EFFECT OF NANOPARTICLES ON THIN-FILM COMPOSITE MEMBRANE SURFACE MORPHOLOGY AND PRODUCTIVITY. Abstract. Background and Applicable Literature

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1 EFFECT OF NANOPARTICLES ON THIN-FILM COMPOSITE MEMBRANE SURFACE MORPHOLOGY AND PRODUCTIVITY Steven J. Duranceau, Ph.D., P.E., University of Central Florida, 4000 Central Florida Blvd., POB 62450, Eng.2-Suite 2, Orlando, FL , Ph. (407) Yuming Fang, University of Central Florida, Orlando, FL Abstract To evaluate the significance of thin-film composite membrane surface morphology on water productivity, flat-sheet experiments were conducted with silicon dioxide, titanium dioxide, and cerium dioxide nanoparticles. The polyamide thin-film active layer exhibited a valley and ridge morphology that was directly related to the surface roughness, and was found to contribute to particle accumulation in the valleys causing a higher flux decline than in smoother cellulose acetate membrane surfaces. Reverse osmosis and nanofiltration membrane flux decline was not affected by particle type when the feed water was laboratory grade water; however, when pretreated diluted seawater measuring 4800 μs/cm served as feed water it was found that cerium oxide addition resulted in the least observable flux decline, followed by silicon dioxide and titanium dioxide. Keywords: nanofiltration; nanoparticles; reverse osmosis; water productivity. Background and Applicable Literature Reverse osmosis (RO) and nanofiltration (NF) membranes represent an important set of pressure driven processes for domestic and industrial water treatment. [Zhao and Taylor 2005; Jamal, Khan and Kamil 2004; Zhao, Taylor and Chellam 2005]. The majority of RO membranes are manufactured in a spiral-wound configuration using thin-film composite (TFC) technologies. TFC membranes consist of three layers: a microscopically-thin active polyamide layer surface, a microporous polysulfone backing layer, and a polyester support layer. The polysulfone and polyester layers serve to support the thin-film membrane while the polyamide layer is the portion of the composite actively participating in the rejection of dissolved solutes [Avlonitis, Pavlou and Skourtis 20; Yip et al. 200]. The influence of surface characteristics on membrane process performance is considered significant and is not well understood. Current mass transport models generally assume constant mass transfer coefficients (MTCs) based on a homogeneous flat surface. With the application of atomic force microscopy (AFM), membrane active-layer characteristic such as surface morphology, pore sizes, and surface porosity can be determined and correlated to membrane fouling behavior. The AFM images presented in the work of Vrijerhoek and colleagues [200] show membrane surfaces as having an elevated ridge and depressed valley morphology, and concluded that the fouling behavior was related to the degree of surface roughness.

2 Fouling remains one of the major issues impacting RO and NF membrane process. Research has been conducted to reduce membrane fouling by improving membrane properties, maintaining ideal operating conditions, and implementing advanced pretreatment processes; however, fouling will still occur to some degree [Kim et al. 2003; Liikanen et al. 2002; Shaalan 2002]. Fouling may occur due to accumulation of particles on the membrane surface and depends on the particle s size, density and membrane surface roughness. An increase in particle concentration can lead to an increase in fouling, while smaller particles either causes more, or less, fouling as compared to larger particles [Tarabara, Koyuncu and Wiesner 2004; Zhang and Song 2004]. In addition, the ionic strength of the solution is an additional factor that can affect membrane fouling. As the ionic strength increases, the fouling potential increases as a result of the double layer compression formed around the colloids [Lee, Cho and Elimelech 2004; Lee, Cho and Elimelech 2005; Sing and Song 2005]. However, less research has been conducted that consider the influence of surface morphology on water productivity. The purpose of this study was to investigate the productivity of RO and NF membranes using flat-sheet, bench-scale equipment under laboratory conditions. It is postulated that nanoparticles impact flux decline depending on membrane morphology. To investigate the effects of chemical and physical interactions between the particles and the membranes, silica dioxide (SiO2), titanium dioxide (TiO2), and cerium dioxide (CeO2) served as foulants during the conduct of the experiments. Materials and Methodology Membranes Evaluated in Testing To take into account different membrane surface properties, two RO flat sheets and one NF flat sheet membrane sample representing different surface roughness were obtained for study (Sterlitech, Kent, WA, USA). The specifications of the membranes investigated in this study are shown in Table. The membrane samples were acquired as dry sheets and were stored in distilled (DI) water at room temperature prior to assembly into flat-sheet test cells. Designation Table. Specification of membranes used in the experiments. Membrane type Manufacturer Polymer * MWCO 2 Pressure, psi BW30 RO Dow Polyamide 00D 260 XLE RO Dow Polyamide 00D 30 CK NF GE Osmonics Cellulose Acetate * MWCO: Molecular Weight Cut Off. Nanoparticles Studies Commercial TiO2 (anatase, 99%, 5 nm), CeO2 (99.9%, nm), and SiO2 (99+%, 80 nm) nanoparticles (NanoAmor, Houston, TX, USA) were used in the fouling experiments. The nanoparticles were supplied in powder forms. The actual densities were g/cm 3 for SiO2, 3.9 g/cm 3 for TiO2, and 7. g/cm 3 for CeO2. This size range was selected so that the particles can pass through a typical cartridge filter. Currently, the engineering design standard of care in

3 pretreatment of brackish water RO desalination and groundwater NF pre-treatment is the use of 5-micron nominal pore-size cartridge filters. The nanoparticles used in this research are on the order of 0.2 µm or less and would pass through a standard cartridge filter. Nanoparticle concentrations were determined after several trials until a flux decline was observed. Prior to each experiment, the nanoparticles were dissolved in deionized water and t sonicated in a water bath ultra-sonicator for 30 min to maintain the nanoparticle suspension. Membrane Performance and Surface Properties Membrane productivity tests were performed using a CF042 cross flow flat sheet membrane filtration unit (CF042, Sterlitech, Kent, WA, USA). The membrane cell allows for evaluation of membrane film with an active surface area of 42 cm 2. The cell dimension is cm cm 30 ml. The pre-cut membrane was loaded into the cell and the system was run under recommended pressure for 20 min with DI water to remove any residual chemicals from manufacturing. The water was then drained and the system was filled with testing solution. The schematic flow diagram for the flat sheet testing instrument is shown in Figure. A.5 gal reservoir provided feed water into a high pressure pump. The flow rate and pressure were adjusted by the two valves located on the bypass and concentrate flow tubes. The feed flow was maintained at 757 ml/min, providing a cross flow velocity of 0.8 m/s (corresponding to a Reynolds number of 307). Permeate and concentrate flows were recycled into the feed tank to ensure a constant background electrolyte condition. The temperature was maintained at 2 C with a coil immersed in the feed tank and connected to a chiller unit. After a constant flux was achieved, a premixed sodium chloride solution was added to produce a 0.05 M salt concentration. After the NaCl solution was added, the unit was allowed to equilibrate for 20 h to allow compaction of the new membranes. A dose of the resultant nanoparticle suspension was then added into the feed tank to provide a feed concentration of either 35 mg/l or 405 mg/l. The flux was monitored by a flow meter continuously for the duration of experiment and recorded on a laboratory computer. Figure. Flat sheet unit testing flow diagram. 3

4 Relative flux, f/f0 Three runs were conducted for each membrane under three conditions: () a baseline, (2) a 35 mg/l nanoparticle addition, and (3) a 405 mg/l nanoparticle addition. Each individual run lasted approximately twenty hours. The membranes were tested with different nanoparticles and evaluated in terms of flux decline and salt rejection over time. Table 3 presents the initial flux rates for membranes that were tested with cerium dioxide. Results are presented in Figures 2 and 3 in terms of relative flux as function of time. Relative flux is expressed as the flux at any time during the test divided by the initial flux (f/f0). The baseline represents the runs with the background solution (0.05 M NaCl) and without nanoparticles. The difference between the permeate flux with nanoparticles in the feed stream and the baseline indicates the net contribution of nanoparticles to membrane productivity. Table 3. Initial flux for membranes being tested using CeO2. Initial flux BW30 XLE CK m/s gal/sfd Figure 2. Example of one experiment showing the relative flux as a function of time with CeO2 at three different particle concentrations for the XLE membranes. Similar curves were prepared for silicon dioxide and titanium dioxide but are presented elsewhere (Fang, Y, Duranceau, S.J. (203). Study of the Effect of Surface Morphology on Reverse Osmosis and Nanofiltration Membrane Fouling Behavior in Membranes. Vol(3): ) Base line 35mg/L 405mg/L Time, min 4

5 Relative flux, f/f0 Figure 3. Example of one experiment showing the relative flux as a function of time with CeO2 at three different particle concentrations for the CK membranes. Similar curves were prepared for silicon dioxide and titanium dioxide but are presented elsewhere (Fang, Y, Duranceau, S.J. (203). Study of the Effect of Surface Morphology on Reverse Osmosis and Nanofiltration Membrane Fouling Behavior in Membranes. Vol(3): ) Time, min Base line 35mg/L 405mg/L Similar to SiO2 and TiO2, there is significant flux decline for BW30 and XLE membranes when dosing with CeO2, while no obvious flux decline was observed for CK membranes. The magnitude of flux decline follows the same trend as testing with TiO2: the XLE membrane shows the most severe flux decline over the testing period, followed by the BW30 membrane; the CK membranes exhibit the least flux decline which indicates fouling resistant properties. The surface roughness of the BW30, XLE and CK membranes was measured by a Digital Instruments Nanoscope Atomic Force Microscope (AFM) and are shown in Figure 4. The AFM scans the surface with a cantilevered tip, generating a three-dimensional elevation map. The tip was operated in tapping mode to reduce the sample damage and maximize resolution. Surface elevation data can be used to determine the average roughness and the root mean squared (RMS) roughness. The average roughness is the average deviation of the peaks and valleys from the center plane; the RMS roughness is defined as the standard deviation of the peaks and valleys from the center plane. The parameters obtained from AFM analysis are shown in Table 2. 5

6 Figure 4. UCF atomic force microscopy (AFM) images of (a) DOW BW30 (RO); (b) DOW XLE (RO); (c) GE Osmonics CK (NF). Note the X and Y dimensions are both 0μm (2 μm/div), and the Z scale is μm (500 nm/div). Note that (c) is the cellulose acetate flat sheet membrane. (a) (b) (c) Table 2. AFM analysis of surface roughness. Membrane Average roughness (nm) RMS * (nm) Mean (nm) BW XLE CK * RMS: root mean square. Results & Discussion The results from the BW30 and XLE membranes show that greater flux decline is obtained at a higher SiO2 particle dosage, while no obvious flux decline was observed for the CK membranes. With an increasing particle concentration, the rate of mass transport of particles toward the membrane surface increases, thereby, the overall rate of particle deposition onto the membrane surface increases. As a result, the total mass of deposited particles increases, which resulting in higher resistance to water permeating the membrane and thus reduced water flux. The BW30 and XLE membranes were found to have a higher relative flux decline rate, while the flux through the CK membrane decreases at a much lower rate relative to the other three membranes. It is also noted that initial flux also plays a role in determining the flux decline rate. Typically a higher initial flux results in a higher flux decline rate [Zhu and Elimelech 997]. The initial flux for the BW30 membrane is slightly higher than the XLE membrane, but the flux decline rate is similar for these two membranes due to the differences in their surface morphology. 6

7 Relative flux, f/f0 Relative flux, f/fo Fouling Under Salinity Conditions Two different salinity waters, one made of 0.05 M NaCl in a laboratory, and a second prepared from pretreated seawater from Tampa Bay Water desalination s plant were evaluated. The particles were dosed into the feed tank at 35 mg/l after 20 h of particle free solution testing. The fouling behavior of the BW30 membranes were investigated and the relative flux with each of the three particles based on a 0.05 M NaCl solution was also determined. When using RO feed water from the Tampa Bay desalination plant, the permeate flux was found to decline at different rates; however, feeding with TiO2 resulted in the highest flux decline, and CeO2 appeared to relieve the fouling as compared to other two particles. It is noted that the flux decline between the laboratory-grade and diluted seawater feed solutions were found to be different. It is noted that the ionic strength differences may help explain the trends observed. Figure 3. Relative flux as a function of time using different source water: (a) 0.05 M NaCl; (b) diluted reverse osmosis (RO) feed water from Tampa Bay desalination plant Base line SiO2 TiO2 CeO Time, min (a) Base line SiO2 TiO2 CeO Time, min (b) 7

8 Conclusions In this work, bench scale membrane productivity experiments were conducted to investigate the role of membrane surface properties on the productivity of RO and NF. The following conclusions were reached. The severity of flux decline was influenced by membrane surface morphology. The polyamide thin-film active layer exhibited a valley and ridge morphology that was directly related to the surface roughness, and was found to contribute to particle accumulation in the valleys causing a higher flux decline than in smoother cellulose acetate membrane surfaces. Particles accumulate within the valley components of thin-film surface morphologies, causing more flux decline than in smoother membranes. Flux decline in laboratory-grade water occurred at a similar rate for the nanomaterials tested that included CeO2, SiO2 and TiO2. On the other hand, when pretreated diluted seawater measuring 4800 μs/cm served as feed water it was found that CeO2 addition resulted in the least observable flux decline, followed by SiO2 and TiO2 particles. Continuing Work This study is a component of ongoing flat-sheet, bench-scale studies being conducted in the Civil, Environmental and Construction Engineering Department within the College of Engineering and Computer Sciences at the University of Central Florida. Portions of this paper were in part published as an open access article by Y. Fang and S.J. Duranceau as Study of the Effect of Surface Morphology on Reverse Osmosis and Nanofiltration Membrane Fouling Behavior in Membranes [Volume (3): ] in 203. Acknowledgments The research was funded, in part, by UCF s Research Foundation through a grant provided by the Jones Edmunds Research Fund (Project ; RF047820), as well as Funding Agreement with the city of Sarasota, Florida. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of UCF (Orlando, FL), its Research Foundation, Jones Edmunds Associates, Inc. (Gainesville, FL) or the city of Sarasota, Florida. The mention of trade names or commercial products does not constitute endorsement or recommendation. The authors acknowledge the contribution of Hydranautics (Oceanside, CA) and UCF s Advanced Materials Processing and Analysis (AMPAC) in their provision of AFM membrane images, without which this work would not have been made possible. The authors would like to thank the City of Sarasota's Utilities and Utilities Department (Sarasota, FL) for providing full-scale reverse osmosis membrane process operations data that was relied upon for model development and validation. 8

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