Bitumen–Toluene Mutual Diffusion Coefficients Using Microfluidics

Article pubs.acs.org/EF

Bitumen−Toluene Mutual Diffusion Coefficients Using Microfluidics Hossein Fadaei,† John M. Shaw,‡ and David Sinton*,† †

Department of Mechanical and Industrial Engineering, and Institute for Sustainable Energy, University of Toronto, Toronto, Canada Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada

‡

S Supporting Information *

ABSTRACT: In this paper, we present a microfluidic approach to measure liquid solvent diffusivity in Athabasca bitumen. The method has three distinguishing features: (a) a sharp initial condition enabled by the high wettability of the solvent; (b) onedimensional diffusive transport (in the absence of convection) ensured by microscale confinement; and (c) visible-light-based measurement enabled by the partial transparency of the bitumen at small scales. The method is applied to measure the diffusion of toluene into bitumen by imaging transmitted light profiles over time, and relating intensities to the mass fractions. Plotting toluene mass fraction versus distance/sqrt(time), results in a tight superposition of all curves (time-dependent mass fractions) demonstrating the diffusion dominated nature of the system and the robustness of the method. The diffusion transport equations were solved and fit to a constant diffusion coefficient as well as a variety of concentration-dependent diffusion coefficient relations found in the literature. For intermediate toluene mass fractions (0.2−0.8), a constant diffusion coefficient of 2.0 × 10−10 m2/s provides an appropriate representation. However, at low toluene mass fractions (0.8), the values trend toward 1.5 × 10−10 m2/s. This microfluidic method provides an inexpensive and rapid mutual diffusion coefficient evaluation, with significantly improved spatial/composition resolution vis-à-vis competing measurement methods.

■

INTRODUCTION Production from unconventional resources, such as heavy oil and bitumen, is becoming more important.1 Large deposits in countries like Venezuela and Canada, and ever increasing world energy demand, are bringing more attention to heavy oil and bitumen resources. High oil viscosity is one of the main challenges for production and transportation of these crudes.2 Different methods have been applied to reduce the viscosity, most commonly the injection of steam and solvents (light hydrocarbons or naphtha).2 A variety of transport mechanisms occur during the solvent injection process (also known as vapor extraction or VAPEX), resulting from a combination of capillary, pressure, viscous, and gravity forces. The transfer of solvent into the oil is ultimately, however, through molecular diffusion.3−5 Thus, the diffusive mass transfer rate, and, in particular, the diffusion coefficient, plays a crucial role in process design and recovery estimations. Different methods have been developed for measuring liquid and gas diffusivity in heavy oils. Gas diffusion into an oil phase has been studied using pressure decay,4,6,7volume change (swelling),38 and concentration measurements.9−11 Liquid (solvent) diffusion into an oil phase has generally involved solvent concentration detection in the oil phase.9,10,12 Nuclear magnetic resonance (NMR) and X-ray have been used to detect the solvent concentration in the heavy oil/bitumen phase for the measurement of mutual diffusion with different solvents (pentane, hexane, heptane, toluene, and kerosene).11−13 Solvent diffusion into a mixture of oil and sand was also studied using X-ray imaging.14 Luo and Kantzas15 used X-ray computer-assisted tomography to study the effect of porous media on the diffusion of solvent in heavy oil, also taking into account the effect of volume change of mixing. Zhang and Shaw,16 Zhang et al.,9 and Sadighian et al.17 © 2013 American Chemical Society

employed X-ray imaging to measure pentane−bitumen diffusion. Diffusion in the bitumen−toluene system was studied by Oballa and Butler10 using a cell with two glass plates, and the solvent concentration detection was based on infrared light absorbance during transmission. Bitumen is semitransparent to infrared light, enabling transmission-style measurements on the scale employed.10 Measurement of diffusivity in complex fluids, such as bitumen, can be complicated by concentration dependency. This behavior is in contrast to ideal binary-system diffusion behavior that is characterized by a constant diffusion coefficient (independent of concentration). A well-studied system exhibiting concentration-dependent diffusivity is that of solvent diffusion in polymers.18 In those cases, swelling of the polymer phase can lead to diffusion coefficients dependent on concentration.19−21 Wen and Kantzas12 reported a concentration-dependent diffusion coefficient for heptane diffusion into Cold Lake bitumen, which shows a maximum value at a solvent concentration of about 45% vol. A noticeable deviation from a typical “S-shaped” curve in the concentration profile (corresponding to constant diffusion) was also observed during toluene diffusion into Suncor coker feed bitumen.10 That study reported a concentration-dependent diffusion coefficient that showed a maximum at midpoint bitumen concentrations (∼0.5 vol %). In most of these studies, the mixture density was considered to be constant in the mathematical formulation used for diffusivity measurement. Zhang and Shaw,16 Zhang et al.,9 and Sadighian et al.17 included the influence of varying density in the mathematical formulation for pentane−bitumen Received: January 5, 2013 Revised: March 8, 2013 Published: March 8, 2013 2042

dx.doi.org/10.1021/ef400027t | Energy Fuels 2013, 27, 2042−2048

Energy & Fuels

Article

diffusion. Their X-ray profiles also showed a deviation from the ideal S-shaped behavior, indicating some concentration dependence in diffusivity, as reported. 16 Measurement of a concentration-dependent diffusion coefficient has been also of interest in other branches of science. Examples include solvent and gas diffusion in polymers and polymer solutions,19,22 diffusion in room-temperature ionic liquids,23 and water diffusion in foods.24 In general, determining diffusion coefficients in complex fluids requires measurement of the concentration profile in the direction of diffusive transport, over time. Originally developed with mostly medical applications in mind,25−29 microfluidics has recently been applied in several areas relevant to energy and fuels. Applications of most interest are those in which the central advantages of microfluidics can be leveraged, namely, high speed analysis due to small transport length scales, low cost, precise control over fluid volumes and contact surfaces, increased safety, capacity for high pressures, potential for multiplexing many operations, and small sample volume requirements.30,31 Examples include the use of micromodels for oil recovery studies,32,33 polymer electrolyte fuel cells,33−39 gas diffusivity in brine,40 and gas diffusivity and swelling in bitumen.8 In the latter work, we developed a microfluidic approach to studying gaseous CO2 diffusion into bitumen at high pressures using a glass microfluidic chip.8 Diffusion of CO2 into the bitumen was quantified by imaging the expansion of the bitumen plug. That approach leveraged the immiscibility of the gas−bitumen system at low pressures. Specifically, although the bitumen was in contact with CO2 during set up, negligible diffusion occurred until the gas pressure was suddenly increased. Thus, pressure was the “switch” that provided the sharp initial condition required to make a quantitative diffusion measurement over time within the microfluidic system. That approach does not, however, translate to liquid solvents, which diffuse into bitumen on contact. Although this previous work demonstrates tremendous potential for rapid and accurate diffusion measurements using microfluidics, a method applicable to liquid solvent−oil systems is required. In this paper, we demonstrate measurement of toluene diffusivity in Athabasca bitumen using a new microfluidicsbased approach. This method leverages the high wettability of the solvent (toluene) to rapidly displace the air initially in contact with bitumen, and to initiate the diffusion process, providing a sharp initial condition for quantitative diffusion measurement. Subsequent one-dimensional diffusion of toluene and bitumen is quantified via through-plane visible-light transmission imaging (made possible by the semitransparency of bitumen on the microscale). By fitting the experimental data to the concentration profiles obtained using a numerical model, diffusion transport dynamics are quantified and compared to the literature data.

■

Figure 1. (a) Schematic of the experimental microfluidics-based setup for toluene−bitumen mutual diffusion coefficient measurement. The magnified image shows the section of the channel near the interface. (b) Images of Athabasca bitumen in a Teflon microchannel, 650 μm wide and 75 μm deep. Top: Before toluene injection, where the rest of the system is filled with the air (dashed rectangle shows the section of the image used for image analysis and diffusion coefficient determination). Middle and bottom: Toluene−bitumen mutual diffusion in the microchannel. With diffusion, transmitted light intensity increases through the bitumen and decreases through the toluene (P = 0.1 MPa, T = ∼294 K). this setup is on the order of a few microliters, which is considerably (∼105 times) less than a typical PVT (pressure−volume−temperature) cell volume. An inverted optical microscope (Olympus CKX41) equipped with a halogen bulb in transmission mode was used with imaging provided by a digital charge-coupled device (CCD) camera (Retiga 1300i, QImaging), and images were automatically transferred to a computer for analysis. All experiments were performed at ∼294 K. A research grade toluene (99.5%, SigmaAldrich) was used as the solvent. Athabasca bitumen (Alberta, Canada) was obtained from Syncrude Canada, Ltd. The oil sample was a mined bitumen, obtained after two extraction processes: warm-water extraction and naphtha dilution. The naphtha was then recovered by distillation between 151 and 623 K. We used the Athabasca bitumen (as received with no further treatment) for the hydrocarbon phase. Detailed properties of the Athabasca bitumen used in our study are presented in Table 1.44 Experimental Procedure. Prior to testing, the Teflon chip was cleaned by injecting isopropanol and deionized water in cycles, followed by drying on a hot plate for ∼0.5 h. A small amount of bitumen was loaded into a plastic syringe and heated up to about 60 C. The syringe was then placed at the channel entrance, and bitumen was

EXPERIMENTAL SECTION

Microfluidic Setup. The schematic of the experimental setup is shown in Figure 1a. A Teflon-based T-shaped microfluidic chip was fabricated using a thermal bounding method. Details of the chip fabrication are presented recently elsewhere. 41 The channel dimensions are 650 μm (width) and 75 μm (height). Teflon is generally considered as a toluene-resistant material as long-term (365 days) exposure showed nonsignificant weight change (less than 0.3%).42 Also in our previous study,43 where much longer exposure times were involved, no change in the geometry and material was observed. Because of its microscale characteristics, the total volume in 2043

dx.doi.org/10.1021/ef400027t | Energy Fuels 2013, 27, 2042−2048

Energy & Fuels

Article

Table 1. Properties of Athabasca Bitumen Used in This Study property

value

density (kg/m3) @ 294 viscosity (Pa·s) @ 294 SARA fractions (wt %) saturate aromatic resin asphaltenes (C5)

1026 ∼2000 16.1 48.5 16.8 18.6

slowly injected into the main channel in the chip (vertical channel in Figure 1a). The length of the bitumen plug needs to be sufficient to approximate a semi-infinite case for the diffusion times of interest. For this study, that minimum length is approximately 2 mm, corresponding to a bitumen volume of 0.1 μL. In practice, a longer channel (∼1 cm) was used for convenience. Once the bitumen was injected, the chip was allowed to cool to testing temperature. The setup was in a darkroom to avoid external light disturbances. After set up, the camera recorded images (every 5 s) and a small drop of toluene was placed at the inlet of the chip on the other side of the Tchannel (left side of the bitumen plug). Because of the high wettability, toluene rapidly filled the chip, displacing the air and coming into contact with the bitumen. This invasion happened in less than a second, which is negligible compared to the total diffusion time (∼240 s). The recorded images were then used for image analysis. Figure 1b shows typical recorded images before and after the toluene injection. The small curvature of the initial interface (Figure 1b) did not affect the one-dimensionality of the diffusion process significantly because only a small portion of the entire channel width, at the channel center, was used for the image analysis and further calculation. The interface on this small portion can be considered as almost a line with negligible curvature. Furthermore, the concentration gradient across the channel is very small compared to the gradient in the axial direction. Lastly, any initial curvature effects are restricted to early diffusion times.

Figure 2. Calibration curve used to calculate the toluene mass fraction based on the light intensity. Circles are the experimental calibration data, and the dotted line is the corresponding fitted line used to calculate the toluene mass fraction. The triangles are the light intensity based on Beer and Lambert’s law.

delineation between the two fluids, clearly indicating the interface location. The deviation from a perfect step function is an artifact of the optical properties (not fluid properties) of the interface. Figure 3b shows the toluene mass fraction versus distance, converted directly from the measured light intensity profiles using the calibration curve. The mass fraction data for each time step is plotted versus distance/sqrt(time)18 in Figure 3c. In the superposition plot (Figure 3c), the x axis is zeroed at the interface. The resulting five curves are tightly superimposed, indicating the fidelity of the individual profiles and providing confirmation that the measured process is diffusion-dominated (in the absence of convective or other effects). While all curves plotted collapse well, the fit is strongest at the longer diffusion times, and weakest at early times. The discrepancy is most significant at early times in the bitumen side, at low solvent mass fractions ( 0.99) obtained with the corresponding diffusion coefficients calculated for that time. Calculated results under the dashed area are out of the fitting range used in the calculation of 0.1−0.5 for the bitumen-rich side, and 0.5−0.9 for the toluene-rich side.

bitumen, which is semisolid at the temperature of the experiment. Collectively, these results demonstrate that the diffusive process is well described by constant diffusivity at intermediate concentrations, with significantly reduced transport observed at the leading front (low toluene concentrations). Calculated diffusion coefficients, as a function of toluene mass fraction, for the bitumen-rich and toluene-rich sides are presented in Figure 7. Constant diffusion coefficients are

to 0.5 at the interface and equal to 0 and 1.0 for the bitumen and toluene sides, respectively. The mass fraction range used for the calculation was 0.1−0.5 for the bitumen-rich side and 0.5−0.9 for the toluene-rich side to avoid error associated with the diminishingly small concentrations at each end (indicated by dashed area in Figure 5a,b). As shown, the agreement between the experimental data and the calculated curves is very good in the 0.1−0.9 range, with the largest deviations at high bitumen fraction (0−0.1). Among the relations used for a concentration-dependent diffusivity, relation 1 and 2 (Table 2) give the best fit (r2 > 0.99). Figure 6 shows the same

Figure 7. Calculated diffusion coefficient, for constant as well as concentration-dependent diffusion coefficient relations, based on fitting the experimental data. Constant diffusion coefficients are plotted as straight lines. Fitting is based, separately, on the toluene-rich side (0.5−0.9) and bitumen-rich side (0.1−0.5). Figure 6. Comparison of experimental data and the calculated toluene mass fraction for various constant diffusion coefficients as indicated.

plotted as straight lines. Concentration-dependent diffusion coefficients are plotted based on the equations presented in Table 2 (with fit parameters for a1, a2, and a3). Values for these parameters are presented in the Supporting Information. The diffusion coefficients corresponding to the mass fraction range of 0.1−0.5 are based on the bitumen side fitting, and coefficients for the 0.5−0.9 mass fraction range are based on the toluene side fitting. The concentration-dependent diffusion coefficients show a maximum at midpoint concentrations (0.45−0.55 wt %); however, because we have treated the two sides separately, the trend near the interface (at ∼0.5 wt %) is not smooth. We also presented the constant diffusion coefficients in this figure to be comparable with the concentration-dependent diffusion results.

comparison between the experimental data and cases where constant diffusion coefficients were applied. As indicated, a constant diffusion value between 1.5 × 10−10 and 2.5 × 10−10 m2/s can reproduce the experimental data for middle concentrations (0.2−0.8) very well (r2 ranging from 0.97 to 0.98). For concentrations in this range, the added complexity of the concentration-dependent formulation does not provide significant value. It is important to note, however, that the constant diffusion coefficient significantly overestimates solvent transport at low concentrations (at the leading edge of the front). This deviation observed at low toluene concentration can be attributed to the complex, multicomponent nature of 2046

dx.doi.org/10.1021/ef400027t | Energy Fuels 2013, 27, 2042−2048

Energy & Fuels

Article

experimental data for intermediate solvent mass fractions (0.2− 0.8) very well (r2, 0.98). For mass fractions in this range, the added complexity of the mass fraction-dependent formulations is not justified. It is important to note, however, that the constant diffusion coefficient significantly overestimates solvent transport at low toluene mass fractions (at the leading edge of the front). This is the first application of a microfluidic technique in the study of solvent−bitumen transport phenomena. The method provides high resolution (∼order of magnitude improvement), is rapid (∼minutes), and is straightforward (visible-light-based) to apply.

The combined results of Figures 5−7 warrant careful interpretation. First and foremost, it is noteworthy that, for intermediate toluene concentrations (0.2−0.8), a constant diffusion coefficient of 2.0 × 10−10 m2/s provides an appropriate representation. Regarding the concentrationdependent representations, one would expect all values to be higher than the expected self-diffusion coefficient of pure bitumen (∼10−11 m2/s at 298 K) and lower than the selfdiffusion coefficient of pure toluene (∼2.6 × 10−9 m2/s at 298 K). The importance of applying this criterion has been discussed in detail by Zhang and Shaw,16 and all the data in Figure 7 are within these physical boundaries. At very high bitumen concentrations, the diffusion coefficient measured here trends toward the self-diffusion limit for bitumen, as expected. At very high toluene concentrations, however, the measured diffusion coefficients do not trend higher, toward the toluene self-diffusion value. Several aspects here are noteworthy: (1) a similar trend has been observed by other researchers with heavy oil/bitumen−solvent systems;10,12 (2) all diffusivity values obtained here are within the range between bitumen and toluene self-diffusion coefficients; (3) extreme values of toluene and bitumen mass fractions are found outside the applicable range used here (0.1−0.9); and (4) the constants in the concentration-dependent formulations are very sensitive to any error in the normalized concentration profile. It is noteworthy that the uncertanity associated with visible-light measurement results in the deviation in diffusion coefficient to be ±0.3 × 10−10 m2/s. The toluene−bitumen mutual diffusion can also be calculated using the Wilke−Chang equation. The calculated diffusion coefficient based on this equation is 7.5 × 10−10 m2/s. It is also noteworthy that bitumen is very multicomponent in nature, with fractions varying greatly in mobility. Put another way, heavy oil/bitumen−solvent systems can provide relevant information for solvent diffusivity into the complex oil phase, but would not be expected to be appropriate for determining the self-diffusion coefficient of a pure solvent. Figures 5−7 permit another useful verification, an order of magnitude analysis based on the length scale of the diffusion process. Considering a constant diffusion coefficient, the characteristic diffusion length, l (here, the length corresponding to concentrations of ∼0.0 and ∼1.0), scales with √(D/2t), that is, √D ≈ l/√(2t). Thus, by measuring the l/√(2t) corresponding to concentrations of ∼0.0 and ∼1.0 in the superimposed profiles of Figure 3c, one can obtain estimates for diffusion coefficients at these bounding concentrations. Such an analysis yields diffusion coefficient values for the bitumen and toluene sides of 4.3 × 10−11 and 1.5 × 10−10 m2/s, respectively, which are relevant expected values for each. Collectively, these results demonstrate the efficacy of the presented microfluidic method to measure diffusion dynamics over a practical range of bitumen−solvent mass fractions.

■

ASSOCIATED CONTENT

S Supporting Information *

Figure showing the estimated error generated during the conversion of light intensity to toluene mass fraction and table containing fitting parameters for different relations of diffusion coefficient presented in Table 2. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*Phone: 1-416 978-1623. Fax: 1-416 978-7753. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The authors wish to gratefully acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Networks of Centres of Excellence program, Carbon Management Canada, Theme B − Emerging Technologies, Project B-04. The authors thank Dr. John E. Nenniger for helpful discussions. The authors also gratefully acknowledge infrastructure funding from the Canada Foundation for Innovation (CFI).

■

REFERENCES

(1) Farouq Ali, S. J. Pet. Sci. Eng. 2003, 37, 5−9. (2) Butler, R. M. Thermal Recovery of Oil and Bitumen; Prentice Hall: Englewood Cliffs, NJ, 1991. (3) James, L. A. Mass Transfer Mechanisms During the Solvent Recovery of Heavy Oil. Ph.D. Thesis, University of Waterloo, Waterloo, Ontario, Canada, 2009. (4) Jamialahmadi, M.; Emadi, M.; Müller-steinhagen, H. J. Pet. Sci. Eng. 2006, 53, 47−60. (5) Upreti, S. R.; Mehrotra, A. K. Can. J. Chem. Eng. 2002, 80, 116− 125. (6) Etminan, S. R.; Maini, B. B.; Chen, Z.; Hassanzadeh, H. Energy Fuels 2010, 24, 533−549. (7) Upreti, S. R.; Mehrotra, A. K. Ind. Eng. Chem. Res. 2000, 1, 1080− 1087. (8) Fadaei, H.; Scarff, B.; Sinton, D. Energy Fuels 2011, 25, 4829− 4835. (9) Zhang, X.; Fulem, M.; Shaw, J. M. J. Chem. Eng. Data 2007, 52, 691−694. (10) Oballa, V.; Butler, R. M. J. Can. Pet. Technol. 1989, 28, 63−69. (11) Wen, Y.; Bryan, J.; Kantzas, A. J. Can. Pet. Technol. 2005, 44, 22−28. (12) Wen, Y. W.; Kantzas, A. Energy Fuels 2005, 19, 1319−1326. (13) Wen, Y.; Kantzas, A.; Wang, G. J. Estimation of Diffusion Coefficients in Bitumen Solvent Mixtures Using X-ray CAT Scanning and Low Field NMR. In 5th Canadian International Petroleum Conference, Calgary, Alberta, Canada, June 8-10, 2004; Petroleum Society of Canada/SPE: Calgary, Alberta, Canada, 2004; pp 1−10.

■

CONCLUSIONS Mutual diffusion coefficients for the toluene + bitumen pseudo binary were measured using a new experimental approach with several distinguishing features: a sharp initial condition enabled by the wettability of the solvent, diffusion-only transport due to microconfinement, and visible light transmission measurements enabled by partial transparency of bitumen on this scale. The measured diffusion coefficients agree well with available published results and reproduce expected physical limits for diffusivity at high and low solvent mass fractions. Specifically, a constant diffusion value of 2.0 × 10−10 m2/s can reproduce the 2047

dx.doi.org/10.1021/ef400027t | Energy Fuels 2013, 27, 2042−2048

Energy & Fuels

Article

(14) Salama, D.; Kantzas, A. In SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium; Society of Petroleum Engineers: Calgary, Alberta, Canada, 2005. (15) Luo, H.; Kantzas, A. J. Can. Pet. Technol. 2011, 50, 24−34. (16) Zhang, X.; Shaw, J. M. Pet. Sci. Technol. 2007, 25, 773−790. (17) Sadighian, A.; Becerra, M.; Bazyleva, A.; Shaw, J. M. Energy Fuels 2010, 8, 779−786. (18) Crank, J. The Mathematics of Diffusion; Oxford University Press: New York, 1975. (19) Long, F. A.; Richman, D. J. Am. Chem. Soc. 1960, 82, 513−519. (20) Pickup, S.; Blum, F. D. Macromolecules 1989, 22, 3961−3968. (21) Duda, L. Pure Appl. Chem. 1985, 57, 1681−1690. (22) Waggoner, R. A.; Blum, F. D.; MacElroy, J. M. D. Macromolecules 1993, 26, 6841−6848. (23) Brooks, C. A.; Doherty, A. P. Electrochem. Commun. 2004, 6, 867−871. (24) HSU, K. H. J. Food Sci. 1983, 48, 618−622. (25) Weibel, D. B.; Diluzio, W. R.; Whitesides, G. M. Nat. Rev. Microbiol. 2007, 5, 209−18. (26) Yager, P.; Edwards, T.; Fu, E.; Helton, K.; Nelson, K.; Tam, M. R.; Weigl, B. H. Nature 2006, 442, 412−8. (27) Hansen, C.; Quake, S. R. Curr. Opin. Struct. Biol. 2003, 13, 538− 544. (28) Ottesen, E.; Hong, J. W.; Quake, S. R.; Leadbetter, J. R. Science 2006, 314, 1464−1467. (29) Groisman, A.; Enzelberger, M.; Quake, S. R. Science 2003, 300, 955−8. (30) Whitesides, G. M. Nature 2006, 442, 368−373. (31) Erickson, D.; Sinton, D.; Psaltis, D. Nat. Photonics 2011, 5, 583− 590. (32) Berejnov, V.; Djilali, N.; Sinton, D. Lab Chip 2008, 8, 689−93. (33) Kjeang, E.; Michel, R.; Harrington, D. A.; Djilali, N.; Sinton, D. J. Am. Chem. Soc. 2008, 130, 4000−4006. (34) Berejnov, V.; Bazylak, A.; Sinton, D.; Djilali, N. J. Electrochem. Soc. 2010, 157, B760−B767. (35) Bazylak, A.; Berejnov, V.; Markicevic, B.; Sinton, D.; Djilali, N. Electrochim. Acta 2008, 53, 7630−7637. (36) Ferrigno, R.; Stroock, A. D.; Clark, T. D.; Mayer, M.; Whitesides, G. M. J. Am. Chem. Soc. 2002, 124, 12930−12931. (37) Kjeang, E.; Djilali, N.; Sinton, D. J. Power Sources 2009, 186, 353−369. (38) Kjeang, E.; Michel, R.; Harrington, D.; Sinton, D.; Djilali, N. Electrochim. Acta 2008, 54, 698−705. (39) Bazylak, A.; Sinton, D.; Djilali, N. J. Power Sources 2005, 143, 57−66. (40) Sell, A.; Fadaei, H.; Kim, M.; Sinton, D. Environ. Sci. Technol. 2013, 47, 71−78. (41) de Haas, T. W.; Fadaei, H.; Sinton, D. Lab Chip 2012, 12, 4236−4239. (42) McKeen, L. W. Fluorinated Coatings and Finishes Handbook: The Definitive User’s Guide (Google eBook); William Andrew Publishing: Norwich, NY, 2006; p 395. (43) de Haas, T. W.; Fadaei, H.; Sinton, D. Lab Chip 2012, 12, 4236−42399. (44) Zhao, B.; Zhang, X.; Shaw, J. M. Energy Fuels 2008, 22, 1747− 1758.

2048

dx.doi.org/10.1021/ef400027t | Energy Fuels 2013, 27, 2042−2048