Interaction energy evaluation of soluble microbial products (SMP) on different membrane surfaces: Role of the reconstructed membrane topology

w a t e r r e s e a r c h 4 6 ( 2 0 1 2 ) 2 6 9 3 e2 7 0 4

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Interaction energy evaluation of soluble microbial products (SMP) on different membrane surfaces: Role of the reconstructed membrane topology Lin Chen a,*, Yu Tian a,b,**, Chu-qing Cao c, Jun Zhang a, Zhi-neng Li a a

School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China c School of Mechatronics engineering, Harbin Institute of Technology, Harbin 150090, China b

article info

abstract

Article history:

Soluble microbial products (SMP), a majority of organic matter in effluents, play a key role

Received 8 November 2011

in membrane fouling. A series of filtration experiments were conducted, and demonstrated

Received in revised form

that the flux decrement rate was in order of cellulose acetate membrane (CA, 65.4%),

4 January 2012

polyvinylidene fluoride (PVDF, 47.9%) and polyether sulfones (PES, 29.2%). Results showed

Accepted 15 February 2012

that the fouling behavior of membrane should be predicted from the combined knowledge

Available online 23 February 2012

of solution chemistry, surface chemical properties and surface morphology. To better understand the interactions between the SMP and different membranes, a technique for

Keywords:

reconstructing the membrane surface topology was developed on the basis of statistical

Soluble microbial products

parameters obtained from atomic force microscopy. The interaction energy, represented

Membrane surface properties

by extended DerjaguineLandaueVerweyeOverbeek (XDLVO) potential, was calculated by

Extended DLVO theory

surface element integration, allowing exploring the interaction energy profiles for different

Surface reconstruction

surfaces and providing considerable insights into the role of such interactions on the

Interaction energy

macroscopic fouling behavior. The resulting interaction energy differed considerably from

Membrane fouling

the corresponding interaction between perfectly smooth surfaces. The great influence of protrusion on the membrane surface was to reduce the primary energy barrier height, thus rendering rough surface more favorable for deposition. An attractive energy region was immediately surrounded by each positive asperity as demonstrated in the roughnessengendered interaction energy maps. As the SMP approached closer to the membrane, they had a high probability of getting trapped in the attractive energy region, leading to a more rapid loss of flux than smooth membrane. ª 2012 Elsevier Ltd. All rights reserved.

1.

Introduction

Membrane separation technology has been widely used as an alternative method in wastewater reclamation; however, the effective application of membrane process requires the

control of membrane fouling. Soluble microbial products (SMP), a significant component of effluent organic matter, have been recognized to play an important role in membrane fouling and flux decline (Jarusutthirak and Amy, 2006; Rosenberger et al., 2006). SMP are known to adsorb at the

* Corresponding author. Tel./fax: þ86 451 86283077. ** Corresponding author. State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China. E-mail addresses: [email protected] (L. Chen), [email protected] (Y. Tian). 0043-1354/$ e see front matter ª 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2012.02.030

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solid surfaces in water, wherein the interaction between membrane surface and solute has usually been explained by pore blocking, ligand exchange reaction, charge interaction or hydrophobic interaction (Maximous et al., 2009). Numerous researchers have been concentrating on studying the governing roles of hydrophobic and charge interactions on membrane fouling, typically represented in terms of the DerjaguineLandaueVerweyeOverbeek (DLVO) theory (Ku¨hnl et al., 2010; Lee et al., 2007). More recently, Xiao et al. (2011) applied extended DLVO (XDLVO) to describe the combined effect of membrane and foulant (dextran, bovine serum albumin and humic acid) hydrophobicity and surface charge on adsorptive fouling during microfiltration. These previous studies provided a sound starting point to understand membrane fouling by solutes that can be treated as colloidal particle. However, most previous evaluation of interaction energy was conducted assuming perfectly smooth surfaces of the colloidal particle and the membranes. Instead, atomic force microcopy (AFM) scans provide considerable insight into the “roughness property” of membrane surface. Recent studies (Elimelech, 1997; Park et al., 2005) found that the surface topological properties of membranes had serious implications on membrane performance and fouling propensity. Rough surfaces fouled more easily because roughness may have an equivalent short-range effect on colloidal interactions (Bhattacharjee et al., 1998) and affect surface properties (Wong et al., 2009), such as the water contact angle, zeta potential and surface area. Darbha et al. (2010) pointed out that surface sections dominated by mean asperities (around 30 nm) and high surface coverage were more effective for colloidal deposition than areas characterized by isolated large asperities (70 nm). In light of these observations, it seemed pertinent that simple means for accurate determination of the interaction energy between SMP and membrane, including experiments and simulations, are critically required along with the consideration of membrane surface topology. In this respect, the surface element integration (SEI) (Bhattacharjee and Elimelech, 1997) of scaling technique was suitable to evaluate the interaction energy taking into account the surface curvature and shape. While the results of

these studies were encouraging, the reconstructed of membrane surface was the key issue and the role of membrane surface properties in SMP fouling was still not well understood. In this study, three types of membranes were used to describe the SMP filtration, providing experimental insight into the fouling phenomena in terms of interaction forces between macromolecules and the membrane surface. A technique of reconstructing membrane topology was proposed using information from AFM scans. Following this, the SEI technique was used to calculate the interaction energy between SMP and the reconstructed rough membrane surfaces in the framework of the XDLVO theory, shedding some light on the realistic mapping of the interaction energy. The critical flux was calculated for the SMP filtration with the combination of the XDLVO potential and the membrane topology, elucidating the important physicochemical property that influenced membrane flux behavior.

2.

Experimental section

2.1.

Microfiltration membranes

Three types of commercial membranes with cellulose acetate (CA), polyvinylidene fluoride (PVDF) and polyether sulfones (PES) were selected for the study. The membrane characteristics are listed in Table 1 (a). PVDF membrane was immersed in 75% (v/v) alcohol for ca. 2 h ensuring the membranes were sufficiently wetted and degassed. Prior to use, all membranes were soaked in deionized water for 24 h with several intermediate water changes to remove impurities or additives.

2.2.

Sampling of SMP

Activated sludge samples were obtained from a lab-scale MBR (Tian et al., 2011). The SMP sample was separated from the sludge mixed liquor by centrifugation (4000 rpm for 5 min) and a successive membrane filtration (0.45 mm, CA membrane).

Table 1 e Properties of membranes and SMP. Membrane

Manufacture

(a) Properties of membrane CA TaoYuan PVDF Millpore PES Lubitech

Foulant

Zeta potentiala (mV)

15.9 15.5 17.4

DOC (mg/L)

Zeta potential (mV)

(b) Properties of foulant SMP 6.1

17.8 

pH ¼ 6.8, temperature ¼ 20 C. a Ionic strength ¼ 10 mM NaCl.

Contact angle ( ) W/DI

W/formamide

W/diiodomethane

67.9 83.1 80.9

10.6 52.8 54.6

19.0 27.0 36.8

Contact angle ( ) W/DI

W/formamide

W/diiodomethane

37.8

23.4

41.5

Average pore size (mm)

Permeability (L/(m2 h kPa))

0.22 0.22 0.22

100.6 89.4 108.7

Ionic strength (M)

pH

0.01

6.8

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The obtained SMP was then stored in the refrigerator at 4  C, and the main characteristics of SMP are shown in Table 1 (b). The size distribution of SMP and the zeta potential trends as function of pH are clearly demonstrated in Supporting Information (SI 1).

2.3.

The interaction energy per unit area for LW, EL and AB is estimated from Eqs. (2e4) (Oss, 2006) as the function of separation distance (h): A ELW 123 ðhÞ ¼  12ph2

Fouling experiments EEL 123 ðhÞ ¼ εr ε0 kx1 x3

The fouling propensity between SMP and different membranes was conducted using a stirred dead-end cell (MSC300, Mosu Corp.) operated at room temperature (20  0.5  C). Before each experiment, deionized (DI) water was filtered through the membrane prior to the fouling experiment for 1 h to allow for membrane compaction and other unknown cause of flux decline. After stable flux was achieved, the membrane permeability was determined by measuring pure water flux over a range of applied pressure. The permeability was 100.6, 89.4 and 108.7 L/(m2 h kPa) for CA, PVDF and PES membrane, respectively. The filtration pressure was operated at 3e4 kPa to produce the same initial flux for each membrane, and the stirring speed in the cell was set at 100 rpm throughout the experiments. The operation was conducted at initial flux of 326 L/(m2 h), and permeate flux data were continuously logged using a top-loading electronic balance (BL-1200S, Setra Systems) connected to a server computer. The filtration experiments stopped when 300 mL permeate was processed.

2.4.

Analytical items

AFM (Veeco, Santa Barbara) was used to describe membrane surface topography in terms of membrane surface roughness (see SI 2). The Nanoscope control software (Version 5.30r3sr3) was adopted for image acquisition (10 mm  10 mm areas), and the following parameters associated with membrane morphology were calculated from at least 7 images for each membrane sample: average roughness (Ra), root-mean-square roughness (Rq), maximum roughness (Rm), peak count (PC ) and surface area difference (SAD). The zeta potential (x) of membrane was measured by the tangential streaming potential method (Shim et al., 2002) using the electrokinetic analyzer (SurPASS, Anton Paar). Surface tensions of SMP and membranes were determined from contact angles (Contact Angle meter, Tantec) of DI water, formamide and diiodomethane by the sessile drop on filtered lawns of SMP or on a clean membrane.

3.

Model development

3.1.

Determination of surface tension energies

The XDLVO theory (Eq. (1)) describes the total interaction energy per unit area (E ) of particle-surface in terms of Lishitzevan der Waals force (LW) energy, electrostatic force (EL) energy and acid-base (AB) interaction energy. EL AB ¼ ELW EXDLVO 123 123 þ E123 þ E123

(1)

where the subscripts 1e3 represent the membrane, water and foulant, respectively.

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(2)
2  x1 þ x23 1 ð1  cothkhÞ þ 2x1 x3 sinhkh

  h0  h AB EAB ðhÞ ¼ DG exp 123 h0 l

(3)

(4)

side of Eq. (2) is the where A ¼ 12ph20 DGLW h0 at the right-hand pffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffi rLW Hamaker constant; DGLW  rLW rLW  rLW 1 Þð 2 3 2 Þ is h0 ¼ 2ð the free LW energy per unit area between the surface; h0 is the minimum cut-off distance due to Born repulsion; rLW is the pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Lifshitzevan der Waals component; 1=k ¼ ε0 εr Rg T=ð2F2 IS Þ is the Debye length; T is the absolute temperature in Kelvin; ε0 is the permittivity of free space; εr is the dielectric constant of the bulk fluid; Rg is the gas constant; F is the Faraday’s constant; Is is the ionic strength; x1 and x3 represent the surface potentials of membrane and foulant, respectively; pffiffiffiffiffi pffiffiffiffiffi ð r 2 rþ l is the decay length of AB interaction; DGAB 1 h0ffi ¼p pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffiffiffiffiffi ffiffiffiffiffiffiffiffiffiþ2ffi pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi þ þ þ þ     Þ is r þ r3  r2 Þ þ 2 r2 ð r1 þ r3  r2 Þ  2ð r1 r3  r 1 3 the acid-base free energy per unit area between solute and membrane surface at contact; rþ is the electron acceptor, and r is the electron donor component. þ  The parameters of rLW i ; ri ; ri (i ¼ 1, 3) can be calculated from YoungeDupre´ equation (Eq. (5)) (Oss, 2006) after measuring contact angle data (q) for three probe liquids with þ  known surface tension parameters ðrLW pl ; rpl ; rpl Þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffi þ LW  r ð1 þ cos qÞrpl ¼ 2 rLW rþ i rpl þ i rpl þ i rpl

3.2.

(5)

Roughness simulation and surface reconstruction

In order to avoid a rigorous computation of the interaction energy between the complexity surface and SMP, a mathematical methodology for the reconstruction of the membrane surface was developed using statistical parameters derived from AFM analyses. For simplicity and conformity to the interaction energy model, the simulated surface was constructed of a flat plate, interrupted by hemispherical protrusions and depressions forming the peaks and valleys. Given the histogram of asperity (see SI 3), the membrane asperities were assumed on the basis of a normal distribution ( f(x), x ˛ [Rm/2, Rm/2]), which chose the Ra as the mean value and the Rq as the standard deviation. Considering the same distribution of asperity number (n) and asperity, the proportion of PC can be calculated by integrating the area with jxj higher than the standard deviation and then dividing the total curve area. The value of n can be obtained by diving the AFM-measured PC with the PC proportion. The parameters of standard deviation and PC were adjusted, then the previous steps were repeated to make the simulated SAD agree with the corresponding AFM-measured SAD, and subject to the constraint that the AFM-derived Ra and Rm were also well approximated. Finally, the complexity of surface morphology was modeled by random arrangement of simple elementary asperities.

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3.3. Calculation of the sphere-rough surface interaction energy The basic governing equation of SEI considered the total interaction energy by integrating the interaction energy per unit area between two surfaces over the actual surfaces (Bhattacharjee and Elimelech, 1997; Vrijenhoek et al., 2001). ZZ ðhÞdA (6) UðSÞ ¼ EXDLVO 123 where U is the interaction energy between the particle and the rough surface, S is the distance of closest approach between the sphere and the mean-plane of the surface and dA is the projected differential surface area of the particles. To provide a narrative description of Eq. (6), the following discussion was conducted on a model of the rough surface (see SI 4), which contained a distribution of hemispherical protrusions and depressions of different radius interacting with a smooth sphere of radius ur located at a veridical distance S. A Cartesian coordinate was employed to evaluate the surface integral with the origin located at one angle of mean-plane, thus the center of the sphere and ith asperity can be fixed with location coordinates of (ux, uy) and (vi,x, vi,y), respectively. Noticeably, the surface integral was calculated over the regions of asperities that overlapped with the projected area of sphere in the energy computation. For each location of the sphere center, the numbers of asperity and regions of each asperity that intersected with the projected area of the sphere were confined by the following inequality:

2

2  

2 vi;x  ux þ vi;y  uy < vi;r  þ ur

(7)

where jvi,rj and ur represent the radius of the ith asperity and sphere, respectively. With respect to the vertical distance h between a surface element on the sphere and the region of the membrane surface, it can be directly determined by:

h ¼ S þ ur 

ffi  qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  vi;r  vi;r 2 v2

vi;r qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  u2r  u2 ðri > 0 for protrusion; ri < 0 for depressionÞ

where v ¼

(8)

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðwx  vi;x Þ2 þ ðwy  vi;y Þ2 is the radial distance of

the asperity surface from the center of the asperity; qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u ¼ ðwx  ux Þ2 þ ðwy  uy Þ2 is the radial distance of the

sphere surface; (wx, wy) is the coordinate of the spherical surface under consideration, depending on the “meshgrid” function relative to the center of sphere. Substituting Eqs. (1) and (7,8) into Eq. (6) yielded the interaction energy between the spherical particle and the membrane surface, and then shifting the horizontal location of the sphere center with respect to the rough membrane surface produced a map of the interaction energy.

4.

Results and discussion

4.1.

Membrane fouling and flux decline by SMP

SMP sample derived from MBR was tested with CA, PVDF and PES membranes in a stirred cell with similar initial flux. The flux decline trends by different membranes are shown in SI 5, and the observed differences in fouling rates are statistically significant at 95% confidence level. The CA membrane exhibited the fastest diminishing rate of flux among the three types of membranes. The flux of CA membrane was found to drop by 65.4% when 300 mL of permeate was collected, while the PVDF and PES membranes resulted in only ca. 47.9% and 29.2% decrement, respectively. Since the same mixed liquor was filtered and similar initial flux was applied, the rate of permeability decline could be much dependent on the characteristics of membrane surface. The hydrophilic/hydrophobic interaction between the SMP and membrane may be of much importance since hydrophobic substances demonstrated stronger interaction with hydrophobic membrane, which was supported by previous researches (Maximous et al., 2009; Van der Bruggen et al., 2004). Hydrophobic interaction is the proclivity for aggregation of apolar of partly apolar chains, molecules or particles when immersed in water; while hydrophilic interaction is the proclivity of strongly polar chains, molecules or particles for repelling each other (Van Oss, 1995). Table 2 shows the calculated surface tension parameters and free energy of cohesion for each membrane and SMP (diameter 100 nm). The D50 (the 50 percentile of the particle size distribution) of 100 nm was adopted for the energy calculation, which was somewhat random. Anyway, the influence of diameter on the magnitude of LW, EL and AB interaction energies was observed in the same relative magnitude, thus the comparability of the different interactions between the different

Table 2 e Surface tension parameters and surface free energies at the separation distance of h0 (0.157 ± 0.009 nm). gþ

gLW

g

gAB

gTOT

(a) Surface tension parameters and the free of cohesion (mJ/m2) for each membrane and SMP CA 48.07 3.48 2.67 6.09 54.16 PVDF 45.40 0.12 2.23 1.03 46.43 PES 41.18 0.19 3.91 1.72 42.90 SMP 38.87 1.52 34.86 14.56 53.43

CA DGLW 123

DGAB 123

DGLW 121

DGAB 121

DGEL 121

10.25 8.56 6.12 4.90

43.51 66.90 56.70 13.04

0.058 0.055 0.069 0.072

PVDF DGEL 123

DGLW 123

DGAB 123

PES DGEL 123

DGLW 123

DGAB 123

DGEL 123

(b) Surface free energy parameters (mJ/m2) for the adhesion of SMP on the membrane surface SMP 7.09 20.63 0.065 6.48 19.11 0.063

5.47

15.57

0.071

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membranes was not affected by the choice of the diameter. P The ionic strength was determined as I ¼ 1=2 Ci Z2i (Ci is the molar concentration of the ith ion and Zi is its charge) (Sawyer et al., 2003), resulting in an approximate value of 0.01 M, which was in accordance with the ionic strength given by Wang et al. (1998). The hydrophobicity of the membrane determined the magnitude of hydrophilic repulsion or hydrophobic attraction that affected the interactions with SMP. All the membranes exhibited hydrophobic characteristics (PVDF > PES > CA), while the SMP presented hydrophilic nature. The free energy of cohesion is the interaction free energy (per unit area) when two surfaces of the same material are immersed in water and brought into contact, providing a quantitative insight regarding the hydrophobicity/hydrophilicity of the membrane and solute (Brant and Childress, 2002). The free energy of PES membrane (20.97 mJ/m2) was lower than that of PVDF (25.53 mJ/m2) and CA (27.66 mJ/m2) membranes with respect to SMP in an aquatic environment, suggesting PES has the lowest SMP fouling tendency in terms of adsorption onto the membrane surface. Significant difference in fouling rate was detected between CA and PVDF membranes regardless of the similar free energy. In terms of Zeta potentials analysis, the membrane with a more negative zeta potential would exhibit higher electrostatic double layer repulsion according to the classical DLVO theory (Vrijenhoek et al., 2001), and thus be more fouling resistant to negatively charged solutes. However, the experimental fouling data consistently showed that the CA fouled more severely than PVDF and PES membranes. It seemed that the characteristics of hydrophobicity and Zeta potential may not be sufficient to predict the effect of membrane property on membrane fouling. The actual geometry of the membrane morphology was another important aspect to be considered. Surface roughness produced tangential colloidal forces which can immobilize colloidal particles on the membrane surface (Carnie et al., 2005). Large-scale surface roughness, of the same order of magnitude as the SMP interacting with the surface, significantly increased the rate of SMP attachment through providing a larger surface area and greater contact opportunities for SMP with the membrane surface. Additionally, as the permeation rate was proportional to the thickness of the active (skin) layer, the bottom of a “valley” presented the “path-of-least resistance” to permeating water (Vrijenhoek et al., 2001). These effects of surface roughness resulted in enhanced attachment of SMP onto the membrane surface, and hence, more severe fouling. As shown in SI 2, both of PVDF and PES exhibited relatively fewer but larger protuberances, compared to the CA with abundant but small asperities. Also, the roughness feature of CA had much smaller peak-to-peak separation distance than that of PVDF and PES. Hence, for a rough membrane (CA), SMP were preferentially transported onto the membrane surface. The surface quickly became clogged with multiple layers of densely packed foulants, leading to an increasing flow resistance and a more rapid flux reduction. Regardless, it can be concluded that the relative fouling behavior of the three commercial membranes should be qualitatively predicted from the combined knowledge of physical surface morphology, surface chemical properties and solution chemistry. Given the irregular morphology of the

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membrane surface, it was really hard to calculate the total interaction between SMP and the actual membrane surface. In the following section, a mathematical methodology for the reconstruction of membrane surface was developed, and SEI technique was used to evaluate the extended DLVO interactions between SMP and the reconstructed rough membranes.

4.2. Interaction energy barrier between SMP and membrane surfaces Fig. 1 demonstrates the reconstructed topologies of the three types of membranes, and Table 3 lists the statistical roughness parameters obtained from the AFM roughness analysis and the model rough surfaces. It clearly showed minor deviations (<1%) from the measured SAD, Ra and Rm values but noticeable deviations from Rq (<25%) and PC, indicating a good match between the statistical roughness parameters of the model surfaces and those of the real membranes. The subsequent calculations of the XDLVO interaction energies between a spherical particle and the three types of rough membranes were performed based on these simulated topologies. Fig. 2a illustrates the dependence of the interaction energy between SMP and different smooth membranes on the separation distance. Noticeably, both LW energy and AB energy were attractive and played important roles at short-range scale (<5 nm), while EL energy was repulsive and long-ranged (>5 nm) which can be attributed to the negatively charged of surfaces and a thick electrical double layer. At even larger separation, the XDLVO interaction became attractive, and a secondary minimum existed at a separation distance of 15 nm. Additionally, the interaction energy decreased from the primary energy barrier to zero over a distance of about 12 nm for all surfaces, which was also true even a positive asperity prevented SMP from attaching to the mean-plane of the membrane surface (as shown in Fig. 2b). The combination of these three energies determined the SMP-membrane interactions as the SMP approaching to the mean-plane. At smooth surface, the primary energy barrier was existed at a separation distance of 3e4 nm from the mean-plane, and the value of primary energy barrier was in the order of 8.36, 8.75, 12.64 kT for CA, PVDF and PES membranes, respectively. Clearly, SMP was subject to the greatest repulsive interaction with PES membrane, which may inhibit the initial deposition of the foulant. CA and PVDF membranes exhibited a similar primary energy barrier but a greatly different fouling rate, which might be explained by the interaction profiles between SMP and the rough membrane surface as provided in Fig. 2(bec) and SI 6. In one extreme, the interaction between SMP and a single, positive asperity produced an interaction energy which was much smaller in magnitude than the calculated sphereeplate interaction energy profile (Fig. 2b). The respective values of primary energy barrier reduced to 4.57, 3.79 and 7.62 kT for positive CA, PVDF and PES asperities, compared with 8.32e12.64 kT for the corresponding planar surface. The existence of asperities counteracted the repulsive interaction energy due to the zeta potential; concomitantly, the large positive asperity physically prevented the particle from attaining a separation distance of less than 81 nm (CA), 52 nm

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Fig. 1 e Representative image of simulated roughness membrane surface: (a) CA; (b) PVDF and (c) PES.

(PVDF) and 98 nm (PES) from the mean-plane. In another extreme, the primary energy barrier reached up to 30%e96% larger than the sphereeplate interaction energy profile if SMP penetrated into a single, negative asperity (Fig. 2c). The occurrence of the enhanced interaction energy might be

attributed to the fact that the effective separation distance between sphere and negative asperity surface was nearly uniform and thus much smaller than the separation distance between sphere and smooth surface. Since the number of positive asperity was much higher than that of negative

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Table 3 e Measured and simulated membrane statistical roughness parameters (Hemispheres). Morphological parameter

unit

CA a

Membrane area Average roughness RMS roughness Maximum roughness Number of asperities Peak count Surface area difference

2

mm nm nm mm no. no. %

PVDF b

PES

AFM

SIM

AFM

SIM

AFM

SIM

100 104.2 160.4 1.081 N/Ac 140 45.96

100 104.2 200.4 1.082 347 140 44.75

100 262.3 338.1 2.715 N/A 28 75.92

100 262.3 417.5 2.716 85 39 76.11

100 178.6 244.1 1.623 N/A 13 17.95

100 178.6 302.0 1.624 48 22 17.86

a Surface area scanned and analyzed by AFM. b Surface area reconstructed using hemispherical asperities. c The number of asperities in AFM surface scans can’t be determined.

asperity and the SMP radius was larger than most of the negative asperity sizes, it was reasonably assumed that the number of interactions falling into the negative asperity was small. Additionally, Fig. 3 evaluates the influence of asperity radius on the energy barrier as a single asperity is placed right under the incoming SMP particle. Similar results can be observed for these three membranes. It clearly showed that,

for the median radius of SMP (50 nm), a critical asperity radius (around 14 nm) resulted in the highest reduction of the energy barrier. For the larger asperity radius, the energy barrier increased since the XDLVO interaction was approximately proportional to vir $ur =ðvir þ ur Þ. With respect to the smaller asperity radius, the asperity size was not large enough to lower the SMP-planar interaction, which accounted for the largest part of the energy barrier. Therefore, the complete

Fig. 2 e SEI model predictions of interaction energy profiles for the SMP (radius [ 50 nm) and different simulated membrane surfaces: (a) smooth surface, (b) positive asperity and (c) negative asperity.

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Fig. 3 e Primary energy barrier between SMP and rough surface with varying asperity radius.

understanding of the roughness distribution was required to determine its impact on the energy barrier. The simulations described above were then repeated for 50 additional randomly selected (x, y) locations, and the primary energy barrier for a given membrane was averaged. For all the surfaces, the presence of roughness features reduced the interaction energy barrier compared to that of smooth surface, wherein the averaged primary energy barriers were 4.35, 6.38 and 9.14 kT for CA, PVDF and PES membranes, respectively. The practical implication for these results was that the rough property of membrane surface would tend to promote fouling or, at least, reduce fouling resistanceregardless of the chemical properties of a membrane material. To provide a thorough understanding of the interaction between SMP and reconstructed membrane surface, interaction energy map was performed at a series of separation distances and over a range of (x, y) locations.

4.3. Interaction energy map between SMP and different membrane surfaces The calculation and drawing of the interaction energy map at a fixed separation distance were conducted by varying the horizontal coordinate (x, y) of the sphere center in a rasterized pattern (the distance between the sphere center ¼ 50 nm). In this study, five different separation distances, including 1, 3.5, 10, 25 and 75 nm from the mean-plane, were performed for the three simulated membrane surface, as shown in Fig. 4. Two different superimposed color maps with “jet” style were adopted to show the magnitude of the interaction energy, one for the 25e75 nm separation distance and another for the 1e10 nm separation distance. Areas filled with red, lavender and blue represented the attractive, neutral and repulsive interaction energy, respectively. The overlap between the SMP and membrane asperity can’t be avoided as the SMP approaching to the mean-plane. Given the physically impossibility for SMP to occupy the membrane asperities, such an

overlapped situation was simply handled by avoiding any energy computation, and the overlapped area was depicted in gray. Noticeably, the XDLVO interaction energy between the SMP and a smooth membrane surface was significantly altered by membrane surface topology (roughness), and the most prominent feature was that the overlapped regions were surrounded by navy-color contours. Fig. 4 (a1-a5) illustrates the interaction energy maps for a simulated CA membrane at different separation distances ranging from 75 nm down to 1 nm. The simulated CA surface was composed of abundant asperities, and the radius of some asperities was large compared with the median radius of SMP (50 nm). At a large separation distance of 75 nm, the entire membrane surface presented extremely weak attractive interaction energy (0.16 kT). Simultaneously, some interesting phenomena can be observed from the careful inspection of figure. The SMP firstly felt an elevated repulsive energy such as at the location around (1500, 1200) (Fig. 4 (a-1)), and then these locations were mapped in gray due to some physical overlap of the SMP with the surface protrusion as shown in Fig. 4 (a2-a5). Another interesting point was that the gray regions were surrounded by blue contours, suggesting the interaction energy in these contours were highly attractive since the SMP colloid nearly contacted with the positive asperity. Some repulsive regions were existed around the attractive contours, which can be explained by the XDLVO theory that the primary minimum immediately follows the primary energy barrier. Additionally, it should be mentioned here that some repulsive regions around the attractive contours can’t be reflected during simulation due to the adopted 50 nm of sphere centerecenter distance during simulation and the short-range (<5 nm) between the primary minimum and the primary energy barrier. The membrane surface demonstrated an increased attractive energy (0.86 kT) as the SMP approached to 25 nm above the mean-plane, while the surface presented an averaged repulsive energy (0.55 kT) as the SMP was further brought to 10 nm from the surface. These phenomena clearly suggested that as the SMP shifted from 75 nm to 10 nm from the membrane surface, the SMP with enough convective energy pushed through the secondary minimum and then experienced electrostatic repulsion from the surfaces in closest proximity. There were also some highly attractive contours surrounded by the physical overlap of the SMP with the positive asperities, thus the SMP might be easily trapped into the energy minimum regions. The CA membrane exhibited strong repulsive interaction energy (6.73 kT) as the SMP arrived at a separation distance of 3.5 nm (Fig. 4 (a-4)). Regarding smooth membrane, no membrane fouling could be observed theoretically if the interaction energy barrier was higher than the hydraulic drag energy. However, the interaction energy in some isolated regions was found to be negligible (mapped in lavender) due to the existence of negative asperity on the surface; simultaneously, the attractive regions around the positive asperity were obviously increased due to the increment of overlapped surface. The existence of these asperities not only reduced the interaction energy barrier but also intensified the SMP deposition, leading to a more rapid flux decrement and severer membrane fouling.

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Fig. 4 e SEI model predictions of interaction energy map for the SMP (radius [ 50 nm) and three different simulated membranes: (a) CA, (b) PVDF and (c) PES at a series of separation distances. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Finally, as SMP was brought to 1 nm from the mean-plane (Fig. 4 (a-5)), the entire membrane surface presented a fairly uniform attractive energy (381.29 kT) for the SMP, interspersed with an increased amount of overlapped regions and a few of valleys. The five energy maps for CA membrane clearly demonstrated the general trends of interaction energy conforming to the XDLVO theory, and also showed the great changes of interaction energy due to the existence of asperities. As the SMP closed to the rough surface, it may simply be drawn toward the regions with lower interaction energy. Under the condition of cross-flow membrane filtration, SMP deposited on the pit wall of rough membranes might be protected from cross-flow shear due to the large positive asperities and the small peak-to-peak separation distance, and thus initial SMP fouling may be enhanced. Fig. 4 (b1-b5) illustrates the corresponding interaction energy maps for the simulated PVDF membrane. As the SMP was brought from 75 nm to 10 nm from the mean-plane, the interaction energy exhibited the general trend of neutrally zero (D ¼ 75 nm, 0.15 kT), slight attraction (D ¼ 25 nm, 0.78 kT), slight repulsion (D ¼ 10 nm, 0.17 kT), elevated repulsion (D ¼ 3.5 nm, 7.41 kT) and strong attraction (D ¼ 1 nm, 350.75 kT). There were also some overlaps of the SMP with the positive asperities on the PVDF surface as indicated by the gray-mapped areas. However, the most striking differences from the CA membrane were the 100 lower of peak count and 31% higher of surface area difference. The number of asperities on the PVDF membrane was obviously decreased, resulting in a reduced overlapped areas and local attractive contours. On the other hand, since the increased surface area difference was companied by significant increment of asperity size, the primary energy barrier was only subtly decreased on the basis of asperity radiusenergy barrier analysis (see Fig. 3). As the SMP approached closer to the membrane surface, its lateral movement was limited by the presence of the peaks, and thus, the SMP would attach to the sidewalls of the asperities. Compared with the CA membrane, the PVDF membrane exhibited the larger peak-to-peak separation distance, less energy barrier reduction and lower attractive contours around the protrusions, indicating the decreased fouling rate of PVDF membrane from another perspective. The interaction energy maps for the simulated PES membrane at different separation distances from 75 nm to 1 nm are depicted in Fig. 4 (c1-c5), exhibiting a similar tendency as the simulated PVDF membrane. However, some noticeable differences can still be found between PVDF and PES membranes, attributing to the surface topology and physicochemical property. Compared with other two membranes, the PES membrane was much smoother with the least asperities, leading to relatively smaller attractive regions around the positive asperities. As the SMP approaching to the mean-plane, the probability of SMP trapped into the lowerenergy valleys significantly decreased. Additionally, the PES membrane showed the higher primary energy barrier than PVDF due to its own surface properties, becoming much fouling resistant. As clearly be presented in Fig. 4 (c4), the interaction energy reached up to 12.43 kT for PES membrane at the separation distance of 3.5 nm, which was 5.70 kT and 5.02 kT higher than that for CA and PVDF membranes,

respectively. Hence, under the same hydraulic condition, the PES exhibited the lowest fouling potential, with 18.7% lower of flux reduction compared with PVDF membrane. As stated above, the energy barrier was significantly reduced by the presence of asperity. Since the SMP deposition was highly dependent on the height of the energy barrier, the SMP fouling would occur mainly near asperities where the energy barrier was low. Furthermore, the membrane fouling would be enhanced by surface roughness, provided that the asperity and peak-to-peak separation distance were not too large to decrease the primary energy barrier and increase the contact probability between the SMP and membrane surface.

4.4.

Implication for membrane process

Generally, the issue of modeling colloidal deposition was addressed as a two-step process (Adomeit and Renz, 1996): first colloid was transported by the motions of the flow toward surface, and second, in the immediate vicinity of the surface, the forces between the incoming colloid and the surface were determined with the XDLVO theory. Critical flux defined as a condition that the hydrodynamic drag force transporting colloids from the bulk to the membrane surface was roughly balanced by repulsive interaction forces (Lee and Elimelech, 2006). Accurate assessment and characterization of membrane-SMP interactions may allow for optimization of repulsive membrane-SMP interactions to operate under appropriate operating conditions, resulting in reduced membrane fouling. Using the measured SMP and membrane properties, it was possible to determine the maximum critical flux (vc) for a membrane process through the modified Bowen and Sharif method (Richard Bowen and Sharif, 1998). A correction factor (Urough/Usmooth) was introduced to take into account the surface roughness as given in Eq. (9), serving as a control strategy for membrane fouling. jvc j ¼

FLW þ FEL þ FAB Urough $ ð6pmur ÞfH Usmooth

(9)

where FLW is the van der Waals force, FEL is the electrostatic repulsive force, FAB is the acid-base force, m is the solution viscosity, fH is the hydrodynamic correction factor (Wang et al., 2005), Urough and Usmooth are the total interaction energy of the simulated rough surface and smooth surface, respectively. Note that FLW, FEL, FAB, Urough and Usmooth must be obtained at the same separation distance between the sphere and the mean-plane. Fig. 5 demonstrates the relationship of critical flux against the particle-membrane separation distance for the SMP and different membranes, wherein Fig. 5(a) and Fig. 5(b) represent the critical flux for the smooth surface and rough surface, respectively. There was a maximum in the critical flux curves as a function of separation distance. If a flux less than this maximum critical velocity was applied, then the hydrodynamic force on the SMP would be balanced by the repulsive electrostatic force before the SMP contacted with the membrane surface. It can be seen from Fig. 5(a) that the distance at which this occurred was 3e9 nm deviations from the mean-plane, and slight difference of the critical flux

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Fig. 5 e Critical velocity as a function of separation distance for different membranes: (a) smooth membrane surface and (b) rough membrane surface.

curves was observed between the CA and PVDF membranes. However, the magnitude of critical flux was obviously decreased with the incorporation of roughness effect (Fig. 5(b)). At a distance of 4 nm, approximate 11.0% and 6.1% reduction of critical flux were obtained for PVDF and PES membranes, respectively. With respect to the CA membrane, the curve shape was significantly changed with more than 70% decrement of critical flux, and the controllable balance region was existed in a separation of 6e8 nm from the meanplane. Great differences of the critical flux were found between the PVDF and PES membranes from the aspects of flux magnitude, tendency and curve shape. These observations could explain the results of fouling experiments to some extent: the CA membrane operated above critical flux resulted in sever membrane fouling while slight fouling occurred for the PES membrane operating below the critical flux. Regardless of the present results, further detailed investigation should be performed. Firstly, additional experimental support was required. The experimental data regarding the deposition of SMP were rare, and it would be much worth considering a more detailed experimental approach (e.g., a roughness controlled surface with protruding spherical asperities (Chen et al., 2009)). Then, the numerical deposition was much dependent on the particle size: larger particle had a higher tendency to attach to the rough surface. The introduction of surface roughness has been shown to reproduce nonzero deposition rate, which was in agreement with the experimental observation (Cerovic et al., 2009). The determination of critical flux might be investigated in future calculation within an acceptable fouling rate.

5.

Conclusions

Compared with PVDF and PES membranes, the CA membrane exhibited the fastest fouling potential during the SMP filtration, which can be qualitatively predicted from the combined knowledge of physical surface morphology, surface chemical properties and solution chemistry. Simulations were conducted to evaluate the interfacial interactions between SMP and reconstructed membrane surfaces via an XDLVO potential. The resulting interaction energy was changed

considerably by membrane surface topology, particularly near the repulsive interaction energy barrier. For the SMP interacting with a flat plate, the interaction energy was substantially reduced in the presence of positive asperity; whereas the primary energy barrier was much larger if SMP penetrated into a single, negative asperity. The magnitude of XDLVO potential was on average decreased by surface roughness, since the number of positive asperity was much higher than that of negative asperity and the SMP radius was larger than most of the negative asperity sizes. The roughnessengendered interaction energy map clearly showed that an attractive energy contour was immediately surrounded by each positive asperity, suggesting that SMP had a high probability of getting trapped in the attractive energy regions as approaching to the membrane surface. Given the surface morphology, a more rapid loss of flux and sever membrane fouling would be observed in the CA membrane filtration of SMP solution. Additionally, the accurate assessment of membrane-SMP interactions allowed identification of critical flux for effective membrane process operation, resulting in more than 70%, 11% and 6% decrement of critical flux for CA, PVDF and PES membranes with the incorporation of roughness effect.

Acknowledgments This study was supported by the National High-tech R&D Program (863 Program) of China (No. 2009AA064704), the National Natural Science Fund of China (No. 50978071) and the State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology (No. 2011DX01). The authors also appreciate the National Innovation Team supported by the National Science Foundation of China (No. 50821002).

Appendix. Supplementary material Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.watres.2012.02.030.

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references

Adomeit, P., Renz, U., 1996. Deposition of fine particles from a turbulent liquid flow: experiments and numerical predictions. Chemical Engineering Science 51, 3491e3503. Bhattacharjee, S., Elimelech, M., 1997. Surface element integration: a novel technique for evaluation of DLVO interaction between a particle and a flat plate. Journal of Colloid and Interface Science 193, 273e285. Bhattacharjee, S., Ko, C.H., Elimelech, M., 1998. DLVO interaction between rough surfaces. Langmuir 14, 3365e3375. Brant, J.A., Childress, A.E., 2002. Assessing short-range membrane-colloid interactions using surface energetics. Journal of Membrane Science 203, 257e273. Carnie, S.L., Chan, D.Y.C., Lewis, C., Manica, R., Dagastine, R.R., 2005. Measurement of dynamical forces between deformable drops using the atomic force microscope. I. Theory. Langmuir 21, 2912e2922. Cerovic, L., Lefe`vre, G., Jaubertie, A., Fe´doroff, M., Milonjic, S., 2009. Deposition of hematite particles on polypropylene walls in dynamic conditions. Journal of Colloid and Interface Science 330, 284e291. Chen, G., Beving, D.E., Bedi, R.S., Yan, Y.S., Walker, S.L., 2009. Initial bacterial deposition on bare and zeolite-coated aluminum alloy and stainless steel. Langmuir 25, 1620e1626. Darbha, G.K., Scha¨fer, T., Heberling, F., Lu¨ttge, A., Fischer, C., 2010. Retention of latex colloids on calcite as a function of surface roughness and topography. Langmuir 26, 4743e4752. Elimelech, M., 1997. Role of membrane surface morphology in colloidal fouling of cellulose acetate and composite aromatic polyamide reverse osmosis membranes. Journal of Membrane Science 127, 101e109. Jarusutthirak, C., Amy, G., 2006. Role of soluble microbial products (SMP) in membrane fouling and flux decline. Environmental Science and Technology 40, 969e974. Ku¨hnl, W., Piry, A., Kaufmann, V., Grein, T., Ripperger, S., Kulozik, U., 2010. Impact of colloidal interactions on the flux in cross-flow microfiltration of milk at different pH values: a surface energy approach. Journal of Membrane Science 352, 107e115. Lee, S., Elimelech, M., 2006. Relating organic fouling of reverse osmosis membranes to intermolecular adhesion forces. Environmental Science and Technology 40, 980e987. Lee, S., Kim, S., Cho, J., Hoek, E.M.V., 2007. Natural organic matter fouling due to foulant-membrane physicochemical interactions. Desalination 202, 377e384. Maximous, N., Nakhla, G., Wan, W., 2009. Comparative assessment of hydrophobic and hydrophilic membrane fouling in wastewater applications. Journal of Membrane Science 339, 93e99. Oss, C.J.v., 2006. Interfacial Forces in Aqueous Media, second ed. Taylor & Francis, Boca Raton.

Park, N., Kwon, B., Kim, I.S., Cho, J., 2005. Biofouling potential of various NF membranes with respect to bacteria and their soluble microbial products (SMP): characterizations, flux decline, and transport parameters. Journal of Membrane Science 258, 43e54. Richard Bowen, W., Sharif, A.O., 1998. Hydrodynamic and colloidal interactions effects on the rejection of a particle larger than a pore in microfiltration and ultrafiltration membranes. Chemical Engineering Science 53, 879e890. Rosenberger, S., Laabs, C., Lesjean, B., Gnirss, R., Amy, G., Jekel, M., Schrotter, J.C., 2006. Impact of colloidal and soluble organic material on membrane performance in membrane bioreactors for municipal wastewater treatment. Water Research 40, 710e720. Sawyer, C.N., McCarty, P.L., Parkin, G.F., 2003. Chemistry for Environmental Engineering and Science. McGraw-Hill, New York. Shim, Y., Lee, H.J., Lee, S., Moon, S.H., Cho, J., 2002. Effects of natural organic matter and ionic species on membrane surface charge. Environmental Science and Technology 36, 3864e3871. Tian, Y., Chen, L., Jiang, T., 2011. Characterization and modeling of the soluble microbial products in membrane bioreactor. Separation and Purification Technology 76, 316e324. Van der Bruggen, B., Kim, J.H., DiGiano, F.A., Geens, J., Vandecasteele, C., 2004. Influence of MF pretreatment on NF performance for aqueous solutions containing particles and an organic foulant. Separation and Purification Technology 36, 203e213. Van Oss, C., 1995. Hydrophobic, hydrophilic and other interactions in epitopeeparatope binding. Molecular Immunology 32, 199e211. Vrijenhoek, E.M., Hong, S., Elimelech, M., 2001. Influence of membrane surface properties on initial rate of colloidal fouling of reverse osmosis and nanofiltration membranes. Journal of Membrane Science 188, 115e128. Wang, J., Huang, C., Allen, H.E., Takiyama, L.R., Poesponegoro, I., Poesponegoro, H., Pirestani, D., 1998. Acid characteristics of dissolved organic matter in wastewater. Water Environment Research 70, 1041e1048. Wang, S., Guillen, G., Hoek, E.M.V., 2005. Direct observation of microbial adhesion to membranes. Environmental Science and Technology 39, 6461e6469. Wong, P.C.Y., Kwon, Y.-N., Criddle, C.S., 2009. Use of atomic force microscopy and fractal geometry to characterize the roughness of nano-, micro-, and ultrafiltration membranes. Journal of Membrane Science 340, 117e132. Xiao, K., Wang, X., Huang, X., Waite, T.D., Wen, V., 2011. Combined effect of membrane and foulant hydrophobicity and surface charge on adsorptive fouling during microfiltration. Journal of Membrane Science 373, 140e151.