- Email: [email protected]
Effect of membrane pore size on the particle fouling in membrane filtration
Desalination 234 (2008) 16–23
Effect of membrane pore size on the particle fouling in membrane filtration Kuo-Jen Hwanga*, Chien-Yao Liaoa, Kuo-Lun Tungb a
Department of Chemical and Materials Engineering, Tamkang University, Tamsui, Taipei Hsien 25137, Taiwan Tel. þ886(2)26219484; Fax þ886(2)26209887; email: [email protected] b R&D Center for Membrane Technology, Department of Chemical Engineering, Chung Yuan Christian University, Chungli, Taoyuan 320, Taiwan Received 6 July 2007; accepted revised 26 September 2007
Abstract The effects of membrane pore size and operating conditions on the particle fouling in ‘‘dead-end’’ microfiltration are studied by use of membrane blocking models. Two track-etched membranes (Isopore1membrane) with the mean pore diameters of 0.2 and 0.4 mm, respectively, are used as the filter media to filter 0.15 mm polymethyl methacrylate (PMMA) particles. A blocking chart is established for relating the operating conditions and the particle fouling for the testing materials. The major factors affecting the blocking index, particle accumulation and filtration flux, are discussed thoroughly. The blocking index varies gradually at the initial period of filtration, keeps at ca. 0.5 for a while and then suddenly drops to zero at a critical condition. The blocking index for 0.4 mm membrane is always larger than that for 0.2 mm membrane under the same filtration pressure and filtration flux due to more severe membrane blocking. The critical point at which the filtration transforms from membrane blocking to cake filtration occurs at a lower filtration flux or a lower particle accumulation for the membrane with larger pore size or under lower filtration pressure. The normalized resistance coefficient can be correlated to a unique function of blocking index under various operating conditions and for different membranes. Keywords: Microfiltration; Particle fouling; Blocking models; Membrane pore size
1. Introduction Microfiltration has been widely employed for separating fine particles in chemical,
biotechnological and materials processes. In order to enhance its economy and efficiency, to understand the membrane fouling mechanism is necessary for the further development.
*Corresponding author. Presented at the Fourth Conference of Aseanian Membrane Society (AMS 4), 16–18 August 2007, Taipei, Taiwan. 0011-9164/08/$– See front matter # 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2007.09.065
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
17
Many theoretical models concerning particle fouling or filtration flux in microfiltration or ultrafiltration have been proposed in the past 40 years. However, when particle size is smaller than or comparable to the membrane pores, the membrane blocking model is commonly a useful tool to explain how and when the particles to penetrate into or block the pores. Hermia [1] derived a blocking model to describe different blocking phenomena occurred in filtration, that is,
In this study, the blocking models are used to analyze the membrane blocking and cake formation in a ‘‘dead-end’’ microfiltration system. The blocking chart for Isopore membranes with different pore sizes is established for relating the blocking index, filtration rate and particle accumulation. The major factors affecting the blocking index are also discussed.
i d2 t dt ¼K 2 dv dv
2. Materials and methods ð1Þ
where t is filtration time, v is the received filtrate volume per unit filtration area, while the blocking index i and the resistance coefficient K are the functions of blocking models. The blocking phenomena can be imaged through the index, for example, i ¼ 2 for a‘‘complete blocking’’, i ¼ 1.5 for the ‘‘standard blocking’’, i ¼ 1 for the ‘‘intermediate blocking’’ and i ¼ 0 for the socalled ‘‘cake filtration’’. Hwang and Lin [2] indicated that different blocking phenomena occurred at the initial stage of filtration using different membranes, e.g., standard blocking in a MF-Millipore membrane, intermediate blocking in a Durapore membrane and complete blocking in an Isopore membrane. The blocking models then changed to the cake filtration after a period of time for all membranes. Ho and Zydney [3] studied the effects of surface morphology and pore structure of membranes on the initial rate of protein aggregates fouling. They also developed a combined pore blockage and cake filtration model for the fouling of protein aggregates during microfiltration [4]. A smooth transition from pore blockage to cake filtration could be derived based on this model. Recently, Hwang et al. [5] proposed an analysis method to establish the membrane blocking chart [5]. The blocking index could be related to filtration rate and particle accumulation by use of this chart.
Polymethyl methacrylate (PMMA) spherical particles with a mean diameter of 0.15 mm and a density of 1210 kg/m3 were suspended in de-ionized water to prepare the suspension used in experiments. The suspension was kept at pH 7 and 20 C during filtration experiments. The particles were suspended stably because their zeta potentials were as high as 32.4 mV. Two kinds of track-etched membranes, Isopore1 membranes manufactured by Millipore Co. in USA, were used in experiments as the filter media. The membranes were made of polycarbonate and their surfaces were hydrophilic. The mean pore sizes of these membranes were 0.2 and 0.4 mm, respectively. ‘‘Dead-end’’ constant pressure microfiltration was carried out by a bomb filter with a filtration area of 8.55 104 m2. The schematic diagram of the filtration system is shown in Fig. 1. The
Fig. 1. A schematic diagram of the ‘‘dead-end’’ microfiltration system.
18
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
suspension with a given PMMA concentration was prepared in the bomb filter and mixed well by a magnetic stirrer. The filtration pressure was supplied by a compressed air and adjusted to the preset value by a regulator. The filtrate was collected into a receiver which was put on a load cell. The filtrate weight could be measured by the load cell and the filtration data of filtrate volume, v, vs. time, t, were recorded via a personal computer.
3. Results and discussion Fig. 2 shows time courses of filtration flux under various conditions during microfiltration using two Isopore membranes. The variation of filtration flux can be divided into two stages, a quickly decay and a pseudo-steady stage. At the early period of filtration, the flux attenuates very quickly due to the quicker membrane blocking and particle deposition. The decrease in filtration flux becomes very slow after ca 15002000 s. In fact, the fluxes approach pseudo-steady values in some conditions, and the flux is quicker to reach the pseudo-steady value under a lower filtration pressure. To compare the curves shown in Fig. 2, an increase in filtration pressure leads to a higher filtration flux due to the higher driving
force. The filtration flux also increases by decreasing the suspension concentration, c, because of less particle accumulation during a fixed time interval. In addition, use of the membrane with a larger pore size causes to a lower filtration flux. This is due to more severe membrane blocking occurring in the larger membrane pores. It can be expected that more particles can accumulate in larger pore volume. However, this phenomenon becomes less obvious under a lower filtration pressure, e.g., P ¼ 50 kPa. In addition, the influences of operating conditions on the filtration flux gradually decrease after the filtration time of 3000 s. To increase the filtration pressure or to decrease the suspension concentration may result in almost the same filtration flux for a long-term filtration. Typical filtration curves of dt/dv versus v for 0.4 mm Isopore membrane under various filtration pressures and suspension concentrations are shown in Fig. 3. Those curves can be divided into two distinct segments. Each curve behaves a concave trend before the critical point C, while changes to a straight line after the critical point. According to previous analyses [1–5], some kinds of membrane blocking may occur at the first period, while the filtration follows the cake 8
4
0.4 μm Isopore membrane 0.15 μm PMMA particles
0.15 μm PMMA, Isopore membrane 0.4 μm 0.2 μm
3
ΔP = 50 kPa, c = 2 kg/m
3
3
Δ P = 50 kPa, c = 2 kg/m
dt/dv × 10–4 (s m2/m3)
3
q × 104 (m3/m2 s)
3
Δ P = 300 kPa, c = 2 kg/m
3
Δ P = 50 kPa, c = 0.5 kg/m 2
1
0 0
1000
2000
3000
ΔP = 100 kPa, c = 2 kg/m
6
4000
t (s)
Fig. 2. Time courses of filtration flux under various conditions during microfiltration using two membranes.
3
ΔP = 300 kPa, c = 2 kg/m
3
C
ΔP = 50 kPa, c = 0.5 kg/m
C
4
C
C
2
0
0
0.1
0.2
0.3
0.4
0.5
v (m3/m2)
Fig. 3. Filtration curves of dt/dv vs. v under various operating conditions.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 100
d2t/dv 2 × 10–5 (s m4/m6)
filtration model after the critical point. This trend can also be seen in previous studies [35]. To compare the first segments of the curves for a given suspension concentration, c ¼ 2 kg/m3, the curvature decreases with the increase in filtration pressure. This indicates that the membrane blocking is more severe under a lower pressure, which can be attributed to fewer particles arriving at the membrane surface simultaneously. In addition, a higher filtration pressure or a lower suspension concentration causes the critical point to occur in the condition of larger received filtrate volume. Since the particle mass transported to the membrane surface per unit area can be calculated by the product of suspension concentration and filtrate volume, i.e. cv, the results shown in Fig. 3 indicate that a greater particle accumulation at the critical point is required under a higher filtration pressure. However, the particle accumulation at the critical point is only slightly higher occurring at a lower suspension concentration under the same filtration pressures. This may be due to less particles instantaneously arriving at the membrane surface at a lower concentration. Since the reciprocal of dt/dv is equal to the transient filtration flux, q, Fig. 3 also depicts that the filtration rate increases with increasing filtration pressure or with decreasing suspension concentration, which have been discussed in Fig. 2. According to Eq. (1), the blocking index and resistance coefficient can be analyzed by plotting d2t/dv2 versus dt/dv in logarithm scales. The blocking index can be obtained from the tangent slope of the curve. Fig. 4 shows the curves of d2t/dv2 versus dt/dv under four different filtration pressures. The mean pore size of the used membrane is 0.4 mm. Each curve shown in Fig. 4 can be divided into two different regions, an increasing – d2t/dv2 region and a constant d2t/dv2 region. The variation of blocking models during a filtration is just reflected upon the curve trend. A larger variation in the tangent slope of the curves at the initial periods of filtration
19
10 0.4 μm Isopore membrane 3 0.15 μm PMMA, c = 2 kg/m ΔP = 50 kPa ΔP = 100 kPa ΔP = 200 kPa ΔP = 300 kPa
1 0.1
1
10
dt/dv × 10–4 (s m2/m3)
Fig. 4. The curves of d2t/dv2 vs. dt/dv under various filtration pressures.
(at smaller dt/dv) reveals the quicker change of blocking models. The slope of the tangent suddenly drops to zero at the critical point; and the curve then becomes a horizontal line. This indicates that the cake filtration model can be applied to explain the filtration data after the critical point. From the trend of those curves shown in Fig. 4, it can be expected that the variation of blocking index is more intense under lower filtration pressure. According to the authors’ previous analysis [5], the major factors affecting membrane blocking include the amount of particle accumulation and the filtration flux. The drag force exerted on particles or the instantaneous flux of particle transportation is significantly determined by the filtration flux, while the particle migration may be influenced or hindered by those accumulated particles. How these factors affect particle fouling will be discussed below. Fig. 5 shows a comparison of the variations of blocking index during microfiltration by use of two different membranes. The solid and hollow symbols represent the data for 0.4 and 0.2 mm membranes, respectively. The blocking index initially approximates 2.0 under a filtration pressure of 50 kPa; this is attributed to the
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 2 3
0.15 μm PMMA, c = 2 kg/m Isopore membrane
1.6
0.2 μm
0.4 μm
ΔP = 50 kPa ΔP = 100 kPa ΔP = 300 kPa
i (–)
1.2
0.8
0.4
0 0
1
2
3
q × 10–4 (m3/m2 s)
Fig. 5. Effect of filtration flux on the blocking index during microfiltration using different membranes under various filtration pressures.
complete blocking of membrane pores [1]. After some particles have blocked the membrane pores or deposited on the membrane surface, the blocking becomes a hybrid type, the blocking index therefore decreases continuously from 2.0 to about 0.5 during the decay of filtration flux. Under a higher filtration pressure, a larger amount of particles are simultaneously transported to the membrane surface at the initial period of filtration due to higher filtration flux, a smaller blocking index is therefore structured due to the hindered effect on the particle penetration. In addition, the blocking index suddenly drops to zero at the critical point. The cake filtration model can then be applied to describe the filtration characteristics after that point. It can be seen that the blocking index of 0.4 mm membranes is always larger than that of 0.2 mm under the same pressure and filtration flux. This can be expected since a larger pore may have more opportunities to be blocked by particles. Moreover, the critical point occurs at a lower filtration flux for the membrane with larger pore size or under a lower filtration pressure. It is inferred that the particles are more easily to penetrate into
or to accumulate in the membranes with a larger pore size. Fig. 6 shows the effect of particle accumulation on the blocking index in microfiltration using two Isopore membranes under various filtration pressures. The symbols and operating conditions are the same as those shown in Fig. 5. The membrane blocking apparently occurs at the initial period of filtration as described previously. The blocking index varies continuously to a certain value (ca. 0.5) during the increase of cv, keeps that value for a while and then suddenly drops to zero at the critical point and becomes invariant thereafter. Since fewer particles simultaneously arrive at the membrane surface under a lower filtration pressure, the blocking index is therefore higher at a fixed value of cv. Furthermore, particles are more easily to migrate into the membrane with larger pores; the blocking index is higher in such a condition. From Figs. 5 and 6, one knows that i ¼ 0.5 is the critical status of the transformation from membrane blocking to cake filtration. Membrane blocking (i > 0) occurs only when cv is smaller than the critical value, which depends on the operating condition and membrane
2 3
0.15 μm PMMA, c = 2 kg/m
1.6
Isopore membrane 0.2 μm
1.2
0.4 μm
ΔP = 50 kPa ΔP = 100 kPa ΔP = 300 kPa
i (–)
20
0.8
0.4
0 0
0.1
0.2
0.3
0.4
cv (kg/m2)
Fig. 6. Effect of particle accumulation on the blocking index during microfiltration using different membranes under various filtration pressures.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
pores. Comparing the critical points under various conditions, the point occurs at a larger cv by using the membrane with smaller pore size or under a higher filtration pressure. This is because a higher filtration flux is always obtained under those conditions (referred to Fig. 2). Fig. 7 shows the membrane blocking chart for 0.15 mm PMMA particles and Isopore membranes with two different pore sizes. The blocking index i is related to filtration flux q and particle accumulation cv in this figure for those test materials. This chart is established by rearranging the data obtained from Figs. 5 and 6. Three contours and the critical curves for those two membranes are selected to plot in the figure. The mapped method has been described in detail in the authors’ recent study [5], while the critical curves are plotted by connecting the critical points obtained in Figs. 5 and 6. One can easily catch the general concepts among membrane blocking and operating conditions from the contours shown in this figure. The blocking index
7
0.15 μm PMMA Isopore membrane
6
0.4 μm (i) 0.2 μm (i) 0.4 μm (cc) 0.2 μm (cc)
q × 104 (m3/m2 s)
5
4 i 3
2
2
Critical curve
1
0.5
1
0 0 0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
2
cv (kg/m )
Fig. 7. The membrane blocking chart for 0.15 mm PMMA particles and Isopore membranes with two different pore sizes.
21
decreases with the increase of particle accumulation or the decrease of filtration flux. It is because the deposited particles may hinder the next coming particles to migrate into the membrane pores. In addition, a lower filtration flux has less effect to drag particles to penetrate into the membrane pores. To compare the contours of i ¼ 1 and 2, the maximum value of cv is larger for 0.4 mm membrane since more particles can deposit in the membrane if its pore size is larger. It is interesting to find that the maximum value of cv is double at the same i contours if the pore size becomes two-fold. However, no distinct difference in filtration flux can be found between these membranes for the contours. Furthermore, for the contour of i ¼ 0.5, the condition before the transformation from membrane blocking to cake formation, the value of cv is larger and the flux is higher for 0.2 mm membrane. This implies that a higher flux is needed to drag the particles into the membrane with smaller pore size. When one focuses on the critical curves shown in Fig. 7, this drag effect also results in a higher critical flux at a fixed value of cv. In addition, the critical value of cv is smaller for 0.2 mm membrane when filtration fluxes are the same. It can be attributed to the smaller pore volume in 0.2 mm membrane. The resistance coefficient, K, can be calculated by solving Eq. (1) once the blocking index is obtained by the method described previously. The calculated values of K are then normalized by dividing by the resistance coefficient in cake filtration mode, Kc. Fig. 8 plots K/Kc against i under various operating conditions and for different membranes. Although the values of Kc are function of filtration pressure, all data of K/Kc shown in Fig. 8 which obtained under different filtration pressures, suspension concentrations and membrane pores are located on the same regressive curve. This implies that the normalized resistance coefficient depends only on the materials of particles and membranes but not on the operating conditions. The relationship
22
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 1 × 101 Isopore membrane 0.15 μm PMMA
0
1 × 10
–1
1 × 10
–2
K/K c (–)
1 × 10
1 × 10
–3
1 × 10
–4
1 × 10
–5
1 × 10
–6
1 × 10
–7
1 × 10
–8
0.4 μm
0.2 μm 3
ΔP = 50 kPa, c = 2 kg/m 3 ΔP = 100 kPa, c = 2 kg/m 3 ΔP = 200 kPa, c = 2 kg/m 3 ΔP = 300 kPa, c = 2 kg/m 3 ΔP = 50 kPa, c = 0.5 kg/m
0
0.4
0.8
1.2
1.6
2
i (–)
Fig. 8. The relationship between normalized resistance coefficient and blocking index.
between K/Kc and i can be regressed to a continuously exponential function as K ¼ 0:38 exp ð8:51iÞ Kc
index varied to a certain value, ca. 0.5, at the early period of filtration, kept at that value for a while and then suddenly dropped to be zero and kept at that value thereafter. The blocking index for 0.4 mm membrane was always larger than that for 0.2 mm membrane under the same pressure and filtration flux. The critical point at which the filtration transformed from membrane blocking to cake filtration would be occurred at a lower filtration flux or lower particle accumulation for the membrane with larger pore size or under a lower filtration pressure. The normalized resistance coefficient could be correlated to a unique function of blocking index under various operating conditions and for different membranes. From the analyses of blocking chart and resistance coefficient, the filtration flux could then be predicted by using the blocking models.
ð2Þ
The data shown in Fig. 8 indicates that the order-of-magnitudes of K/Kc for Hermia’s four blocking models (i ¼ 2, 1.5, 1 and 0, respectively) are extremely different. The quantitative expression, Eq. (2), provides us a way to estimate the filtration resistance using the membrane blocking models. Once the blocking index and resistance coefficient are related to the operating conditions, e.g., Figs. 7 and 8, the filtration flux during microfiltration can then be predicted by using the blocking models [5]. 4. Conclusions The blocking index and resistance coefficient in the ‘‘dead-end’’ microfiltration using Isopore membranes with two mean pore diameters have been analyzed by use of blocking models. The blocking chart for these membranes and 0.15 mm PMMA particles was established for discussing the effects of pore size and operating conditions on the particle fouling. The blocking
Acknowledgements The authors wish to express their sincere gratitude to the National Science Council (NSC), the Center-of-Excellence (COE) Program on Membrane Technology from the Ministry of Education (MOE), R.O.C. and the Technology Development Program for Academia (TDPA) from the Ministry of Economic Affairs (MOEA), R.O.C. for the financial supports.
References [1] J. Hermia, Constant pressure blocking filtration laws–application to power law non-Newtonian fluid, Trans. Inst. Chem. Eng., 60 (1982) 183–187. [2] K.J. Hwang and T.T. Lin, Effect of morphology of polymeric membrane on the performance of crossflow microfiltration, J. Membr. Sci., 199 (2002) 41–52. [3] C.C. Ho and A.L. Zydney, Effect of membrane morphology on the initial rate of protein fouling during microfiltration, J. Membr. Sci., 155 (1999) 261–275.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 [4] C.C. Ho and A.L. Zydney, A combined pore blockage and cake filtration model for protein fouling during microfiltration, J. Colloid Interf. Sci., 232 (2000) 389–399.
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[5] K.J. Hwang, C.Y. Liao and K.L. Tung, Analysis of particle fouling during microfiltration by use of blocking models, J. Membr. Sci., 287 (2007) 287–293.
Effect of membrane pore size on the particle fouling in membrane filtration Kuo-Jen Hwanga*, Chien-Yao Liaoa, Kuo-Lun Tungb a
Department of Chemical and Materials Engineering, Tamkang University, Tamsui, Taipei Hsien 25137, Taiwan Tel. þ886(2)26219484; Fax þ886(2)26209887; email: [email protected] b R&D Center for Membrane Technology, Department of Chemical Engineering, Chung Yuan Christian University, Chungli, Taoyuan 320, Taiwan Received 6 July 2007; accepted revised 26 September 2007
Abstract The effects of membrane pore size and operating conditions on the particle fouling in ‘‘dead-end’’ microfiltration are studied by use of membrane blocking models. Two track-etched membranes (Isopore1membrane) with the mean pore diameters of 0.2 and 0.4 mm, respectively, are used as the filter media to filter 0.15 mm polymethyl methacrylate (PMMA) particles. A blocking chart is established for relating the operating conditions and the particle fouling for the testing materials. The major factors affecting the blocking index, particle accumulation and filtration flux, are discussed thoroughly. The blocking index varies gradually at the initial period of filtration, keeps at ca. 0.5 for a while and then suddenly drops to zero at a critical condition. The blocking index for 0.4 mm membrane is always larger than that for 0.2 mm membrane under the same filtration pressure and filtration flux due to more severe membrane blocking. The critical point at which the filtration transforms from membrane blocking to cake filtration occurs at a lower filtration flux or a lower particle accumulation for the membrane with larger pore size or under lower filtration pressure. The normalized resistance coefficient can be correlated to a unique function of blocking index under various operating conditions and for different membranes. Keywords: Microfiltration; Particle fouling; Blocking models; Membrane pore size
1. Introduction Microfiltration has been widely employed for separating fine particles in chemical,
biotechnological and materials processes. In order to enhance its economy and efficiency, to understand the membrane fouling mechanism is necessary for the further development.
*Corresponding author. Presented at the Fourth Conference of Aseanian Membrane Society (AMS 4), 16–18 August 2007, Taipei, Taiwan. 0011-9164/08/$– See front matter # 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2007.09.065
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
17
Many theoretical models concerning particle fouling or filtration flux in microfiltration or ultrafiltration have been proposed in the past 40 years. However, when particle size is smaller than or comparable to the membrane pores, the membrane blocking model is commonly a useful tool to explain how and when the particles to penetrate into or block the pores. Hermia [1] derived a blocking model to describe different blocking phenomena occurred in filtration, that is,
In this study, the blocking models are used to analyze the membrane blocking and cake formation in a ‘‘dead-end’’ microfiltration system. The blocking chart for Isopore membranes with different pore sizes is established for relating the blocking index, filtration rate and particle accumulation. The major factors affecting the blocking index are also discussed.
i d2 t dt ¼K 2 dv dv
2. Materials and methods ð1Þ
where t is filtration time, v is the received filtrate volume per unit filtration area, while the blocking index i and the resistance coefficient K are the functions of blocking models. The blocking phenomena can be imaged through the index, for example, i ¼ 2 for a‘‘complete blocking’’, i ¼ 1.5 for the ‘‘standard blocking’’, i ¼ 1 for the ‘‘intermediate blocking’’ and i ¼ 0 for the socalled ‘‘cake filtration’’. Hwang and Lin [2] indicated that different blocking phenomena occurred at the initial stage of filtration using different membranes, e.g., standard blocking in a MF-Millipore membrane, intermediate blocking in a Durapore membrane and complete blocking in an Isopore membrane. The blocking models then changed to the cake filtration after a period of time for all membranes. Ho and Zydney [3] studied the effects of surface morphology and pore structure of membranes on the initial rate of protein aggregates fouling. They also developed a combined pore blockage and cake filtration model for the fouling of protein aggregates during microfiltration [4]. A smooth transition from pore blockage to cake filtration could be derived based on this model. Recently, Hwang et al. [5] proposed an analysis method to establish the membrane blocking chart [5]. The blocking index could be related to filtration rate and particle accumulation by use of this chart.
Polymethyl methacrylate (PMMA) spherical particles with a mean diameter of 0.15 mm and a density of 1210 kg/m3 were suspended in de-ionized water to prepare the suspension used in experiments. The suspension was kept at pH 7 and 20 C during filtration experiments. The particles were suspended stably because their zeta potentials were as high as 32.4 mV. Two kinds of track-etched membranes, Isopore1 membranes manufactured by Millipore Co. in USA, were used in experiments as the filter media. The membranes were made of polycarbonate and their surfaces were hydrophilic. The mean pore sizes of these membranes were 0.2 and 0.4 mm, respectively. ‘‘Dead-end’’ constant pressure microfiltration was carried out by a bomb filter with a filtration area of 8.55 104 m2. The schematic diagram of the filtration system is shown in Fig. 1. The
Fig. 1. A schematic diagram of the ‘‘dead-end’’ microfiltration system.
18
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
suspension with a given PMMA concentration was prepared in the bomb filter and mixed well by a magnetic stirrer. The filtration pressure was supplied by a compressed air and adjusted to the preset value by a regulator. The filtrate was collected into a receiver which was put on a load cell. The filtrate weight could be measured by the load cell and the filtration data of filtrate volume, v, vs. time, t, were recorded via a personal computer.
3. Results and discussion Fig. 2 shows time courses of filtration flux under various conditions during microfiltration using two Isopore membranes. The variation of filtration flux can be divided into two stages, a quickly decay and a pseudo-steady stage. At the early period of filtration, the flux attenuates very quickly due to the quicker membrane blocking and particle deposition. The decrease in filtration flux becomes very slow after ca 15002000 s. In fact, the fluxes approach pseudo-steady values in some conditions, and the flux is quicker to reach the pseudo-steady value under a lower filtration pressure. To compare the curves shown in Fig. 2, an increase in filtration pressure leads to a higher filtration flux due to the higher driving
force. The filtration flux also increases by decreasing the suspension concentration, c, because of less particle accumulation during a fixed time interval. In addition, use of the membrane with a larger pore size causes to a lower filtration flux. This is due to more severe membrane blocking occurring in the larger membrane pores. It can be expected that more particles can accumulate in larger pore volume. However, this phenomenon becomes less obvious under a lower filtration pressure, e.g., P ¼ 50 kPa. In addition, the influences of operating conditions on the filtration flux gradually decrease after the filtration time of 3000 s. To increase the filtration pressure or to decrease the suspension concentration may result in almost the same filtration flux for a long-term filtration. Typical filtration curves of dt/dv versus v for 0.4 mm Isopore membrane under various filtration pressures and suspension concentrations are shown in Fig. 3. Those curves can be divided into two distinct segments. Each curve behaves a concave trend before the critical point C, while changes to a straight line after the critical point. According to previous analyses [1–5], some kinds of membrane blocking may occur at the first period, while the filtration follows the cake 8
4
0.4 μm Isopore membrane 0.15 μm PMMA particles
0.15 μm PMMA, Isopore membrane 0.4 μm 0.2 μm
3
ΔP = 50 kPa, c = 2 kg/m
3
3
Δ P = 50 kPa, c = 2 kg/m
dt/dv × 10–4 (s m2/m3)
3
q × 104 (m3/m2 s)
3
Δ P = 300 kPa, c = 2 kg/m
3
Δ P = 50 kPa, c = 0.5 kg/m 2
1
0 0
1000
2000
3000
ΔP = 100 kPa, c = 2 kg/m
6
4000
t (s)
Fig. 2. Time courses of filtration flux under various conditions during microfiltration using two membranes.
3
ΔP = 300 kPa, c = 2 kg/m
3
C
ΔP = 50 kPa, c = 0.5 kg/m
C
4
C
C
2
0
0
0.1
0.2
0.3
0.4
0.5
v (m3/m2)
Fig. 3. Filtration curves of dt/dv vs. v under various operating conditions.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 100
d2t/dv 2 × 10–5 (s m4/m6)
filtration model after the critical point. This trend can also be seen in previous studies [35]. To compare the first segments of the curves for a given suspension concentration, c ¼ 2 kg/m3, the curvature decreases with the increase in filtration pressure. This indicates that the membrane blocking is more severe under a lower pressure, which can be attributed to fewer particles arriving at the membrane surface simultaneously. In addition, a higher filtration pressure or a lower suspension concentration causes the critical point to occur in the condition of larger received filtrate volume. Since the particle mass transported to the membrane surface per unit area can be calculated by the product of suspension concentration and filtrate volume, i.e. cv, the results shown in Fig. 3 indicate that a greater particle accumulation at the critical point is required under a higher filtration pressure. However, the particle accumulation at the critical point is only slightly higher occurring at a lower suspension concentration under the same filtration pressures. This may be due to less particles instantaneously arriving at the membrane surface at a lower concentration. Since the reciprocal of dt/dv is equal to the transient filtration flux, q, Fig. 3 also depicts that the filtration rate increases with increasing filtration pressure or with decreasing suspension concentration, which have been discussed in Fig. 2. According to Eq. (1), the blocking index and resistance coefficient can be analyzed by plotting d2t/dv2 versus dt/dv in logarithm scales. The blocking index can be obtained from the tangent slope of the curve. Fig. 4 shows the curves of d2t/dv2 versus dt/dv under four different filtration pressures. The mean pore size of the used membrane is 0.4 mm. Each curve shown in Fig. 4 can be divided into two different regions, an increasing – d2t/dv2 region and a constant d2t/dv2 region. The variation of blocking models during a filtration is just reflected upon the curve trend. A larger variation in the tangent slope of the curves at the initial periods of filtration
19
10 0.4 μm Isopore membrane 3 0.15 μm PMMA, c = 2 kg/m ΔP = 50 kPa ΔP = 100 kPa ΔP = 200 kPa ΔP = 300 kPa
1 0.1
1
10
dt/dv × 10–4 (s m2/m3)
Fig. 4. The curves of d2t/dv2 vs. dt/dv under various filtration pressures.
(at smaller dt/dv) reveals the quicker change of blocking models. The slope of the tangent suddenly drops to zero at the critical point; and the curve then becomes a horizontal line. This indicates that the cake filtration model can be applied to explain the filtration data after the critical point. From the trend of those curves shown in Fig. 4, it can be expected that the variation of blocking index is more intense under lower filtration pressure. According to the authors’ previous analysis [5], the major factors affecting membrane blocking include the amount of particle accumulation and the filtration flux. The drag force exerted on particles or the instantaneous flux of particle transportation is significantly determined by the filtration flux, while the particle migration may be influenced or hindered by those accumulated particles. How these factors affect particle fouling will be discussed below. Fig. 5 shows a comparison of the variations of blocking index during microfiltration by use of two different membranes. The solid and hollow symbols represent the data for 0.4 and 0.2 mm membranes, respectively. The blocking index initially approximates 2.0 under a filtration pressure of 50 kPa; this is attributed to the
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 2 3
0.15 μm PMMA, c = 2 kg/m Isopore membrane
1.6
0.2 μm
0.4 μm
ΔP = 50 kPa ΔP = 100 kPa ΔP = 300 kPa
i (–)
1.2
0.8
0.4
0 0
1
2
3
q × 10–4 (m3/m2 s)
Fig. 5. Effect of filtration flux on the blocking index during microfiltration using different membranes under various filtration pressures.
complete blocking of membrane pores [1]. After some particles have blocked the membrane pores or deposited on the membrane surface, the blocking becomes a hybrid type, the blocking index therefore decreases continuously from 2.0 to about 0.5 during the decay of filtration flux. Under a higher filtration pressure, a larger amount of particles are simultaneously transported to the membrane surface at the initial period of filtration due to higher filtration flux, a smaller blocking index is therefore structured due to the hindered effect on the particle penetration. In addition, the blocking index suddenly drops to zero at the critical point. The cake filtration model can then be applied to describe the filtration characteristics after that point. It can be seen that the blocking index of 0.4 mm membranes is always larger than that of 0.2 mm under the same pressure and filtration flux. This can be expected since a larger pore may have more opportunities to be blocked by particles. Moreover, the critical point occurs at a lower filtration flux for the membrane with larger pore size or under a lower filtration pressure. It is inferred that the particles are more easily to penetrate into
or to accumulate in the membranes with a larger pore size. Fig. 6 shows the effect of particle accumulation on the blocking index in microfiltration using two Isopore membranes under various filtration pressures. The symbols and operating conditions are the same as those shown in Fig. 5. The membrane blocking apparently occurs at the initial period of filtration as described previously. The blocking index varies continuously to a certain value (ca. 0.5) during the increase of cv, keeps that value for a while and then suddenly drops to zero at the critical point and becomes invariant thereafter. Since fewer particles simultaneously arrive at the membrane surface under a lower filtration pressure, the blocking index is therefore higher at a fixed value of cv. Furthermore, particles are more easily to migrate into the membrane with larger pores; the blocking index is higher in such a condition. From Figs. 5 and 6, one knows that i ¼ 0.5 is the critical status of the transformation from membrane blocking to cake filtration. Membrane blocking (i > 0) occurs only when cv is smaller than the critical value, which depends on the operating condition and membrane
2 3
0.15 μm PMMA, c = 2 kg/m
1.6
Isopore membrane 0.2 μm
1.2
0.4 μm
ΔP = 50 kPa ΔP = 100 kPa ΔP = 300 kPa
i (–)
20
0.8
0.4
0 0
0.1
0.2
0.3
0.4
cv (kg/m2)
Fig. 6. Effect of particle accumulation on the blocking index during microfiltration using different membranes under various filtration pressures.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23
pores. Comparing the critical points under various conditions, the point occurs at a larger cv by using the membrane with smaller pore size or under a higher filtration pressure. This is because a higher filtration flux is always obtained under those conditions (referred to Fig. 2). Fig. 7 shows the membrane blocking chart for 0.15 mm PMMA particles and Isopore membranes with two different pore sizes. The blocking index i is related to filtration flux q and particle accumulation cv in this figure for those test materials. This chart is established by rearranging the data obtained from Figs. 5 and 6. Three contours and the critical curves for those two membranes are selected to plot in the figure. The mapped method has been described in detail in the authors’ recent study [5], while the critical curves are plotted by connecting the critical points obtained in Figs. 5 and 6. One can easily catch the general concepts among membrane blocking and operating conditions from the contours shown in this figure. The blocking index
7
0.15 μm PMMA Isopore membrane
6
0.4 μm (i) 0.2 μm (i) 0.4 μm (cc) 0.2 μm (cc)
q × 104 (m3/m2 s)
5
4 i 3
2
2
Critical curve
1
0.5
1
0 0 0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
2
cv (kg/m )
Fig. 7. The membrane blocking chart for 0.15 mm PMMA particles and Isopore membranes with two different pore sizes.
21
decreases with the increase of particle accumulation or the decrease of filtration flux. It is because the deposited particles may hinder the next coming particles to migrate into the membrane pores. In addition, a lower filtration flux has less effect to drag particles to penetrate into the membrane pores. To compare the contours of i ¼ 1 and 2, the maximum value of cv is larger for 0.4 mm membrane since more particles can deposit in the membrane if its pore size is larger. It is interesting to find that the maximum value of cv is double at the same i contours if the pore size becomes two-fold. However, no distinct difference in filtration flux can be found between these membranes for the contours. Furthermore, for the contour of i ¼ 0.5, the condition before the transformation from membrane blocking to cake formation, the value of cv is larger and the flux is higher for 0.2 mm membrane. This implies that a higher flux is needed to drag the particles into the membrane with smaller pore size. When one focuses on the critical curves shown in Fig. 7, this drag effect also results in a higher critical flux at a fixed value of cv. In addition, the critical value of cv is smaller for 0.2 mm membrane when filtration fluxes are the same. It can be attributed to the smaller pore volume in 0.2 mm membrane. The resistance coefficient, K, can be calculated by solving Eq. (1) once the blocking index is obtained by the method described previously. The calculated values of K are then normalized by dividing by the resistance coefficient in cake filtration mode, Kc. Fig. 8 plots K/Kc against i under various operating conditions and for different membranes. Although the values of Kc are function of filtration pressure, all data of K/Kc shown in Fig. 8 which obtained under different filtration pressures, suspension concentrations and membrane pores are located on the same regressive curve. This implies that the normalized resistance coefficient depends only on the materials of particles and membranes but not on the operating conditions. The relationship
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K.-J. Hwang et al. / Desalination 234 (2008) 16–23 1 × 101 Isopore membrane 0.15 μm PMMA
0
1 × 10
–1
1 × 10
–2
K/K c (–)
1 × 10
1 × 10
–3
1 × 10
–4
1 × 10
–5
1 × 10
–6
1 × 10
–7
1 × 10
–8
0.4 μm
0.2 μm 3
ΔP = 50 kPa, c = 2 kg/m 3 ΔP = 100 kPa, c = 2 kg/m 3 ΔP = 200 kPa, c = 2 kg/m 3 ΔP = 300 kPa, c = 2 kg/m 3 ΔP = 50 kPa, c = 0.5 kg/m
0
0.4
0.8
1.2
1.6
2
i (–)
Fig. 8. The relationship between normalized resistance coefficient and blocking index.
between K/Kc and i can be regressed to a continuously exponential function as K ¼ 0:38 exp ð8:51iÞ Kc
index varied to a certain value, ca. 0.5, at the early period of filtration, kept at that value for a while and then suddenly dropped to be zero and kept at that value thereafter. The blocking index for 0.4 mm membrane was always larger than that for 0.2 mm membrane under the same pressure and filtration flux. The critical point at which the filtration transformed from membrane blocking to cake filtration would be occurred at a lower filtration flux or lower particle accumulation for the membrane with larger pore size or under a lower filtration pressure. The normalized resistance coefficient could be correlated to a unique function of blocking index under various operating conditions and for different membranes. From the analyses of blocking chart and resistance coefficient, the filtration flux could then be predicted by using the blocking models.
ð2Þ
The data shown in Fig. 8 indicates that the order-of-magnitudes of K/Kc for Hermia’s four blocking models (i ¼ 2, 1.5, 1 and 0, respectively) are extremely different. The quantitative expression, Eq. (2), provides us a way to estimate the filtration resistance using the membrane blocking models. Once the blocking index and resistance coefficient are related to the operating conditions, e.g., Figs. 7 and 8, the filtration flux during microfiltration can then be predicted by using the blocking models [5]. 4. Conclusions The blocking index and resistance coefficient in the ‘‘dead-end’’ microfiltration using Isopore membranes with two mean pore diameters have been analyzed by use of blocking models. The blocking chart for these membranes and 0.15 mm PMMA particles was established for discussing the effects of pore size and operating conditions on the particle fouling. The blocking
Acknowledgements The authors wish to express their sincere gratitude to the National Science Council (NSC), the Center-of-Excellence (COE) Program on Membrane Technology from the Ministry of Education (MOE), R.O.C. and the Technology Development Program for Academia (TDPA) from the Ministry of Economic Affairs (MOEA), R.O.C. for the financial supports.
References [1] J. Hermia, Constant pressure blocking filtration laws–application to power law non-Newtonian fluid, Trans. Inst. Chem. Eng., 60 (1982) 183–187. [2] K.J. Hwang and T.T. Lin, Effect of morphology of polymeric membrane on the performance of crossflow microfiltration, J. Membr. Sci., 199 (2002) 41–52. [3] C.C. Ho and A.L. Zydney, Effect of membrane morphology on the initial rate of protein fouling during microfiltration, J. Membr. Sci., 155 (1999) 261–275.
K.-J. Hwang et al. / Desalination 234 (2008) 16–23 [4] C.C. Ho and A.L. Zydney, A combined pore blockage and cake filtration model for protein fouling during microfiltration, J. Colloid Interf. Sci., 232 (2000) 389–399.
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[5] K.J. Hwang, C.Y. Liao and K.L. Tung, Analysis of particle fouling during microfiltration by use of blocking models, J. Membr. Sci., 287 (2007) 287–293.