and intercept of the linear plots, respectively. The obtained values are presented in Table 4.
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Fig. 14. Plot of log(Qe Q) versus time for kinetic study of BSA adsorption on conductive PM30 membrane at 24 8C and 1 bar (pseudo-first-order model).
Fig. 16. Plot of t/Q versus time for kinetic study of BSA adsorption on conductive PM30 membrane at 24 8C and 1 bar (pseudo-second-order model).
Fig. 15. Plot of log(Qe Q) versus time for kinetic study of BSA adsorption on nonconductive PM30 membrane at 24 8C and 1 bar (pseudo-first-order model).
Fig. 17. Plot of t/Q versus time for kinetic study of BSA adsorption on nonconductive PM30 membrane at 24 8C and 1 bar (pseudo-second-order model).
3.4.2. Pseudo-second-order kinetic model The pseudo-second-order equation [26] based on equilibrium adsorption is expressed as:
nonconductive membranes can be approximated using pseudofirst-order kinetic model. The rate constants (K-values) for adsorption of BSA on conductive membrane is high compared to nonconductive membrane (Table 4). In other words a longer term is required to reach to the equilibrium (saturated adsorption capacity) in the case of nonconductive membrane. The quantity of the active adsorption sites on the surface of conductive is presumably less compared to nonconductive membrane due to the coverage of the membrane surface with pyrrole during chemical polymerization [9]. Moreover, the basic anionexchangeable groups which exist on the membrane surface repel back the negatively charged BSA molecules from the conductive surface [8]. In this case fewer numbers of adsorptive sites on the conductive surface are able to participate in equilibrium adsorption cycle. Consequently equilibrium occurs during a shorter time. Also higher adsorption capacity of the nonconductive compared to the conductive membrane (as presented in Table 2) leads to an appropriate time required for completion of the equilibrium adsorption capacity of nonconductive membrane.
dQ ¼ K 2 ðQ e Q Þ2 dt
(11)
After integrating and rearrangement: t 1 t ¼ þ Q K 2 Qe2 Q e
(12)
where K2 (m2/min g) is the rate constant of second-order adsorption. Pre-estimation of the value of Qe is not required in this case. The plots of t/Q versus time for adsorption of BSA onto the both membranes are presented in Figs. 16 and 17. The slope and intercept of Eq. (12) yield Qe and K2, respectively. The data are presented in Table 4. The R-squares in Figs. 14–17 indicate that the pseudo-firstorder model is more conveniently fitted to the equilibrium data for both membranes. Furthermore, the Qe values of the first-order model (Table 4) are comparable to the quantity of final adsorbed capacity (Qmax) of the membranes using Langmuir isotherm (Table 2). Accordingly adsorption of BSA on conductive and Table 4 Kinetic models’ parameters for adsorption of BSA on conductive and nonconductive PM30 membranes. Membrane
Pseudo-first-order model
Pseudo-second-order model
Conductive PM30
K 1 ¼ 6:9 103 ðmin1 Þ Q e ¼ 18:45 ðg=m2 Þ
K 2 ¼ 3:23 103 ðm2 =min gÞ Q e ¼ 21:6 ðg=m2 Þ
Nonconductive PM30
K 1 ¼ 2:303 103 ðmin1 Þ Q e ¼ 140:1 ðg=m2 Þ
K 2 ¼ 1:977 103 ðm2 =min gÞ Q e ¼ 400:03 ðg=m2 Þ
4. Conclusion Adsorption of BSA-protein on nonconductive ultrafiltration membrane was compared with conductive membrane. Both Langmuir and Redlich–Peterson isotherms conveniently describe the equilibrium adsorption data. The adsorption spontaneity and capability of nonconductive membrane for adsorption were high compared to conductive one. Therefore the nonconductive membrane shows a superior potential of fouling due to adsorption. A greater negative value of DG for nonconductive membrane indicates additional possibility and feasibility of adsorption. Separation mechanisms of BSA using conductive and nonconduc-
E. Salehi, S.S. Madaeni / Applied Surface Science 256 (2010) 3010–3017
tive membranes were determined as intermediate blocking and cake layer formation, respectively. Moreover, pseudo-first-order kinetic model is able to properly interpret the adsorption kinetics of BSA on both membranes. Various adsorptive properties of the membranes are mainly justified on the basis of negative electrostatic field which is established on the surface of conductive membrane and acts as a barrier against passage of negatively charged BSA molecules. References [1] V. Mavrov, T. Erwe, C. Blocher, H. Chmiel, Study of new integrated processes combining adsorption membrane separation and flotation for heavy metal removal from waste water, Desalination 157 (2003) 97–104. [2] C.Y. Wu, S.Y. Suen, S.C. Chen, J.H. Tzeng, Analysis of protein adsorption on regenerated cellulose-based immobilized copper ion affinity membrane, J. Chromatogr. A 996 (2003) 53–70. [3] J.F. Lapointe, Y. Pouliot, C. Bouchard, Fouling of a nanofiltration membrane by a blactoglobulin tryptic hydrolystate: impact on the membrane sieving and electrostatic properties, J. Membr. Sci. 235 (2005) 89–102. [4] A.I. Schafer, A.G. Fane, T.D. Waite, Fouling effects on rejection in the membrane filtration of natural waters, Desalination 131 (2000) 215–224. [5] H. Bourne, G.C. Eastmond, M. Gibas, W.F. Pacynko, J. Paprotny, Grafted and segmented hydrophilic polyimides for microfiltration membrane II. Fouling measurements, J. Membr. Sci. 207 (2002) 17–27. [6] K.J. Kim, V. Chen, A.G. Fane, Ultrafiltration of colloidal silver particles: flux, rejection and fouling, J. Colloid Interface Sci. 155 (1993) 347–359. [7] S.S. Madaeni, Sh. Sharifnia, Gh. Moradi, Chemical cleaning of reverse osmosis membranes fouled by whey, Desalination 161 (2004) 17–27. [8] A. Bhattacharya, D.C. Mukherjee, J.M. Gohil, Y. Kumar, S. Kundu, Preparation, characterization and performance of conducting polypyrrole composites based on polysulfone, Desalination 225 (2008) 366–372. [9] S.S. Madaeni, Preparation and properties of composite membranes composed of non-conductive membranes and polypyrrole, Indian J. Chem. Technol. 13 (2006) 65–70. [10] P. Wang, K.L. Tan, E.T. Kang, K.G. Neoh, Preparation and characterization of semiconductive poly(vinylidene fluoride)/polyaniline blends and membranes, Appl. Surf. Sci. 193 (2002) 36–45.
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Influence of conductive surface on adsorption behavior of ultrafiltration membrane E. Salehi, S.S. Madaeni * Membrane Research Center, Chemical Engineering Department, Razi University, Tagh Bostan, Kermanshah 67149, Iran
A R T I C L E I N F O
A B S T R A C T
Article history: Received 28 July 2009 Received in revised form 20 October 2009 Accepted 22 November 2009 Available online 3 December 2009
In this research the influence of conductivity on adsorptive behavior of PM30 ultrafiltration membrane was investigated using BSA solution as the feed. The conductive membrane was prepared from the originally nonconductive membrane by chemical polymerization of pyrrole as the conducting media on the membrane surface. Both Langmuir and Redlich–Peterson isotherms properly describe the quasiequilibrium adsorption data which are produced using experimental results of flux and rejection. Higher capacity of protein adsorption was achieved using nonconductive in comparison with conductive membrane. Using nonconductive membrane, an excessive feasibility and spontaneity of BSA adsorption was observed based on the greater negative value of Gibbs free energy change (DG ) which is a criterion for spontaneity of adsorption. Determination of filtration mechanism was conducted for elucidation the dominant adsorption region within the membranes i.e. membrane surface or internal pores. The filtration mechanisms for BSA solution using nonconductive and conductive membranes were surface cake deposition and intermediate (partial) blocking, respectively. First-order-kinetic model versus second-order-kinetic model indicated a superior interpretation of adsorption kinetics for both membranes; however, the required time to reach to the equilibrium for nonconductive membrane was slightly higher. All the distinctions in adsorption behavior of the conductive membrane originate from the repulsive potential field appears on the surface of the membrane during preparation. This electrostatic field acts as a barrier against the passage of the negatively charged proteins. Moreover, the partial coverage of membrane surface and internal pores with poly(pyrrole) may reduce the quantity of the active adsorptive sites on the membrane surface and matrix or presumably deactivates a part of the sites. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Adsorption Conductive membrane Isotherm Filtration mechanism
1. Introduction The benefits of membrane technologies include smaller footprint, less operating complexity, saving in energy consumption and requirement of fewer chemicals. Adsorptive membranes offer advantages over conventional processes for separation of biomolecules, heavy metal ions and proteins from solutions [1,2]. Fouling is an important limitation for wide application of membrane technology [3–6]. Fouling mechanism of charged membranes with charged species may be described on the basis of sieving and adsorption [3]. Regeneration of fouled membranes and control of fouling are mainly established via chemical cleaning [7], backwashing and preparation of conductive membrane [8,9]. In the recent years, interest in application of conducting membranes is growing due to the elevated rejection without noticeable fouling. The basic reason for this behavior is the appearance of electrical potential field on the membrane surface * Corresponding author. Tel.: +98 831 4274530; fax: +98 831 4274542. E-mail address: [email protected] (S.S. Madaeni). 0169-4332/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2009.11.065
due to the presence of conductive media. Many polymers have been employed for preparation of conductive layer on the surface of membranes including poly(vinylidene fluoride/polyaniline) blends [10], sulfonated poly(phenylsulfone) [11] and a mixture of poly(carbonate)–poly(pyrrole) [12]. Among conducting polymers, polypyrrole is one of the most promising materials for multifunctionalized applications due to the good environmental stability and higher conductivity compared to other conducting polymers [13]. Polypyrrole has a tight, rigid structure with weakly basic anion-exchangeable groups, which is easily polymerized by chemical or electrochemical oxidation. The conducting layer pushes back the charged particles due to the electrostatic effect i.e. membrane surface acts as a barrier against the passage of charged particles [10]. Adsorption is an important fouling mechanism for the membranes [14–16]. Metal ion adsorption onto the nanofiltration membrane was investigated by the current authors using Langmuir, Freundlich and Redlich–Peterson equilibrium isotherms [17–19]. There is a strong motivation to have a technique that will allow in situ measurement of the adsorption properties of the
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Nomenclature a b c0 csi cei cp cf F D G h i k, m K1 K2 K0 Qm Qsi Qei R rej T
R–P isotherm constant affinity parameter of Langmuir and R–P isotherms initial concentration of BSA-protein in the solution (g/l) equilibrium BSA concentration in any adsorption stage (g/l) residual BSA in the solution contacting with the adsorbed phase from the process initiation (g/l) permeate concentration of BSA (g/l) feed concentration of BSA (g/l) permeate flux (l/m2 h) Gibbs free energy change of adsorption (kJ/mol) a constant reflecting heterogeneity of adsorbent surface stage counter Freundlich isotherm equilibrium constant rate constant of the first-order-kinetic model (min1) rate constant of the second-order-kinetic model (m2/min g) thermodynamic equilibrium constant Langmuir final adsorption quantity (g/m2) quantity of BSA adsorbed by membrane per any adsorption stage (g/m2) equilibrium quantity of BSA adsorbed by membrane from the process initiation (g/m2) universal gas constant (8.314 J/mol K) BSA rejection by the membrane temperature (K)
membranes [16]. As a novel presented method for in situ measurement of adsorption equilibrium data, the quasi-equilibrium adsorption data were generated on the basis of flux and rejection data in our previous (and present) works [17,18]. The influences of conductivity on membranes performances have been adequately discussed in the literatures [8–10]; however, the effect of surface conductivity on adsorption behavior of membranes has not been tackled yet. By study of adsorption properties (as the most important fouling mechanism) of conductive membranes, it may be further clarified why conductive membranes possess a superior performance (flux and rejection) with less fouling potential compared to nonconductive. Various factors affect the adsorption properties of a membrane i.e. membrane material and morphology, surface charge, hydrophilicity, surface roughness, etc. This study focuses on the effect of ‘conductivity’ on adsorptive characteristics of an ultrafiltration membranes challenged with BSA solution and in comparison with nonconductive membrane. Separation mechanisms of BSA by both membranes are illustrated using blocking laws. Moreover crucial adsorptive parameters including adsorption favorability, Gibbs free energy change due to adsorption and adsorption kinetics are compared for both membranes. 2. Experimental 2.1. Chemicals Pyrrole, ferric chloride, NaH2PO4, Na2HPO4 all from Merck, crystalline BSA (A-2934, Lot93H0291) from Sigma were used in the
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experiments. BSA is an ellipsoid charged protein (negatively charged in the solution pH 7) with dimensions of 14 4 nm and the molecular weight of 67 kDa [9]. Freshly distilled pyrrole was employed for each trial. 2.2. Conductive and nonconductive membranes Amicon PM30 (MWCO = 30 kDa) membrane was employed. This is a commercially available nonconductive ultrafiltration membrane. The characteristic of the membrane is presented in Table 1. This ultrafilter was converted to conductive membrane by applying a thin layer of conductive polymer (polypyrrole) on the surface by chemical polymerization. The nonconductive membrane was soaked in 25 ml pyrrole solution (0.2 M) for 60 min. After that the membrane was taken out and immersed in 25 ml ferric chloride solution (0.2 M) without drying. When the support was soaked in the oxidant medium, chemical polymerization occurred at the interface leading to formation of a thin layer on the membrane surface. After 60 min, the membrane was taken out from FeCl3 solution and then washed with water to remove the excess monomer and the adhered oxidizing agent. At the final stage, the membrane was dried by placing between two sheets of filter paper. A perfect investigation of conductive membrane preparation is presented in Ref. [9] of the current author. 2.3. Apparatus All experiments were carried out in an 110 ml capacity batch dead end cell with a membrane area of 15.2 cm2. The cell consisted of a cylindrical vessel containing the test solution; two circular end pieces made from Perspex and a porous medium to support the membrane (Fig. 1). The top end piece of the cell contained a feed and a gas inlet and a pressure relief valve. Stirring was achieved by an internal magnetic bar (25.4 mm long, 6.4 mm diameter) suspended 2 mm above the membrane. Nitrogen gas was used to pressurize the cell to the operating pressures. A reservoir was connected to the cell to replenish the permeate. 2.4. Filtration procedure The performances of the prepared membranes were characterized by filtration of BSA solution through the membrane. The experiments were started after 100 ml of BSA solution was poured into the cell. The experiments were carried out at ambient temperature (24 1 8C) and operating pressure of 100 kPa. The system was run for 30 min to reach to steady state. The magnetic stirrer was started with a stirring speed of 400 rpm prior to the filtration. The concentration of feed was 0.15 g/l of BSA at neutral pH (pH 7). The flux (F) was measured gravimetrically with a Mettler PJ 6000 electronic balance by continuously weighing the permeate. The rejection of BSA was determined as: R% ¼ 100½1 ðC p =C f Þ where Cp and Cf are BSA concentrations in permeate and feed, respectively. Table 1 Characteristic of PM30 ultrafiltration membrane. Manufacturer Material Hydrophobicity MW cut-off (kDa) Water fluxa (l m2 h1) Permeability (109 m Pa1 s1) Membrane resistance (1011 m1) a
DP = 100 kPa.
Amicon Polysulphone Hydrophobic 30 640–1130 1.7–3.1 3.5–4.0
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Fig. 1. Schematic of dead end system.
2.5. Determination of BSA concentration The rejection of protein was estimated by measuring the BSA in permeate. The absorption of each sample was measured at 280 nm using spectrophotometer (JASCO, FP6200). 3. Results and discussion The rejection and water flux of BSA solution using conductive and nonconductive PM30 ultrafiltration membranes are depicted in Figs. 2 and 3, respectively. Rejection was increased and flux was decreased during the trials as expected in conventional ultrafiltration processes. Lower flux observed for conductive membrane can be attributed to the partial blocking of the membrane pores with polypyrrole used for preparation of conductive membrane. 3.1. Isotherm confirmation BSA molecules in the solution passing through the membrane are assumed to be in equilibrium with BSA molecules in the adsorbed phase which is formed onto the membrane (surface and/ or internal pores) during the filtration process. There was adequate contact time between two phases to reach to quasi-equilibrium due to low applied operating pressure (1 bar) as the driving force in the system. A very long term is required to establish a real thermodynamic equilibrium in the system. Adsorption isotherms are commonly used for modeling the equilibrium adsorption processes. The Langmuir adsorption isotherm [20] explains monolayer adsorption of substances from liquid solution on homogeneous adsorbent surface. There is no interaction between molecules adsorbed on neighboring sites. This is represented as: Q ¼ Q max
bc 1 þ bc
(1)
Fig. 2. Rejection versus time for BSA solution using conductive and nonconductive membranes (1 bar, 24 8C, 0.15 g/l, 400 rpm).
where Q is equilibrium adsorbed amount per dry adsorbent unit area (g/m2), Q max is the final adsorbed quantity (g/m2), c is the adsorbate equilibrium concentration in solution (g/l) and b is a constant reflecting the affinity of the membrane for adsorbate. The empirical Freundlich isotherm [21] describes multilayer adsorption with interaction between molecules on heterogeneous adsorbent surface as: Q ¼ k cm
(2)
where Q is sorption at equilibrium (g/m2), c is the residual concentration of adsorbate at equilibrium (g/l), k is the relative sorption capacity and m is an indicator of sorption intensity or surface heterogeneity. Redlich–Peterson [20,21] is a three parameters empirical equation which may be used to represent adsorption equilibria over a wide range of concentrations. This can be applied either in homogeneous or heterogeneous systems. This isotherm considers the lateral interactions between adsorbing species and is represented by: Q¼
abc 1 þ b ch
(3)
where a and b are isotherm constants, c is solute (BSA) concentration in the solution and h is an exponent which indicates the heterogeneity of the adsorption surface. Three equilibrium adsorption isotherms i.e. Langmuir, Freundlich and Redlich–Peterson were applied to fit to the quasiequilibrium adsorption data. Using a new method for in situ measurement of equilibrium adsorption data [17,18], the quasiequilibrium adsorption data were generated on the basis of the flux and rejection of the filtration process. Every 15 min portion of the process time (Dt) was assumed to be an ‘adsorption stage’. The amount of BSA adsorbed per unit area
Fig. 3. Flux versus time for BSA solution using conductive and nonconductive membrane (1 bar, 24 8C, 0.15 g/l, 400 rpm).
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Fig. 4. Langmuir isotherm for adsorption of BSA using conductive PM30 membrane at 1 bar and 24 8C.
Fig. 6. Redlich–Peterson isotherm for adsorption of BSA using conductive PM30 membrane at 1 bar and 24 8C.
of the membrane in one stage was defined as Qsi (g/m2):
Fitting results for conductive and nonconductive case studies show that both two-parameter Langmuir isotherm (Figs. 4 and 5) and three-parameter Redlich–Peterson (R–P) isotherm (Figs. 6 and 7) are adequately fitted to the evaluated equilibrium data. Rsquares and equilibrium parameters are presented in Table 2. The Freundlich isotherm is not fitted to the equilibrium data desirably (results are not shown). A comparison between final adsorbed quantities (Qmax) of BSA onto the conductive and nonconductive membranes using Langmuir isotherm (Table 2), indicates that the adsorptive capacity of the conductive membrane is considerably lower. Chemical polymerization of pyrrole on the surface of the nonconductive ultrafiltration membrane leads to a repulsive electrical potential field develops on the membrane’s surface. The negatively charged membrane surface acts as a barrier against the negatively charged BSA molecules and decreases the final adsorption quantity. Higher negative ionic charge for polypyrrole-coated polysulfone membranes results in superior electrostatic repulsion of ions from the surface [22] leading to elevated rejection. This observation can be
Q si ¼ re ji c0 F i Dt
ði ¼ 1; 2; 3; . . .Þ
(4) 2
where i is the stage counter, Fi is the permeate flux (l/m h), c0 is the initial BSA concentration in the feed (g/l) and reji is the rejection. The equilibrium amount of protein adsorbed from the beginning to the ith stage was defined as Qei (g/m2): Q ei ¼ Q eði1Þ þ Q si
ðQ e0 ¼ 0; i ¼ 1; 2; 3; . . .Þ
(5)
The approximate BSA concentration in any adsorption stage which is in equilibrium with the adsorbed phase is defined as Csi (g/ l): C si ¼ ð1 re jÞ c0
(6)
The residual BSA concentration in the solution in equilibrium with the adsorbed phase which is accumulated from the beginning of the process is represented as Cei (g/l): C ei ¼ C eði1Þ þ C si
ðC e0 ¼ 0; i ¼ 1; 2; 3; . . .Þ
(7)
Fig. 5. Langmuir isotherm for adsorption of BSA using nonconductive PM30 membrane at 1 bar and 24 8C.
Fig. 7. Redlich–Peterson isotherm for adsorption of BSA using nonconductive PM30 membrane at 1 bar and 24 8C.
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Table 2 The isotherms fitting results and equilibrium parameters for BSA adsorption on conductive and nonconductive PM30 membranes. Membrane
R-square
Equilibrium parameters
Conductive PM30
Langmuir: 0.9955 R–P: 0.9988
Qmax = 19.17 (g/m2), b = 0.9419 a = 8.9, b = 1.58, h = 3.83
Nonconductive PM30
Langmuir: 0.9999 R–P: 0.9999
Qmax = 139.9 (g/m2), b = 0.9419 a = 141, b = 0.293, h = 1.25
attributed to the partial blocking of the membrane adsorptive sites with polypyrrole which reduces the adsorption capability. 3.2. Gibbs free energy change of adsorption Gibbs free energy change (DG ) is the fundamental criterion of spontaneity. Adsorption occurs spontaneously at a given temperature if DG has a negative value. This thermodynamic parameter is calculated using following equation:
DG ¼ RT ln K 0
(8)
where R is universal gas constant (8.314 J/mol K) and T is the absolute temperature in K. K0 is the thermodynamic equilibrium constant, which defines as the ratio of adsorption rate constant to desorption one when adsorption–desorption cycle reaches to an equilibrium. This parameter may be evaluated from the intercept of ln(Q/C) versus Q [23]. The plots for conductive and nonconductive membranes are presented in Figs. 8 and 9, respectively. The negative values of DG as 2.601 kJ/mol for conductive and as 3.233 kJ/mol for nonconductive membranes confirm the feasibility of the process and the spontaneous nature of BSA adsorption on the membranes. The negative value of DG for BSA adsorption on nonconductive membrane is greater compared to conductive membrane indicating that the adsorption process is more feasible and comfortable in the case of nonconductive membrane.
Fig. 10. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (t=v versus v).
This observation may be justified on the basis of the presence of repulsive electrical field on conductive surface which pushes back the BSA molecules from the surface. Consequently for adsorption of BSA on the conductive surface, further activation energy is required compared with the nonconductive membrane. 3.3. Filtration mechanism Determination of filtration mechanism was conducted for elucidation of the occurrence of adsorption i.e. membrane surface or internal pores. Adsorption may occur throughout the membrane; however, the dominant adsorption region can be elucidated as the most promising part of the membrane involves in equilibrium adsorption cycle. Furthermore, the modality of adsorption and the spatial distribution of adsorbed species which foul the membrane may be estimated on the basis of separation (filtration) mechanisms. Filtration mechanism can be elucidated using blocking laws [24]. For a mechanism of pore blocking the plot of exp(t) versus v (permeate volume) should be linear. Fore intermediate blocking
Fig. 8. The plot of ln(Q/C) versus Q for adsorption of BSA on conductive PM30 membrane (T = 24 8C).
Fig. 9. The plot of ln(Q/C) versus Q for adsorption of BSA on the nonconductive PM30 membrane (T = 24 8C).
Fig. 11. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (t=v versus t).
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ln(t) versus v is linear. Fore cake (gel) deposition t=v versus v is linear and for internal pore-closure t=v versus t should be linear. The generated plots are depicted in Figs. 10–13. The linearity of the plots is the criterion for interpretation of filtration behavior. However this should be coupled with other evidences for elucidation of the mechanism. The R-squares of Hermia curves are listed in Table 3. On the basis of the linearity, t=v versus t with the highest R-square value for nonconductive membrane provides a basis for selection of internal pore-closure mechanism. This means BSA molecules must enter into the membrane’s pores and deposit on the pores’ walls. The molecular weigh cut off of the PM30 membrane is 30 kDa (Table 1) which is less than molecular weight of BSA molecules (67 kDa) [9]. Therefore, it seems that BSA molecules are not able to enter into the membrane’s pores i.e. internal blocking is not the dominant mechanism. The t=v versus v i.e. cake formation is the second mechanism of choice (Table 3) for nonconductive membrane. Protein molecules may be adsorbed and deposited on the membrane surface due to electrostatic forces, Van Der Waals interactions, sieving mechanism and inertia effects.
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Table 3 Hermia tests’ R-squares for filtration of BSA solution using conductive and nonconductive PM30 membranes. Hermia test
Conductive membrane R-square
Nonconductive membrane R-square
t=v versus t t=v versus v exp(t) versus v ln(t) versus v
0.678 0.889 0.970 0.991
0.991 0.980 0.951 0.861
For conductive membrane ln(t) versus v is linear with the highest R-square. Intermediate blocking means that surface pores of the membrane are partially covered (blocked) with the adsorbing species. The surface pores and adsorption sites of the PM30 membrane may be partially blocked or deactivated during the conducting process by chemical polymerization of pyrrole on the membrane surface. Moreover, repulsive electrostatic field on the surface of conductive membrane repels back the BSA molecules leading to less occupation of the membrane surface with the molecules. In other words the surface of the conductive membrane is partially (and not completely) covered by the protein molecules. In summary, the cake formation and intermediate blocking may be the separation mechanisms for ultrafiltration of BSA using nonconductive and conductive PM30 membranes respectively. In other words, the surface of the membranes is the main section involved in adsorption and fouling; however, for conductive membrane the adsorptive sites on the surface are not entirely involved in equilibrium adsorption cycle and fouling of surface pores is better controlled and decreased consequently. 3.4. Kinetic study The kinetic of adsorption describes the rate of BSA movement towards the membrane surface. This controls the required equilibrium time. The kinetic parameters are helpful for the prediction of adsorption rate, which provides significant information for designing and modeling the process. The kinetic of the adsorption data were analyzed using two different kinetic models: the pseudo-first-order and pseudo-second-order.
Fig. 12. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (ln(t) versus v).
3.4.1. Pseudo-first-order kinetic model The pseudo-first-order model [25] is widely used to predict sorption kinetics. The model is defined as: dQ ¼ K 1 ðQ e Q Þ dT
(9)
Integrating form of Eq. (9) is represented as: logðQ e Q Þ ¼ log Q e
Fig. 13. Mechanism determination for BSA filtration using conductive and nonconductive PM30 membranes (exp(t) versus v).
K 1t 2:303
(10)
where Qe and Q (g/m2) are the amounts of adsorbate (BSA) adsorbed at equilibrium and at time t (min), respectively and K1 (min1) is the adsorption rate constant. However, to fit Eq. (10) to the experimental data, the Qe value must be pre-estimated. The final adsorbed quantities (Qmax) obtained from the Langmuir isotherm (Table 2) were used as the first estimation. For conductive membrane after the third try and for nonconductive membrane at the first try a proper value for Qe was adjusted. The plots of firstorder kinetic model (Eq. (10)) for kinetic of BSA adsorption onto the conductive and nonconductive membranes are depicted in Figs. 14 and 15, respectively. Using Eq. (10), values of K1 and Qe were determined from the slope and intercept of the linear plots, respectively. The obtained values are presented in Table 4.
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Fig. 14. Plot of log(Qe Q) versus time for kinetic study of BSA adsorption on conductive PM30 membrane at 24 8C and 1 bar (pseudo-first-order model).
Fig. 16. Plot of t/Q versus time for kinetic study of BSA adsorption on conductive PM30 membrane at 24 8C and 1 bar (pseudo-second-order model).
Fig. 15. Plot of log(Qe Q) versus time for kinetic study of BSA adsorption on nonconductive PM30 membrane at 24 8C and 1 bar (pseudo-first-order model).
Fig. 17. Plot of t/Q versus time for kinetic study of BSA adsorption on nonconductive PM30 membrane at 24 8C and 1 bar (pseudo-second-order model).
3.4.2. Pseudo-second-order kinetic model The pseudo-second-order equation [26] based on equilibrium adsorption is expressed as:
nonconductive membranes can be approximated using pseudofirst-order kinetic model. The rate constants (K-values) for adsorption of BSA on conductive membrane is high compared to nonconductive membrane (Table 4). In other words a longer term is required to reach to the equilibrium (saturated adsorption capacity) in the case of nonconductive membrane. The quantity of the active adsorption sites on the surface of conductive is presumably less compared to nonconductive membrane due to the coverage of the membrane surface with pyrrole during chemical polymerization [9]. Moreover, the basic anionexchangeable groups which exist on the membrane surface repel back the negatively charged BSA molecules from the conductive surface [8]. In this case fewer numbers of adsorptive sites on the conductive surface are able to participate in equilibrium adsorption cycle. Consequently equilibrium occurs during a shorter time. Also higher adsorption capacity of the nonconductive compared to the conductive membrane (as presented in Table 2) leads to an appropriate time required for completion of the equilibrium adsorption capacity of nonconductive membrane.
dQ ¼ K 2 ðQ e Q Þ2 dt
(11)
After integrating and rearrangement: t 1 t ¼ þ Q K 2 Qe2 Q e
(12)
where K2 (m2/min g) is the rate constant of second-order adsorption. Pre-estimation of the value of Qe is not required in this case. The plots of t/Q versus time for adsorption of BSA onto the both membranes are presented in Figs. 16 and 17. The slope and intercept of Eq. (12) yield Qe and K2, respectively. The data are presented in Table 4. The R-squares in Figs. 14–17 indicate that the pseudo-firstorder model is more conveniently fitted to the equilibrium data for both membranes. Furthermore, the Qe values of the first-order model (Table 4) are comparable to the quantity of final adsorbed capacity (Qmax) of the membranes using Langmuir isotherm (Table 2). Accordingly adsorption of BSA on conductive and Table 4 Kinetic models’ parameters for adsorption of BSA on conductive and nonconductive PM30 membranes. Membrane
Pseudo-first-order model
Pseudo-second-order model
Conductive PM30
K 1 ¼ 6:9 103 ðmin1 Þ Q e ¼ 18:45 ðg=m2 Þ
K 2 ¼ 3:23 103 ðm2 =min gÞ Q e ¼ 21:6 ðg=m2 Þ
Nonconductive PM30
K 1 ¼ 2:303 103 ðmin1 Þ Q e ¼ 140:1 ðg=m2 Þ
K 2 ¼ 1:977 103 ðm2 =min gÞ Q e ¼ 400:03 ðg=m2 Þ
4. Conclusion Adsorption of BSA-protein on nonconductive ultrafiltration membrane was compared with conductive membrane. Both Langmuir and Redlich–Peterson isotherms conveniently describe the equilibrium adsorption data. The adsorption spontaneity and capability of nonconductive membrane for adsorption were high compared to conductive one. Therefore the nonconductive membrane shows a superior potential of fouling due to adsorption. A greater negative value of DG for nonconductive membrane indicates additional possibility and feasibility of adsorption. Separation mechanisms of BSA using conductive and nonconduc-
E. Salehi, S.S. Madaeni / Applied Surface Science 256 (2010) 3010–3017
tive membranes were determined as intermediate blocking and cake layer formation, respectively. Moreover, pseudo-first-order kinetic model is able to properly interpret the adsorption kinetics of BSA on both membranes. Various adsorptive properties of the membranes are mainly justified on the basis of negative electrostatic field which is established on the surface of conductive membrane and acts as a barrier against passage of negatively charged BSA molecules. References [1] V. Mavrov, T. Erwe, C. Blocher, H. Chmiel, Study of new integrated processes combining adsorption membrane separation and flotation for heavy metal removal from waste water, Desalination 157 (2003) 97–104. [2] C.Y. Wu, S.Y. Suen, S.C. Chen, J.H. Tzeng, Analysis of protein adsorption on regenerated cellulose-based immobilized copper ion affinity membrane, J. Chromatogr. A 996 (2003) 53–70. [3] J.F. Lapointe, Y. Pouliot, C. Bouchard, Fouling of a nanofiltration membrane by a blactoglobulin tryptic hydrolystate: impact on the membrane sieving and electrostatic properties, J. Membr. Sci. 235 (2005) 89–102. [4] A.I. Schafer, A.G. Fane, T.D. Waite, Fouling effects on rejection in the membrane filtration of natural waters, Desalination 131 (2000) 215–224. [5] H. Bourne, G.C. Eastmond, M. Gibas, W.F. Pacynko, J. Paprotny, Grafted and segmented hydrophilic polyimides for microfiltration membrane II. Fouling measurements, J. Membr. Sci. 207 (2002) 17–27. [6] K.J. Kim, V. Chen, A.G. Fane, Ultrafiltration of colloidal silver particles: flux, rejection and fouling, J. Colloid Interface Sci. 155 (1993) 347–359. [7] S.S. Madaeni, Sh. Sharifnia, Gh. Moradi, Chemical cleaning of reverse osmosis membranes fouled by whey, Desalination 161 (2004) 17–27. [8] A. Bhattacharya, D.C. Mukherjee, J.M. Gohil, Y. Kumar, S. Kundu, Preparation, characterization and performance of conducting polypyrrole composites based on polysulfone, Desalination 225 (2008) 366–372. [9] S.S. Madaeni, Preparation and properties of composite membranes composed of non-conductive membranes and polypyrrole, Indian J. Chem. Technol. 13 (2006) 65–70. [10] P. Wang, K.L. Tan, E.T. Kang, K.G. Neoh, Preparation and characterization of semiconductive poly(vinylidene fluoride)/polyaniline blends and membranes, Appl. Surf. Sci. 193 (2002) 36–45.
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