Properties of protein adsorption onto pore surface during microfiltration: Effects of solution environment and membrane hydrophobicity

Journal of Membrane Science 280 (2006) 363–374

Properties of protein adsorption onto pore surface during microfiltration: Effects of solution environment and membrane hydrophobicity Kazuho Nakamura ∗ , Kanji Matsumoto Department of Chemical Engineering, Yokohama National University, 79-5 Tokiwadai, Todogaya-ku, Yokohama 240-8501, Japan Received 3 October 2005; received in revised form 17 January 2006; accepted 20 January 2006 Available online 28 February 2006

Abstract Properties of bovine serum albumin (BSA) adsorption onto pore surface during the filtration of BSA containing solution with the Sirasu porous glass membrane with a pore size of 0.1 ␮m were studied. The effects of pH, ionic strength, and surface modification on the flux decline and breakthrough curves were observed. The adsorption properties of BSA were estimated quantitatively by using the internal fouling model, which relates the filtration performance to the adsorption interaction, the adsorption capacity, and the thickness of the adsorption layer. The electrostatic interaction between BSA and pore surface was estimated by the streaming potential measurement. The BSA adsorption involved a rapid adsorption in the early stage of filtration followed by a slow multilayer adsorption that dominates the long-term filtration performance. The electrostatic repulsive force reduced the overall adsorption interaction but the electrostatic attractive force did not affect the adsorption interaction. The effect of ionic strength on the BSA adsorption could be explained in terms of the shift of the IEP of BSA toward lower pH with the increase in ionic strength. The hydrophobicity of membrane did not affect the adsorption properties except for the adsorption interaction in the early stage of the filtration. © 2006 Elsevier B.V. All rights reserved. Keywords: Microfiltration; Protein adsorption; Fouling; Zeta potential; Fouling model

1. Introduction Microfiltration (MF) is widely used in bioseparation processes as a solid–liquid separation method. In these applications MF membrane is required to remove particles or microorganisms for clarification or sterilization and to pass a macrosolutes like a soluble protein through the membrane. Although the pore size of MF membrane is generally much larger than protein molecule size, protein molecules can be trapped by the membrane. The protein transmission performance of MF membranes or semi-permeable ultrafiltration (UF) membranes depends on various filtration conditions such as operating conditions [1–3], solution chemistry [4–14], or surface physicochemical [15–20] and pore morphology [21–23] and would change with the filtration time. Due to this alternation of filtration performance during filtration, i.e. membrane fouling, MF has not been considered as a reliable separation method.

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0376-7388/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2006.01.039

The protein adsorption on the surface or within pores of a MF membrane is a major cause of the membrane fouling in the MF of protein containing solution. To eliminate the protein adsorption many researcher have been trying various surface modifications or synthesizations of membrane with novel polymers. Sun et al. wildly reviewed the studies on protein adsorption phenomena and control methods [24]. The protein adsorption on MF membrane during filtration remains a poorly understood phenomenon although there is growing interest in the control or elimination of the protein adsorption. One of the major problem in understanding the protein adsorption is the difficulty in distinguishing the protein adsorption onto pore surface, i.e. the internal fouling, from the protein deposition on the membrane surface, i.e. the external fouling. Many researchers have indirectly distinguished the location of fouling in terms of flux decline with the blocking filtration models [1,3,4,25–27] while the flux decline reflects the overall blockage of the membrane. The static adsorption method, which means the adsorption by immersing a piece of membrane into protein solution, is also generally employed to characterize the effect of protein adsorption on the filtration performance of MF

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or UF membranes [6,11,15,17,20,23,28,29] while the adsorption isotherm during filtration can be affected by convective flow in pore [2]. Su et al. studied the location of protein fouling by small angle neutron scattering (SANS) combined with the flux decline under dynamic filtration conditions [5]. Nakamura and Matsumoto confirmed the location of fouling by comparing the filtration performance in a dead-end mode to that in a cross-flow concentration mode [2]. The protein adsorption property of MF membrane is generally characterized in terms of the protein adsorption capacity and many measurement methods have been employed to characterize the status of the adsorbed protein, such as TOF-SIMS [30], FTIR [8,31], ELIZA [32], SANS [5], EPR [33,34], MALDI-MS [35], etc. On the other hand, the protein adsorption will occur due to various physicochemical interactions between protein molecules and the membrane, such as electrostatic interaction, hydrogen bonding, or hydrophobic interactions, etc. The overall interaction between protein molecules and their adsorption sites is called as the adsorption interaction in this paper. The electrostatic interaction can be estimated by the combination of the zeta potential of pore surface and protein. However the protein adsorption capacity is not always elucidated in term of the electrostatic interaction [4,5,13]. Generally the maximum adsorption capacity was observed at the isoelectric point (IEP) of protein, where no electrostatic interaction is expected, and it is generally accepted as the causes for this maximum in adsorption capacity that the protein solubility tend to be lowest at the IEP of protein and repulsive electrostatic interaction among the closely packed proteins in the adsorbed monolayer is minimized [36]. In order to elucidate the protein adsorption phenomena onto pore surface during MF we have investigated the adsorption of bovine serum albumin (BSA) onto pore surface during MF with Sirasu porous glass (SPG) membrane with a pore size of 0.1 ␮m, which will allow the observation of a clear breakthrough curve providing the rate and amount of the BSA adsorption during filtration. We showed the BSA adsorption properties from the viewpoints of the mass transfer and adsorption isotherm at a fixed solution condition of pH 5.0 and ionic strength 0.01 [2] and concluded that the BSA adsorption should be multilayer type, which consisted of the adsorption on clean pore surface, i.e. the primary adsorption, followed by the adsorption on the BSA adsorbed pore surface, i.e. the secondary adsorption, and the protein adsorption rate was proportional to the feed rate of BSA and the proportional coefficient depended on the adsorption type. And we also developed a mathematical model, i.e. the internal fouling model, describing the relationship between the adsorption properties and the filtration performance [37] based on the experimental observation [2]. By using this model the protein adsorption properties, which are an index of the adsorption interaction, adsorption capacity and thickness of adsorption layer for both the primary and secondary adsorptions, can be phenomenologically evaluated from the flux decline and breakthrough curves. In this paper we focus on the effects of the physicochemical interaction between BSA molecules and pore surface on the BSA adsorption properties during filtration. The effects of pH and

ionic strength on the filtration performance were observed with SPG membranes, which had two extreme surface conditions of hydrophilic (unmodified membrane) and hydrophobic (surface modified membrane). The filtration experiments were performed under the condition where only the internal fouling occurred. The adsorption properties were evaluated by using the internal fouling model and discussed with the electrostatic interaction between BSA molecules and the pore surface which estimated from streaming potential measurement. 2. A mathematical model for protein fouling during microfiltration: the internal fouling model For evaluating the protein adsorption properties on pore surface during microfiltration we developed a mathematical model [37] based on the experimental results [2], i.e. the internal fouling model, which relates the filtration performance to the adsorption properties. The general outline is shown here. 2.1. A mathematical model for protein fouling during microfiltration The assumptions of membrane structure and protein behavior during filtration are illustrated in Fig. 1. The membrane has a symmetric pore structure, which consists of uniform and straight capillaries with capillary density, N. The radius and length of the capillary are equal to the membrane mean pore radius, r0 , and the membrane thickness, Lm , respectively. A protein solution of concentration c0 is fed to the membrane at a constant pressure, PTM . The protein concentration of permeate, c(t), and flux J(t) change

Fig. 1. Schematic view of protein microfiltration for the internal fouling model.

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with time due to protein adsorption on the pore surface. The following assumptions about mass transfer condition are made in order to simplify the model: (1) the protein are not retained at the membrane surface, that is, all protein molecules flow into the pores, (2) a concentration gradient in the radial direction in pores can be negligible, (3) the mass transfer for the axial direction is carried out only by convection, and (4) only the protein adsorption on pore surface will change the protein concentration. The assumptions about protein adsorption are also made: (a) adsorption is irreversible, (b) adsorption is multilayer type which consists of the primary and secondary adsorptions, (c) for both the primary and the secondary adsorption the amount of adsorbed protein is limited at a certain value, i.e. the adsorption capacity, and (d) the adsorption isotherm is a high affinity (HA) type, which means the adsorption capacity is not affected by feed protein concentration. The adsorption process on the pore surface can be schematically expressed by the following forms: S + P → Pads · S (the primary adsorption)

(1)

Pads + P → Pads · Pads (the secondary adsorption)

(2)

P denotes the protein in the solution in the pores, S denotes the adsorption sites on clean pore surface, and Pads denotes the adsorbed protein on the pore surface. For the expressing the change in protein concentration in pore the basic equation of the depth filtration, i.e. Iwasaki’s equation [38], was employed. A protein concentration gradient in a small section for axial direction is given by the following equation: ∂c(z, t) = −K · c(z, t) ∂z

(3)

where K is the adsorption coefficient, which has the same meaning and dimension of m−1 as the filter coefficient used in Iwasaki’s equation [38]. And it can be used as an index of the magnitude of the overall adsorption interaction between protein molecules and their adsorption sites. A mass balance for protein in a section of z gives a following equation: J(t)

∂c(z, t) ∂q(z, t) = −av0 · ∂z ∂t

(4)

where q is the amount of adsorbed protein per unit pore surface area, and av0 is the specific surface area of clean membrane based on membrane volume. The adsorption rate in a section of z can be written by substituting Eq. (3) into Eq. (4) as follows: ∂q(z, t) 1 = · K · J(t) · c(z, t) ∂t av0

1 ∂q2 (z, t) = K2 · J(t) · c(z, t) · · ∂t av
 q2 (z, t) × 1− QMAX,2

q1 (z, t) QMAX,1

 ·

r(z, t) = r0 − r(z, t)

(8)

(9)

where r(z, t) is the thickness of the protein adsorption layer. With the assumption that the thickness of the protein layer is proportional to the amount of adsorbed protein r(z, t) can be expressed as following: r(z, t) = B1 · q1 (z, t) + B2 · q2 (z, t)

(10)

where B is the thickness of the adsorption layer per unit amount of adsorbed protein. Permeate flux can be expressed in terms of the Hagen–Poiseuille equation, Darcy’s law, and filtration resistance law in a small section of z: J(t) =

kp (z, t)P P Nπr(z, t)4 P = = 8µz zµ R(z, t)µ

(11)

where P is the pressure difference across the section of z, µ is the viscosity of fluid, kp (z, t) is the hydraulic permeability coefficient, and R(z, t) is the filtration resistance in a section of z. The total hydraulic resistance, Rm (t), is described as Eq. (12):  Lm 1 Rm (t) = dz (12) k (z, t) p 0 The change in kp and av with the increase in the pore radius are given as follows:
 r(z, t) 4 (13) kp (z, t) = kp0 1 − r0
 r(z, t) av (z, t) = av0 1 − (14) r0 where kp0 is the hydraulic permeability of the clean membrane. The initial and boundary conditions are as follows: c(z, t) = q1 (z, t) = q2 (z, t) = 0 at 0 ≤ z ≤ Lm ,

t=0

The other hand, the adsorption rate can be also written as follows considering the multilayer adsorption:

av (z, t) = av0 ,

kp (z, t) = kp0

at 0 ≤ z ≤ Lm ,

t=0


 ∂q1 (z, t) 1 q1 (z, t) = K1 · J(t) · c(z, t) · · 1− ∂t av0 QMAX,1




where av is the specific surface area based on membrane volume, QMAX is the protein adsorption capacity. Subscripts 1 and 2 mean the primary and secondary adsorption, respectively. The pore radius, r(z, t), is given by the following equation:

(5)

∂q(z, t) ∂q1 (z, t) ∂q2 (z, t) = + ∂t ∂t ∂t

365

(15)

(16)

(6) c(z, t) = c0 (7)

J(t) = J0

at z = 0, at t = 0.

t>0

(17) (18)

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2.2. Calculation The calculation was carried out by solving Eqs. (3)–(14) numerically and simultaneously using the Runge–Kutta method in steps of z = 1 × 10−6 m and t = 1 s with the initial and boundary conditions, Eqs. (15)–(18). The parameters, K1 , K2 , QMAX,1 , QMAX,2 , B1 , and B2 , were determined by fitting the calculated flux decline and breakthrough curves to experimental results (J/J0 and cp /c0 versus t plots). The other parameters needed for the calculation, av0 , Lm , r0 , J0 , and c0 , were determined experimentally. The calculation curves could be well fitted to the experimental results and the six fitting parameters could be determined distinctively by the curve fitting except for the case of the fitting for a flat type breakthrough curve, which will be explained later in Fig. 3. The sensitivity of the fitted parameters depended on individual fitting parameters. The details of the response of the calculated curves to the variation of the fitting parameters were discussed in our previous study [37]. The coefficient of variation (CV) of the fitting parameters determined for a typical experimental result in this study was 1% for QMAX,1 , 5% for K2 , B1 , B2 , and 10% for K1 , QMAX,2 . 3. Experimental The membrane used was Sirasu porous glass (SPG) tubular membrane (230 mm long, 4 mm I.D., and 5 mm O.D.) supplied by Ind. Res. Inst. of Miyazaki prefecture. The SPG membrane has symmetric structure and a narrow pore size distribution with mean pore size of 100 nm determined by mercury porosimetry. The surface area and porosity of the membrane were 19 m2 /g and 0.53, respectively. The ratio of the pore surface area to the effective filtration area was approximately 1 × 104 m2 /m2 , of which features allow the observation of a clear breakthrough curve. Some membranes were modified with octadecyl-trichlorosilane (ODS: M.W. = 387.9 g/mol) and trimethylchlorosilane (TMS: M.W. = 108.6 g/mol) in order to alter the pore surface property from hydrophilic, which is original instinct of SPG membrane, to hydrophobic. The modification was performed by the following way: (1) membrane was dried in a vacuumed desiccator at 383 K over 2 h, (2) the membrane was submerged in the toluene containing 5 vol.% ODS under reflux condition for 8 h, (3) the membrane was rinsed with toluene and submerged toluene containing 1 vol.% TMS for 12 h, and (4) the membrane was rinsed with toluene. It seemed that the membrane pore structure was not affected by this modification because the molecular size of these agents were much smaller than the pore size. This surface modified membrane was wetted with ethanol before use. Membranes, both the unmodified and modified membranes, were reused after the cleaning with dilute sodium hypochlorite solution and were checked by pure water flux and streaming potential before use. BSA was obtained from Sigma (Fraction V; A6794) and is a well-characterized protein having molecular weight 67,000 g/mol, molecular size 14 nm × 4 nm × 4 nm [39] and isoelectric point (IEP) at pH 4.7–4.9. The concentration of BSA was adjusted to 0.2 kg/m3 with phosphate buffer in all experiments. pH of the buffer solution (ionic strength 0.01) was adjusted with appropriate amounts of sodium H2 PO4 − , sodium HPO4 2− ,

Fig. 2. Experimental set-up: 1, membrane module; 2, membrane; 3, platinum black electrodes; 4, N2 gas cylinder; 5, pressure regulator; 6, feed tank; 7, thermostatic bath; 8, UV flow cell; 9, beaker; 10, electrical balance; 11, digital multimeter; 12, pressure transducer; 13, personal computer.

or phosphoric acid. Ionic strength of the buffer solution was adjusted by adding appropriate NaCl. The water used was Millipore Q grade. BSA concentration was determined by measuring absorbance at 280 nm with an UV spectrometer. The experimental apparatus is shown schematically in Fig. 2. The solution in the feed tank was pressurized with N2 gas at 98 kPa and fed to the membrane module and filtered from inner side of the membrane in dead-end mode. The membrane module was made of glass tube (I.D. 6 mm) and equipped with a set of platinum black electrodes for measuring the potential difference developed across the membrane, ETM . ETM was measured with a digital multimeter. The trans-membrane pressure, PTM , was measured by a pressure transducer. The weight and absorbance at 280 nm of permeate solution were measured continuously with an electric balance and an UV spectrometer with flow cell, respectively. The temperature of this equipment was kept at 298 K. All the measurements were recorded with a personal computer at a constant time intervals. The streaming potential is defined as the slope of linear regression for ETM versus PTM plots, as ETM /PTM . The streaming potential was measured before and after each filtration experiment by following procedure. The ETM measured by increasing PTM from 0 to 300 kPa continuously in about 10 s and then the feed tank was depressed. This pressurization was repeated three times at least. The filtration experiment carried out according to following procedure: (1) pure water and phosphate buffer flux measured, (2) streaming potential was measured with the phosphate buffer, (3) BSA solution was filtered at 98 kPa until the permeate volume became to about 1600 ml, and (4) streaming potential was measured again with the phosphate buffer. 4. Results The effects of pH, ionic strength, and hydrophobicity of pore surface on the flux decline and breakthrough curves were observed. The breakthrough curve, which will reflect the rate and extent of the BSA adsorption, could be classified into three patterns by the shape of the curve. Fig. 3 shows the typical three

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Fig. 3. The typical patterns of breakthrough curve: (1) flat type, (2) two-stage type, and (3) normal type.

patterns. The first type is the flat type, of which the breakthrough curve starts at a relatively higher value and then increases gradually. The second type is the two-stage type, of which the breakthrough curve starts at zero and then shows a steep increase to a certain value followed by a gradual increasing. And the third type is the normal type, of which the breakthrough curve starts at zero and then shows a steep increasing to 1. 4.1. Effects of pH (ionic strength 0.01, hydrophilic membrane) The filtration performance was expected to depend on pH because BSA is an ampholyte having an isoelectric point (IEP) of pH 4.7–4.9 and the SPG membrane has negative charge over the pH range studied, as will be shown later. It was expected that the electrostatic interaction between BSA and pore surface was repulsive at pH above the IEP, ignorable at the IEP, and attractive at pH below the IEP. Fig. 4 shows the effects of pH on the flux decline and the breakthrough curves at ionic strength 0.01 for the unmodified (hydrophilic) membrane. It can be seen that both the flux decline and breakthrough curves depended on pH. Substantial flux decline, which can be caused by the pore blocking resulting from the deposition of protein aggregation on the membrane surface, was not observed. The flux tended to decline relatively rapidly in the early stage of the filtration and then decline gradually responding to the changes in the breakthrough curves. The relative flux at the end of the filtration was lowest at pH 5.0 and increased at the pH values away from the IEP of BSA. According to Hagen–Poiseuille equation the corresponding decrease in pore radius for the lowest relative flux of 0.6 is expected as 6 nm, which is consistent with BSA molecule size range. The shape of the breakthrough curve (Fig. 4(B)) strongly depended on the expected electrostatic interaction between BSA molecules and the pore surface. At pH 7.0 and 6.0, where a repulsive electrostatic interaction would be expected, the breakthrough curves were the flat type and the values at the starting point were 0.91 and 0.75, respectively. At pH 5.0 and 4.5, where little electrostatic interaction would be expected, the breakthrough curves were the two-stage type, which started from 0 and

Fig. 4. Effect of pH on (A) flux decline curve and (B) breakthrough curve for the unmodified (hydrophilic) SPG membrane at ionic strength 0.01, c0 0.2 kg/m3 , and J0 5.4 ± 1.2 × 10−5 m/s.

showed a steep increase to about 0.8 at V/Vm = 200 followed by gradual increase. At pH 4.0 and 3.0, where an attractive interaction would be expected, the breakthrough curves were the normal type with the increasing point at V/Vm = 200 and 120, respectively. This pH dependence of breakthrough curve will reflect the changes in the electrostatic interaction on the rate and extent of the BSA adsorption. The BSA adsorption properties will be discussed with the result of zeta potential measurement in the Section 5. 4.2. Effects of ionic strength (hydrophilic membrane) The filtration performance is also affected by ionic strength because the electrostatic interaction between BSA molecules and pore surface could be shielded by electrolyte. It was expected that the pH dependence of the filtration performance would become insignificant at higher ionic strength. The effects of ionic strength on the filtration performance at different pH for the unmodified membrane were observed. In all pH and ionic strength conditions the flux tended to decline relatively rapidly in the early stage of filtration and then decline gradually (data not shown). And any substantial flux decline, suggesting the pore blocking caused by the deposition of BSA aggregation on the membrane surface, was not observed in these filtration conditions. Fig. 5 shows the effects of ionic strength on breakthrough curve. At pH 7.0 the breakthrough curve was a flat type and was hardly affected by the increase in ionic strength. At pH 5.0 and 4.5 the breakthrough curves drastically changed from a two-

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Fig. 5. Effect of ionic strength on breakthrough curve for the unmodified (hydrophilic) membrane at different pH.

stage type to a flat type with the increase in ionic strength. At pH 4.0 the breakthrough curve changed from a normal type to a two-stage type with the increase in ionic strength. At pH 3.0 the normal type breakthrough curve shifted toward right-hand with the increase in ionic strength. In contrast to the expectation the effect of ionic strength on the breakthrough curve was significant in the pH near the IEP of BSA, where little electrostatic interaction would be expected, as compared to that in pH away from the IEP of BSA, where the strong electrostatic interaction would be expected. These results suggest that the effect of ionic strength on the BSA adsorption onto pore surface could not be explained simply in terms of the shielding of the electrostatic interaction between the BSA molecule and pore surface. 4.3. Effect of the surface modification (ionic strength 0.01, hydrophobic membrane) The filtration performance could be affected by the hydrophobicity of pore surface because the hydrophobic interaction could play magnificent role in the interaction between BSA molecules and pore surface. Fig. 6 shows the effects of pH on the filtra-

tion performance at ionic strength 0.01 for the surface modified (hydrophobic) membrane. The flux decline curves (Fig. 6(A)) showed almost same manner as those for the unmodified membrane (Fig. 4(A)), that is, the flux tended to decline relatively rapidly in the early stage of the filtration and then decline gradually responding to the change in the breakthrough curve and substantial flux decline suggesting the pore blocking due to BSA aggregation was not observed. The relative flux at the end of the filtration was lowest at pH 5.0 and increased at the pH values away from the IEP of BSA. According to Hagen–Poiseuille equation the corresponding decrease in pore radius for the lowest relative flux of 0.65 is expected as 5 nm, which is somewhat smaller than that for the hydrophilic membrane as 6 nm. All breakthrough curves for the modified membrane (Fig. 6(B)) started from zero at all pH values. It is expected that BSA can be trapped on pore surface by a hydrophobic interaction in the early stage of filtration regardless of the charge condition of BSA. Except for the early stage at pH 6.0 and 7.0 the pH dependence of the breakthrough curve for the surface modified membrane (Fig. 6(B)) was almost the same as those

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369

Fig. 7. Apparent zeta potential of the unmodified and modified SPG membrane before and after the BSA filtration.

Fig. 6. Effect of pH on (A) flux decline curve and (B) breakthrough curve for the surface modified (hydrophobic) SPG membrane at ionic strength 0.1, c0 0.2 kg/m3 , and J0 2.8 ± 0.2 × 10−5 m/s.

for the unmodified membrane (Fig. 4(B)), showing that the surface hydrophobicity affects only the early stage of filtration and the long-term behavior of the protein adsorption is not affected by the hydrophobicity of pore surface. 4.4. Zeta potential measurement The electrostatic interaction between BSA molecules and pore surface can be estimated by the combination of the zeta potential between BSA molecule and the pore surface. The zeta potential of the membrane was measured by the streaming potential method before and after the filtration of BSA. At ionic strength 0.01 ETM versus PTM plots showed good linearity, suggesting the validity of the measurement, but at ionic strength 0.1 and 0.5 the slope could not be determined because the change in ETM was too small. Apparent zeta potential ζ obs was estimated with Helmholtz–Smoluchowski equation: ζobs =

µλ ETM ε0 εr PTM

(19)

where ε0 is the permittivity of free space, εr is relative dielectric constant, and λ is solution conductivity. Fig. 7 shows the change in the zeta potential before and after the BSA filtration for both the unmodified and modified membranes. Before the BSA filtration both the unmodified and modified membranes had almost constant negative values at all pH values as about −30 and −20 mV, respectively. These negative charges would be derived from silanol groups on the pore surface and/or an anion adsorption for the unmodified membrane

and from residual silanol groups and/or an anion adsorption for the surface modified membrane. After the BSA filtration the pH dependence of zeta potential for both membranes changed to almost the same as that of BSA [40], which had an IEP at pH 4.9. Similar results were obtained by some researchers [8–10,18,41,42]. From these observations the electrostatic interaction between BSA molecule and clean pore surface or BSA adsorbed pore surface can be estimated. The interaction between BSA molecules and the clean pore surface would be repulsive at pH above the IEP of BSA, negligible at pH of the IEP, and attractive in pH range blow the IEP. The electrostatic interaction between BSA molecules and the BSA adsorbed pore surface would be repulsive over the pH range studied with a minimum at the IEP of BSA like the electrostatic interaction among BSA molecules. 5. Discussion The flux decline and breakthrough curves will reflect the BSA adsorption properties such as the rate and extent of the BSA adsorption and the thickness of the BSA adsorption layer. These BSA adsorption properties can be evaluated separately from the filtration results by using the internal fouling model as six fitting parameters, which are adsorption coefficient K, adsorption capacity QMAX , and thickness of adsorption layer per unit amount of adsorbed protein B, for both the primary and secondary adsorption. The calculation results are shown in Figs. 4–6 as solid lines. In all experimental condition the experimental results were well simulated by this model, suggesting the validity of this model for the results. In the cases of the experimental conditions showing a flat type breakthrough curve, which were observed at higher pH in the unmodified membranes, the six fitting parameters could not be determined distinctively by the curve fitting. In these cases the value of QMAX,2 obtained for the modified membrane at the same solution condition was

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showed almost two orders smaller value than that in the lower pH (Fig. 8(A)). K2 was almost two orders smaller than K1 and had a maximum at pH 5.0 (Fig. 8(A)). Adsorption capacities, QMAX,1 and QMAX,2 , also depended on pH (Fig. 8(B)). QMAX,1 showed a maximum value of about 2 mg/m2 at pH 4.5, which is almost the same value as the capacity of the monolayer adsorption of BSA, approximately 2.5 mg/m2 [36]. The secondary adsorption was apt to occur in the pH range from 4.5 to 6.0 and QMAX,2 had the maximum value of about 3.8 mg/m2 at pH 6.0. The maximum of total adsorption capacity, QMAX,1 + QMAX,2 , was obtained at pH 5.0 and the number of adsorption layer was expected as two layers at most. The range of B1 or B2 were about 1–6 nm/(mg/m2 ), which was the same order as the value expected from BSA molecular size (4 nm × 4 nm × 14 nm [39]) and the monolayer adsorption capacity of BSA (2.5 mg/m2 ), approximately 1.6 nm/(mg/m2 ). B1 and B2 tended to decrease with decreasing with pH, suggesting the BSA molecules might adsorb more loosely at the higher pH. 5.2. The contribution of the electrostatic interaction to the adsorption interaction The adsorption coefficient K, which can be regarded as an index of the magnitude of the overall interaction between BSA molecules and their adsorption sites, was expected to

Fig. 8. Effect of pH on the adsorption properties estimated by the internal fouling model for the unmodified (hydrophilic) membrane at ionic strength 0.01: (A) K, (B) QMAX , and (C) B.

adopted for the QMAX,2 for the unmodified membrane and the other five parameters were determined by the curve fitting with the assumption that the membrane surface modification had no influence on QMAX,2 . In this section the relationship among the adsorption properties and the electrostatic interaction were discussed. 5.1. Adsorption properties estimated by the internal fouling model (ionic strength 0.01, hydrophilic membrane) Fig. 8 shows the fitting parameters derived from the filtration results at ionic strength 0.01 for the unmodified membrane (Fig. 4) as functions of pH. K1 showed a stepwise change at pH 5.0, where K1 was almost constant value as approximately 2.5 × 104 m−1 in pH 5.0 and below while K1 at pH above 6.0

Fig. 9. The relationship between the electrostatic interaction and the adsorption coefficient K of (A) primary adsorption and (B) the secondary adsorption for the unmodified (hydrophilic) membrane at ionic strength 0.01.

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have a strong correlation with the electrostatic interaction. The electrostatic interaction can be evaluated by the product of both the zeta potentials of membrane ζ m and BSA molecules ζ BSA [4,13,41]. ζ m ·ζ BSA and ζ BSA ·ζ BSA should give an index of the repulsive electrostatic force for the primary and secondary adsorption, respectively. Fig. 9 shows the electrostatic interaction for both the primary and secondary adsorption as functions of pH. K1 and K2 were also plotted in Fig. 9. The value of the zeta potential for the membrane after BSA filtration was adopted for ζ BSA . The electrostatic interaction for the primary adsorption (Fig. 9(A)) was attractive at pH 4.5 and below and repulsive at pH 5 and above. The electrostatic interaction changed linearly with the increase in pH. The electrostatic interaction for the secondary adsorption (Fig. 9(B)) was repulsive all over the pH range and showed a minimum at pH 5. It can be seen from Fig. 9(A) that in the pH range from 3 to 5, where the electrostatic force changes from attractive to slight repulsive, K1 showed an almost constant value regardless of the change in the electrostatic force while at pH 6 and 7, where the electrostatic repulsive force is expected, K1 decreased drastically compared to that in the lower pH. This observation suggests that the electrostatic repulsive force can reduce K1 whereas the electrostatic attractive force would have no influence on K1 . A

371

possible explanation for this observation is as follows. K1 could depend on the combination of the rates of the true adsorption step and the mass transfer step for radial direction in pore, which will be dominated by Brownian motion in the pore size range of MF membrane. These steps might be much faster regardless of the existence of an electrostatic attractive force while the electrostatic repulsive force could behave as an energetic barrier for these steps. The pH dependence of K2 (Fig. 9(B)) showed a clear correlation with that of the electrostatic repulsive force ζ BSA ·ζ BSA . At the pH away from the IEP of BSA K2 would decrease due to the energetic barrier provided by the electrostatic repulsive force for the interaction between BSA and BSA adsorbed on pore surface while at the pH around IEP the adsorption interaction of the secondary adsorption would be hardly disturbed by the electrostatic interaction. Although the promoting force for the secondary adsorption is not clear from our observation, the hydraulic shear stress in pore can be considered as a cause for the promoting force. From these observations it is clear that the electrostatic repulsive force should provide an energetic barrier for the interaction between BSA molecules and their adsorption sites while the electrostatic attractive force might have no significant influence on the over all adsorption interaction.

Fig. 10. Effect of ionic strength on the adsorption properties for unmodified (hydrophilic) membrane.

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5.3. Effect of ionic strength on the adsorption properties (hydrophilic membrane) The magnitude of the electrostatic interaction between BSA and pore surface will be declined with the increase in ionic strength because the electrolytes provide a shield for the electrostatic interaction. It was expected that the effect of ionic strength on the adsorption properties is more significant at the pH away from IEP of BSA, where strong electrostatic interaction would be expected. Fig. 10 shows the effects of ionic strength on the BSA adsorption properties as six fitting parameters estimated from the breakthrough curves (Fig. 5) and flux decline curves (data not shown). Contrast to the expectation the effects of ionic strength on these fitting parameters were more significant at the pH near the IEP. K1 (Fig. 10(A)) was not affected by the increase in ionic strength at pH 7.0 and 3.0, where the strong electrostatic repulsion or attraction were expected, while K1 drastically decreased with the increase in ionic strength in the pH range from 4 to 5, where little electrostatic attraction were expected. With the increase in ionic strength K2 decreased at pH 5 and increased in pH range 3 to 4.5 while K2 was not affected by the increase in ionic strength at pH 7 (Fig. 10(B)). These observations suggest that the effect of the ionic strength on the adsorption interaction cannot be explained in terms of the shielding effect for the electrostatic interaction. As K should reflect only the electrostatic repulsive force according to the previous section, an increase or a decrease in K can imply a decrease or an increase in the electrostatic repulsive force, respectively. The decrease in K1 in the pH range of 4–5 (Fig. 10(A)) and the decrease in K2 at pH 5.0 (Fig. 10(B)) can be elucidated by an arising of the electrostatic repulsive force with the increase in ionic strength. The increase in K2 in the pH range from 3 to 4.5 (Fig. 10(B)) can be also elucidated by the decrease in the electrostatic repulsive force although this increase in K2 can be also elucidated by the shielding effect with the increase in ionic strength. The shift of the IEP of BSA toward lower pH with the increase in ionic strength is a possible explanation for these behaviors of K against the increase in ionic strength. QMAX,1 decreased with the increase in ionic strength at the pH near the IEP of BSA while QMAX,1 was not affected by the increase in ionic strength at the pH away from IEP of BSA (Fig. 10(C)). QMAX,2 decreased at pH 5.0 and increased at pH 4.0 and 4.5 while QMAX,2 was not affected at pH 7.0 and 3.0 (Fig. 10(D)). This decrease in adsorption capacity at the IEP of BSA with the increase in ionic strength was also observed by some researchers [6,11,12,19] and was explained in terms of the change in the charge condition [19], the solubility [11], and molecular size [6] of BSA with the increase in ionic strength. B1 (Fig. 10(E)) increased with the increase in ionic strength at pH 4.5 and 5 and was not affected by the increase in ionic strength at pH 3 and 4. B2 (Fig. 10(F)) increased with the increase in ionic strength at pH 5 and was not affected at pH 4.5 and below. These results suggest that at pH 5 the BSA adsorption layer became more loose structure with the increase in ionic strength. In general, it seemed that the pH dependence of these adsorption properties tended to shift toward left-hand with the increase

in ionic strength. The change in the IEP of BSA with the increase in ionic strength is most likely explanation for the effect of ionic strength on our experimental results. 5.4. Effect of the surface modification on the adsorption properties (hydrophobic membrane) The hydrophobicity of pore surface will alter the BSA adsorption properties due to the hydrophobic interaction between BSA molecules and the pore surface. Fig. 11 shows the BSA adsorption properties for the surface modified (hydrophobic) membrane estimated from Fig. 6. K1 for the modified membrane showed almost constant value against pH (Fig. 11(A)) suggesting the hydrophobic interaction would not be affected by the change in the electrostatic interaction. Except for K1 there were no remarkable differences from the adsorption properties for the hydrophilic membrane (Fig. 8), showing that the adsorption

Fig. 11. Effect of pH on the adsorption properties estimated by the internal fouling model for the modified (hydrophobic) membrane at ionic strength 0.01: (A) K, (B) QMAX , and (C) B.

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streaming potential measurement. The following results were obtained. The BSA adsorption onto pore surface during the filtration involved a rapid adsorption in the early stage of filtration followed by a slow multilayer adsorption, which determines the long-term filtration performance. The electrostatic repulsive force reduced the overall adsorption interaction but the electrostatic attractive force did not affect the adsorption interaction. The effect of ionic strength on the BSA adsorption could be explained in terms of the shift of the IEP of BSA toward lower pH with the increase in ionic strength. The hydrophobicity of membrane did not affect the adsorption properties except for the adsorption interaction in the early stage of the filtration. Fig. 12. The relationship between the adsorption coefficient and adsorption capacity for both the unmodified and the surface modified membrane: () K1 (unmodified); (
) K1 (surface modified); () K2 (unmodified); (䊉) K2 (surface modified).

properties will depend on the status of BSA molecules in solution rather than the difference in hydrophobicity of pore surface. With respect to the secondary adsorption the adsorption properties for the hydrophobic membrane were almost same as that for hydrophilic membrane, that is, once the primary adsorption occurred the adsorption performance will be entirely determined by the condition of BSA molecule. 5.5. Relationship between the adsorption interaction and the adsorption capacity In this study both the adsorption interaction and the adsorption capacity were separately evaluated from filtration results by the internal fouling model. Fig. 12 shows the relationship between K and QMAX , indicating the relationship between the adsorption interaction and the adsorption capacity. In general it was seen that the primary adsorption had higher interaction force and lower adsorption capacity while the secondary adsorption had lower interaction force and higher adsorption capacity, suggesting that the BSA adsorption during microfiltration can involve a rapid adsorption on pore surface in the early stage of filtration followed by a slow multilayer adsorption with high adsorption capacity. As the secondary adsorption will be a governing factor of the long-term filtration performance and could not be controlled by the modification of pore surface, the fundamental understanding of the secondary adsorption will be needed for the efficient filtration process of protein containing solution. 6. Conclusion The effects of pH, ionic strength, and pore surface hydrophobicity on the filtration performance of BSA solution with SPG membrane of pore size of 0.1 ␮m were observed. The adsorption properties of BSA during filtration were estimated quantitatively by using the internal fouling model from the flux decline and breakthrough curves and were discussed with the electrostatic interaction between BSA and pore surface estimated by the

Nomenclature List of symbols av specific surface area of membrane based on membrane volume (m2 /m3 ) av0 specific surface area of clean membrane based on membrane volume (m2 /m3 ) B thickness of BSA adsorption layer per unit amount of adsorbed protein per unit pore surface area (nm/(mg/m2 )) c concentration (kg/m3 ) cf concentration in feed solution (kg/m3 ) cp concentration in permeate solution (kg/m3 ) ETM potential difference across membrane (V) J permeate flux (m3 /(m2 s)) initial permeate flux (m3 /(m2 s)) J0 hydraulic permeability (m2 ) kp kp0 hydraulic permeability of clean membrane (m2 ) K adsorption coefficient (m−1 ) Lm membrane thickness (m) N pore density (m−2 ) P pressure difference in a small distance of z (Pa) PTM trans-membrane pressure (Pa) q amount of adsorbed protein (mg/m2 ) QMAX adsorption capacity (mg/m2 ) r pore radius (m) r thickness of protein adsorption layer (m) r0 pore radius of clean membrane (m) R filtration resistance (m−1 ) Rm filtration resistance of membrane (m−1 ) t filtration time (s) V permeate volume (m3 ) Vm membrane volume (m3 ) z distance from membrane surface (m) Greek letters ε0 permittivity of free space (F m−1 ) εr relative dielectric constant ζ BSA zeta potential of BSA (V) ζm zeta potential of pore surface of membrane (V) ζ obs apparent zeta potential (V)

374

λ µ

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solution conductivity viscosity (Pa s)

(S m−1 )

Subscripts 1 primary adsorption 2 secondary adsorption

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