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. 2021 Sep 16;13(38):46202–46212. doi: 10.1021/acsami.1c15948

Dual Functions of a Au@AgNP-Incorporated Nanocomposite Desalination Membrane with an Enhanced Antifouling Property and Fouling Detection Via Surface-Enhanced Raman Spectroscopy

Shixin Zhang †,‡, Durga P Acharya ‡, Xiaomin Tang ‡,§, Huaili Zheng †,*, Guang Yang ‡, Derrick Ng ‡, Zongli Xie ‡,*
PMCID: PMC8485324  PMID: 34528779

Abstract

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Membrane fouling has remained a major challenge limiting the wide application of membrane technology because it reduces the efficiency and shortens the lifespan of the membrane, thus increasing the operation cost. Herein we report a novel dual-function nanocomposite membrane incorporating silver-coated gold nanoparticles (Au@AgNPs) into a sulfosuccinic acid (SSA) cross-linked poly(vinyl alcohol) (PVA) membrane for a pervaporation desalination. Compared with the control PVA membrane and PVA/SSA membrane, the Au@AgNPs/PVA/SSA membrane demonstrated a higher water flux and better salt rejection as well as an enhanced antifouling property. More importantly, Au@AgNPs provided an additional function enabling a foulant detection on the membrane surface via surface-enhanced Raman spectroscopy (SERS) as Au@AgNPs could amplify the Raman signals as an SERS substrate. Distinct SERS spectra given by a fouled membrane helped to distinguish different protein foulants from their characteristic fingerprint peaks. Their fouling tendency on the membrane was also revealed by comparing the SERS intensities of mixed foulants on the membrane surface. The Au@AgNPs/PVA/SSA nanocomposite membrane presented here demonstrated the possibility of a multifunction membrane to achieve both antifouling and fouling detection, which could potentially be used in water treatment.

Keywords: membrane, pervaporation, antifouling, raman signals, SERS spectra, fouling tendency

1. Introduction

The rapid advance of membrane-based technology provides a cutting-edge strategy for water purification and the sustainable development of water resources via desalination.1−3 Among various membrane desalination technologies, pervaporation desalination has received increasing attention due to its unique advantages in handling high-salinity water, as its energy demand is independent of the salt concentration.4,5 However, membrane fouling and the lack of a high-performance membrane have been well-recognized as major obstacles to limit its commercial application. The severity of membrane fouling is a complex phenomenon that depends upon the type of foulant(s), the feed concentration, temperature, pH, and ionic strength as well as the separation system hydrodynamics, which could irreversibly reduce the overall performance of a membrane, including reduced water flux, salt rejection, and the stability of membrane properties; also, the increased replacement cost of a membrane furthermore hinders its economic viability.6−10 Among various types of membrane fouling, organic fouling is profound in membrane filtration dealing with source water containing proteins and other organic compounds.11 Significant studies have been conducted to overcome membrane fouling including pretreatment, membrane surface modification, and advanced mixed matrix membranes by doping nanomaterials.12,13 Despite these approaches, the identification of different types of pollutants on a membrane, the fouling process, and the tendency should also be taken into account as a vector of importance.

Numerous approaches have been applied to study the mechanism and fouling process of a membrane.14,15 Effective methods of monitoring and controlling the fouling would not only reduce membrane fouling but would also lead to an improved membrane cleaning. In particular, a real-time monitoring has the potential to achieve long-term stable industrial membrane processes.16,17 Ultrasonic time-domain reflectometry (UTDR) acts as a noninvasive and real-time technology to monitor the accumulation of pollutants on the surface of a membrane.18 Three-dimensional (3D) optical coherence tomography imaging is employed to clarify the 3D structure of filter cake and diagnose the deposit of the foulants precisely.19 Even though these techniques can reveal the fouling process in real-time, the difficulty in discriminating specific foulants limits their use to realize the fouling tendency of different molecules.

Surface-enhanced Raman scattering (SERS) is a powerful analytical tool that provides structural information on chemical and biological surfaces that can reach to the single-molecule level, making it a technique of high sensitivity, high efficiency, and short time consumption in discriminating substances at low concentrations20,21 and has been well-recognized as an effective tool in various fields, such as bacterial and virus detection, protein identification, protein sequence analysis, and environmental tests.22−24 The enhancement of an electromagnetic effect provided by gold nanoparticles (AuNPs) or silver nanoparticles (AgNPs) on a surface or near a surface of samples results in a stronger Raman scattering signal of adsorbed molecules than the ordinary Raman scattering signal.25,26 SERS has a great potential to detect and identify the trace organic matter on the fouled membrane surface.27 The versatile discrimination ability of SERS can reveal more information on foulants and help to explore a deeper understanding of complex membrane fouling mechanisms, but there are only a few reports of SERS being applied in the understanding of membrane fouling.28−30

Silver-coated gold nanoparticles (Au@AgNPs) are a widely utilized SERS substrate for its high Raman enhancement of 106 attributed to a higher SERS sensitivity and a better uniform distribution compared with AuNPs and AgNPs. It is a well-known mixed matrix membrane featuring inorganic fillers dispersed in a polymer matrix to form an organic–inorganic hybrid that can effectively improve the membrane performance such as water flux, salt rejection, and antifouling property.5,31−33 It is therefore speculated that the integrated assembly of Au@AgNPs incorporated into a traditional membrane can not only act as an SERS signal reporter for foulants discrimination but also control membrane fouling.

Herein we report a novel dual-function pervaporation membrane by doping Au@AgNPs into poly(vinyl alcohol) (PVA) cross-linked with sulfosuccinic acid (SSA) using a simple solution casting method.34 For the first time, Au@AgNPs were employed in a pervaporation membrane and served two crucial functions in both improving the membrane performance and enabling foulant detection. The desalination performance including water flux and antifouling property of the Au@AgNPs/PVA/SSA nanocomposite membranes were studied and compared with the control PVA membrane and PVA/SSA membrane. More importantly, we focus on the SERS activity of Au@AgNPs as a Raman signal reporter to detect and identify the type of proteins when mixed protein foulants (e.g., bovine serum albumin (BSA), ovalbumin (OVA), and lysozyme (LYS)) are present on the membrane surface. This strategy was further used to evaluate their fouling tendency and make a potential early diagnosis of membrane fouling.

2. Experimental Section

2.1. Materials

PVA (98+% hydrolyzed, molecular weight (Mw) 1.6 × 105), SSA, sodium chloride, potassium chloride, silver nitrate, sodium citrate (C6H5Na3O7), and ascorbic acid (C6H8O6) were obtained from Sigma-Aldrich. Gold chloride trihydrate (HAuCl4·3H2O), Rhodamine 6G (Mw: 497), humic acid (HA, Mw: 2000–5000), BSA (Mw: 66 430), OVA (Mw: 44 500) and LYS (Mw: 15 000) were purchased from Aladdin Chemical. All reagents were of analytical grade and used without further purification.

2.2. Synthesis of PVA/Au@AgNPs/SSA Membrane

The Au@AgNPs are described in the Supporting Information (Text S1: Synthesis of AgNPs; Text S2: Synthesis of AuNPs; Text S3: Synthesis of Au@AgNPs). The Au@AgNPs/PVA/SSA membrane was synthesized via an aqueous sol–gel route.34 Briefly, a predetermined amount of PVA powder was dissolved in 100 mL of deionized water at 90 °C until it fully dissolved to obtain a 3 wt % PVA solution. The solution was left to cool to room temperature, and an already prepared Au@AgNPs suspension was added into the uniformly dispersed PVA solution to achieve different Au@AgNPs loadings, followed by an addition of SSA, which accounts for 20% of the PVA mass. The doping mixture was then ultrasonicated in an ice bath for 30 min prior to being caste on a microporous substrate (polypropylene, 0.22 μm) using an automated coater via a solution casting method followed by ambient air drying for 16 h and heat treatment at 100 °C for 1 h. The mass ratio of Au@AgNPs to PVA was kept as 0.5, 1.0, 1.5, and 2.0% w/w, and the resulting membranes were named as M0.5, M1.0, M1.5, and M2.0, respectively. The control PVA/SSA membrane was named as M0. The thickness of the above membrane after drying is 230–250 nm.

2.3. Characterization

X-ray diffraction patterns of the membranes were collected on a Bruker D8 A25 wide-angle X-ray diffractometer (WAXD) with Cu K radiation (40 kV, 40 mA), and the crystallite size was estimated using MDI Jade 6 software. The surface and cross-section morphology of the membranes was analyzed using a Zeiss Merlin Gemini 2 Field Emission Scanning Electron Microscope (SEM). SEM images were obtained using an accelerating voltage of 3 kV. A Technai T12 Transmission Electron Microscope (TEM) was used to image the AgNPs, AuNPs, and Au@AgNPs. The surface roughness of the membrane was analyzed by atomic force microscopy (AFM, NSK Ltd., SPA400). An X-ray photoelectron spectroscopy (XPS) analysis of the fouled membrane was conducted with an ESCALAB250Xi (30 W, hv = 1486.5 eV, 1 eV energy resolution). SERS measurements were conducted by a confocal micro-Raman system (HORIBA Jobin Yvon S.A.S., LabRAM HR Evolution) with a 50× microscope objective and a 4 mm working distance, the laser tuned at 512 nm with 10% laser power level, and 10 s of exposure time.

The prepared membrane samples were dried to a constant weight and then immersed in deionized water at 25 °C for 2 d to reach their absorption equilibrium. The wet membranes were pat-dried with tissue paper, and their weights (Ws) were noted quickly. To obtain their dry weights (Wd) the membranes were dried for 16 h at 55 °C and weighed quickly to avoid moisture reabsorption. The degree of swelling (S) of the membrane can be obtained as follows.

2.3. 1

A KSV CAM200 contact angle meter equipped with an image capture and analysis function was used to measure the contact angle of the membrane by a sessile drop method. A 5 μL water drop was formed on the leveled surface of the membrane for contact angle measurements.

2.4. Pervaporation Test

The membrane performance was evaluated using a lab-scale pervaporation testing unit with details reported previously.35 Briefly, the membrane was placed in the middle of a pervaporation cell with a transport area of 9.6 cm2. Concentrated saline solutions or organic solutions (R6G, HA, BSA, OVA, and LYS as appropriate) were preheated to 35 °C in a water bath, which was then pumped to the pervaporation cell via a Masterflex peristaltic pump with a feed flow rate of 40 mL/min. The vacuum pressure on the membrane side of the membrane was kept at 6 Torr, and the permeate was condensed in a dry ice cold trap. The temperature of the feed solution was measured by a K-type thermocouple fixed in the feed chamber. Each experiment was conducted continuously for 2 h after it reached the steady-state operation. The conductivity of the feed and permeate were measured using a precalibrated Oakton Con 110 conductivity meter.

Water flux and salt rejection were used to evaluate the pervaporation desalination performance of membranes. The water flux (J) was determined from the mass (M) of permeate collected in the trap, the effective surface area of membrane (A), and the pervaporation time (t) (eq 2). The salt rejection (R) was calculated from the salt concentration of the feed (Cf) and permeate (Cp) derived from the measured conductivity of the feed and permeate, respectively (eq 3).

2.4. 2
2.4. 3

To ensure the accuracy of the salt rejection result, the permeate side of the membrane cell was flushed with a known volume of deionized water at the end of each experiment, and the conductivity measured in this washing water was also accounted toward the overall salt rejection.

3. Results and Discussion

3.1. Membrane Characterization

X-ray diffractograms collected from control (PVA/SSA) and doped membranes are presented in Figure 1A. The characteristic peak for the control membrane appears at ∼19.8, which corresponds to the typical peak for PVA and is consistent with previous studies.34,36 Three distinct peaks at 2θ ∼38°, ∼44°, and ∼64°in the X-ray diffractogram collected from the doped membranes correspond to the (111), (200), and (220) peaks for Au@AgNPs,37 confirming the presence of Au@AgNPs. With the increased loading of Au@AgNPs in the membrane, the intensity of Au@AgNPs peaks increased, but the characteristic peak of PVA became broader and smaller. This occurs as a result of the increase in amorphicity and a decrease in crystallinity for the composite membrane owing to the cross-linking among PVA, SSA, and Au@AgNPs.38 A further exploration of the crystallite size of a PVA membrane and its composite membrane, as shown in Table 1, reveals that the crystallite size of M0 was the largest, whereas that of M2.0 was the smallest. As the loading of nanoparticles increases, the size of the membrane crystal becomes smaller. For a single crystal, the smaller the size, the smaller the resistance to water, which will lead to greater water flux. Besides, nanoparticles will induce an increased disorder in the molecule chain arrangement of PVA resulting in a lower crystal growth velocity; it may also reflect an increase in membrane flux,34 which will be demonstrated in Section 3.2 (Pervaporation Test).

Figure 1.

Figure 1

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(A) XRD patterns of M0, M1.0, M1.5, M2.0; (B) SEM images of M0 (surface); (C) SEM images of M0.5 (surface); (D) SEM images of M1.0 (surface); (E) SEM images of M1.5 (surface); (F) SEM images of M2.0 (surface); (G) SEM images of M0 (cross-section); (H) SEM images of M2.0 (cross-section); (I) EDS layer image of M2.0, green is C, blue is Au, and pink is Ag; (J) EDS spectra of area shown in layer image of M2.0 (taken from the circled part of figure I).

Table 1. Crystallite Size and Full Width at Half-Maximum of M0, M1.0, M1.5 and M2.0.

sample type fwhm crystallite size (nm)
M0 0.585 2.4 ± 0.1
M1.0 0.953 2.0 ± 0.3
M1.5 0.971 1.9 ± 0.2
M2.0 0.973 1.8 ± 0.1
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Figure 1B, Figure 1C, Figure 1D, Figure 1E, and Figure 1F show surface SEM images of M0, M0.5, M1.0, M1.5, and M2.0, respectively. M0 exhibited a clean, smooth, and nonporous surface, but as the Au@AgNPs loading increases, more nanoparticles appeared on the surface making the membrane surface rougher and uneven in thickness, which seems to have an impact on the water flux of the membrane, which will be discussed later. Cross-section SEM images of M0 and M2.0 are presented in Figure 1G and Figure 1H, respectively. It is speculated that the reduced crystallinity due to the incorporation of Ag@AgNPs improved the free volume and therefore enhanced the filtration performance as demonstrated in previous studies.34,35 An energy-dispersive X-ray spectroscopy (EDS) analysis of the M2.0 surface confirms the presence of the main elements C, O, Ag, and Au (Figure 1J), and an EDS layered image showed that these elements are uniformly distributed on the surface of the hybrid membrane (Figure 1I). EDS elemental mappings of C, O, S, Na, Ag, N, and Cl on the surface of M2.0 are presented in Supporting Information (Figure S1), and the results comply with the theoretical added amount.

Another important property of a membrane is the swelling tendency. Figure 2 shows the results of the swelling degree of all hybrid membranes after being soaked in water. The pristine PVA swelling degree was 285 ± 5%, much greater than that of M0 (52.1 ± 5%), which indicated that the swelling behavior of the PVA membrane was greatly suppressed owing to the covalent linkages formed between SSA and PVA. Although there are no chemical reactions between SSA and Ag@AuNPs, the doped nanoparticles increased the cross-linking density between PVA and SSA, resulting in a suppression of polymer chain mobility.39−41 That also contributed to a restraint of the membrane swelling in water. The swelling degrees of a hybrid membrane with different Au@AgNPs loading are as follows M0 > M0.5 > M1.0 > M1.5 > M2.0. That is, an increase of the Au@AgNPs loading in a PVA/SSA membrane helps to restrain the membrane swelling properties. The results of a contact angle measurement (Figure 2) show that the membrane surface becomes more hydrophilic with the loading of Au@AgNPs, and with the increasing loading of nanoparticles, the contact angle decreases monotonically from 80.7° for M0 to 68.5° for M2.0. It is well-known that the improved hydrophilicity will favor the water transport and enhance the water flux, while reduced swelling will enhance the salt rejection.38

Figure 2.

Figure 2

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Swelling degree and contact angle of M0, M0.5, M1.0, M1.5, and M2.0.

3.2. Pervaporation Test

Figure 3A shows the pervaporation desalination performance of a Au@AgNPs/PVA/SSA nanocomposite membrane and a PVA/SSA control membrane using a 3.5 wt % KCl and 3.5 wt % NaCl aqueous solution at a feed temperature of 35 °C and a permeate pressure of 6 Torr. Compared to the control membrane M0 (18.6 kg/m2 h), all the Au@AgNPs doped nanocomposite membranes showed a significantly enhanced water flux, which doubled at the 0.5% loading (M0.5) and more than three times (57.8 kg/m2 h) at the 1.5% loading (M1.5). This could be attributed to the following reasons. First, it is expected that the incorporation of a Au@AgNPs nanofiller disrupts the polymer chain packing to increase the membrane free volume, resulting in the enhanced water flux.38 In addition, as a semicrystalline polymer, the crystalline region of PVA is impermeable to the water, which reduces the polymer chain mobility thus increasing the path length of diffusion. When more Au@AgNPs are introduced into the PVA chain, the amorphous region of the membrane increases, as confirmed by X-ray diffraction (XRD), which could aid the diffusions of water molecules.42 Moreover, the increased membrane hydrophilicity with increased Au@AgNPs loading, as indicated by contact angle data (Figure 2), could have facilitated the sorption of a membrane surface contributing to the water flux increase. At the same time, the nanoparticle also affects the channel of water. The crystallite size in M1.0, M1.5, and M2.0 is 2.0, 1.9, and 1.8, respectively. And their increased water flux ratio compared with that of M0 is 134.41%, 211.29%, and 187.63%, respectively. With the increase of surface roughness, the effective surface area of the membrane increases, and consequently the water flux of the membrane increases. The rough region of the membrane could also affect the physical and chemical properties of the membrane such as surface tension, tensile properties, temperature resistance, and oxidation resistance properties, as reported in previous studies.43,44 It is worth noting that a further increase of Au@AgNPs loading to 2.0% (M2.0) has resulted in the decrease of water flux, which could be due to the uneven distribution of nanoparticles in the polymer matrix. A similar phenomenon was also found with graphene oxide (GO), carbon nanotubes (CNT), and silica nanoparticles in a membrane.31,32,45 The salt rejection performance of a hybrid membrane was also improved by the addition of Au@AgNPs (Figure 3B). Compared with the control PVA/SSA membrane, the Au@AgNPs modified membranes show a further enhancement on salt rejection for both NaCl and KCl, achieving a high salt rejection of 99.0%. Combining the membrane performance based on water flux, salt rejection, and swelling behavior, M1.5 appears to be the best-performing hybrid membrane and was therefore chosen for further study on antifouling performance. We compared the performance of the Au@AgNPs enhanced PVA membrane at the optimal loading (M1.5) in this study with those best-performing membranes reported in the literature, and the results are shown in Table S1 in the Supporting Information. The M1.5 membrane has outperformed most of the membranes reported in the literature and achieved the highest water flux at a feed temperature of only 35 °C (Table S1).

Figure 3.

Figure 3

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(A) Water flux. (B) Salt rejection of M0, M0.5, M1.0, M1.5, and M2.0.

3.3. Antifouling Properties of the Membrane

3.3.1. Membrane Fouling Test

M0 and M1.5 were subject to fouling study using the feed solution containing a single organic foulant, and the results are shown in Figure 4. Three compounds, namely, Rhodamine 6G (R6G), HA, and BSA, which are common organic foulants present in wastewater and have different molecular weights (Mw: R6G < HA < BSA), were chosen as the model foulant to investigate the antifouling properties of these membranes. As shown in Figure 4A, over the 2 h testing, the water flux of the Au@AgNPs/PVA/SSA membrane only shows a negligible or slight decrease for all three types of foulant. As a comparison, the M0 showed a significant decrease over the 2 h (41%∼43%) for these foulants. Interestingly, M0 showed a different sensitivity and vulnerability toward the organic foulant with a different molecular weight. The water flux decreased faster for the foulant with a higher molecular weight and, therefore, is more prone to be fouled by a macromolecular organic foulant. On the contrary, the incorporation of Au@AgNPs significantly improved the antifouling property of the membrane; its high water flux is retained over the testing period of 2 h and is hardly affected by the organic foulant molecular weight differences. The organic foulant concentration effect on the fouling property of the membrane was also studied. For each foulant, three different feed concentrations (10, 100, and 200 mg/L) were used, and the water flux after 2 h is shown in Figure 4B. M1.5 exhibited a 3.9% and 7.1% decline of flux when the concentration of R6G increased from 10 to 100 mg/L and to 200 mg/L, respectively. For HA, the corresponding declines are 2.6% and 8.3%, whereas for BSA, these are 2.9% and 9.1%. For M0, however, the corresponding flux drop is significantly worsened for all three foulants, with a 22.0% decline with an increase in the R6G concentration from 10 to 100 mg/L and 42.4% for 10 to 200 mg/L, and corresponding flux decline values are 22.1% and 44.7% for HA and 26.8% and 45.6% for BSA, respectively. On the basis of these results, M1.5 shows a superior and enduring antifouling ability regardless of the organic species, concentration, and molecular weight during pervaporation.

Figure 4.

Figure 4

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(A) Flux change of M0 and M1.5 vs time with single foulant at the concentration of 100 mg/L. (B) Flux comparison of M0 and M1.5 at different foulant concentrations after 2 h of testing.

3.3.2. Membrane Fouling Analysis

To further investigate the membrane fouling from a quantitative perspective, XPS was employed to reveal more information about the elemental components present on the membrane surface before and after the pervaporation (PV) test using BSA as the foulant. A wide-scan survey of XPS spectra displayed the extent of fouling on M0 and M1.5. X-ray photoelectron spectroscopy surveys are shown in Figure S2 in the Supporting Information. Figure S2A,C showed that the main elements of both membranes are C, O, N, and S. With the element S in membranes attributed to BSA and SSA, and N mainly attributed to BSA, a change in the ratio of elements S and N before and after the pervaporation test was used as a quantitative measure of membrane fouling arising from the deposition of BSA on a membrane in this study. As shown in Table 2, there are big differences in the proportion of two elements in M0 and M1.5. For M0, the proportion of N has increased from 0.6% to 8.6% (net gain of 8%), and S has increased from 0.7% to 1.7% (net gain of 1%) after 2 h of pervaporation, which is much higher than the net gains of 1.3% and 0.4% for N and S, respectively, for the M1.5 during the same time. These results provide evidence that the doping of Au@AgNPs on a membrane greatly suppresses the deposition of protein-based foulants, thus improving the membrane antifouling property, which is also consistent with the flux variation as discussed earlier.

Table 2. Proportion Change of N and S on the Membrane Surface (M0 and M1.5) before and after the Membrane Fouling Test.
  element (atom %)
  C O S N Aga Aua
M0 before test 75.3 23.4 0.7 0.6 N/A N/A
M0 after test 64.8 24.9 1.7 8.6 N/A N/A
M1.5 before test 70.3 24.8 0.8 0.5 1.7 2.0
M1.5 after test 68.3 25.3 1.2 1.8 1.5 1.9
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a

N/A indicates not applicable.

The morphology and surface roughness of M0 and M1.5 before and after the pervaporation testing were further studied using AFM, with results shown in both Figure 5 and Table 3. AFM images in Figure 5 showed a big difference between both M0 and M1.5 after these membranes were fouled by BSA. Although the surface of the initial M0 (roughness parameter Rq = 33.8) is smoother than that of M1.5 (Rq = 70.7), its roughness increased by 173.7% after 3 h of pervaporation testing. On the contrary, the roughness of the M1.5 only increased by 13.4% over the same period. This is comprehensible in that more protein molecules blocked on the surface of M0 greatly changed the roughness of the membrane as well as the height of the membrane from −81.4–94.9 nm to −280.5–310.1 nm. These data have provided a substantial evidence of the enhanced antifouling property of the M1.5, which is mainly attributed to the enhanced hydrophilic property of Au@AgNPs doped membrane (Figure 2), as hydrophilic membranes are less prone to organic fouling.46,47 In addition, the good antibacterial property of Au@AgNPs might have been an added advantage to inhibit the bacterial growth on the membrane surface,45,46,48,49 thereby contributing to the better antifouling property of the NP-doped membrane compared to that of the control.

Figure 5.

Figure 5

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Surface morphology of M0 before (A) and after (B) pervaporation and that of M1.5 before (C) and after (D) 3 h of pervaporation.

Table 3. Rq and Height of M0 and M1.5 before and after the Pervaporation Test.
  Rq (nm) height (nm)
M0 before test 33.8 –81.4–94.9
M0 after test 92.5 –280.5–310.1
M1.5 before test 70.7 –266.5–287.4
M1.5 after test 80.2 –279.6–270.6
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3.4. SERS Activities of M1.5

SERS is a promising technique that can provide a spectral fingerprint of biological and chemical molecules with high sensitivity and high selectivity, with the aid of a strong electromagnetic field generated by metallic nanoparticles. Its detection capability will enable the discrimination of multiple proteins of membrane fouling even in a low concentration,50,51 and because of this ability the technique has been used here to study the fouled surface of the doped membrane.

The high SERS activity of M1.5 was evaluated through the Raman spectra of R6G. The Raman intensity of R6G powder on a glass slide is very weak compared to the SERS intensity of 10–9 R6G dropped on the surface of M1.5 (Figure 6D). TEM images of AgNPs, AuNPs, and nanoparticles with a 5 nm shell core thickness are shown in Figure 6A–C. The SERS enhancement of the three kinds of nanoparticles was evaluated by dispersing a drop of 10–9 R6G on the surface of these nanoparticles, and results are shown in Figure 6E. It was found that AgNPs with a high SERS enhancement lacked regularity in particle size and caused an unstable SERS intensity in practical tests, and AuNPs were uniform in particle size but were poor in SERS enhancement. The combined metal Au@AgNPs were shown to be stable and gave the most intense SERS signals, and therefore they were employed in this study.

Figure 6.

Figure 6

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TEM of (A) AgNPs, (B) AuNPs, and (C) Au@AgNPs; (D) SERS intensity of R6G powder on a glass slide and 10–9 R6G dropped on the surface of M1.5; (E) SERS intensity of 10–9 R6G dropped on the surface of the three nanoparticles. (F) SERS intensity of 10–9 R6G dropped on the surface of the M1.5 membrane that has a different shell thickness of Au@AgNPs.

We also investigated the SERS activities of Au@AgNPs with different thicknesses of Ag shell with a Au core diameter of 1, 3, 5, and 7 nm, and as it can be seen in Figure 6F, the SERS intensity and sensitivity of Au@AgNPs are enhanced as the shell thickness is increased from 1 to 5 nm, but the SERS activity is reduced once the shell thickness exceeds 5 nm, which is probably caused by the precipitation and the instability of Au@AgNPs as the shell thickness increases. Hence, Au@AgNPs with a 5 nm shell (Ag) thickness are used to fabricate M1.5 and are applied in the following SERS test.

3.5. Protein Fouling Identification by SERS

Figure 7A shows Raman spectra of three different solutions of protein (BSA, OVA, and LYS; 100 mg/L, respectively) fouled on M1.5 and BSA fouled on M0 (control group) after 4 h of pervaporation, together with the spectra of a blank solution without Au@AgNPs, where no signal was obtained. These results show, consistent with previous reports,52 that distinctly different SERS spectra observed for these proteins can be used to identify these individual proteins from their peak positions. Specifically, BSA shows seven characteristic peaks at 617, 650, 1219, 1355, 1499, 1522, and 1650 cm–1, which could be attributed to C–C twisting, OH out-of-plane bending, the amine III of proteins, tryptophan, C=C stretching in a benzenoid ring, carotene, and amide I, respectively.53−55 These peaks are almost missing in the case of LYS and OVA. Six peaks that were observed in SERS spectra of OVA are assigned to tryptophan, collagen, d(CH), υs COO– (IgG), C=C stretching in benzenoid ring, and protein amide I absorption from left to right, respectively.55−57 SERS features from LYS were also distinguishable from two other proteins. They are dominated by the bands of amino acids, such as the C–S stretching mode of cysteine, proline, phenylalanine, tyrosine, and amide I band of proteins, due to C=O stretching (at 653, 825, 1032, 1164, and 1600 cm–1, respectively).53,58 These differences may be correlated with different amino acid species and protein spatial structures and, therefore, produce a signature pattern that allows us to distinguish three proteins.

Figure 7.

Figure 7

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(A) Raman spectra of three different solutions of protein (BSA, OVA, and LYS; 100 mg/L, respectively) fouled on M1.5 and BSA fouled on M0 (control) after 4 h of pervaporation. (B) Intensity and RSD of the 1650 cm–1 peak of BSA fouled on M1.5.

Additionally, to verify the uniformity and stability of the SERS intensity, five sites on each fouled membrane were selected to measure the SERS spectra for a total of 50 measurements (5 spots × 10 measurements at one spot = 50 measurements for a protein). Very good consistency in the intensity values of BSA for its characteristic peak at 1650 cm–1 were obtained from five different spots with a relative standard deviation of 10.4%, and this serves as a reliable basis for the identification of the proteins on the fouled membrane. The consistency of the intensity values of signature peaks obtained from different spots of doped membranes for LSY and OVA as well, as shown in the Supporting Information (Figure S3: SERS intensity of five sites of membrane and the relative standard deviation (RSD) of (A) LYS and (B) OVA), means this approach has a high potential to identify different kinds of proteins fouled on a membrane and to evaluate their roles in the fouling process, which in turn can pave an easy way for a deeper exploration of membrane fouling processes and mechanisms.

In real situations, the wastewater generally contains a mixture of different foulant types. It is worthwhile to investigate the fouling tendency of different proteins on a membrane exposed to the mixture of foulant proteins to explore the mechanism of membrane fouling, which in turn can provide crucial information needed to develop a membrane pretreatment method before the pervaporation and also to design a specific membrane with a high selectivity and high durability. Herein, a new approach was employed to study the fouling tendency by comparing the intensity of SERS spectra of a protein mixture simply dropped on the membrane surface and that of foulants from the surface of a membrane filtrated by a protein mixture after a pervaporation for 2 h. The fouling tendency should be reflected by their SERS signals, because the SERS intensity of the protein with a higher tendency to cause fouling in pervaporation is expected to be stronger than that of the membrane surface receiving a protein solution dropped onto it.

Figure 8A displays the SERS spectra of a protein mixture (LYS and OVA at different ratios, combined concentration: 100 mg/L) dropped on M1.5. The characteristic peaks of LYS start to appear when LYS/OVA = 6:4 and become more distinct at a ratio of 9:1. After a pervaporation by M1.5, the SERS spectra of the two proteins do not show a significant difference compared to that of a dropped protein mixture on the membrane (Figure 8B), which implies that LYS and OVA have a similar fouling tendency on the M1.5. The fouling tendency of BSA and LYS was also investigated by the same method (BSA and LYS at different ratios, combined concentration 100 mg/L). The SERS intensity of BSA is much stronger than that of LYS when the protein solution is dripped onto the membrane (Figure 8C), and only at the ratio of LYS/BSA = 9:1 did the typical SERS spectra of LYS appear at 825, 1032, 1164, and 1600 cm–1 together with the characteristic peaks of BSA. We can barely see the SERS bands of LYS at the ratio of LYS/BSA = 7:3 and 6:4, and only peaks of BSA can be observed. However, after a pervaporation, only bands of LYS appeared, and no bands of BSA were found (Figure 8D), which indicated that the membrane was fouled predominantly by LYS. The SERS spectra of BSA on a fouled membrane can only be observed when the protein in the fouling solution was at a high concentration (200 mg/L) indicating that BSA when compared to the other two proteins has a low tendency to foul the membrane. Overall, the order of membrane fouling tendency of the three proteins was found to be LYS ≈ OVA > BSA.

Figure 8.

Figure 8

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SERS spectra of BSA (B, C), LYS (A–D), and OVA (A, B) with different ratios from a drop of protein solution on the membrane M1.5 (A, C) and from the foulant after pervaporation (B, D) through the membrane. Total concentration of protein was 100 mg/L (A–D) except the first (top) line of Figure 8D, for which the total concentration is 200 mg/L.

4. Conclusions

This study developed a new Au@AgNPs/PVA/SSA nanocomposite membrane by doping the surface-enhanced Raman spectroscopy substrate silver-coated gold nanoparticles Au@AgNPs into the polymer membrane matrix via a simple solution casting method, and this membrane was evaluated for a pervaporation desalination. The antifouling property of the membrane for some common organic foulants as well as the tendency of the membrane to be fouled by three different proteins was studied using the highly selective and extremely sensitive SERS as a tool. At a 1.5% loading of nanoparticles, the nanostructured Au@AgNPs/PVA/SSA membrane showed an excellent desalination performance with 99% salt rejection and a high water flux of 57.9 kg/m2 h, tripled to that of the pristine membrane. The enhancement in the water flux is attributed to a more hydrophilic and rough surface as resulted from Au@AgNPs doping. Moreover, the Au@AgNP-doped membrane showed significantly improved antifouling properties toward common organic foulants compared to the pristine membrane. Taking three proteins (LYS, OVA, BSA) as foulants, we have demonstrated that SERS can not only detect the foulant but also distinguish the type of proteins deposited on the membrane surface by analyzing intensities of recognition peaks from the fingerprint SERS spectra unique to each protein. The order of fouling tendency by these three proteins is LYS ≈ OVA > BSA. It is worth noting there are still some limitations of application of SERS for a complex membrane fouling detection due to its reproducibility and stability of SERS signal. Further development is required to expand its application. In addition, SERS can be combined with other technologies/materials to increase the application scope in the identification of membrane pollutants, such as antibiotics, pathogen, dyes, virus, and aromatic molecules.59−64 This study also provides a promising approach toward sensing and monitoring membrane fouling as well as comparing the affinity of foulants toward a membrane surface by using SERS as a tool in more complex conditions to get an insight into the fouling mechanism. This can further provide crucial tips for a fouling control and the development of antifouling membranes. It is worth mentioning that the use of Au@AgNPs as nanoadditives could slightly increase the membrane manufacturing cost due to the high cost of Au@Ag nanoparticles but will have the advantage of cost savings in the pervaporation process that resulted from the required membrane area and the membrane replacement and cleaning cost. Further optimization and a techno-economic study are still needed in the future work.

Acknowledgments

The authors acknowledge the financial support from CSIRO Manufacturing and Chongqing University. S.Z. acknowledges the scholarship from China Scholarship Council (CSC). The authors acknowledge the CSIRO characterization group and facilities for the great support in material characterization and analysis. Special thanks are given to Dr. A. Trinchi (CSIRO) for the Raman training, M. Greaves (CSIRO) and Dr. M. de Vries (CSIRO) for the SEM analysis, J. White (CSIRO) for the TEM imaging, and Dr. A. Seeber (CSIRO) for the XRD analysis.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsami.1c15948.

  • Additional synthetic experimental details; EDS elemental mapping; X-ray photoelectron spectroscopy survey; SERS intensity of five sites of membrane and RSD of LYS and OVA; and comparison of the PV (M1.5) performances to those reported in literature (PDF)

The authors declare no competing financial interest.

Supplementary Material

am1c15948_si_001.pdf (572KB, pdf)

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