Performance evaluation and fouling analysis for reverse osmosis and nanofiltration membranes during processing of lignocellulosic biomass hydrolysate

Journal of Membrane Science 451 (2014) 252–265

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Performance evaluation and fouling analysis for reverse osmosis and nanofiltration membranes during processing of lignocellulosic biomass hydrolysate AmitKumar Gautam, Todd J. Menkhaus n Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, 501 East St. Joseph Street, Rapid City, SD 57701, United States

art ic l e i nf o

a b s t r a c t

Article history: Received 30 July 2013 Received in revised form 18 September 2013 Accepted 20 September 2013 Available online 14 October 2013

Lignocellulosic biomass is a renewable feedstock for the production of fuels and chemicals. After acid pretreatment and enzymatic hydrolysis, the biomass produces a stream containing dilute sugars, along unwanted fermentation inhibitory compounds. Two promising approaches to increase process efficiencies and economics are to increase the sugar concentration and decrease inhibitor concentrations prior to fermentation. In this study, reverse osmosis (RO) and nanofiltration (NF) membranes were evaluated for their ability to separate inhibitors (e.g., organic and mineral acids, furans and phenolic compounds) from sugars, while simultaneously concentrating the sugars. A range of RO and NF membranes were tested that exhibited different chemistries and pore-sizes, and performance evaluation was assessed by measuring permeate flux, retention (yield) of sugars, the ability to separate inhibitors, and ease of cleaning. Performance varied considerably between the different membranes evaluated, with sugar yields in the retentate ranging from below 20% to nearly 100%. Generally, lower sugar yields also corresponded to higher inhibitor separation factors. Flux reduction for most membranes was primarily caused by reversible fouling, but in many cases a significant contribution also came from elevated osmotic pressure due to retention of soluble compounds. To improve fouling characteristics and maintain elevated flux during operation of the RO and NF membranes, lower surface roughens and higher hydrophilicity provided more favorable properties, along with larger number of pores. At the same time, the ability to separate inhibitors, which contributed significantly to osmotic pressure flux reduction, was also beneficial. & 2013 Elsevier B.V. All rights reserved.

Keywords: Biorefinery Biorenewable processing Reverse osmosis Nanofiltration Membrane fouling

1. Introduction Biorenewable fuels and chemicals have shown tremendous potential toward reducing our dependence on petroleum derived products. Different raw materials have been used for the production of biorenewables, such as rice straw, switch grass, aspen, poplar, corn stover, pine, and municipal solid waste [1–3]. Many of the feedstocks are regionally available and make biorefining possible throughout the United States. One example is the Black Hills of South Dakota, which are a rich source of ponderosa pine and can be used for biorefinery applications. This is especially important as dead and dying pine wood is abundantly available due to recent pine beetle infestations [4]. Within a typical bio-refinery, the raw biomass material undergoes size reduction and pretreatment (e.g., liquid hot water, weak

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acid, strong acid, alkaline, organic-solvent, wet oxidation, steam explosion, ammonia fiber expansion [AFEX], or CO2 explosion) to breakdown the biomass structure and release cellulose and hemicellulose from the lignin sheath. This is followed by enzymatic hydrolysis to convert cellulose and hemicellulose into hexose and pentose sugars, respectively [5–12]. While these operations have been extensively developed and have become very efficient at conversion of the biomass into monomeric sugars, unfortunately the final sugar concentration prior to downstream conversion to fuels and chemicals by fermentation is often very low ( o30 g/L). This is because of the fibrous nature of the lignocellulosic feed stock results in thick, viscous slurries when blended with water during pretreatment and enzymatic hydrolysis. This limits the percentage of biomass in the original slurry and ultimately the final sugar concentration at the end of hydrolysis [5]. For example, using reported compositional analysis data, dry pine wood contains
37 wt% glucan, and
21 wt% combined fraction of xylan, mannan and galactan [5]. Along with this, a typical starting ratio of dry biomass in a slurry is 10% (w/v) [5,8]. Therefore, assuming

A. Gautam, T.J. Menkhaus / Journal of Membrane Science 451 (2014) 252–265

100% conversion of cellulose and hemicellulose into sugars during pretreatment and enzymatic hydrolysis, the final glucose concentration would only be
37 g/L and a combined xylose, mannose and galactose concentration of 21 g/L. More realistically, due to the economic need for lower enzyme loading during enzymatic hydrolysis, as well as the presence of enzymatic inhibitors in the pretreated biomass (e.g., aldehydes, acids, and phenolic compounds), the conversation of biomass into sugars is often less than 80%, which results in glucose concentrations below 30 g/L, and similar reductions in other sugar concentrations [5,7]. In turn, for ethanol production, the final product concentration following fermentation is a direct function of sugars concentrations, and thus is also limited to relatively low values (e.g. at 30 g/L glucose, ethanol has a maximum final concentration of
15 g/L, if only glucose is fermented) [13–16]. The final fermented product concentration has a dramatic effect on the requirements of the downstream separations (operations required to recover product and remove residual water and other impurities). For instance, in order to minimize energy in the downstream recovery of ethanol from water via distillation, the glucose concentration should be as high as possible prior to fermentation, leading to elevated ethanol concentrations (the maximum threshold may be limited by the tolerance of the fermentation organism to ethanol toxicity). Distillation is the most energy intensive operation in a standard lignocellulosic bioethanol process, consuming more than 50% of the total energy consumption. If the feed glucose concentration can be increased from 30 g/L to 100 g/L, Aspen Plus process simulations indicate that distillation energy will be reduced by over 70% [17]. Therefore, efficient and economical processes are needed to concentrate sugars prior to fermentation by removing water from the hydrolysate. Reverse osmosis (RO) and Nano-Filtration (NF) have been found to be promising operations for similar water removal requirements in the desalination and fruit juice industries as an alternative to evaporation [18–21]. Evaporation itself is an energy intensive process due to the high latent heat of water and could also be problematic because of the high temperatures employed that may thermally degrade the sugars, resulting in low quality dark colored/charred products with high concentrations of fermentation inhibitory compounds (i.e., acetic acid, hydroxymethyl furfural and furfural) [5,18,22]. It has previously been shown that for concentration of “thin juice” in the sugar industry by reverse osmosis in conjunction with an evaporator, a 33% reduction in energy consumption was reported relative to an evaporation only process [18–21]. However, concerns remain

Biomass (Ponderosa pine)

Size Reduction

253

regarding the robustness of the RO and NF membranes for these applications, with a high propensity for severe fouling. Another concern when employing reverse osmosis is that permeated water could have a small amount of sugar, which would translate into reduced product yields. Neither of these concerns (membrane fouling and sugar loss) have been explored within a biorefinery process when applying real biomass RO or NF system. During pretreatment of the lignocellulosic biomass, some sugar decomposition and lignin degradation occurs, resulting in fermentation inhibitory compounds formation, such as acetic acid, levulinic acid, formic acid, uronic acid, furfural and 5hydroxymethylfurfural (HMF), and phenolic compounds such as 4-hydroxybenzoic acid, vanillic acid, vanillin, phenol, catechol, and cinnamaldehyde [22,23]. One concern with using reverse osmosis or nanofiltration is that not only will sugars be concentrated, but there is the possibility that inhibitors will also become concentrated in the retentate. A high concentration of inhibitors will negatively impact the fermentation and hence there would be a need to remove these inhibitors prior to fermentation in order to achieve a high yield and elevated rate of product formation. Fortunately, several methods have been developed specifically for inhibitory compounds removal from biomass process streams, either before or after enzymatic hydrolysis. For instance, membrane extraction using an aliphatic amine allowed for 60% removal of acetic acid from glucose [24]. Other methods, such as polyelectrolyte adsorption with polyethyleneimine (PEI) showed up to 88% and 66% removal of furfural and HMF, respectively, from different biomass hydrolysate samples [25,26]. As an extension of this, sequential polyelectrolyte (PEI) and resin–wafer electrodeionization (RW-EDI), indicated more than 77%, 60% and 74% removal of acetic acid, HMF and furfural respectively, and reported an increase in downstream fermentation conversion efficacy by 94% after removal of inhibitory compounds [5]. Currently, even without the additional steps that would be needed for removing inhibitory compounds, separation accounts for 60–80% of the processing cost of a typical biorefinery process [24]. Fortunately, in addition to allowing for increased downstream processing efficiencies due to reduced inhibitory compound concentration, the separated chemicals could also act as high value co-products to offset some of the additional costs. Fig. 1 shows a general biorefinery process to convert biomass into biofuels via the biochemical pathway. Of particular note is that reverse osmosis and nanofiltration are options to simultaneously concentrate sugars and remove inhibitors in an enzymatic hydrolysate. If the separation could be achieved, the cost of

Enzymatic Hydrolysis

Lignin-rich solids

Pre-treatment (Dilute acid)

Solid/Liquid Separation (0.22µm filter) Soluble (dilute) sugars Distillation Concentrated sugars Fermentation

Reverse Osmosis/ Nanofiltration

High value Inhibitory Compounds

Fig. 1. Flowsheet for sugar concentration and inhibitor recovery using reverse osmosis or nanofiltration within a biorefinery.

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multiple steps for sugar concentration and inhibitors separation can be minimized. Previous studies suggest that RO membranes have been able to retain all sugars in a simulated hydrolysate, but also retained any inhibitors that were added to the artificial mixture. On the other hand, NF membranes have shown the ability to concentrate and separating sugars from other soluble components in simple mixtures [27–31]. For instance, using a simple acetic acid and glucose binary solution that would be found in thermochemical biomass process, it was shown that over 90% of the sugar could be retained while permeating up to approximately 50% of the acetic acid. Similarly, it was shown that approximately 90% of a sugar mixture could be retained while removing over 30% of aldehyde compounds [32,33]. However, it was also discovered that the interaction of the different compounds with glucose may have contributed to unexpected retention of some species. As part of this, the solution conditions (especially pH) were found to play an important role in the ability to concentrate sugars and remove other soluble compounds [29–31]. Thus, as the solution became more complex within a real biomass hydrolysate, the separation became more difficult to predict. In addition, flux decline, membrane fouling and cleaning requirements of reverse osmosis and nanofiltration membranes were not addressed. In this paper we report the ability to separate sugars from inhibitors, within a real biomass enzymatic hydrolysate, in a single step using five different RO and six different NF membranes. In addition to yield and separation factors, extensive evaluations were completed to understand flux decline and fouling mechanisms associated with the operation. Combining the different performance indicators has provided a well-defined road map for the utilization of RO and NF membranes within biorefining to concentrate sugars and simultaneously remove and purify inhibitory compounds such as acetic acid, furfural and hydroxymethyl furfural.

2. Materials and methods 2.1. Materials 2.1.1. Dead-end filtration system A dead-end filtration system with stationary mixer was used for all RO and NF experiments. The system consisted of a 300 mL

stirred cell (Sterlitech, HP4750) pressurized with nitrogen, and active membrane surface area of 14.6 cm2. The maximum pressure that the system could withstand was 1000 psi. A pressure gauge and regulator to adjust the pressure according to the membrane limits were purchased from Sterlitech Corporation. Compressed nitrogen for all experiments was supplied by Linweld (Rapid City, South Dakota). A Corning stirrer/hot plate was used to maintain the desired constant stirring speed within the stirred cell at 500 RPM and temperature at 25 1C. A 100 mL graduated cylinder was used to determine all initial and final permeate and retentate volumes, and 15 mL centrifuge tubes were used to collect 10 mL permeate samples with time to calculate flux and store for compositional analysis. All supplies mentioned above for flux and volume measurements were purchased from Fisher Scientific. 2.1.2. Membranes Commercially available thin film (GE Osmonics SE), thin film composite polyamide (TFC-XR Koch) and polyamide flat sheet (Toray-70UB) reverse osmosis (RO) membranes, and thin film (TF GE Osmonics HL), thin film composite polyamide (TFC-SR100 Koch), proprietary composition (SelMPF-34 Koch), polypiperazine amide (TriSep-TS40) and polyamide (TriSep-TS80) nanofiltration (NF) membranes were purchased from Sterlitech Corporation (Kent, WA). Thin film composite BW30, SW30 and thin film composite polyamide NF90 flat sheet membranes were kindly donated by Dow Filmtech™. A detailed list of all membranes and the basic parameters provided by supplier are listed in Table 1. The membrane thickness provided by the supplier is give as a total thickness (active “skin” layer plus support layer). All RO and NF membranes were cleaned with de-ionized (DI) water to remove any surface preserving agents prior to testing and were stored in DI water between experiments, with water replaced frequently to prevent microbial growth. 2.1.3. Chemicals Ultrapure water, hexose sugars (glucose, galactose and mannose), pentose sugars (xylose and arabinose), sulfuric acid (95–98% w/w) and ammonium hydroxide were purchased from Fisher Scientific.

Table 1 Membrane characteristics provided by individual suppliers (Sterlitech Corporation and Dow Filmtech). Designation (SKU)

Reverse osmosis SW30HR BW30 Koch TFC-XR

GESE Toray 70UB

Manufacturer

membrane Dow Dow Koch membrane systems GE osmonics Toray

Nanofiltration membrane SelRO MPFKoch 34 membrane systems NF90 Dow TS40 TriSep

Polymer

Molecular weight cut-off (MWCO)

NaCl rejection %

Membrane thickness, Δx (m)

25C pH range

Typical flux/ operating pressure, GFD (psi)

Polyamide Polyamide TF (thin film) composite polyamide TF (thin film) Polyamide


100 Da
100 Da 0 MWCO

99.6 99.5 99.7

1.60E  04 1.60E  04 1.30E  04

2–11 2–11 4–11

17-24/800 26/255 Not measured

0 MWCO 0 MWCO

98.9 99.7

1.70E 04 1.40E  04

1–11 2–11

22/425 27/225

Proprietary

200 MWCO

2.30E  04

0–14

35/440


200–400 D 200 MWCO

1.60E  04 1.40E  04

2–11 2–11

46.0-60.0/130 20/110

1.10E  04

2–11

20/110

150–300 MWCO 200 MWCO

1.40E  04 1.30E  04

3–9 4–10

39/100 Not measured

TS80

TriSep

Polyamide Polypiperazine amide Polyamide

GE HL TFC-SR3/TFCSR100

GE osmonics Koch membrane systems

TF (thin film) TF (thin film) composite polyamide

150 MWCO

40–60% (99.0% – MgSO4) 80–90% (99.0% – MgSO4) 98% – MgSO4

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2.1.4. Woodchips Ponderosa pine wood chips (containing approximately 15 wt% moisture) were kindly provided by Baker Timber (Rockerville, SD) in sawdust form. The saw dust was sieved to obtain a dust size of o850 mm for all experiments and air dried. The composition of the pine wood, as determined by using chemical analysis and testing laboratory analytical procedures (LAP) – LAP-002, LAP-003, LAP-004, LAP-014, LAP-015 developed at the National Renewable Energy Laboratory (NREL), was 36.5% glucan, 20.9% combined xylan, mannan, and galactan, 7.3% acid soluble lignin, 30.5% acid insoluble lignin, 1.6% ash, 1.8% ethanol extractive and 1.4% water extractive [5,7]. 2.2. Methods 2.2.1. AFM analysis Surface roughness of the RO membranes was determined by Atomic Force Microscopy (AFM) imaging and analysis (Multi-Mode AFM, Digital Instruments, Santa Barbara, CA). Imaging was performed in tapping mode with aluminum coated, silicon doped probes (MULTI40A, Bruker Nano Inc. Camarillo, CA) by using a set variable Z (nm/division) established for each membrane. MULTI40A probes, used for all AFM measurements, had a spring constant of 0.9 N/m, resonant frequency of 34–46 kHz, normal tip radius of 8 nm, and cantilever length of 225 mm [32–34]. Surface roughness of the NF membranes was determined by using an Agilent SPM 5500 equipped with MAC III controller from Agilent technologies. Imaging was performed in tapping mode with Pt/Ir coated, silicon doped probes, type PPP-NCLPt-SPL, by using a set variable Z (nm/division) established for each membrane as discussed in results. Membranes capable of utilizing a low Z value during testing resulted in a low RMS values, indicating the membrane was relatively smooth; conversely membranes with a high Z value led to a high RMS value, indicating the membrane surface was relatively rough. SPL probes, used for all NF AFM measurements, had a force constant of 21–98 N/m, resonant frequency of 146–236 kHz, tip height of 10–15 mm, and cantilever thickness 7 mm, length 225 mm and width 38 mm [32,33]. 2.2.2. Contact angle measurement Contact angle as a measure of hydrophobicity or hydrophilicity of the RO or NF membranes was measured using the ramé-hart Model 500 Advanced Goniometer with DROP image Advanced v 2.4 analysis (City NJ, US) [35,36]. Ten equilibrium contact angles were measured at different locations for each membrane within two seconds for each location, and each equilibrium contact angle was the average of the left and right contact angles. Reported values are the average of the ten equilibrium measurements. 2.2.3. BET for pore size and pore volume measurement Clean membranes were removed from storage in DI water, allowed to air dry, and then in order to minimize error of pore blockage from water molecules were degassed with nitrogen at 20 1C for 30 min. These clean and dry membranes were used to determine the average pore diameter, pore surface area and pore volume using the micromeritics Gemini II e 2375 Brunauer Emmett Teller (BET) surface area analyzer. BET analysis was carried out three times for each membrane and the average value of the pore diameter was reported. Once the pore diameter was determined, the number of pores was calculated in conjunction with pure water flux measurements for each membrane [37–43]. According to Hagen–Poiseuille law for no fouling, when there is no solute in the feed water, and assuming laminar flow through capillary tubes (membrane pores) of radius r, the flux is proportional to the number of pores, pore size and transmembrane pressure as shown by Eq. (1), where J, d, ΔP, μ; Δx and N are the flux, pore diameter,

255

transmembrane pressure, viscosity of the permeate (water in this case), membrane thickness and number of pores, respectively. Thus, by measuring the pore diameter, flux and transmembrane pressure, we were able to estimate the average total number of pores [44]. NπΔPd 128μΔx

4

J¼

ð1Þ

2.2.4. HPLC analysis For both pure sugars and enzymatic hydrolysate experiments (discussed below), the original feed, permeate, retentate and wash samples were first filtered through a 0.2 mm nylon syringe filter (Fisher Scientific, Pittsburgh, PA) to remove any suspended solids. In order to analyze for sugars and inhibitory concentrations, clear filtrate (50 mL) was injected on to a heated Aminex ion exclusion column HPX-87H (Bio-rad, Hercules, CA). The HPLC system (Beckman Coulter, Brea, CA) was equipped with a refractive index (RI) detector (Model RI-1530) and the column was heated to 65 1C with a Timberline Instruments Model 105 column heater. Samples were eluted with a flow rate of 0.6 mL/min using 5 mM H2SO4 as the mobile phase. The system was equipped with a Cation-H Refill Cartridge (Bio-Rad, Hercules, CA) as a guard column. Five standard concentrations of each compound being measured (glucose, xylose, arabinose, mannose and galactose (499% pure, Fisher Scientific, Pittsburgh, PA), acetic acid, ethanol (200 proof), and aldehydes: 5hydroxymethyl furfural and furfural (Sigma Aldrich, St. Louis, MO)) were prepared to calibrate the column for accurate analysis. Due to the separation using the HPX-87H column, xylose, mannose and galactose were combined into a single “xylose peak” and analyzed as a combined concentration as discussed in more detail by Carter et al. [25,26]. All other species were separated as single compounds and the concentration analyzed individually. 2.2.5. Measurement for the concentration of total solids Dilute acid pretreatment not only produced pentose sugars, hexose sugars, acetic acid, HMF and furfural, but it also produced some “unmeasured” components (unidentifiable by the HPLC methods used) such as mineral and organic acids, ash components, phenolic compounds and suspended solids. These additional components, along with others not analyzed by HPLC, but quantified as part of the total solids (suspended plus soluble), will be referred to as “unidentified components”. These “unidentified components” were taken into account during mass balance calculations. In order to carry out the mass balance for all of the measured and unidentified components present in feed, retentate and permeate, 5 mL samples were dried in an oven at 100 1C for a minimum of 36 h (this allowed all of the water to evaporate without fusing solids that would trap water). The remaining total solids (composed of suspended and soluble solids) were weighed, and the concentration determined by difference compared to the initial mass of sample. The concentration for all the “measured components” was obtained from HPLC analysis as described above. Then the concentration of measured components was subtracted from the dried samples to determine the mass of “unidentified components” in the feed, retentate and permeate samples. 2.2.6. Dilute acid pretreatment All biomass pretreatment processing was performed using a 4-L stirred vessel Parr reactor (Parr Instrument Company, Moline, IL) equipped with an internal cooling jacket, along with temperature and agitation control. Slurry was prepared according to NREL LAP 007 with 10 dry wt% pine and 1% w/v H2SO4. Pretreatment was performed at 160–165 1C, at 120–150 psi, and 100 RPM stirring for 30 min [5,25]. The calculated combined severity factor for these operating conditions was 2.39. After cooling to room

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temperature the slurry was neutralized from pH
1.3 to pH 5.0 by addition of NH4OH. Due to the limited size of the reactor, the pine wood was pretreated in batches of 3 L and the slurries obtained were mixed to form one large batch of 9 L to ensure continuity between processing operations. The pretreated slurry was stored at 4 1C until further analysis and testing. 2.2.7. Enzymatic hydrolysis The commercial second-generation cellulase cocktail Cellic CTec (supplied by Novozymes A/S, Bagsvaerd, Denmark) was used in all enzymatic hydrolysis experiments. A dosage of 3.4 g enzyme/ 100 g cellulose was added to the pre-treated slurry. The amount of cellulose was calculated from composition of pine wood and the amount of biomass added during pretreatment. Enzymatic hydrolysis was carried out at 50 1C in 500 mL Erlenmeyer flasks placed in a shaker at 200 RPM for 72 h [5]. 2.2.8. RO and NF performance experiments using pure sugar mixtures A pure sugars mixture mimicking a typical biomass enzymatic hydrolysate was prepared by using 40 g/L glucose, 20 g/L xylose, 10 g/L mannose, 10 g/L galactose and 10 g/L arabinose. This mixture was utilized to isolate performance characteristics prior to the addition of the complex hydrolysate containing sugars, inhibitory compounds, suspended solids and potentially unknown species. For each of the RO and NF membranes, a challenge loading volume of 70 mL of the sugars solution was added to the membrane cell. All of the membranes were operated at their respective constant maximum operating pressure and room temperature (RO membranes SW30, BW30, Koch and GE were analyzed at 4.035 MPa, while Toray used 3.345 MPa; similarly NF membranes MPF34, NF90 and GEHL were tested at 3.35 MPa and TS40, TS80 and SR100 at 2.66 MPa). The stirred cell was set at a constant stirring speed of 500 RPM using a magnetic stirrer provided with the system that was approximately 4 mm above the membrane surface. Once a constant flux was obtained for ultrapure water (the “pre-water flux”), the water was removed and 70 mL of sugars mixture was added to the stirred cell and allowed to operate while concentrating the sugars. All of the experiments were repeated two times with a new membrane for each trial. To obtain the permeate flux, 10 mL of permeate was collected in a 15 mL of centrifuge tube and the required time was noted for every 10 mL of permeate. Once 50 mL of permeate were collected, the final retentate volume was collected in a separate centrifuge tube and its volume was measured. A brief 20 mL water flush was used in the stirred cell at 500 RPM for 10 min to remove any residual solution on the membrane surface. Then in order to thoroughly clean the membrane, it was rinsed (both back side and forward side) under a high flow stream of DI water for 10 min. The membrane was again placed into the stirred cell, the permeate flux was measured with ultrapure water and flux was reported as the “post cleaning water flux” as an indication of to irreversible fouling due to permanent pore fouling and clogging. The same procedure was repeated for all of the RO and NF membranes. 2.2.9. RO and NF experiments using lignocellulosic hydrolysate The prepared lignocellulosic hydrolysate was passed through a 0.2 μm membrane using vacuum filter in order to separate any large insoluble solid particles prior to RO and NF experiments. Ultrapure water was used to measure the pre-use water flux through the stirred cell as described previously. After microfiltration, 85 mL of the clarified enzymatic hydrolysate was fed to the stirred cell (this volume allowed for the same total sugars being loaded to the membrane as the pure sugars analyses experiments). All membranes were operated at their respective constant

maximum operating pressure at room temperature as indicated previously. The stirred cell was set at a constant stirring speed of 500 RPM using a magnetic stirrer. All of the experiments were repeated two times with the new membranes for each trial. For every 10 mL of permeate collected in a 15 mL centrifuge tube the time was noted to determine the permeate flux. Once the flux reduced to approximately zero, the final retentate volume was collected in a separate centrifuge tube and its volume was measured. Following the RO and NF experiments with enzymatic hydrolysis, the post use sequence described above for the pure sugars experiments was completed.

3. Calculation of flux reduction values Three different flux reduction values were calculated as an indication of where flux loss came from during operation: reversible fouling, irreversible fouling and osmotic pressure. For this, pre-use water flux ðJ prewater Þ and postcleaning water flux ð J postwater Þ were measured as described above. The difference between these water flux values was due to irreversible fouling, and this loss of flux was denoted J if ; as shown in Eq. (2). At the end of each trail, for either pure sugar or enzymatic hydrolysate, the final flux was calculated and given the notation J sugar mixture or J enzymatic hydrolysate . Also at the end of the RO or NF process, flux decline due to osmotic pressure of soluble compounds (J Δπ ) was calculated by Eq. (3), where Rm was the membrane resistance calculated from pre-use water flux values when osmotic pressure was zero, R was the ideal gas constant and T was the absolute temperature. Osmotic pressure was estimated from measured concentrations of total soluble compounds in the retentate (Cret) and permeates (Cperm), as shown in Eq. (4). Bulk concentration values at the end of concentration were used as estimates of concentrations at the membrane surface, which is assumed to be a close estimate because flux in all cases approached zero. Finally, flux loss due to reversible gel layer formation ðJ gel Þ was calculated as shown in Eq. (5). These methods of identifying different flux resistance values during operation and the associated flux reduction has been reported in detail previously [45–50]. J if ¼ J prewater  J postwater J Δπ ¼

ðΔπ Þ μRm

ð2Þ ð3Þ

Δπ ¼ ðC ret  C perm Þ RT

ð4Þ

J gel ¼ J prewater  ðJ sugar mixture þ J if þ J Δπ Þ

ð5Þ

3.1. Calculation of RO and NF membrane separation performance The performance of the different membranes to separate sugars from inhibitors within a lignocellulosic hydrolysate was calculated from the separation factor (α). This was completed as shown in Eq. (6), where C inh; p and C sug; p are the concentrations of inhibitors and sugars, respectively, in the permeate, and C inh; r and C sug; r are the concentrations of inhibitors and sugars, respectively, in the retentate. Separation factor αinh=sug indicates the separation of all inhibitors with respect to sugars [30,51,52]. Separation factors for individual sugar and inhibitor pair were calculated in a similar fashion.

αinh=sug ¼

C inh; p =C sug; p C inh; r =C sug; r

ð6Þ

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257

Fig. 2. (a) AFM images showing surface roughness of the RO membranes evaluated. (b) Atomic force microscope images showing surface roughness of the nanofiltration membranes. Table 2 RO and NF membrane measured parameters. Contact angle (deg)

Membrane thickness, Δx (m)

Δp (MPa)

Number of pores, N

Diameter of pore d (m)

Reverse osmosis membranes BW30 75 SW30 103 KOCH 8 GE 20 Toray 72

45 51 33 64 57

1.60E  04 1.60E  04 1.30E  04 1.70E  04 1.40E  04

4 4 4 4 3.3

1.10E þ 14 1.10E þ 14 2.00E þ 14 6.10E þ 13 1.10E þ 14

4.90E  09 3.90E  09 3.70E 09 4.60E  09 4.70E 09

Nanofiltration membranes MPF34 NF90 TS40 TS80 GEHL SR100

39 52 22 51 29 39

2.30E  04 1.60E  04 1.40E  04 1.10E  04 1.40E  04 1.30E  04

3.35 3.35 2.66 2.66 3.35 2.66

2.16E þ 14 1.11E þ 14 1.70Eþ 14 1.89E þ 14 1.53E þ 14 6.85E þ 14

3.90E  09 4.52E  09 5.17E  09 4.53E  09 4.13E  09 3.86E  09

Membrane

Atomic force microscopy (AFM), RMS (Rq) (nm)

42 36 48 17 10 9

4. Results and discussion 4.1. Characterization of the RO membranes 4.1.1. Surface roughness of RO membranes AFM images displaying the surface roughness of the five RO membranes are shown in Fig. 2(a). The in-plane horizontal (X and Y) scales are 20 mm  20 mm (5 mm/div), while the vertical Z-axis varied with respect to the surface roughness of each of the RO membranes. As can be seen from the analysis shown in Table 2,

the RMS (Rq) value of SW30 membrane is 103 nm, which indicates that the surface roughness is very high compared to the other membranes. On the other hand, the Koch membrane was found to be the smoothest, with an RMS (Rq) value of 8 nm. In the case of the GE membrane, the roughness was visible directly, without magnification. It appeared that this membrane was manufactured with more than
80% of the surface having a very high roughness that could not be measured by AFM, because of the high probability of breaking the AFM tips. Outside of areas with course roughness, the smooth part of the GE membrane showed an RMS

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(Rq) of only 20 nm, which was similar to other relatively smooth membranes [53,54]. Atomic Force Microscopy (AFM) images showing the surface roughness of the six nanofiltration (NF) membranes are shown in Fig. 2(b). The in-plane horizontal (X and Y) scales are 5 mm  5 mm (5 mm/div). As can be seen from this analysis, and shown quantitatively in Table 2, the RMS (Rq) roughness value of the membranes varies from below 10 nm to nearly 50 nm. The lowest RMS values were found for the SR100 and GEHL membrane, which indicates that these membranes are relatively smooth compared to the others; especially the TS40 and MPF34 membranes [32–34]. “Valley” regions on rough membranes are of irregular shapes and may become clogged by insoluble solids or similarly sized molecules. Thus, depending upon the particle size of insoluble solids present in the feed, they may not completely plug the porelike valley, but are still capable of clogging and restricting the flow through that valley. Furthermore, since particles are preferentially transported into the valley, valleys quickly becomes clogged with multiple layers of densely packed particles, which in turn are responsible for building up of the resistance to flow through the membrane. According to the Carman–Kozeny equation, the resistance of a single layer of 140 nm particles to pure water permeation is over 1000 times more than that of the clean membrane. This analysis indicates that for a 10% observed declination in permeate flux, it would require a cake layer of only approximately 1 nm thick [54,55]. Therefore, the surface roughness provides an easily measured membrane physical property that may indicate a propensity for rapid decrease in the permeate flux if any small insoluble solids are present in the feed stream (as was the case when using biomass enzymatic hydrolysate). Conversely, in the case of relatively smooth membranes, the chances of valley clogging are reduced and offer a higher probability of sustaining elevated fluxes.

Table 3 RO and NF membrane water flux values and percentage flux reductions from different forms of fouling; where “Jif” represents flux decline from irreversible fouling, “Jgel” shows reversible gel layer fouling flux decline, and “JΔπ” corresponds to flux reduction from osmotic pressure.

4.1.2. Hydrophilicity and pore characterization of RO and NF membranes Depending on the chemical characteristics of the membrane material, the surface displays hydrophilic or hydrophobic properties, which in turn can be correlated to pure water permeability of the membrane (PM), and may also provide a reason for fouling from similarly hydrophilic/hydrophobic molecules in a complex feed stream. The contact angle, used as a quantitative measure of hydrophobicity/hydrophilicity, depends on the interfacial tensions of the interfaces involved. For a highly hydrophilic surface, a water droplet placed on the surface spreads along the surface and the contact angle is small [35,36]. In contrast, the water contact angle at a hydrophobic surface is high. The fouling potential of hydrophobic membranes may be higher due to the high binding affinity of other hydrophobic substances, especially in complex feed samples such as lignocellulosic hydrolysate, which contain elevated concentrations of hydrophobic phenolic compounds from lignin. In addition to the hydrophilic/hydrophobic properties, the membrane pore size, porosity (number of pores) and roughness also affect the contact angle measurement for the membrane. As can be seen from Table 2, the estimated pore sizes of all the RO membranes are similar and on the order of 4–5 nm, which may have been elevated due to inclusion of all pores (both within the active skin layer as well as supporting structure). However, the contact angle is significantly different for RO membranes. The Koch membrane was found to be the most hydrophilic, while the GE membrane was the most hydrophobic. Membrane characteristics such as high hydrophilicity, low surface roughness, bigger pore size and high porosity has been shown to lead to high

flux and minimum fouling for desalination and other separation operations [54,56–64]. For the NF membranes evaluated in this study, the contact angle value suggests that all NF membranes were relatively hydrophilic, but that the TS40 and GEHL were the most hydrophilic compared to rest of the membranes. It is expected that hydrophobic foulants (such as soluble and insoluble phenolic compounds present in biomass hydrolysates) will be less likely to cause fouling on more highly hydrophilic membrane surfaces. Along with hydrophilic/hydrophobic properties, membrane porosity, pore size, surface charge and surface roughness also increase/decrease the flow properties of a membrane. As can be seen from Table 2 the number of pores for RO and NF membranes ranges from 6.1E þ13 to 2.0E þ 14 and 1.11E þ 14 to 6.85E þ14, respectively. Depending upon the pore characteristics and molecular size of the foulants in the biomass hydrolysate, the pore can become completely clogged or constricted. Especially problematic are physical and chemical interactions between insoluble solids and the membrane, as well as bridging effects between a small molecule interacting with the membrane surface and a larger insoluble solid [25,26]. Pore diameter was similar for all NF membranes as shown in Table 2, but SR100 had a relatively high porosity (high number of calculated pores) compared to the other NF membranes. SR100 being relatively hydrophilic, less rough and highly porous, explains the reasoning for having a higher relative water flux compared to the other NF membranes, even though operated at a lower pressure. NF90 on the other hand, being relatively less hydrophilic, higher roughness and lower porosity resulted in lower relative water flux, even though operated at a higher pressure compared to

Post Membrane Sugar mixture (SM) Pre-use water flux cleaning or enzymatic 2 (L/m /h) water flux hydrolysate (EH) (L/m2/h) Reverse osmosis membrane BW30 SM EH

Individual % flux reduction %Jif

%Jgel %JΔπ

115.8 115.8

89.4 58.8

22.8 49.2

49.6 27.4 27.8 22.6 55.1 25.8 16.9 18.2

SW30

SM EH

45.6 45.6

37.2 16.2

18.4 64.5

KOCH

SM EH

82.2 82.2

75 54.6

8.76 62.9 27.8 33.6 40 26.2

GE

SM EH

45.6 45.6

29.4 19.8

35.5 56.6

Toray

SM EH

91.2 91.2

82.2 75

9.87 53.4 36.6 17.8 78.8 2.61

Nanofiltration membrane MPF34 SM EH

52.6 52.6

52.2 52.6

0.54 96.1 3.37 0 47.1 52.9

34.6 26.8 15.4 27

NF90

SM EH

70.2 70.2

64.1 49.3

8.88 58 33.1 29.8 36.1 34.1

TS40

SM EH

167.8 167.8

164.5 167.8

TS80

SM EH

139.3 139.3

137.2 97.6

1.67 95.9 2.42 29.9 28.7 41.3

GEHL

SM EH

77.0 77.0

70.6 69.5

8.58 11.8 79.7 9.97 28.8 61.3

SR100

SM EH

224.6 224.6

224.6 224.6

2 0

0 0

83.4 14.6 31.4 68.6

63 36.9 26.3 73.7

A. Gautam, T.J. Menkhaus / Journal of Membrane Science 451 (2014) 252–265

30 25

Flux (L/m2h)

some other membranes. It should be re-iterated that all membranes were operated at their maximum supplier recommended pressure, as a basis for comparison. Finally, it was found that the MPF34 was relatively thicker than other membranes evaluated. Membrane thickness provides additional resistance to flow and leads to decrease in the membrane permeability as the pore where water flows is longer and provides additional resistance and greater opportunities for constriction. The size of pore, pore volume, and surface area all play a major role in membrane selectivity, along with the hydrophilic/hydrophobic interactions and charge interactions between the surface and soluble and insoluble particles in the feed stream. While no charge characteristics were measured for the membranes, this may also contribute to observed differences seen in the results that follow.

259

20 BW30

15

SW30 KOCH

10

GE Toray

5 0

0

0.01

0.02

0.03

0.04

0.05

0.06

Cumulative Vol. (L)

4.2. Flux profiles and separation performance during RO and NF operations for pure sugar mixtures and enzymatic hydrolysate

18 16 14

Flux (L/m2h)

In the stirred cell apparatus used for all experiments, equal membrane area was available for filtration irrespective of the membrane types and operating conditions. All of the RO and NF membranes were operated at their maximum operating pressure and at room temperature of
25 1C to evaluate the flux with pure water, sugars mixture and enzymatic hydrolysate. Table 3 shows the pre-use water flux results for the all of RO and NF membranes with respect to ultrapure water, along with the percentage flux reduction values during operation for the various contributors to flux decline. In the case of RO membranes, the BW30 membrane had a relatively larger pore size and higher number of pores, along with being more hydrophilic and less rough [34,54,56]. This combination resulted in the highest pre-use water flux value. On the other hand, GE and SW30, which showed the opposite characteristics compared to BW30 as seen in Table 3, had lower pre-use water flux values [56–64]. This served as the baseline for other comparisons. Fig. 3A shows the flux profile of RO membranes during concentration of the pure sugar mixture. BW30 and Koch, even though they are relatively highly porous (large number of pores), less rough and more hydrophilic, showed lower flux performance for the pure sugar mixture; whereas Toray, SW30 and GE, being more rough and less hydrophilic showed better flux performance (higher sustained values) [34,35]. In general, for the pure sugar solution, membranes with larger pore sizes (with either relatively more or less total number of pores) proved to have the highest sustained flux values. In addition to flux performance, the ability to retain sugars was also considered as an important metric for comparison. As shown in Table 4, the sugar concentrations for the Toray membrane showed 27–36% loss of sugars in the permeate, even though it had a better flux performance than other membranes. Similarly, the GE membrane also exhibited higher sugar losses, especially arabinose. As expected, this elevated sugar loss is highly correlated to the membranes with relatively larger pore sizes. Fig. 3B shows the flux profile of RO membranes during processing of the lignocellulosic hydrolysate mixture. The flux values for the lignocellulosic hydrolysate were found to be lower than the pure sugars mixture for all membranes due to the much more complex feedstock [25,28,29]. The Toray RO membrane had the highest flux throughout the operation, followed by BW30 and Koch. As can be seen from Table 5, retentate concentrations for all five membranes were similar, with all components being highly retained. Thus, the addition of compounds beyond sugars likely caused pore constriction that reduced losses in the permeate (especially for the Toray membrane) compared to pure sugars alone.

12 BW30

10

SW30

8

KOCH

6

GE

4

Toray

2 0

0

0.01

0.02

0.03

0.04

0.05

0.06

Cumulative Vol. (L) Fig. 3. Reverse osmosis: flux profiles during sugar concentration process with either [A] a pure sugars mixture, or [B] a pretreated enzymatic hydrolysate. [A] Flux profile during concentration of pure sugars mixture. [B] Flux profile during concentration of enzymatic hydrolysate.

Table 4 Percentage rejection and concentration of pure sugars in feed and retentate. Sugar components

Glucose (g/L)

Reverse osmosis membrane Feed concentration (g/L) 36.3

Xylose (g/L)

37.1

Arabinose (g/L)

7.6

Percentage rejection of each sugar component BW30 96 93 89 SW30 99 99 99 KOCH 92 92 76 GE 97 96 61 Toray 73 70 64 Nanofiltration membrane Feed concentration (g/L) 36.3

37.1

7.6

Percentage rejection of each sugar component MPF34 87 86 85 NF90 81 80 79 TS40 77 66 61 TS80 80 75 72 GEHL 58 51 46 SR100 65 58 55

Total sugar concentration (g/L)

81.0 211 224 204 211 160 81.0 240 224 188 199 126 155

Unfortunately, along with high retention of sugars, inhibitors and unmeasured components were also nearly all retained. The inhibitory component concentrations for acetic acid, HMF and furfural were relatively high compared to that in the feed, and these elevated concentrations are problematic for fermentation

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Table 5 Percentage rejection and concentration factors for enzymatic hydrolysis following RO and NF processing. Hydrolysate components

Glucose (g/L)

Xylose (g/L)

Reverse osmosis membrane Feed concentration 22.4

10.9

Percentage rejection of each component BW30 95 SW30 99 KOCH 92 GE 91 Toray 99

96 99 92 91 99

Nanofiltration membrane Feed concentration

10.9

22.4

Percentage rejection of each component MPF34 88 NF90 99 TS40 82 TS80 88 GEHL 93 SR100 78

Arabinose (g/L)

Acetic acid (g/L)

3.3

8.4

96 99 92 92 99

86 98 79 90 94 77

1.7

72 89 37 72 47 41

62 82 28 57 36 29

Furfural (g/L)

1.5

Total unmeasured (g/L)

2

92 99 89 88 94

48.2

92 99 78 77 97

1.5

159 166 154 152 165

2

50 42 32 35 33 32

Total measured components (g/L)

48.2

43 68 9 38 8 4

114 127 95 111 110 92

35 30

MPF34

25

NF90

20

TS40

15

TS80

10

GEHL

Percentage permeation

60

40

Flux (L/m2h)

94 99 91 90 97

8.4

45

0

0.01

0.02

0.03

0.04

0.05

50 40 30

Glucose Xylose

20

Arabinose

10 0

SR100

5 0

1.7

95 99 92 91 98

3.3

87 99 82 89 98 79

HMF (g/L)

MPF34

NF90

TS-40

TS-80

GEHL

SR100

NFMembrane

0.06

Cumulative Vol. (L) 45 40

Flux (L/m2h)

35 30

MPF34

25

NF90

20

TS40

15

TS80 GEHL

10

SR100

5 0

Percentage Permeation

80 70 60 Glucose

50

Xylose

40

Arabinose

30

AceticAcid

20

HMF

10

Furfural

0

MPF34

NF90

TS-40

TS-80

GEHL

SR100

NFMembrane 0

0.01

0.02

0.03

0.04

0.05

0.06

Cumulative Vol. (L) Fig. 4. Nanofiltration: flux profiles during sugar concentration process with either [A] a pure sugars mixture, or [B] a pretreated lignocellulosic hydrolysate. [A] Flux profile during concentration of pure sugars mixture. [B] Flux profile during concentration of enzymatic hydrolysate.

organisms [65–68]. Thus, in-order to increase the fermentation efficiency there would be a potential need to separate all of these inhibitors from sugars, either before or after the concentration process, but prior to fermentation as shown in Fig. 1. This could be achieved by developing a membrane which can selectively separate inhibitors and concentrate sugars in a single step (as discussed later in this paper using nanofiltration membranes). As shown in Table 5, the Koch and GE membranes showed 22% and 23% loss of the unidentified components in their permeates, respectively. All others showed minor losses of these materials in

Fig. 5. Permeation of components during concentration/separation process for [A] a pure sugars mixture and [B] a lignocellulosic hydrolysate. [A] Percentage sugar permeation through NF membrane using pure sugar mixture feed. [B] Percentage components permeation through NF membrane using enzymatic hydrolysis feed.

the permeate. These unidentified components included soluble/ insoluble phenolics and other derivatives of sugars and inhibitors. These phenolics (especially residual insoluble solids) were likely also responsible for the membrane fouling and hence should be completely removed prior to concentration process to minimize fouling [69,70], especially considering that during membrane cleaning some suspended solids were visually observed to be retained on or within the membrane at the end of concentration process. The flux profiles for the NF membranes when processing either the pure sugar mixture or lignocellulosic hydrolysate are shown in Fig. 4A and B, respectively. In general, membranes that performed

A. Gautam, T.J. Menkhaus / Journal of Membrane Science 451 (2014) 252–265

best with pure sugars also had higher flux profiles with hydrolysate. The NF membrane SR100 and TS40 showed similar flux performance for both the sugar mixture and hydrolysate. Interestingly, SR100 and TS40 being operated at relatively lower pressure, showed better flux performance compared to rest of the membranes, by maintaining the highest fluxes throughout the process. The GEHL membrane also performed admirably, and actually had the highest flux at more concentrated pure sugar values. The number of pores, pore diameter, and surface roughness did not appear to influence the flux profiles to a large extent. More detailed discussion regarding fouling mechanisms and other rational for flux decline is presented below. In addition to the flux performance, it would also be desirable to achieve simultaneous retention of sugars (to concentrate) and allow inhibitors to permeate the membrane. Percentage permeation as shown in Fig. 5A and B can be defined as the recovery of sugars or hydrolysate components in the permeate during the concentration process. As shown in Fig. 5A and Table 4 for pure sugar retention results, the MPF34, NF90 and TS-80 all showed relatively higher yields of sugar (lower loss to the permeate). However, even with these losses, the final retentate concentration was 224–240 g/L of sugars, indicating an ability to achieve a 3-fold concentration. It is important to realize that membranes exhibiting the higher flux profiles for faster filtration (TS-40, SR100 and GEHL) were also those with the lower sugar retentions. As expected, this elevated sugar loss is also highly correlated to the membranes with relatively larger pore sizes. As shown in Fig. 5B and Table 5, the ability to retain sugars was elevated when processing real biomass hydrolysate compared to pure sugars. This is likely due to the pore constriction of the membranes, as well as interactions between sugar molecules and other soluble components in the complex feedstock [25,26]. NF90 retained more than 98% of sugars, but also retained a relatively high percentage of inhibitors. Other membranes performed similarly, with high yield of sugars, and varying ability to separate inhibitors. GEHL interestingly retained more than 93% sugars and separated 53–67% of inhibitors in permeate, away from sugars, which is beneficial for the overall biorefinery. Unidentified components were primarily permeated through the membrane, with the exception of NF90, which retained nearly 70% of these compounds. The unidentified components included soluble/insoluble phenolics and other derivatives of sugars and inhibitors, which are often responsible for fouling of membrane surfaces [69,70], as discussed in more detail below.

Table 6 Separation performance of RO and NF membranes as measured by concentrations in the permeate and retentate and calculated by Eq. (6). Inh ¼ combination of all inhibitors, glu ¼ glucose, xyl¼ xylose, arb¼ arabinose. Membrane

Separation factor αinh/glu

αacetic

αHMF/glu

αfurfural/glu

Reverse osmosis membrane BW30 1.26 1.14 SW30 1.19 0.95 KOCH 1.11 1.05 GE 1.12 1.07 Toray 2.19 1.77

1.24 1.90 1.13 1.11 2.15

Nanofiltration membrane MPF34 4.46 2.68 NF90 45.9 11.1 TS40 8.64 7.64 TS80 6.35 2.88 GEHL 20.2 15.1 SR100 6.2 5.1

4.27 19.5 11.5 5.5 24.5 8.78

acid/glu

αxyl/glu

αarb/glu

1.95 1.72 1.38 1.40 4.59

0.97 0.86 0.99 0.99 0.89

0.98 0.75 1.00 0.96 0.64

7.01 122 9.64 13.4 27 7.4

1.01 0.54 0.98 0.9 0.34 0.96

1.19 1.59 1.18 0.83 0.92 1.02

261

The calculated separation factor was an indication of separation performance of each of the membranes, as shown in Table 6, where higher values indicate the desired separation of inhibitor while retaining higher concentration of sugars [30]. As already described above, all of the membranes are hydrophilic, less rough in nature and almost similar pore size, but still there is a difference in separation efficiency of these membranes [35]. As can be seen from Table 5, NF90 and GEHL were found to be the best candidates for high sugars retention and lower inhibitors retention. The NF90 and GEHL membranes, which showed higher irreversible fouling described below, were the ones that reported higher separation efficiency of inhibitors with respect to glucose. Both of these membranes were operated at higher pressure compared to other NF membranes, which could be one of the reasons for having higher inhibitors separation efficiency. 4.3. Effect of reversible fouling in flux decline Following processing with pure sugars or hydrolysate, any deposited layer of suspended solids (or other cake/gel components such as concentrated sugars) was gently flushed with water to remove any reversible fouling. Finally, the membrane was thoroughly cleaned and water flux measured again. At that stage, only irreversible fouling was present within the membrane. This combination of measurements allowed us to isolate the effects of reversible and irreversible fouling, along with osmotic pressure flux reduction as described above using Eqs. (2)–(5). Flux decline during processing occurred not only by the fouling components such as reversible and irreversible fouling, but also by a non-fouling osmotic pressure component. For processing of the sugar mixture, flux decline due to reversible fouling for RO membranes accounted for between 35-63% of the total flux decline, whereas in case of NF membranes flux decline due to reversible fouling was 12–96% as shown in Table 3. This factor along with osmotic pressure were temporary declines seen only during processing, and were the dominant factors for reducing flux during concentration of pure sugars. In the case of enzymatic hydrolysate, the percentage flux decline due to reversible fouling was relatively low compared to the pure sugar mixture for both RO and NF membranes as shown in Table 3. For NF membranes, the reason is quite clear; the total retentate concentration in the pure sugars mixture is relatively high compared to hydrolysate as shown in Tables 4 and 5, respectively. The lower total concentration of compounds provided a lower propensity for the gel layer to form, and also reduced osmotic effects. A reduced reversible fouling component may have also indicated that there was a shielding of the surface with the complex feedstock, which actually discouraged formation of a thick gel as the sugars were concentrated. This may have resulted from either direct interactions of components with the surface, or from secondary interactions between adsorbed species on the surface and repulsion of remaining soluble components in the feed above the membrane [25,26]. Reversible fouling, although contributing to flux decline can be easily removed after the process (in this case with a simple high shear water wash), which makes it a more desirable form of fouling. 4.4. Irreversible fouling of RO and NF membranes For RO and NF studies completed here, the percentage resistance responsible for flux decline for the sugar mixture from irreversible fouling is not as significant when compared to gel layer (reversible fouling) and osmotic pressure flux decline. In the case of RO membranes for the sugar mixture, it can be seen from Table 3 that the GE membrane showed a high percentage of irreversible fouling, followed by BW30 and SW30. This may be due

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residual insoluble solids) were likely most responsible for the membrane irreversible fouling and hence should be completely removed prior to the concentration/separation process to minimize fouling [69,70]. With the TS40, GEHL and SR100, because all of these phenolic components were collected in permeate, it helps explain the reason for having lower irreversible fouling (phenolics did not accumulate on the surface and in membrane valleys and pores). In the case of hydrolysate processing, MPF34, TS40 and SR100 showed no irreversible fouling, which increases the reusability of these membranes and makes the overall process much more economical for this particular application. 4.5. Effect of osmotic pressure in flux decline

Fig. 6. Examples of membrane operating conditions and visual comparison between fresh membrane and membrane after one time use with enzymatic hydrolysate.

to the small pore size, less hydrophilicity and high surface roughness of these membranes. Koch and Toray having lower surface roughness and more hydrophilicity, were less prone to irreversible fouling. For enzymatic hydrolysate concentration experiments, again SW30 and GE showed 65% and 57% irreversible fouling as shown in Table 3. Even though these two membranes showed an ability to provide high retentate concentrations, the large permanent flux reduction decreases the reusability and increases the cleaning cost of the membrane. In this case, since all membranes except Koch and Toray showed more than 50% irreversible fouling, the membrane life must be taken into account when considering economics of the overall process (e.g., Fig. 1). Fig. 6 shows the condition of membranes before and after one use with lignocellulosic hydrolysate. We can clearly see the fouling on membrane surface, especially in case of GE where a change in color was observed indicating severe fouling or other chemical transformation, which would make it unsuitable for this particular application. In all cases, there is a potential need to modify the membranes to minimize fouling and increase separation efficiency without compromising the retentate concentration of the components. Unlike RO membranes where maximum flux reduction came from irreversible fouling, NF membranes, due to their relatively larger pore sizes were able to minimize irreversible fouling and simultaneously showed higher flux performance. NF90 and TS80 were relatively less hydrophilic and hence were prone to irreversible fouling, especially when processing the complex lignocellulosic hydrolysate. Even though these two membranes showed an ability to provide high flux and high separation factors, the large permanent flux reduction decreases the reusability and increases the cleaning cost of the membrane. The phenolics (especially

Percentage flux decline as shown in Table 3 accounts not only for fouling components such as reversible and irreversible fouling, but also a non-fouling osmotic pressure component. As can be noticed, osmotic pressure accounted for between 26-37% and 3-80% of the total flux decline for RO and NF membranes, respectively, for processing the sugar mixture. Interestingly, for hydrolysate, the flux decline due to osmotic pressure was relatively low for RO membranes compared to NF membranes, even though RO membranes showed higher retention of components. The reason for this was that RO membranes showed more irreversible fouling compared to NF, so on a total flux decline basis irreversible fouling became more significant in case of RO compared to NF. Furthermore, during the concentration process, due to the high retention capacity of the RO membranes evaluated, the concentration of soluble and insoluble components increased in the retentate due to removal of nearly pure water in permeate. With an increase in concentration of components in the retentate relative to that in permeate, the osmotic pressure also increased [18,70,71]. If the total osmotic pressure (osmotic pressure contribution from each individual component) became equal to that of trans-membrane pressure, flux would be reduced to zero [72–74] even without any fouling. Osmotic pressure cannot be avoided without compromising the loss of components in permeate. However, in the case of the hydrolysate, the effect can be minimized if only the desired sugar components are retained, or if the additional components are removed (or never generated) prior to concentrating. The total retentate concentration of soluble and insoluble compounds in the hydrolysate was 170–190 g/L for RO membranes, which led to flux decline due to gel layer formation and osmotic pressure, leading to relatively faster flux decline compared to the pure sugars mixture. Whereas due to variation in the retention capacities of the respective NF membranes, the retentate concentration of soluble and insoluble components was lower than the reverse osmosis membranes due to their higher separation efficiency for removal of inhibitory components in the permeate. At the same time, loss of components in the permeate led to a decrease in the observed osmotic pressure [18,70,71]. In this case, loss of components in the NF permeate (separation from sugars) restricted the increase in osmotic pressure, and hence was less responsible for the flux decline [72–74]. The osmotic pressure contribution from individual components for both RO and NF membranes, for the pure sugar mixture and the enzymatic hydrolysate are shown in Table 7. It can be observed from Table 7 that the osmotic pressure contribution from acetic acid is very large compared to other inhibitors and is actually comparable or even more than glucose (acetic acid 41 MPa, glucose o1 MPa) in the retentate. This indicates a potential need for removal of acetic acid prior to the concentration process in order to achieve elevated sugar yields in retentate if using membranes. On the other hand, in the case of NF membranes,

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263

Table 7 Osmotic pressure contribution from individual components during sugar concentration process in RO and NF operations, indicating benefits from permeation of inhibitor compounds. Membrane

Sugar mixture (SM)

Glucose

xylose

Arabinose

Acetic acid

HMF

Furfural

Total osmotic pressure

Enzymatic hydrolysat (EH)

Δπ (MPa)

Δπ (MPa)

Δπ (MPa)

Δπ (MPa)

Δπ (MPa)

Δπ (MPa)

Δπ (MPa)

Applied trans-membrane pressure ΔP (MPa)

1.32 0.97

1.38 0.50

0.26 0.17

N/A 1.07

N/A 0.10

N/A 0.11

2.96 2.94

4.03 4.03

Reverse osmosis membrane BW30 SM EH SW30

SM EH

1.40 1.06

1.51 0.55

0.30 0.19

N/A 1.18

N/A 0.11

N/A 0.13

3.20 3.22

4.03 4.03

KOCH

SM EH

1.26 0.90

1.36 0.46

0.20 0.16

N/A 0.99

N/A 0.10

N/A 0.11

2.81 2.72

4.03 4.03

GE

SM EH

1.36 0.88

1.43 0.46

0.14 0.16

N/A 0.97

N/A 0.09

N/A 0.10

2.93 2.67

4.03 4.03

Toray

SM EH

0.90 1.04

0.90 0.54

0.15 0.18

N/A 1.14

N/A 0.11

N/A 0.12

1.95 3.14

3.34 3.34

1.38 0.81

1.48 0.27

0.44 0.04

N/A 0.59

N/A 0.01

N/A 0.19

3.30 1.91

3.35 3.35

Nanofiltraation membrane MPF34 SM EH NF90

SM EH

1.24 0.96

1.36 0.32

0.40 0.05

N/A 0.81

N/A 0.02

N/A 0.12

3.01 2.28

3.35 3.35

TS40

SM EH

1.05 0.73

1.02 0.24

0.29 0.04

N/A 0.13

N/A 0.00

N/A 0.04

2.36 1.17

2.66 2.66

TS80

SM EH

1.07 0.81

1.18 0.27

0.35 0.05

N/A 0.58

N/A 0.01

N/A 0.07

2.61 1.80

2.66 2.66

GEHL

SM EH

0.57 0.88

0.55 0.31

0.15 0.05

N/A 0.26

N/A 0.00

N/A 0.05

1.27 1.56

3.35 3.35

SR100

SM EH

0.76 0.68

0.79 0.23

0.23 0.04

N/A 0.18

N/A 0.00

N/A 0.04

1.78 1.16

2.66 2.66

the osmotic pressure contribution from acetic acid was found to be relatively lower compared to sugars due to permeation of acetic acid (acetic acid o0.26 MPa, glucose 4 0.68 MPa), as shown in Table 7. The acetic acid dissociation starts at pH values greater than the pKa of acetic acid (4.75); dissociation degree increases rapidly with an increase in pH. High retention of acetic acid at high pH is attributed to electrostatic repulsion between the negatively charged acetic acid molecules and the negatively changed surface of the polyamide membranes at higher pH values [30]. For NF membranes, more than 50% permeation of acetic acid was observed at an operating pH of 5.0. However, more than 91% rejection of acetic acid was found for RO membranes at same pH. Zeta potential (surface streaming) studies are required to understand the interaction between membranes and hydrolysate components at different pH values, which was not available for this study [29,31]. In a practical sense, all non-sugar components should be permeated through an ideal membrane. This would not only provide higher purity for sugars, but would also allow higher maximum concentration of sugars (by limiting osmotic pressure limitations to those created by sugars alone). NF membranes were able to overcome this challenge by recovery of inhibitors in permeate and hence supported concentration build up of sugars in retentate. High permeation of inhibitors will not only make the sugar concentration process more efficient but it will simultaneously increase the fermentation efficiency due to minimization of inhibitory components during fermentation of glucose to ethanol. All membranes can be further modified to achieve higher sugar levels in retentate, more complete separation of sugar from other

inhibitory components, and to provide lower irreversible fouling characteristics [75–76]. Ideally, a membrane would contain a large number of relatively small pores, have low surface roughness, high hydrophilicity and operate under conditions where the membrane is negatively charged.

5. Conclusions Reverse osmosis and nanofiltration membranes have been evaluated for their ability to concentrate sugars within a pure sugar feed stream and from a biomass hydrolysate. The effectiveness of the separation was found to depend on membrane chemistry, pore size, porosity (number of pores), hydrophilicity and membrane surface roughness. Membrane characteristics such lower hydrophilicity, lower porosity and higher surface roughness were responsible for higher surface fouling when processing enzymatic hydrolysate. Also, important distinctions between processing pure sugars and real enzymatic hydrolysate have been identified. For example, even though a very high sugar loss (over 30%) was observed for some membranes in the case of processing the pure sugar mixture, losses were reduced to minimal in the case of lignocellulosic hydrolysate, indicating an interaction among hydrolysate components. RO membranes showed higher osmotic pressure flux resistance from acetic acid, which was minimized in the case of NF membranes due to recovery of acetic acid in permeate. The rates of fouling and dominant fouling mechanisms were also different depending upon membrane and feed material. For pure sugars, reversible and osmotic pressure

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effects were most important; while for enzymatic hydrolysate irreversible fouling became much more problematic.

Acknowledgments Financial support for A. Gautam was provided by the USDA NIFA, AFRI Competitive Grant # 2010-65504-20372, and the South Dakota School of Mines and Technology.

Nomenclature Cinh,p,

Cinh,r inhibitor concentration in permeate and retentate, g/L Csug,p, Csug,r sugar concentration in permeate and retentate, g/L d pore diameter, m. J flux, L/m2/h Jif, JΔπ, Jgel flux decline due to irreversible fouling, osmotic pressure and gel layer, L/m2/h N number of pores ΔP transmembrane pressure, MPa R gas constant, 8.314 J mol  1 K  1 Rm membrane resistance, m  1 T temperature, K Δx membrane thickness, m ΔC component concentration gradient between retentate and permeate CR concentration of component in retentate, g/L CP concentration of component in permeate, g/L Greek symbols

αinh/sug separation factor of inhibitor with respect to Δπ μ

glucose osmotic pressure of soluble compounds, MPa viscosity of solution, Pa s

References [1] O.J. Sanchez, C.A. Cardona, Trends in biotechnological production of fuel ethanol from different feedstocks, Bioresour. Technol. 99 (2008) 5270–5295. [2] Y.-H. Weng, H.-J. Wei, T.-Y. Tsai, T.-Y. Wei, G.-L. Guo, C.-P. Huang, Separation of furans and carboxylic acids from sugars in dilute acid rice straw hydrolyzates by nanofiltration, Bioresour. Technol. 101 (2010) 4889–4894. [3] A. Demirbas, Bioethanol from cellulosic materials: a renewable motor fuel from biomass, Energy Sources 27 (2005) 327–337. [4] J.F. Negron, K. Allen, B. Cook, J.R. Withrow Jr., Susceptibility of ponderosa pine, Pinus ponderosa (Dougl. ex Laws.), to mountain pine beetle, Dendroctonus ponderosae Hopkins, attack in uneven-aged stands in the Black Hills of South Dakota and Wyoming USA, For. Ecol. Manag. 254 (2) (2008) 327–334. [5] R.N. Gurram, S. Datta, Y.J. Lin, S.W. Snyder, T.J. Menkhaus, Removal of enzymatic and fermentation inhibitory compounds from biomass slurries for enhanced biorefinery process efficiencies, Bioresour. Technol. 102 (17) (2011) 7850–7859. [6] M. Sagehashi, T. Nomura, H. Shishido, A. Sakoda, Separation of phenols and furfural by pervaporation and reverse osmosis membranes from biomasssuperheated steam pyrolysis-derived aqueous solution, Bioresour. Technol. 98 (2007) 2018–2026. [7] M. Falls, J. Shi, M.A. Ebrik, T. Redmond, B. Yang, C.E. Wyman, R. Garlock, V. Balan, B.E. Dale, V.R. Pallapolu, Y.Y. Lee, Y. Kim, N.S. Mosier, M.R. Ladisch, B. Hames, S. Thomas, B.S. Donohoe, T.B. Vinzant, R.T. Elander, R.E. Warner, R. S-Ramirez, M.T. Holtzapple, Investigation of enzyme formulation on pretreated switchgrass, Bioresour. Technol. 102 (2011) 11072–11079. [8] N. Mosier, C. Wyman, B. Dale, R. Elander, Y.Y. Lee, M. Holtzapple, M. Ladisch, Features of promising technologies for pretreatment of lignocellulosic biomass, Bioresour. Technol. 96 (2005) 673–686.

[9] C.E. Wyman, V. Balan, B.E. Dale, R.T. Elander, M. Falls, B. Hames, M. T. Holtzapple, M.R. Ladisch, Y.Y. Lee, N. Mosier, V.R. Pallapolu, J. Shi, S. R. Thomas, R.E. Warner, Comparative data on effects of leading pretreatments and enzyme loadings and formulations of sugar yields from different switchgrass sources, Bioresour. Technol. 102 (2011) 11052–11062. [10] R. Kumar, C.E. Wyman, Does change in accessibility with conversion depend on both the substrate and pretreatment technology? Bioresour. Technol. 100 (2009) 4193–4202. [11] C.E. Wyman, B.E. Dale, R.T. Elander, M. Holtzapple, M.R. Ladisch, Y.Y. Lee, Comparative sugar recovery data from laboratory scale application of leading pretreatment technologies to corn stover, Bioresour. Technol. 96 (2005) 2026–2032. [12] C.E. Wyman, B.E. Dale, R.T. Elander, M. Holtzapple, M.R. Ladisch, Y.Y. Lee, Coordinated development of leading biomass pretreatment technologies, Bioresour. Technol. 96 (2005) 1959–1966. [13] G. Najafpour, H. Younesi, K.S.K. Ismail, Ethanol fermentation in an immobilized cell reactor using Saccharomyces cerevisiae, Bioresour. Technol. 92 (2004) 251–260. [14] M. Sedlak, N.W.Y. Ho, Production of ethanol from cellulosic biomass hydrolysates using genetically engineered saccharomyces yeast capable of cofermenting glucose and xylose, Appl. Biochem. Biotechnol. 113–116 (2004) 403–416. [15] B.S. Dien, M.A. Cotta, T.W. Jeffries, Bacteria engineered for fuel ethanol production: current status, Appl. Microbiol. Biotechnol. 63 (2003) 258–266. [16] N.G. Cheng, M. Hasan, A.C. Kumoro, C.F. Ling, M. Tham, Production of ethanol by fed-batch fermentation, Pertanika J. Sci. Technol. 17 (2009) 399–408. [17] K.A. Standish, M.R. Mallem, P.C. Gilcrease, D.J. Dixon, Extruder pretreatment of ponderosa pine to enhanced cellulose hydrolysis, in: Proceedings of the 35th Annual Biochemical Engineering Symposium, April 29th, 2006, South Dakota School of Mines and Technology, Rapid City, SD, 2007. [18] S.S. Madaeni, S. Zereshki, Reverse osmosis alternative: energy implication for sugar industry, Chem. Eng. Process. 47 (2008) 1075–1080. [19] S.S. Madaeni, S. Zereshki, Energy consumption for sugar manufacturing. Part1: evaporation versus reverse osmosis, Energy Convers. Manag. 51 (2010) 1270–1276. [20] S.S. Madaeni, K. Tahmasebi, S.H. Kerendi, Sugar syrup concentration using reverse osmosis membranes, Eng. Life Sci. 4 (2004) 187–190. [21] I. Kiss, Gy. Vatai, E. Bekassy-Molnar, Must concentrate using membrane technology, Desalination 162 (2004) 295–300. [22] S. Brethauer, C.E. Wyman, Review: continuous hydrolysis and fermentation for cellulosic ethanol production, Bioresour. Technol. 101 (2010) 4862–4874. [23] Q. Qing, B. Yang, C.E. Wyman, Xylooligomers are strong inhibitors of cellulose by enzymes, Bioresour. Technol. 101 (2010) 9624–9630. [24] D.L. Grzenia, D.J. Schell, S.R. Wickramasinghe, Membrane extraction for removal of acetic acid from biomass hydrolysates, J. Membr. Sci. 322 (2008) 189–195. [25] B. Carter, P.C. Gilcrease, T.J. Menkhaus, Removal and recovery of furfural, 5-hydroxymethylfurfural and acetic acid from aqueous solutions using a soluble polyelectrolyte, Biotechnol. Bioeng. 108 (2011) 2046–2052. [26] B. Carter, P. Squillace, P.C. Gilcrease, T.J. Menkhaus, Detoxification of a lignocellulosic biomass slurry by soluble polyelectrolyte adsorption for improved fermentation efficiency, Biotechnol. Bioeng. 108 (2011) 2053–2060. [27] A. Teella, G.W. Huber, D.M. Ford, Separation of acetic acid from the aqueous fraction of fast pyrolysis bio-oils using nanofiltration and reverse osmosis membranes, J. Membr. Sci. 378 (2011) 495–502. [28] Y. Weng, H. Wei, T. Tsai, T. Lin, T. Wei, G. Guo, C. Huang, Separation of furans and carboxylic acids from sugars in dilute acid rice straw hydrolyzates by nanofiltration, Bioresour. Technol. 101 (2010) 4889–4894. [29] S.K. Maiti, Y.L. Thuyavan, S. Singh, H.S. Oberoi, G.P. Agarwal, Modeling of the separation of inhibitory components from pretreated rice straw hydrolysate by nanofiltration membranes, Bioresour. Technol. 114 (2012) 419–427. [30] F. Zhou, C. Wang, J. Wei, Separation of acetic acid from monosaccharides by NF and RO membranes: performance comparison, J. Membr. Sci. 429 (2013) 243–251. [31] F. Zhou, C. Wang, J. Wei, Simultaneous acetic acid separation and monosaccharide concentration by reverse osmosis, Bioresour. Technol. 131 (2013) 349–356. [32] J.A. Brant, K.M. Johnson, Amy E. Childress, Characterizing NF and RO membrane surface heterogeneity using chemical force microscopy, Colloids Surf. A: Physicochem. Eng. Asp. 280 (2006) 45–57. [33] Y. Zhao, J. Taylor, S. Hong, Combined influence of membrane surface properties and feed water qualities on RO/NF mass transfer, a pilot study, Water Res. 39 (2005) 1233–1244. [34] W. Lee, C.H. Ahn, S. Hong, S. Kim, S. Lee, Y. Baek, J. Yoon, Evaluation of surface properties of reverse osmosis membranes on the initial biofouling stages under no filtration condition, J. Membr. Sci. 351 (2010) 112–122. [35] C.W. Extrand, Water contact angles and hysteresis of polyamide surfaces, J. Colloid Interface Sci. 248 (2002) 136–142. [36] Y. Wayne, C. Yoram, R.S. Faibish, Contact angle study on polymer-grafted silicon wafers, J. Colloid Interface Sci. 256 (2002) 341–350. [37] H. Matsumoto, A. Tanioka, Functionality in electrospun nanofibrous membranes based on fiber's size, surface area, and molecular orientation, Membranes 1 (2011) 249–264.

A. Gautam, T.J. Menkhaus / Journal of Membrane Science 451 (2014) 252–265

[38] J. Wang, Z. Yue, J.S. Ince, J. Economy, Preparation of nanofiltration membranes from polyacrylonitrile ultrafiltration membranes, J. Membr. Sci. 286 (1–2) (2006) 333–341. [39] F. Tomicki, D. Krix, H. Nienhaus, M. Ulbricht, Stimuli-responsive track-etched membranes via surface-initiated controlled radical polymerization: Influence of grafting density and pore size, J. Membr. Sci. 377 (1–2) (2011) 124–133. [40] J.I. Calvo, P. Prádanos, A. Hernández, W.R. Bowen, N. Hilal, R.W. Lovitt, P. M. Williams, Bulk and surface characterization of composite UF membranes atomic force microscopy, gas adsorption–desorption and liquid displacement techniques, J. Membr. Sci. 128 (1) (1997) 7–21. [41] S. Brunauer, P.H. Emmett, E. Teller, Adsorption of gases in multimolecular layers, J. Am. Chem. Soc. 60 (2) (1938) 309–319. [42] J.I. Calvo, A. Hernandez, P. Pradanos, L. Martibnez, W.R. Bowen, Pore size distributions in microporous membranes II. Bulk characterization of tracketched filters by air porometry and mercury porosimetry, J. Colloid Interface Sci. 176 (1995) 467–478. [43] C.A. Smolders, M.H.V. Mulder, P.M. Velden van der, A survey of structure characterization methods for ultrafiltration and reverse osmosis membranes, Desalination 19 (1–3) (1976) 481. [44] N.N. Li, A.G. Fane, W.S.W. Ho, T. Matsuura, Advanced Membrane Technology and Applications, John Wiley & Sons, Inc., Hoboken, NJ, 2008. [45] A. Arora, B.S. Dien, R.L. Belyea, P. Wang, V. Singh, M.E. Tumbleson, K.D. Rausch, Thin stillage fractionation using ultrafiltration: resistance in series model, Bioprocess. Biosyst. Eng. 32 (2009) 225–233. [46] J. Leberknight, B. Wielenga, A. Lee-Jewett, T.J. Menkhaus, Recovery of high value from a corn ethanol process by ultrafiltration and an exploration of the associated membrane fouling, J. Membr. Sci. 366 (2011) 405–412. [47] P.K. Bhattacharya, S. Agarwal, S. De, U.V.S. Rama Gopal, Ultrafiltration of sugar cane juice for recovery of sugar: analysis of flux and retention, Sep. Purif. Technol. 21 (2001) 247–259. [48] P. Rai, C. Raia, G.C. Majumdara, S. DasGupta, S. De, Resistance in series model for ultrafiltration of mosambi (Citrus sinensis (L.) Osbeck) juice in a stirred continuous mode, J. Membr. Sci 283 (2006) 116–122. [49] J.G. Wijmans, S. Nakao, C.A. Smolders, Flux limitation in ultrafiltration: osmotic pressure model and gel layer model, J. Membr. Sci. 20 (1984) 115–124. [50] S.V. Satyanarayana, P.K. Bhattacharya, S. De, Flux decline during ultrafiltration of kraft black liquor using different flow modules: a comparative study, Sep. Purif. Technol. 20 (2000) 155–167. [51] Y. Weng, H. Wei, T. Tsai, W. Chen, T. Wei, W. Hwang, C. Wang, C. Huang, Separation of acetic acid from xylose by nanofiltration, Sep. Purif. Technol. 67 (2009) 95–102. [52] J. Lapointe, S.F. Gauthier, Y. Pouliot, C. Bouchard, Characterization of interactions between B-lactoglobulin tryptic peptides and a nanofiltration membrane: impact on the surface membrane properties as determined by contact angle measurements, J. Membr. Sci. 261 (2005) 36–48. [53] G.B. Van Den Berg, C.A. Smolders, Flux decline in ultrafiltration processes, Desalination 77 (1990) 101–133. [54] E.M. Vrijenhoek, S. Hong, M. Elimelech, Influence of membrane surface properties on initial rate of colloidal fouling of reverse osmosis and nanofiltration membranes, J. Membr. Sci. 188 (2001) 115–128. [55] M. Elimelech, X. Zhu, A.E. Childress, S. Hong, Role of membrane surface morphology in colloidal fouling of cellulose acetate and composite aromatic polyamide reverse osmosis membranes, J. Membr. Sci. 127 (1997) 101–109. [56] K.C. Khulbe, T. Matsuura, Characterization of synthetic membranes by Raman spectroscopy, electron spin resonance and atomic force microscopy: a review, Polymer 41 (2000) 1917–1935. [57] Z. Yi, L. Zhu, Y. Xu, J. Jiang, B. Zhu, Polypropylene glycol: the hydrophilic phenomena in the modification of polyethersulfone membranes, Ind. Eng. Chem. Res. 50 (2011) 11297–11305.

265

[58] N. Nady, M.C.R. Franssen, H. Zuilhof, M.S.M. Eldin, R. Boom, K. Schroen, Modification methods for poly(arylsulfone) membranes: a mini-review focusing on surface modification, Desalination 275 (2011) 1–9. [59] G. Kang, Y. Cao, Development of antifouling reverse osmosis membranes for water treatment: a review, Water Res. 46 (2012) 584–600. [60] G. Chen, S. Li, X. Zhang, S. Zhang, Novel thin-film composite membranes with improved water flux sulfonated cardo poly(arylene ether sulfone) bearing pendant amino groups, J. Membr. Sci. 310 (2008) 102–109. [61] G. Hurwitz, G.R. Guillen, E.M.V. Hoek, Probing polyamide membrane surface charge, zeta potential, wettability, and hydrophilicity with contact angle measurements, J. Membr. Sci. 349 (2010) 349–357. [62] N.K. Saha, S.V. Joshi, Performance evaluation of thin film composite polyamide nanofiltration membrane with variation in monomer type, J. Membr. Sci. 342 (2009) 60–69. [63] G. Artug, J. Hapke, Characterization of nanofiltration membranes by their morphology, charge and filtration performance parameters, Desalination 200 (2006) 178–180. [64] S. Saksena, A.L. Zydney, Pore size distribution effects on electrokinetic phenomena in semipermeable membranes, J. Membr. Sci. 105 (1995) 203–215. [65] S. Larsson, E. Palmqvist, B. Hahn-Hagerdal, C. Tengborg, K. Stenberg, G. Zacchi, et al., The generation of fermentation inhibitors during dilute acid hydrolysis of softwood, Enzyme Microb. Technol. 24 (1999) 151–159. [66] J.R.M. Almeida, T. Modig, A. Petersson, B. Hahn-Hagerdal, G. Liden, M.F. Gorwa-Grauslund, Increased tolerance and conversion of inhibitors in lignocellulosic hydrolysates by Saccharomyces cerevisiae, J. Chem. Technol. Biotechnol. 82 (2007) 340–349. [67] L.J. Boyer, J.L. Vega, K.T. Klasson, E.C. Clausenv, J.L. Gaddy, The effects of furfural on ethanol production by Saccharomyces cerevisiae in batch culture, Biomass Bioenergy 3 (1) (1992) 41–48. [68] E. Palmqvist, H. Grage, N.Q. Meinander, B. Hahn-Hagerdal, Main and interaction effects of acetic acid, furfural and p-hydroxybenzoic acid on growth and ethanol productivity of yeasts, Biotechnol. Bioeng. 63 (1) (1999) 46–55. [69] M.F.A. Goosen, S.S. Sablani, H. Al-Hinai, S. Al-Obeidani, R. Al-Belushi, D. Jackson, Fouling of reverse osmosis and ultrafiltration membranes: a critical review, Sep. Sci. Technol. 39 (2004) 2261–2298. [70] B.R. Babu, N.K. Rastogi, K.S.M.S. Raghavarao, Effect of process parameters on transmembrane flux during direct osmosis, J. Membr. Sci. 280 (2006) 185–194. [71] K.B. Petrotos, P. Quantick, H. Petropakis, A study of the direct osmotic concentration of tomato juice in tubular membrane-module configuration. I. The effect of certain basic process parameters on the process performance, J. Membr. Sci. 150 (1998) 99–110. [72] S. Lee, R.M. Lueptow, Reverse osmosis filtration for space mission wastewater: membrane properties and operating conditions, J. Membr. Sci. 182 (2001) 77–90. [73] K. Jamal, M.A. Khan, M. Kamil, mathematical modeling of reverse osmosis systems, Desalination 160 (2004) 29–42. [74] S. Nicolas, B. Balannec, F. Beline, B. Bariou, Ultrafiltration and reverse osmosis of small non-charge molecules: a comparison study of rejection in a stirred and an unstirred batch cell, J. Membr. Sci. 164 (2000) 141–155. [75] A.K. Gautam, T.J. Menkhaus, Surface modified reverse osmosis and nanofiltration membranes for the production of biorenewable fuels and chemicals, MRS Proceed. (2013), http://dx.doi.org/10.1557/opl.2013.347, mrsf12-1502t10-06. [76] J. Leberknight, T.J. Menkhaus, Membrane separations for solid–liquid clarification within lignocellulosic biorefining processes, Biotechnol. Prog., Available on-line, 2013, doi: 10.1002/btpr.1778.