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Quantitative assessment of interfacial interactions with rough membrane surface and its implications for membrane selection and fabrication in a MBR
Bioresource Technology 179 (2015) 367–372
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Quantitative assessment of interfacial interactions with rough membrane surface and its implications for membrane selection and fabrication in a MBR Jianrong Chen a, Rongwu Mei b, Liguo Shen a, Linxian Ding a, Yiming He c, Hongjun Lin a,⇑, Huachang Hong a,1 a
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, PR China Environmental Science Research and Design Institute of Zhejiang Province, Hangzhou 310007, PR China c Department of Materials Physics, Zhejiang Normal University, Jinhua 321004, PR China b
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
Interfacial interactions with rough
surface were quantitatively assessed. Interactions were significantly
affected by roughness scale and foulant size. Existence of a critical range of roughness scale for fouling mitigation was revealed. Implications for membrane selection and fabrication in MBRs were provided.
a r t i c l e
i n f o
a b s t r a c t
Article history: Received 20 September 2014 Received in revised form 12 December 2014 Accepted 15 December 2014 Available online 23 December 2014
The interfacial interactions between a foulant particle and rough membrane surface in a submerged membrane bioreactor (MBR) were quantitatively assessed by using a new-developed method. It was found that the profile of total interaction versus separation distance was complicated. There were an energy barrier and two negative energy ranges in the profile. Further analysis showed that roughness scale significantly affected the strength and properties of interfacial interactions. It was revealed that there existed a critical range of roughness scale within which the total energy in the separation distance ranged from 0 to several nanometers was continually repulsive. Decrease in foulant size would increase the strength of specific interaction energy, but did not change the existence of a critical roughness scale range. These findings suggested the possibility to ‘‘tailor’’ membrane surface morphology for membrane fouling mitigation, and thus gave significant implications for membrane selection and fabrication in MBRs. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Membrane bioreactor Membrane fouling Surface interaction Rough surface Wastewater treatment
1. Introduction While membrane bioreactor (MBR) technology has gained its popularity in industrial and municipal wastewater treatment due ⇑ Corresponding author. Tel.: +86 579 82282273. E-mail addresses: [email protected] (H. Hong). 1 Tel.: +86 13967477601.
(H.
Lin),
http://dx.doi.org/10.1016/j.biortech.2014.12.055 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
[email protected]
to its significant merits over some other technologies (Santos and Judd, 2010; Dereli et al., 2012; Lin et al., 2012), membrane fouling is one of the biggest problems impeding its more widespread applications (Wang et al., 2011; Chen et al., 2012b; Su et al., 2013; Lin et al., 2014b). Membrane fouling in MBRs was related to the interactions between membrane and sludge foulants (Wang et al., 2011; Chen et al., 2012b; Lin et al., 2014b). The interfacial interactions directly
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determined the processes of foulant adhesion and cake layer formation (van Oss, 1997; Hong et al., 2013; Wang et al., 2013), which were considered as the main causes of membrane fouling (Chen et al., 2012a; Zhang et al., 2013). Thus, quantitative assessment of these interactions is essential to better understand and resolve the membrane fouling problem. The interfacial interactions between a sludge foulant and membrane surface can be generally assessed within the framework of the extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) theory (van Oss, 1995, 1997). XDLVO theory provides a method to quantitatively analyze three types of interaction energies between two infinite parallel flat plates (van Oss, 1995). However, as a general knowledge, both of sludge foulant and membrane surface are not infinite flat. Sludge foulant is generally assumed to be spherical (Bhattacharjee and Elimelech, 1997; Hoek and Agarwal, 2006; Hong et al., 2013), and almost all the commercial membranes have significantly rough surface (Hoek et al., 2003; Mahendran et al., 2011; Lin et al., 2014a). Therefore, conventional methods in XDLVO theory cannot calculate the interfacial interactions between a particle and a rough surface. This situation calls for development of a new method to quantitatively evaluate the interfacial interactions with the rough surface. For a given MBR system, membrane fouling is directly determined by the applied membrane. As the characteristics of the optional membranes in MBRs vary remarkably, selecting a suitable membrane is of primary importance for membrane fouling control and application of MBRs. The criteria of membrane selection should be related to the bulk properties and surface morphology of the membranes (Vaidya et al., 1992; Pearce, 2007). It is no doubt that the suitable membranes used in MBRs should have the chemical, thermal and mechanical integrity of the bulk properties (Santos and Judd, 2010; Lin et al., 2013). The surface morphology is generally characterized by surface roughness. Some studies reported that adhesion of bacteria cells to a surface would be improved with the increase in the surface roughness (Charman et al., 2009; Giraldez et al., 2010), whereas, some other studies reported the opposite results (Ivanova et al., 2010; Singh et al., 2011). No explanation of these findings has been provided. It can be seen from the above analyses that, there are no definite conclusions drawn regarding the effects of surface morphology. This is possibly not surprising as consider that the adhesion ability has not been quantitatively evaluated in these studies. Moreover, there is still a challenge to produce reliable membranes with high antifouling properties although remarkable progress has been made in fabrication of membranes for water treatment (Lalia et al., 2013). In the current stage, membrane selection in MBRs with aims to mitigate membrane fouling is mostly based on experiences, or even intuition. A quantitative assessment of these interactions with the rough surface would provide a justified guideline for membrane fabrication and selection in MBRs. Therefore, the aim of this study was to analysis the interfacial interactions between sludge foulant and rough membrane surface. A new method which combines the surface element integration (SEI) method with composite Simpson’s rule was developed to compute these interfacial interactions. Effects of membrane surface properties on the interfacial interactions were investigated. Furthermore, the implications for membrane selection and fabrication in MBRs were discussed.
2.Methods 2.1. Experimental setup A submerged MBR (SMBR) setup (65 L effective volume) was continuously run to supply sludge samples for interaction analysis.
The flat sheet membrane model used in the SMBR was supplied by Shanghai SINAP Co. Ltd. The membrane had a normalized pore size of 0.3 lm, and the membrane material was polyvinylidene fluoride (PVDF). PVDF membrane has been reported to be one of the most widely used membrane types in MBRs (Pearce, 2007; Santos and Judd, 2010; Lin et al., 2013). The sludge retention time (SRT) and hydraulic retention time (HRT) of the SMBR were approximately 45.5 d and 5.5 h, respectively. 2.2. XDLVO approach According to XDLVO theory, the total interaction between two surfaces comprises of 3 components: attractive Lifshitz–van der Waals (LW), acid–base (AB) interactions, and repulsive electrostatic double layer (EL) interaction. The individual interaction energy per unit area (DGLW (h), DGAB (h) and DGEL (h)) between two infinite planar surface can be described by Eqs. (1–3) (van Oss, 1995). 2
h0
DGLW ðhÞ ¼ DGLW h0
h
ð1Þ
2
DGAB ðhÞ ¼ DGAB h0 exp
h0 h k
EL
DG ðhÞ ¼ jer e0 ff fm
ð2Þ
! f2f þ f2m 1 ð1 coth jhÞ þ sinh jh 2ff fm
ð3Þ
where h is the separation distance between two planar surfaces; two planar surfaces are assumed to contact each other at a minimum separation distance (h0) of 0.158 nm (Meinders et al., 1995); AB EL DGLW h0 , DGh0 and DGh0 are the LW, AB and EL interaction energy per unit area between two infinite planar surfaces in contact, respectively. k (=0.6 nm) is the decay length of AB energy in water; j is the reciprocal Debye length; ere0 is the permittivity of sludge suspension; ff and fm are the zeta potential of foulant and membrane, respectively. AB EL Relationships between DGLW h0 , DGh0 , DGh0 and the surface properties of the two interacting surfaces are shown in Eqs. (4–6), respectively (van Oss, 1995).
DGLW h0 ¼ 2 DGAB h0 ¼ 2
qffiffiffiffiffiffiffiffi
cLW m
qffiffiffiffiffiffiffiffiqffiffiffiffiffiffiffiffi
hpffiffiffiffiffiffipffiffiffiffiffiffi
cþw
cLW w
cf þ
pffiffiffiffiffiffi
cm
cLW f
qffiffiffiffiffiffiffiffi
cLW w
pffiffiffiffiffi ffi
cw þ
ð4Þ
ffi pffiffiffiffiffi ffiqffiffiffiffiffi þ
cw
cf þ
pffiffiffiffiffiffi
cþm
qffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffi i cf cþm cþf cm
DGEL h0
¼
e0 er j 2
þ
n2m Þ
cþw
ð5Þ
" ðn2f
pffiffiffiffiffiffi
1 cothðjh0 Þ þ
2nf nm n2f þ n2m
# cschðjh0 Þ
ð6Þ
where cLW, c+ and c are the LW, electron donor and electron acceptor surface tension components of a substance (foulant (notated as subscript f), water (notated as subscript w) or membrane (notated as subscript m)), respectively. These surface tension components of a solid substance can be numerically computed by solving a set of three Young’s equations (van Oss, 1995).
ð1 þ cos /Þ Tol cl ¼ 2
qffiffiffiffiffiffiffiffiqffiffiffiffiffiffiffiffi
cLW cLW þ s l
ffi pffiffiffiffiffi ffipffiffiffiffiffi þ
cl
cs þ
qffiffiffiffiffiffipffiffiffiffiffiffi
cþl cs
ð7Þ
This operation requires measurement of the contact angle (/) of three probe liquids on the objective solid substance. The free energy of interaction between two identical surfaces immersed in water (DGSWS) was used to evaluate the surface hydrophobicity/hydrophilicity of a substance.
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DGsws ¼ 2csw qffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffi2 ¼ 2 cLW cLW s w p ffiffiffiffiffiffiffiffiffiffi ffi pffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffi 4 cþs cs þ cþw cw cþs cw cs cþw
ð8Þ
If DGSWS > 0, the surface is considered to be hydrophilic, and vice versa (van Oss, 1995). AB The three types of interaction energies (U LW fwm ðDÞ, U fwm ðDÞ and U EL ðDÞ) between a particle (foulant) and a planar surface (smooth fwm membrane surface) can be calculated by Eqs. (9–11):
estimated. In the composite Simpson’s rule, certain point x1 = a, xi = x1 + ih (i = 1, 2, . . ., 2m + 1) and y1 = b, yj = y1 + jk (j = 1, 2, . . ., 2n + 1) were used to subdivide the interval [a, b] of variable x and the interval [c, d] of variable y in a double integral, respectively. Herein, h = (b a)/2m, and k = (d c)/2n. Defining fi,j as the function value of f (xi, yj), the double integral could be obtained as follows:
Z a
b
Z
RDDGAB h0
¼ 2p
ð9Þ
h0 D exp k
2.3. Combined method for analyzing interfacial interactions The SEI method, which integrates the interaction energy per unit area between opposing differential planar elements over the entire surfaces (Bhattacharjee and Elimelech, 1997), was used to analyze the interfacial interaction energies between a foulant particle and rough membrane surface. In this method, the spherical surface of a particle was treated as a series of concentric rings. The calculation equations for the three types of interaction energies can be expressed as follows:
DGLW ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
0
ð12Þ U AB fwm ðDÞ ¼
Z 2p Z 0
R
DGAB ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
ð13Þ U EL fwm ðDÞ ¼
Z 2p Z
R
DGEL ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
0
ð14Þ where la is the height of asperity on membrane surface; r is the radius of circular ring on particle surface; dh is the differential angle corresponding to the differential circular arc in the circular ring; f(r,h) is local amplitude directly below the circular arc as a function of the position defined by r and h. In this study, a sine function was assigned for f(r,h) to reflect the membrane surface morphology according to the literature studies (Whitehead and Verran, 2006; Verran et al., 2010).
f ðr; hÞ ¼ la sin
pr cos h 2r a
þu
Z
x2i2
y2j
f ðx; yÞdxdy y2j2
m X n hk X ðf þ f 2i;2j2 þ f 2i;2j þ f 2i2;2j Þ 9 i¼1 j¼1 2i2;2j2
þ 16f 2i1;2j1
ð10Þ
where D is the closest distance between a particle and local position of planar surface; R is the particle radius.
R
x2i
þ 4ðf 2i1;2j2 þ f 2i;2j1 þ f 2i1;2j þ f 2i2;2j1 Þ
ð11Þ
Z 2p Z
m X n Z X i¼1 j¼1
1 þ ejD 2 2 2jD þ ðn U EL þ n Þ lnð1 e Þ f m fwm ðDÞ ¼ per e0 R 2nf nm ln 1 ejD
U LW fwm ðDÞ ¼
f ðx; yÞdxdy ¼
c
2
LW h0 R U LW fwm ðDÞ ¼ 2pDGh0 D
U AB fwm ðDÞ
d
ð15Þ
where u is the phase shift of the sine function; ra is the radius of the asperity or the valley. However, due to the difficulty to obtain the antiderivative of the double integrals shown in Eqs. (12–14), this method cannot be applied in the quantitative calculation of interactions with rough surface in practice (Hoek and Agarwal, 2006). Combined with composite Simpson’s rule, the double integrals can be numerically
ð16Þ
where, m and n are the number of segments for the variable interval of x and y, respectively. The calculation error (E) of the Eq. (16) can be estimated by the following equation:
E¼
" # 4 ~ ~Þ ðb aÞðd cÞ 4 a@ 4 f ðn; gÞ 4 @ f ðn; g h þ k 180 @x4 @y4
ð17Þ
~ are the n are the values in the interval [a, b]. g and g where, n and ~ values in the interval [c, d]. By setting m = n = 2000 or above, it was confirmed that the calculation error was negligible in this study. It can be seen that, setting high value of m and n would cause a heavy computation burden. To resolve this problem, computation programs run in MATLAB platform were implemented in this study. As an example, a MATLAB program with the original code used to calculate the double integrals under certain condition was provided in the Supplementary Data. 2.4. Analytical methods The sludge samples were obtained from the MBR system operated at stable operation period. The performance of the MBR system, as well as sludge properties, at the stable operation period was quite stable. Therefore, the sludge samples were representative for the experiments and measurements. A Zetasizer Nano ZS (Malvern Instruments Ltd., UK) was used to measure zeta potential of sludge foulants based on the electrophoretic mobility method. The samples were prepared by first filtration of the sludge suspension through a filter with 0.45 lm pore size, followed by immersing the resulted sludge to 0.01 mol L1 NaCl solution. Triplicate measurements were conducted for each sample. The membrane surface zeta potential was measured by a particle size analyzer (Zeta 90 Plus, Brookhaven Instruments, UK). Static contact angle on the membrane and sludge samples was measured based on the sessile drop method using a contact angle meter (Kino industry Co., Ltd, USA). Three liquids including ultrapure water, glycerol and diiodomethane were used as probe liquids for determination of the surface tension parameters. The procedure of membrane sample preparation is as follows: the virgin PVDF membrane was firstly cut into small pieces (2 cm 4 cm), and then immersed in ultrapure water for 48 h. These membrane pieces were then mounted on a glass slide. In order to prepare sludge samples, the retained sludge through filtration was pressed by using two glass slides to form a relatively flat surface. Thereafter, both the membrane pieces and the resulted sludge samples, together with the pressing slides were dried in a desiccator for 24 h to remove surplus water. Particle size distribution (PSD) of sludge suspension was measured using a Malvern Mastersizer 2000 instrument. The morphology of the clean membrane surface was observed by an atomic force microscopy (AFM) (NT-MDT).
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3. Results and discussion
400
Quantitative assessment of the interfacial interactions required determination of the properties of the two interacting surfaces. These properties including surface contact angle, surface tensions, zeta potential were experimentally measured, and the results are presented in Table 1. The sludge samples had a relatively high c component and zeta potential, which are comparable with those literature data (Feng et al., 2009; Su et al., 2013), indicating the representativeness of the sludge samples in this study for MBRs. The PVDF membrane was highly negatively charged, and was considered to be hydrophobic as DGSWS values were negative. The membrane surface morphology was scanned by AFM. The AFM images of the membrane surface are shown in Fig. S1 in the Supplementary Data. It can be seen that membrane surface morphology takes the form of a series of valleys and asperities with different amplitude and spacing. The average roughness was estimated to be about 100 nm. Comparable average roughness has been also reported for the membranes used in MBRs in previous studies (Mahendran et al., 2011; Chen et al., 2012b). Although the randomness of surface roughness precludes a rigorous mathematical model describing surface morphology, it is possible to propose a hypothetical surface topology that represents some pertinent statistical properties of a rough surface (Hoek et al., 2003). It is reasonably realistic to conceive asperities on surface as sinusoidal waves (Bhattacharjee and Elimelech, 1997). As mentioned in Section 2.3, a sine function was assigned for f(r,h) in this study. The average la and ra of approximately 100 nm and 100 nm, respectively, were used in calculation in this study.
3.2. Interfacial interactions between the sludge foulant and rough membrane surface The interfacial interactions between a sludge foulant and rough membrane surface under conditions in this study can be calculated by using Eqs. (12–14), and the double integrals in Eqs. (12–14) can be solved by using Eq. (16). The calculation results when la = ra = 100 nm are shown in Fig. 1. As shown in Fig. 1, the LW, AB and EL interaction energies have different strength and property, corresponding to a complicated profile of total interaction. There exists an energy barrier in the separation distance range of 2.0–7.1 nm which have to be overcome for eventual adhesion of a sludge foulant to the membrane surface. When the separation distance <2.0 nm or >7.1 nm, the total interaction is attractive, indicating two negative energy ranges in the profile. Particularly, the interaction energy in contact (separation distance = 0.158 nm) is 5328 kT (calculated through Eqs. (12–14)), indicating highly attractive. This characteristic suggests that, once a foulant overcome the energy barrier, it will be hard to be detached from the membrane surface due to the attractive interaction. Fig. 1 not only confirms that the interactions between a foulant particle and rough membrane surface can be quantitatively assessed by using the combined method, but also indicates that the membrane used in this study is not the optimal option for membrane fouling control
Interaction energy (kT)
300
3.1. Surface properties of the sludge foulant and membrane
EL interaction
200
total interaction
100 energy barrier
0 -100 LW interaction
-200
AB interaction
-300 -400 0
2
4 6 8 10 Separation distance (nm)
12
14
Fig. 1. Profiles of the interaction energies between a foulant particle and rough membrane surface (asperity height = 100 nm, asperity radius = 100 nm, foulant radius = 10 lm, pH = 7.0).
in the MBR system. Since the combined method provided a useful tool to quantitatively calculate interfacial interactions between foulant particle and rough membrane surface, it is possible to explore the suitable membranes based on assessment of interfacial interactions. 3.3. Implications for membrane selection and fabrication The interfacial interactions will change with membrane surface roughness. Fig. 2 shows the profiles of the interfacial interactions between the rough membrane surface and a foulant particle when la = ra = 300 nm. Herein, roughness scale was defined as the ratio of current roughness to the original roughness (100 nm). It can be seen that the profiles of the LW, AB and EL interaction are much similar to those shown in Fig. 1, respectively. However, the total interaction profile with separation distance is much different from that shown in Fig. 1. The total energy is continually repulsive when the separation distance is in the range of 0–5 nm. Such a characteristic is very beneficial for membrane fouling control, and has been infinitely desired by the research community concerned with membrane fouling control. This result demonstrated that this desired characteristic could be possibly achieved by designing the membrane with such a roughness. Fig. 3 shows how roughness scale affects the total interaction profile. Basically, the strength of the total interfacial interaction decreases with the roughness scale. The strength is very weak when the roughness scale >5. It is interesting to note that there exists a critical scale range within which the continually repulsive total energy exists in the separation distance ranged from 0 to several nanometers. Apparently, membrane with roughness within the critical scale range will have strong anti-fouling property. Under conditions in this study, the critical scale range was 2.3– 4.5 (asperity height in the range of 230–450 nm). Studies have reported that the super anti-adhesion ability of the front surface of lotus leaf was mainly resulted from its unique surface morphology (Wang et al., 2009; Zhang et al., 2012), which is similar to the hypothesized membrane surface morphology in this study. These
Table 1 Contact angle of three probe liquids, surface tensions and Zeta potential (in 0.01 mol L1 NaCl solution at pH 7.0) data for membrane and sludge foulants. Material
PVDF membrane Sludge foulant
Surface tensions (mJ m2)
Contact angle ()
Zeta potential (mV)
Ultrapure water
Glycerol
Diiodomethane
cLW
c+
c
DGSWS
58.39 ± 1.22 71.18 ± 2.14
53.03 ± 1.56 68.73 ± 2.02
18.05 ± 0.87 31.43 ± 0.95
48.33 43.62
0.09 0.09
18.10 13.88
20.32 32.08
31.3 ± 1.1 16.9 ± 0.7
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(a) 6
200
5
EL interaction
100 50
total interaction
0 AB interaction
-50
LW interaction
-100
4
Volume (%)
Interaction energy (kT)
150
3 2
-150
1
-200 0
2
4 6 8 10 Separation distance (nm)
12
0
14
Fig. 2. Profiles of the interaction energies between a foulant particle and rough membrane surface (asperity height = 300 nm, asperity radius = 300 nm, foulant radius = 10 lm, pH = 7.0).
0.1
(b)
1
10 100 Particle size (μm)
Scenario 1
1000
10000
Scenario 2
particle
particle rough membrane surface
rough membrane surface
Fig. 4. (a) PSD of the sludge suspension in the MBR, and (b) schematic of two possible interaction scenarios regarding particle size.
Fig. 3. Variation of the total interaction profiles with roughness scale (foulant radius = 10 lm, pH = 7.0).
studies give a solid support to the conclusions obtained from assessment of interfacial interactions. It should be noted that the foulant particle size of 10 lm was assumed in Figs. 1–3. However, the PSD of the sludge suspension in the MBR was significantly varied in the range of 1.8–650 lm (Fig. 4(a)). Therefore, the effect of particle size on the interaction energy should be evaluated. Fig. 4(b) shows the schematic of two possible interaction scenarios regarding particle size. Since almost all of the particles in the sludge suspension were much larger than the asperity radius (100 nm), it is reasonable to consider that the interactions between the sludge foulants and rough membrane surface fall into scenario 1. The effect of particle size on the total interactions in scenario 1 is depicted in Fig. 5. Basically, increase in particle size would increase the absolute value of total interaction energy, and decrease the absolute value of the specific interaction energy (the ratio of total interaction energy to foulant mass). It was worth noting that the variation in foulant particle size did not change the fact that there exists a critical roughness scale (Fig. 5). This result indicated that the existence of a critical roughness scale was applicable for the vast majority of foulant particles in the MBR reactor.
Total interaction energy (kT)
300 20 µm foulant
200
15 µm foulant 10 µm foulant
100 0
5 µm foulant
-100 -200 -300 0
2
4 6 8 10 Separation distance (nm)
12
14
Fig. 5. Variation of the total interaction profiles with particle size (asperity height = 300 nm, asperity radius = 300 nm, pH = 7.0).
This study revealed the existence of a critical roughness scale for interfacial interactions with rough surface, and thus provided important implications for membrane selection and fabrication in MBRs. If a membrane is designed to be with critical scale roughness, it is expected that foulant adhesion could be significantly impeded, and thus membrane fouling could be significantly reduced. For example, by simulating the lotus leaf surface morphology, some materials with high anti-adhesion ability have been fabricated (Yuan et al., 2013; Wang et al., 2014). The calculation method present in this study also provided a guideline for determining the value of critical roughness scale for a given MBR. This study suggested that membrane could be designed accurately for membrane fouling control based on assessment of interfacial inter-
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actions rather than experiences. In a recent review, Lalia et al. (2013) summarized the progress in membrane fabrication, and mentioned that there is still a challenge to ‘‘tailor’’ membranes with anti-fouling properties. The word ‘‘tailor’’ mainly refers to ‘‘design membrane surface morphology’’. By using the method developed in this study, such a challenge is expected to be overcome. This study showed the great potential to ‘‘tailor’’ membrane surface morphology to mitigate membrane fouling. In this regard, the findings of this study are significant. 4. Conclusion A combined method can be used to calculate the interfacial interactions between a foulant particle and rough membrane surface in a SMBR. There exist an energy barrier and two negative energy ranges in the profile of total interaction. The strength and properties of the interfacial interactions were significantly affected by the roughness scale and foulant size. A critical range of roughness scale was identified to be 2.3–4.5 in this study. This study provided a new method to ‘‘tailor’’ membrane surface morphology for membrane fouling mitigation. Acknowledgements Financial support of National Natural Science Foundation of China (Nos. 21275131, 51108424), Project of Science and Technology Department of Zhejiang Province (No. 2015F50013) and Zhejiang Provincial Environmental Protection Scientific Research Project (No. 2013A024) is highly appreciated. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2014. 12.055. References Bhattacharjee, S., Elimelech, M., 1997. Surface element integration: a novel technique for evaluation of DLVO interaction between a particle and a flat plate. J. Colloid Interface Sci. 193 (2), 273–285. Charman, K.M., Fernandez, P., Loewy, Z., Middleton, A.M., 2009. Attachment of Streptococcus oralis on acrylic substrates of varying roughness. Lett. Appl. Microbiol. 48 (4), 472–477. Chen, J., Zhang, M., Wang, A., Lin, H., Hong, H., Lu, X., 2012a. Osmotic pressure effect on membrane fouling in a submerged anaerobic membrane bioreactor and its experimental verification. Bioresour. Technol. 125, 97–101. Chen, L., Tian, Y., Cao, C.-Q., Zhang, J., Li, Z.-N., 2012b. Interaction energy evaluation of soluble microbial products (SMP) on different membrane surfaces: role of the reconstructed membrane topology. Water Res. 46 (8), 2693–2704. Dereli, R.K., Ersahin, M.E., Ozgun, H., Ozturk, I., Jeison, D., van der Zee, F., van Lier, J.B., 2012. Potentials of anaerobic membrane bioreactors to overcome treatment limitations induced by industrial wastewaters. Bioresour. Technol. 122, 160– 170. Feng, L., Li, X., Du, G., Chen, J., 2009. Adsorption and fouling characterization of Klebsiella oxytoca to microfiltration membranes. Process Biochem. 44 (11), 1289–1292. Giraldez, M.J., Resua, C.G., Lira, M., Oliveira, M.E., Magarinos, B., Toranzo, A.E., YebraPimentel, E., 2010. Contact lens hydrophobicity and roughness effects on bacterial adhesion. Optom. Vis. Sci. 87 (6), E426–31. Hoek, E.M.V., Agarwal, G.K., 2006. Extended DLVO interactions between spherical particles and rough surfaces. J. Colloid Interface Sci. 298 (1), 50–58.
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Environ. Sci. Technol. 42 (7), 677–740. Lin, H., Peng, W., Zhang, M., Chen, J., Hong, H., Zhang, Y., 2013. A review on anaerobic membrane bioreactors: applications, membrane fouling and future perspectives. Desalination 314, 169–188. Lin, H., Zhang, M., Mei, R., Chen, J., Hong, H., 2014a. A novel approach for quantitative evaluation of the physicochemical interactions between rough membrane surface and sludge foulants in a submerged membrane bioreactor. Bioresour. Technol. 171, 247–252. Lin, H., Zhang, M., Wang, F., Meng, F., Liao, B.-Q., Hong, H., Chen, J., Gao, W., 2014b. A critical review of extracellular polymeric substances (EPSs) in membrane bioreactors: characteristics, roles in membrane fouling and control strategies. J. Membr. Sci. 460, 110–125. Mahendran, B., Lin, H., Liao, B., Liss, S.N., 2011. Surface properties of biofouled membranes from a submerged anaerobic membrane bioreactor after cleaning. J. Environ. Eng. 137 (6), 504–513. Meinders, J.M., van der Mei, H.C., Busscher, H.J., 1995. Deposition efficiency and reversibility of bacterial adhesion under flow. J. Colloid Interface Sci. 176 (2), 329–341. Pearce, G., 2007. Introduction to membranes: membrane selection. Filtr. Sep. 44 (3), 35–37. Santos, A., Judd, S., 2010. The commercial status of membrane bioreactors for municipal wastewater. Sep. Sci. Technol. 45 (7), 850–857. Singh, A.V., Vyas, V., Patil, R., Sharma, V., Scopelliti, P.E., Bongiorno, G., Podesta, A., Lenardi, C., Gade, W.N., Milani, P., 2011. Quantitative characterization of the influence of the nanoscale morphology of nanostructured surfaces on bacterial adhesion and biofilm formation. PLoS ONE 6 (9), e25029. Su, X., Tian, Y., Li, H., Wang, C., 2013. New insights into membrane fouling based on characterization of cake sludge and bulk sludge: an especial attention to sludge aggregation. Bioresour. Technol. 128, 586–592. Vaidya, A.M., Bell, G., Halling, P.J., 1992. Aqueous-organic membrane bioreactors. Part I. A guide to membrane selection. J. Membr. Sci. 71 (1–2), 139–149. van Oss, C.J., 1995. Hydrophobicity of biosurfaces – origin, quantitative determination and interaction energies. Colloids Surf. B 5 (3–4), 91–110. van Oss, C.J., 1997. Hydrophobicity and hydrophilicity of biosurfaces. Curr. Opin. Colloid Interface Sci. 2 (5), 503–512. Verran, J., Packer, A., Kelly, P., Whitehead, K.A., 2010. The retention of bacteria on hygienic surfaces presenting scratches of microbial dimensions. Lett. Appl. Microbiol. 50 (3), 258–263. Wang, J., Chen, H., Sui, T., Li, A., Chen, D., 2009. Investigation on hydrophobicity of lotus leaf: experiment and theory. Plant Sci. 176 (5), 687–695. Wang, P., Wang, Z., Wu, Z., Mai, S., 2011. Fouling behaviours of two membranes in a submerged membrane bioreactor for municipal wastewater treatment. J. Membr. Sci. 382 (1–2), 60–69. Wang, Q., Wang, Z., Zhu, C., Mei, X., Wu, Z., 2013. Assessment of SMP fouling by foulant–membrane interaction energy analysis. J. Membr. Sci. 446, 154–163. Wang, T., Chang, L., Hatton, B., Kong, J., Chen, G., Jia, Y., Xiong, D., Wong, C., 2014. Preparation and hydrophobicity of biomorphic ZnO/carbon based on a lotusleaf template. Mater. Sci. Eng. C 43, 310–316. Whitehead, K.A., Verran, J., 2006. The effect of surface topography on the retention of microorganisms. Food Bioprod. Process. 84 (4), 253–259. Yuan, Z., Wang, X., Bin, J., Peng, C., Xing, S., Wang, M., Xiao, J., Zeng, J., Xie, Y., Xiao, X., Fu, X., Gong, H., Zhao, D., 2013. A novel fabrication of a superhydrophobic surface with highly similar hierarchical structure of the lotus leaf on a copper sheet. Appl. Surf. Sci. 285 (Part B), 205–210. Zhang, Y., Wu, H., Yu, X., Chen, F., Wu, J., 2012. Microscopic observations of the lotus leaf for explaining the outstanding mechanical properties. J. Bionic Eng. 9 (1), 84–90. Zhang, M., Peng, W., Chen, J., He, Y., Ding, L., Wang, A., Lin, H., Hong, H., Zhang, Y., Yu, H., 2013. A new insight into membrane fouling mechanism in submerged membrane bioreactor: osmotic pressure during cake layer filtration. Water Res. 47 (8), 2777–2786.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Quantitative assessment of interfacial interactions with rough membrane surface and its implications for membrane selection and fabrication in a MBR Jianrong Chen a, Rongwu Mei b, Liguo Shen a, Linxian Ding a, Yiming He c, Hongjun Lin a,⇑, Huachang Hong a,1 a
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, PR China Environmental Science Research and Design Institute of Zhejiang Province, Hangzhou 310007, PR China c Department of Materials Physics, Zhejiang Normal University, Jinhua 321004, PR China b
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
Interfacial interactions with rough
surface were quantitatively assessed. Interactions were significantly
affected by roughness scale and foulant size. Existence of a critical range of roughness scale for fouling mitigation was revealed. Implications for membrane selection and fabrication in MBRs were provided.
a r t i c l e
i n f o
a b s t r a c t
Article history: Received 20 September 2014 Received in revised form 12 December 2014 Accepted 15 December 2014 Available online 23 December 2014
The interfacial interactions between a foulant particle and rough membrane surface in a submerged membrane bioreactor (MBR) were quantitatively assessed by using a new-developed method. It was found that the profile of total interaction versus separation distance was complicated. There were an energy barrier and two negative energy ranges in the profile. Further analysis showed that roughness scale significantly affected the strength and properties of interfacial interactions. It was revealed that there existed a critical range of roughness scale within which the total energy in the separation distance ranged from 0 to several nanometers was continually repulsive. Decrease in foulant size would increase the strength of specific interaction energy, but did not change the existence of a critical roughness scale range. These findings suggested the possibility to ‘‘tailor’’ membrane surface morphology for membrane fouling mitigation, and thus gave significant implications for membrane selection and fabrication in MBRs. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Membrane bioreactor Membrane fouling Surface interaction Rough surface Wastewater treatment
1. Introduction While membrane bioreactor (MBR) technology has gained its popularity in industrial and municipal wastewater treatment due ⇑ Corresponding author. Tel.: +86 579 82282273. E-mail addresses: [email protected] (H. Hong). 1 Tel.: +86 13967477601.
(H.
Lin),
http://dx.doi.org/10.1016/j.biortech.2014.12.055 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
[email protected]
to its significant merits over some other technologies (Santos and Judd, 2010; Dereli et al., 2012; Lin et al., 2012), membrane fouling is one of the biggest problems impeding its more widespread applications (Wang et al., 2011; Chen et al., 2012b; Su et al., 2013; Lin et al., 2014b). Membrane fouling in MBRs was related to the interactions between membrane and sludge foulants (Wang et al., 2011; Chen et al., 2012b; Lin et al., 2014b). The interfacial interactions directly
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determined the processes of foulant adhesion and cake layer formation (van Oss, 1997; Hong et al., 2013; Wang et al., 2013), which were considered as the main causes of membrane fouling (Chen et al., 2012a; Zhang et al., 2013). Thus, quantitative assessment of these interactions is essential to better understand and resolve the membrane fouling problem. The interfacial interactions between a sludge foulant and membrane surface can be generally assessed within the framework of the extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) theory (van Oss, 1995, 1997). XDLVO theory provides a method to quantitatively analyze three types of interaction energies between two infinite parallel flat plates (van Oss, 1995). However, as a general knowledge, both of sludge foulant and membrane surface are not infinite flat. Sludge foulant is generally assumed to be spherical (Bhattacharjee and Elimelech, 1997; Hoek and Agarwal, 2006; Hong et al., 2013), and almost all the commercial membranes have significantly rough surface (Hoek et al., 2003; Mahendran et al., 2011; Lin et al., 2014a). Therefore, conventional methods in XDLVO theory cannot calculate the interfacial interactions between a particle and a rough surface. This situation calls for development of a new method to quantitatively evaluate the interfacial interactions with the rough surface. For a given MBR system, membrane fouling is directly determined by the applied membrane. As the characteristics of the optional membranes in MBRs vary remarkably, selecting a suitable membrane is of primary importance for membrane fouling control and application of MBRs. The criteria of membrane selection should be related to the bulk properties and surface morphology of the membranes (Vaidya et al., 1992; Pearce, 2007). It is no doubt that the suitable membranes used in MBRs should have the chemical, thermal and mechanical integrity of the bulk properties (Santos and Judd, 2010; Lin et al., 2013). The surface morphology is generally characterized by surface roughness. Some studies reported that adhesion of bacteria cells to a surface would be improved with the increase in the surface roughness (Charman et al., 2009; Giraldez et al., 2010), whereas, some other studies reported the opposite results (Ivanova et al., 2010; Singh et al., 2011). No explanation of these findings has been provided. It can be seen from the above analyses that, there are no definite conclusions drawn regarding the effects of surface morphology. This is possibly not surprising as consider that the adhesion ability has not been quantitatively evaluated in these studies. Moreover, there is still a challenge to produce reliable membranes with high antifouling properties although remarkable progress has been made in fabrication of membranes for water treatment (Lalia et al., 2013). In the current stage, membrane selection in MBRs with aims to mitigate membrane fouling is mostly based on experiences, or even intuition. A quantitative assessment of these interactions with the rough surface would provide a justified guideline for membrane fabrication and selection in MBRs. Therefore, the aim of this study was to analysis the interfacial interactions between sludge foulant and rough membrane surface. A new method which combines the surface element integration (SEI) method with composite Simpson’s rule was developed to compute these interfacial interactions. Effects of membrane surface properties on the interfacial interactions were investigated. Furthermore, the implications for membrane selection and fabrication in MBRs were discussed.
2.Methods 2.1. Experimental setup A submerged MBR (SMBR) setup (65 L effective volume) was continuously run to supply sludge samples for interaction analysis.
The flat sheet membrane model used in the SMBR was supplied by Shanghai SINAP Co. Ltd. The membrane had a normalized pore size of 0.3 lm, and the membrane material was polyvinylidene fluoride (PVDF). PVDF membrane has been reported to be one of the most widely used membrane types in MBRs (Pearce, 2007; Santos and Judd, 2010; Lin et al., 2013). The sludge retention time (SRT) and hydraulic retention time (HRT) of the SMBR were approximately 45.5 d and 5.5 h, respectively. 2.2. XDLVO approach According to XDLVO theory, the total interaction between two surfaces comprises of 3 components: attractive Lifshitz–van der Waals (LW), acid–base (AB) interactions, and repulsive electrostatic double layer (EL) interaction. The individual interaction energy per unit area (DGLW (h), DGAB (h) and DGEL (h)) between two infinite planar surface can be described by Eqs. (1–3) (van Oss, 1995). 2
h0
DGLW ðhÞ ¼ DGLW h0
h
ð1Þ
2
DGAB ðhÞ ¼ DGAB h0 exp
h0 h k
EL
DG ðhÞ ¼ jer e0 ff fm
ð2Þ
! f2f þ f2m 1 ð1 coth jhÞ þ sinh jh 2ff fm
ð3Þ
where h is the separation distance between two planar surfaces; two planar surfaces are assumed to contact each other at a minimum separation distance (h0) of 0.158 nm (Meinders et al., 1995); AB EL DGLW h0 , DGh0 and DGh0 are the LW, AB and EL interaction energy per unit area between two infinite planar surfaces in contact, respectively. k (=0.6 nm) is the decay length of AB energy in water; j is the reciprocal Debye length; ere0 is the permittivity of sludge suspension; ff and fm are the zeta potential of foulant and membrane, respectively. AB EL Relationships between DGLW h0 , DGh0 , DGh0 and the surface properties of the two interacting surfaces are shown in Eqs. (4–6), respectively (van Oss, 1995).
DGLW h0 ¼ 2 DGAB h0 ¼ 2
qffiffiffiffiffiffiffiffi
cLW m
qffiffiffiffiffiffiffiffiqffiffiffiffiffiffiffiffi
hpffiffiffiffiffiffipffiffiffiffiffiffi
cþw
cLW w
cf þ
pffiffiffiffiffiffi
cm
cLW f
qffiffiffiffiffiffiffiffi
cLW w
pffiffiffiffiffi ffi
cw þ
ð4Þ
ffi pffiffiffiffiffi ffiqffiffiffiffiffi þ
cw
cf þ
pffiffiffiffiffiffi
cþm
qffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffi i cf cþm cþf cm
DGEL h0
¼
e0 er j 2
þ
n2m Þ
cþw
ð5Þ
" ðn2f
pffiffiffiffiffiffi
1 cothðjh0 Þ þ
2nf nm n2f þ n2m
# cschðjh0 Þ
ð6Þ
where cLW, c+ and c are the LW, electron donor and electron acceptor surface tension components of a substance (foulant (notated as subscript f), water (notated as subscript w) or membrane (notated as subscript m)), respectively. These surface tension components of a solid substance can be numerically computed by solving a set of three Young’s equations (van Oss, 1995).
ð1 þ cos /Þ Tol cl ¼ 2
qffiffiffiffiffiffiffiffiqffiffiffiffiffiffiffiffi
cLW cLW þ s l
ffi pffiffiffiffiffi ffipffiffiffiffiffi þ
cl
cs þ
qffiffiffiffiffiffipffiffiffiffiffiffi
cþl cs
ð7Þ
This operation requires measurement of the contact angle (/) of three probe liquids on the objective solid substance. The free energy of interaction between two identical surfaces immersed in water (DGSWS) was used to evaluate the surface hydrophobicity/hydrophilicity of a substance.
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J. Chen et al. / Bioresource Technology 179 (2015) 367–372
DGsws ¼ 2csw qffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffi2 ¼ 2 cLW cLW s w p ffiffiffiffiffiffiffiffiffiffi ffi pffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffi 4 cþs cs þ cþw cw cþs cw cs cþw
ð8Þ
If DGSWS > 0, the surface is considered to be hydrophilic, and vice versa (van Oss, 1995). AB The three types of interaction energies (U LW fwm ðDÞ, U fwm ðDÞ and U EL ðDÞ) between a particle (foulant) and a planar surface (smooth fwm membrane surface) can be calculated by Eqs. (9–11):
estimated. In the composite Simpson’s rule, certain point x1 = a, xi = x1 + ih (i = 1, 2, . . ., 2m + 1) and y1 = b, yj = y1 + jk (j = 1, 2, . . ., 2n + 1) were used to subdivide the interval [a, b] of variable x and the interval [c, d] of variable y in a double integral, respectively. Herein, h = (b a)/2m, and k = (d c)/2n. Defining fi,j as the function value of f (xi, yj), the double integral could be obtained as follows:
Z a
b
Z
RDDGAB h0
¼ 2p
ð9Þ
h0 D exp k
2.3. Combined method for analyzing interfacial interactions The SEI method, which integrates the interaction energy per unit area between opposing differential planar elements over the entire surfaces (Bhattacharjee and Elimelech, 1997), was used to analyze the interfacial interaction energies between a foulant particle and rough membrane surface. In this method, the spherical surface of a particle was treated as a series of concentric rings. The calculation equations for the three types of interaction energies can be expressed as follows:
DGLW ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
0
ð12Þ U AB fwm ðDÞ ¼
Z 2p Z 0
R
DGAB ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
ð13Þ U EL fwm ðDÞ ¼
Z 2p Z
R
DGEL ðD þ R þ la
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2 r 2 f ðr; hÞÞrdrdh
0
0
ð14Þ where la is the height of asperity on membrane surface; r is the radius of circular ring on particle surface; dh is the differential angle corresponding to the differential circular arc in the circular ring; f(r,h) is local amplitude directly below the circular arc as a function of the position defined by r and h. In this study, a sine function was assigned for f(r,h) to reflect the membrane surface morphology according to the literature studies (Whitehead and Verran, 2006; Verran et al., 2010).
f ðr; hÞ ¼ la sin
pr cos h 2r a
þu
Z
x2i2
y2j
f ðx; yÞdxdy y2j2
m X n hk X ðf þ f 2i;2j2 þ f 2i;2j þ f 2i2;2j Þ 9 i¼1 j¼1 2i2;2j2
þ 16f 2i1;2j1
ð10Þ
where D is the closest distance between a particle and local position of planar surface; R is the particle radius.
R
x2i
þ 4ðf 2i1;2j2 þ f 2i;2j1 þ f 2i1;2j þ f 2i2;2j1 Þ
ð11Þ
Z 2p Z
m X n Z X i¼1 j¼1
1 þ ejD 2 2 2jD þ ðn U EL þ n Þ lnð1 e Þ f m fwm ðDÞ ¼ per e0 R 2nf nm ln 1 ejD
U LW fwm ðDÞ ¼
f ðx; yÞdxdy ¼
c
2
LW h0 R U LW fwm ðDÞ ¼ 2pDGh0 D
U AB fwm ðDÞ
d
ð15Þ
where u is the phase shift of the sine function; ra is the radius of the asperity or the valley. However, due to the difficulty to obtain the antiderivative of the double integrals shown in Eqs. (12–14), this method cannot be applied in the quantitative calculation of interactions with rough surface in practice (Hoek and Agarwal, 2006). Combined with composite Simpson’s rule, the double integrals can be numerically
ð16Þ
where, m and n are the number of segments for the variable interval of x and y, respectively. The calculation error (E) of the Eq. (16) can be estimated by the following equation:
E¼
" # 4 ~ ~Þ ðb aÞðd cÞ 4 a@ 4 f ðn; gÞ 4 @ f ðn; g h þ k 180 @x4 @y4
ð17Þ
~ are the n are the values in the interval [a, b]. g and g where, n and ~ values in the interval [c, d]. By setting m = n = 2000 or above, it was confirmed that the calculation error was negligible in this study. It can be seen that, setting high value of m and n would cause a heavy computation burden. To resolve this problem, computation programs run in MATLAB platform were implemented in this study. As an example, a MATLAB program with the original code used to calculate the double integrals under certain condition was provided in the Supplementary Data. 2.4. Analytical methods The sludge samples were obtained from the MBR system operated at stable operation period. The performance of the MBR system, as well as sludge properties, at the stable operation period was quite stable. Therefore, the sludge samples were representative for the experiments and measurements. A Zetasizer Nano ZS (Malvern Instruments Ltd., UK) was used to measure zeta potential of sludge foulants based on the electrophoretic mobility method. The samples were prepared by first filtration of the sludge suspension through a filter with 0.45 lm pore size, followed by immersing the resulted sludge to 0.01 mol L1 NaCl solution. Triplicate measurements were conducted for each sample. The membrane surface zeta potential was measured by a particle size analyzer (Zeta 90 Plus, Brookhaven Instruments, UK). Static contact angle on the membrane and sludge samples was measured based on the sessile drop method using a contact angle meter (Kino industry Co., Ltd, USA). Three liquids including ultrapure water, glycerol and diiodomethane were used as probe liquids for determination of the surface tension parameters. The procedure of membrane sample preparation is as follows: the virgin PVDF membrane was firstly cut into small pieces (2 cm 4 cm), and then immersed in ultrapure water for 48 h. These membrane pieces were then mounted on a glass slide. In order to prepare sludge samples, the retained sludge through filtration was pressed by using two glass slides to form a relatively flat surface. Thereafter, both the membrane pieces and the resulted sludge samples, together with the pressing slides were dried in a desiccator for 24 h to remove surplus water. Particle size distribution (PSD) of sludge suspension was measured using a Malvern Mastersizer 2000 instrument. The morphology of the clean membrane surface was observed by an atomic force microscopy (AFM) (NT-MDT).
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3. Results and discussion
400
Quantitative assessment of the interfacial interactions required determination of the properties of the two interacting surfaces. These properties including surface contact angle, surface tensions, zeta potential were experimentally measured, and the results are presented in Table 1. The sludge samples had a relatively high c component and zeta potential, which are comparable with those literature data (Feng et al., 2009; Su et al., 2013), indicating the representativeness of the sludge samples in this study for MBRs. The PVDF membrane was highly negatively charged, and was considered to be hydrophobic as DGSWS values were negative. The membrane surface morphology was scanned by AFM. The AFM images of the membrane surface are shown in Fig. S1 in the Supplementary Data. It can be seen that membrane surface morphology takes the form of a series of valleys and asperities with different amplitude and spacing. The average roughness was estimated to be about 100 nm. Comparable average roughness has been also reported for the membranes used in MBRs in previous studies (Mahendran et al., 2011; Chen et al., 2012b). Although the randomness of surface roughness precludes a rigorous mathematical model describing surface morphology, it is possible to propose a hypothetical surface topology that represents some pertinent statistical properties of a rough surface (Hoek et al., 2003). It is reasonably realistic to conceive asperities on surface as sinusoidal waves (Bhattacharjee and Elimelech, 1997). As mentioned in Section 2.3, a sine function was assigned for f(r,h) in this study. The average la and ra of approximately 100 nm and 100 nm, respectively, were used in calculation in this study.
3.2. Interfacial interactions between the sludge foulant and rough membrane surface The interfacial interactions between a sludge foulant and rough membrane surface under conditions in this study can be calculated by using Eqs. (12–14), and the double integrals in Eqs. (12–14) can be solved by using Eq. (16). The calculation results when la = ra = 100 nm are shown in Fig. 1. As shown in Fig. 1, the LW, AB and EL interaction energies have different strength and property, corresponding to a complicated profile of total interaction. There exists an energy barrier in the separation distance range of 2.0–7.1 nm which have to be overcome for eventual adhesion of a sludge foulant to the membrane surface. When the separation distance <2.0 nm or >7.1 nm, the total interaction is attractive, indicating two negative energy ranges in the profile. Particularly, the interaction energy in contact (separation distance = 0.158 nm) is 5328 kT (calculated through Eqs. (12–14)), indicating highly attractive. This characteristic suggests that, once a foulant overcome the energy barrier, it will be hard to be detached from the membrane surface due to the attractive interaction. Fig. 1 not only confirms that the interactions between a foulant particle and rough membrane surface can be quantitatively assessed by using the combined method, but also indicates that the membrane used in this study is not the optimal option for membrane fouling control
Interaction energy (kT)
300
3.1. Surface properties of the sludge foulant and membrane
EL interaction
200
total interaction
100 energy barrier
0 -100 LW interaction
-200
AB interaction
-300 -400 0
2
4 6 8 10 Separation distance (nm)
12
14
Fig. 1. Profiles of the interaction energies between a foulant particle and rough membrane surface (asperity height = 100 nm, asperity radius = 100 nm, foulant radius = 10 lm, pH = 7.0).
in the MBR system. Since the combined method provided a useful tool to quantitatively calculate interfacial interactions between foulant particle and rough membrane surface, it is possible to explore the suitable membranes based on assessment of interfacial interactions. 3.3. Implications for membrane selection and fabrication The interfacial interactions will change with membrane surface roughness. Fig. 2 shows the profiles of the interfacial interactions between the rough membrane surface and a foulant particle when la = ra = 300 nm. Herein, roughness scale was defined as the ratio of current roughness to the original roughness (100 nm). It can be seen that the profiles of the LW, AB and EL interaction are much similar to those shown in Fig. 1, respectively. However, the total interaction profile with separation distance is much different from that shown in Fig. 1. The total energy is continually repulsive when the separation distance is in the range of 0–5 nm. Such a characteristic is very beneficial for membrane fouling control, and has been infinitely desired by the research community concerned with membrane fouling control. This result demonstrated that this desired characteristic could be possibly achieved by designing the membrane with such a roughness. Fig. 3 shows how roughness scale affects the total interaction profile. Basically, the strength of the total interfacial interaction decreases with the roughness scale. The strength is very weak when the roughness scale >5. It is interesting to note that there exists a critical scale range within which the continually repulsive total energy exists in the separation distance ranged from 0 to several nanometers. Apparently, membrane with roughness within the critical scale range will have strong anti-fouling property. Under conditions in this study, the critical scale range was 2.3– 4.5 (asperity height in the range of 230–450 nm). Studies have reported that the super anti-adhesion ability of the front surface of lotus leaf was mainly resulted from its unique surface morphology (Wang et al., 2009; Zhang et al., 2012), which is similar to the hypothesized membrane surface morphology in this study. These
Table 1 Contact angle of three probe liquids, surface tensions and Zeta potential (in 0.01 mol L1 NaCl solution at pH 7.0) data for membrane and sludge foulants. Material
PVDF membrane Sludge foulant
Surface tensions (mJ m2)
Contact angle ()
Zeta potential (mV)
Ultrapure water
Glycerol
Diiodomethane
cLW
c+
c
DGSWS
58.39 ± 1.22 71.18 ± 2.14
53.03 ± 1.56 68.73 ± 2.02
18.05 ± 0.87 31.43 ± 0.95
48.33 43.62
0.09 0.09
18.10 13.88
20.32 32.08
31.3 ± 1.1 16.9 ± 0.7
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(a) 6
200
5
EL interaction
100 50
total interaction
0 AB interaction
-50
LW interaction
-100
4
Volume (%)
Interaction energy (kT)
150
3 2
-150
1
-200 0
2
4 6 8 10 Separation distance (nm)
12
0
14
Fig. 2. Profiles of the interaction energies between a foulant particle and rough membrane surface (asperity height = 300 nm, asperity radius = 300 nm, foulant radius = 10 lm, pH = 7.0).
0.1
(b)
1
10 100 Particle size (μm)
Scenario 1
1000
10000
Scenario 2
particle
particle rough membrane surface
rough membrane surface
Fig. 4. (a) PSD of the sludge suspension in the MBR, and (b) schematic of two possible interaction scenarios regarding particle size.
Fig. 3. Variation of the total interaction profiles with roughness scale (foulant radius = 10 lm, pH = 7.0).
studies give a solid support to the conclusions obtained from assessment of interfacial interactions. It should be noted that the foulant particle size of 10 lm was assumed in Figs. 1–3. However, the PSD of the sludge suspension in the MBR was significantly varied in the range of 1.8–650 lm (Fig. 4(a)). Therefore, the effect of particle size on the interaction energy should be evaluated. Fig. 4(b) shows the schematic of two possible interaction scenarios regarding particle size. Since almost all of the particles in the sludge suspension were much larger than the asperity radius (100 nm), it is reasonable to consider that the interactions between the sludge foulants and rough membrane surface fall into scenario 1. The effect of particle size on the total interactions in scenario 1 is depicted in Fig. 5. Basically, increase in particle size would increase the absolute value of total interaction energy, and decrease the absolute value of the specific interaction energy (the ratio of total interaction energy to foulant mass). It was worth noting that the variation in foulant particle size did not change the fact that there exists a critical roughness scale (Fig. 5). This result indicated that the existence of a critical roughness scale was applicable for the vast majority of foulant particles in the MBR reactor.
Total interaction energy (kT)
300 20 µm foulant
200
15 µm foulant 10 µm foulant
100 0
5 µm foulant
-100 -200 -300 0
2
4 6 8 10 Separation distance (nm)
12
14
Fig. 5. Variation of the total interaction profiles with particle size (asperity height = 300 nm, asperity radius = 300 nm, pH = 7.0).
This study revealed the existence of a critical roughness scale for interfacial interactions with rough surface, and thus provided important implications for membrane selection and fabrication in MBRs. If a membrane is designed to be with critical scale roughness, it is expected that foulant adhesion could be significantly impeded, and thus membrane fouling could be significantly reduced. For example, by simulating the lotus leaf surface morphology, some materials with high anti-adhesion ability have been fabricated (Yuan et al., 2013; Wang et al., 2014). The calculation method present in this study also provided a guideline for determining the value of critical roughness scale for a given MBR. This study suggested that membrane could be designed accurately for membrane fouling control based on assessment of interfacial inter-
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actions rather than experiences. In a recent review, Lalia et al. (2013) summarized the progress in membrane fabrication, and mentioned that there is still a challenge to ‘‘tailor’’ membranes with anti-fouling properties. The word ‘‘tailor’’ mainly refers to ‘‘design membrane surface morphology’’. By using the method developed in this study, such a challenge is expected to be overcome. This study showed the great potential to ‘‘tailor’’ membrane surface morphology to mitigate membrane fouling. In this regard, the findings of this study are significant. 4. Conclusion A combined method can be used to calculate the interfacial interactions between a foulant particle and rough membrane surface in a SMBR. There exist an energy barrier and two negative energy ranges in the profile of total interaction. The strength and properties of the interfacial interactions were significantly affected by the roughness scale and foulant size. A critical range of roughness scale was identified to be 2.3–4.5 in this study. This study provided a new method to ‘‘tailor’’ membrane surface morphology for membrane fouling mitigation. Acknowledgements Financial support of National Natural Science Foundation of China (Nos. 21275131, 51108424), Project of Science and Technology Department of Zhejiang Province (No. 2015F50013) and Zhejiang Provincial Environmental Protection Scientific Research Project (No. 2013A024) is highly appreciated. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2014. 12.055. References Bhattacharjee, S., Elimelech, M., 1997. Surface element integration: a novel technique for evaluation of DLVO interaction between a particle and a flat plate. J. Colloid Interface Sci. 193 (2), 273–285. Charman, K.M., Fernandez, P., Loewy, Z., Middleton, A.M., 2009. Attachment of Streptococcus oralis on acrylic substrates of varying roughness. Lett. Appl. Microbiol. 48 (4), 472–477. Chen, J., Zhang, M., Wang, A., Lin, H., Hong, H., Lu, X., 2012a. Osmotic pressure effect on membrane fouling in a submerged anaerobic membrane bioreactor and its experimental verification. Bioresour. Technol. 125, 97–101. Chen, L., Tian, Y., Cao, C.-Q., Zhang, J., Li, Z.-N., 2012b. Interaction energy evaluation of soluble microbial products (SMP) on different membrane surfaces: role of the reconstructed membrane topology. Water Res. 46 (8), 2693–2704. Dereli, R.K., Ersahin, M.E., Ozgun, H., Ozturk, I., Jeison, D., van der Zee, F., van Lier, J.B., 2012. Potentials of anaerobic membrane bioreactors to overcome treatment limitations induced by industrial wastewaters. Bioresour. Technol. 122, 160– 170. Feng, L., Li, X., Du, G., Chen, J., 2009. Adsorption and fouling characterization of Klebsiella oxytoca to microfiltration membranes. Process Biochem. 44 (11), 1289–1292. Giraldez, M.J., Resua, C.G., Lira, M., Oliveira, M.E., Magarinos, B., Toranzo, A.E., YebraPimentel, E., 2010. Contact lens hydrophobicity and roughness effects on bacterial adhesion. Optom. Vis. Sci. 87 (6), E426–31. Hoek, E.M.V., Agarwal, G.K., 2006. Extended DLVO interactions between spherical particles and rough surfaces. J. Colloid Interface Sci. 298 (1), 50–58.
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