Characteristics of Pickering Emulsion Gels Formed by Droplet

ARTICLE pubs.acs.org/Langmuir

Characteristics of Pickering Emulsion Gels Formed by Droplet Bridging Matthew N. Lee, Hubert K. Chan, and Ali Mohraz* Department of Chemical Engineering & Materials Science, University of California, Irvine, California 92697, United States

bS Supporting Information ABSTRACT: We experimentally characterize the microstructure and rheology of a carefully designed mixture of immiscible fluids and near-neutral-wetting colloidal particles. Particle bridging across two fluid interfaces provides a route to highly stable gel-like emulsions at volume fractions of the dispersed phase well below the random close-packing limit for spheres. We investigate the microstructural origins of this behavior by confocal microscopy and reveal a percolating network of colloidal particles that serves as a cohesive scaffold, bridging together droplets of the dispersed phase. Remarkably, the mixture’s salient rheological characteristics are governed predominantly by the solids loading and can be tailored irrespective of the droplet volume fraction. The identification of this rheological hallmark could provide a means toward the improved design of modern products that utilize solid-stabilized interfaces.

’ INTRODUCTION The ability of fine solid particles to stabilize fluid
fluid interfaces was first reported over a century ago, leading to the subsequent development of Pickering
Ramsden emulsions and their widespread use in foods, cosmetics, and personal products.1
3 With new applications of solid-stabilized interfaces emerging in drug delivery,4 oil recovery,5 and composites,6,7 the past decade has seen revived interest in this field with the aim of better understanding the physicochemical and mechanical properties of particle-laden interfaces and the multiphase emulsions that are based on them. Of particular technological interest are the microstructure and rheology of the complex formulations that may arise in these multiphase mixtures because they carry important implications for the processing, functionality, and stability of their end-use products. Previous research has focused on the effects of particle wettability,8,9 shape,8,10 size,11,12 the thermodynamic properties of the fluid constituents,13,14 interparticle interactions,15,16 and the solids volume fraction11,17 on the phase behavior of particle-stabilized emulsions, unveiling a rich array of accessible soft materials including droplet dispersions and concentrated emulsions with points of catastrophic phase inversion,18,19 gels,20 foams,21 and dynamically arrested bicontinuous microstructures.22,23 The equilibrium position of a colloidal particle residing at a fluid/fluid interface can be characterized by the three-phase contact angle, θ, that is related to the governing surface free energies through Young’s equation.24 In mixtures involving aqueous and organic liquids, θ is commonly measured through the aqueous phase. For colloidal particles with near-neutral wetting properties (θ ≈ 90°), interfacial adsorption is typically r 2011 American Chemical Society

Figure 1. Schematic representation of droplet bridging by spherical particles. The equilibrium contact angle can be realized on both sides of the bridging particle.

irreversible; the detachment energy can be several orders of magnitude larger than the particle’s thermal energy, kT, where k is Boltzmann’s constant and T is the absolute temperature.25 Partially hydrophobic particles with θ somewhat greater than 90° tend to stabilize water-in-oil (w/o) emulsions where particles slightly protrude from droplet surfaces to maintain the equilibrium contact angle; this also facilitates efficient packing and a steric barrier against droplet coalescence. In a unique case, particles protruding from a droplet can simultaneously adsorb to another interface, bridging two droplets with a shared particle monolayer; this configuration allows the equilibrium contact angle to be satisfied on both sides of the bridging particle (Figure 1). Previous studies have characterized strong adhesive forces between isolated droplet pairs sharing a particle Received: August 29, 2011 Revised: October 17, 2011 Published: October 18, 2011 3085

dx.doi.org/10.1021/la203384f | Langmuir 2012, 28, 3085–3091

Langmuir monolayer.26
28 Such considerations point to conceivably unique rheology in solid-stabilized emulsions with bridged droplets resulting from the complex mechanics involved in deforming, rearranging, and breaking the soft building blocks that are brought together by a cohesive layer of fine solid particles. It has been suggested that droplet bridging can impart prolonged mechanical stability and contribute to gel-like rheology in these systems.29
32 A thorough experimental assessment of this phenomenon and its microstructural origins would be of great interest to the wide host of technologies that utilize solidstabilized emulsions and can pave the way to the synthesis and engineering of new multiphase systems with enhanced stability, morphology, and rheological properties. Such a study would require the 3D microstructure of the emulsion to be characterized with fine spatial resolution. However, because of the inherent abundance of scattering surfaces in these multiphase mixtures, direct visualization and quantification of their 3D morphology are experimentally challenging and have generally prevented the links between their microstructure and rheology from being fully established. In this article, we report the salient characteristics of a model solid-stabilized emulsion that we have carefully designed in our laboratory such that (1) the refractive indices of the liquid phases and the solid particles approximately coincide, allowing 3D microstructural characterization of the mixture by confocal microscopy and (2) the colloid surface chemistry is carefully tuned to allow the stabilization of two interfaces by each particle through bridging. (See below for more details.) We show that under such conditions the mixture can form a network of colloid-stabilized droplets with the majority of particles being shared by neighboring droplet pairs. As a whole, the emulsion microstructure bears a striking resemblance to a colloidal gel, only with solid-stabilized droplets replacing the colloidal building blocks. The multiphase mixture exhibits arrested dynamics, long-term mechanical stability, and gel-like rheology with key parameters determined solely by the solids volume fraction. We hereafter refer to this system as a Pickering emulsion gel. We discuss our findings in light of the microstructural origins of gel-like rheology in this intriguing class of soft materials and present new questions exploring possible directions for future research in this area.

’ MATERIALS AND METHODS Particle Synthesis and Sample Preparation. Nearly monodisperse fluorescent silica microspheres with an average diameter of D = 975 nm and a coefficient of variation of CV = 4.5% were synthesized using a seeded growth technique.33 The particles were tagged with fluorescent rhodamine dye (RITC) during synthesis to enable imaging using confocal microscopy and were subsequently rendered partially hydrophobic by modifying their surface chemistry.9,34 Briefly, 5.8 g of dry particles was suspended in 190 g of toluene, and then 5 mL of a 0.1 M dichlorodimethylsilane-in-toluene solution was added to the suspension dropwise and stirred for 18 h. This treatment rendered the particle surface chemistry hydrophobic, resulting in an equilibrium three-phase contact angle of θ = 135° as measured by the immersed droplet method (Supporting Information).35 The particles would therefore stabilize w/o Pickering emulsions, protruding from the interface to allow droplet bridging, as determined experimentally. The incorporation of rhodamine B dye in the aqueous phase of the emulsions confirmed the w/o droplet arrangement (Supporting Information). Emulsions with particle volume fractions in the range of ϕP = 8
17.4% and volume ratios of the aqueous to organic phase ranging from η = 20/80 to 50/50 were prepared by dispersing the

ARTICLE

required number of dry particles in a two-phase liquid mixture using an ultrasonic probe (Branson Sonifier 250) operating at 2 W for 20 s continuously. The composition of each fluid phase was chosen to match the refractive index of the particles approximately (np ≈ 1.43), which enabled a visualization of the local microstructure at depths of up to 50 μm in the specimens using a confocal microscope. The aqueous phase was a mixture of dimethylsulfoxide and water (65/35 v/v, naq = 1.437, Faq = 1.057 g/mL), and the oil (organic) phase was a mixture of toluene and dodecane (18/82 v/v, noil = 1.434, Foil = 0.764 g/mL), resulting in a final mixture with nmixture = 1.438. The interfacial tension between the liquids was γ = 24 mN/m, as measured by a Kruss K100 tensiometer. In one experiment reported here for comparison, the composition of the organic phase was changed to toluene, dodecane, and 1,6-hexanediol diacrylate (9/41/50 v/v, noil2 = 1.445, Foil2 = 0.893 g/mL). Upon sonication, the samples immediately transitioned from a multiphase liquid-like mixture to a self-supporting gel that appeared macroscopically homogeneous to the naked eye (Supporting Information). This transition was achieved only by sonication; vortex mixing did not induce gel-like behavior. Confocal Microscopy and Image Processing. Samples were visualized using a confocal scanner (Vt-eye, Visitech International) attached to an inverted microscope (Axio Observer, Carl Zeiss Microimaging, Inc.). Volumetric stacks of 2D images were acquired using a 100 NA = 1.4 oil-immersion objective to construct the 3D local microstructure. For the analysis of droplet curvatures, digital image volumes of 66  66  30 μm3 were processed by Gaussian filtering using the FFT plugin in ImageJ software to isolate bright particle contours. Segmentation, surface reconstruction, and measurement of the Gaussian curvature, K, for bridged and nonbridged emulsions were performed using Avizo software (Visualization Sciences Group) with an average triangle edge length of approximately 0.5 μm. For each type of emulsion, curvature data gathered across three image volumes were combined to generate probability density distributions for K. To generate the Voronoi volume distributions for particles at droplet interfaces, 16 image volumes of 68  68  50 μm3 each were systematically acquired in a 4  4 grid for each sample by translating the microscope stage along the image plane using manual micrometers and were stitched together to generate mosaics of the long-ranged microstructure. The composite image volumes were processed using Interactive Data Language software (IDL, ITT Visual Information Solutions, Boulder, CO) to identify the centers of individual particles using previously reported methods of digital microscopy for colloidal suspensions.36,37 The Voronoi volumes of particles were calculated in IDL using the Voro++ algorithm.38 Rheometry. The rheological properties of the emulsions were measured on a stress-controlled rheometer (MCR301, Anton Paar) with sandblasted cone-and-plate geometry (d = 25 mm, angle = 2°), and a solvent trap was utilized to minimize evaporation at the set measurement temperature of 25 °C. After sonication, the viscoelastic samples were carefully loaded onto the rheometer stage using a spatula, and the cone was lowered slowly into position to minimize changes to the microstructure from sample handling and loading. This procedure yielded highly reproducible and geometry-independent data for a given emulsion, indicating that our measurements were not contaminated by wall slip and that any differences observed between samples were not due to their loading history (Supporting Information). Each mixture first underwent a frequency sweep spanning f = 0.1
80 Hz with a constant oscillatory strain of γ = 0.1%, followed by an oscillatory strain sweep (γ = 0.005
100%) at a constant f = 1 Hz. The storage and loss moduli (G0 and G00 , respectively) were recorded throughout both tests. The zero-shear elastic modulus, G0 0, was estimated as the average value of G0 over the range of 0.005% < γ < 0.01%. The yield stress, τy, was defined as the stress value at which G0 = G00 .

’ RESULTS AND DISCUSSION Figure 2a shows a representative 2D confocal microscopy image of a sample prepared at η = 30/70 and ϕP = 0.08. Droplet 3086

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091

Langmuir surfaces are rendered visible by the fluorescent particles that cover them. Qualitatively, the long-range microstructure bears a striking resemblance to a concentrated colloidal gel, only with the particulate building blocks replaced by particle-armored droplets; the mixture is composed of a sample-spanning cluster of droplets and large regions containing the continuous fluid phase alone (herein referred to as voids for simplicity). Video microscopy revealed the droplet dynamics to be fully arrested, and images captured over a 24 h period showed no discernible changes to the mixture’s local microstructure (data not shown). Furthermore, despite the density gap between the two fluid phases (Faq
Foil = 0.293 g/mL) and the attachment of particles to the heavy droplets, the emulsions showed no signs of sedimentation or creaming over at least a 7 day period (Supporting Information). This long-term mechanical stability is remarkable given that the volume fraction of the dispersed phase is well below the random close packing limit of spheres in all samples. A higher-magnification image of the cluster interior clearly shows a monolayer of nearly touching particles being shared among several droplets (Figure 2b). Interestingly, the bridging phenomenon appears to favor the formation of flat droplet boundaries. This morphology is similar to the structure of foams and to a recent report on particle bridging across organic and ionic liquid phases39 but is distinctly different from the more familiar Pickering emulsions, which are typically characterized by spherical particle-armored droplets. To quantify this important morphological signature, we compared the distributions of the Gaussian curvature, K, for reconstructed particle surfaces in a bridged emulsion to its nonbridging counterpart each prepared

Figure 2. Confocal microscopy images of Pickering emulsion gels. (a) Low-magnification image showing tortuous clusters of droplets in the continuous fluid phase. (b) High-magnification image showing a monolayer of nearly touching particles bridging a number of faceted droplets in the gel interior.

ARTICLE

at η = 50/50 (Figure 3). The nonbridging morphology was realized by modifying the organic-phase composition, thereby changing the three-phase contact angle to θ = 110° (Materials and Methods). For the Pickering emulsions formed with little or no bridging particles, values of K are predominately positive and show a relatively narrow peak in their distribution, which is consistent with spherical droplets of roughly uniform size (Figure 3b). For the Pickering emulsion gel, however, the distribution of K exhibits a sharp asymmetric peak at K = 0, indicating that the majority of particles reside at an interface that is locally planar. Confocal microscopy images of the gel interior where droplet bridging is most abundant clearly reveal faceted polygonal cells armored by planar particle assemblies (Figure 3c). We also note that within the facets, particles display local 2D crystalline order of hexagonal symmetry with occasional vacancies and dislocations. Hence, the sharp peak at K = 0 indicates that most of the particles are shared between neighboring droplet pairs and participate in bridging. The asymmetry in the distribution of K probably arises from the predominantly positive local curvature at the cluster exteriors where droplet boundaries are not shared. Both the bridging and the exterior particles show caged dynamics and an average interparticle spacing of r = 1.05 μm, as determined by calculating the particle mean-squared displacements and pair distribution functions, respectively (Supporting Information). Moreover, the particle coverage on the droplet boundaries is found to be uniform with a surface coverage of approximately 76%. Collectively, the results of Figures 2 and 3 reveal an interconnected web of nearly touching solid particles that serves as a cohesive scaffold, bridging droplets of the dispersed phase into a percolating cluster. This picture could potentially explain the origins of arrested dynamics and gel-like behavior in these systems. The multiphase nature of Pickering emulsions gives rise to a rich morphology diagram and phase behavior. For a given set of fluids and particles, the volume fractions of the constituent liquid phases or the particles can each dramatically influence the microstructure and physical properties of the resulting mixtures. In Figure 4, we demonstrate three different approaches to tuning the microstructure of our samples. As mentioned earlier, we consider the building blocks of a Pickering gel to be solidstabilized droplets of approximately uniform size. Here we will denote the average droplet radius as RD, the particle volume fraction as ϕP, and the volume ratio of the aqueous to the organic phase as η. Increasing η at constant ϕp results in a monotonic increase in RD (Figure 4a); this will decrease the surface area per

Figure 3. Effect of particle bridging on droplet geometry. (a) Distributions of Gaussian curvature, K, generated from triangulated surfaces approximating the particle-laden interface for two types of Pickering emulsions. (b) Spherical droplets with K > 0. (c) Polygonal droplets caused by bridging with a sharply peaked distribution near K = 0. 3087

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091

Langmuir

ARTICLE

Figure 4. Three strategies for tuning the microstructure in Pickering emulsion gels. (a) An increase in the volume ratio of the aqueous (dispersed) to organic (continuous) phase (η) at a constant particle volume fraction (ϕP) produces successively larger droplets. (b) An increase in ϕP at constant η reduces the droplet size. (c) A proportional increase in both ϕP and η increases the volume fraction of droplets without affecting their size.

Figure 5. Distributions of Voronoi polyhedra volumes for individual particles in Pickering emulsion gels shown in Figure 4c. (Inset) Schematic representation of a test particle residing at a bridged interface. The Voronoi volume may be estimated from a bicone with the halfheight equal to the droplet radius RDand the base equal to the particle diameter.

unit volume of the droplets, allowing the same number of particles to stabilize a larger body of fluid. Alternatively, increasing ϕp at constant η results in a monotonic decrease in RD because more particles are progressively available to stabilize a fixed volume of fluid per unit volume of the mixture (Figure 4b). Finally, a proportional increase in both η and ϕP will increase the volume fraction of the dispersed phase without affecting RD because the increase in surface area is accommodated by a proportional increase in the number of stabilizing particles

(Figure 4c). This scenario also facilitates a rudimentary comparison to colloidal gels, where the volume fraction of the dispersed building blocks can be changed without affecting their size. Each of the routes presented has important implications for the microstructure and rheology of the samples, which we wish to characterize and discuss here. As illustrated in the low-magnification images, the emulsion microstructure is heterogeneous with randomly distributed voids whose characteristic sizes are strong functions of η and ϕp. We quantified these visual observations in Figure 5 by generating the Voronoi volume (VVP) distributions for the interfacial particles across the four samples presented in Figure 4c. We chose these samples for the VVP analysis because the uniform droplet size would allow a more straightforward interpretation of the void distribution and its comparison to dense colloidal gels, for which typical VVP distributions have been previously established.40 The peaks of all distributions in Figure 5 approximately coincide, which can be explained as follows: from the confocal micrographs and interfacial curvatures shown before, it is clear that the majority of particles reside at a bridged droplet interface. For this case, the approximate Voronoi volume of a bridging particle can be estimated as the volume of a bicone with base diameter D (particle diameter) and half-height RD (droplet radius), as shown schematically in the inset of Figure 5. For D = 975 nm particles bridging an interface between two RD = 7 μm droplets (the average droplet radius estimated from microscopy images), the bicone volume amounts to 1.74 μm3, which is in reasonable agreement with the peaks of the VVP distributions (VVP,peak ≈ 2 μm3). We note that this estimate likely oversimplifies the geometries of the individual Voronoi cells, which are influenced by variations in droplet size and local curvature. Regardless, this analysis provides further support for the abundance of bridging monolayers in Pickering emulsion gels. 3088

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091

Langmuir

ARTICLE

Figure 7. Strain
sweep profiles for the Pickering emulsion gels shown in Figure 4a.

Figure 6. Rheology of Pickering emulsion gels. (a) Strain
sweep profiles for samples shown in Figure 4b,c measured at a constant frequency of 1 Hz. (b) Scaling of the zero-shear elastic modulus, G0 0, and yield stress, τy, with particle volume fraction. The insets specify which parameter was held constant in each data set.

The VVP distributions are asymmetric, indicative of a heterogeneous void morphology and arrangement. As the volume fraction of the droplet (aqueous) phase increases, the tails of the distributions are suppressed, indicating that the largest voids are progressively reduced in size. We note that the droplet size is held constant throughout the samples; the qualitative resemblance of the shape of the Vvp distribution to dense colloidal gels is therefore noteworthy. Moreover, in both systems, an increase in the volume fraction of the building blocks results in a progressive reduction in the size of the largest (intercluster) voids. These qualitative observations again point to structural commonalities between colloidal and Pickering emulsion gels. We theorized that the unique morphology of Pickering emulsion gels and its similarities to colloidal gels would be manifest in nontrivial mechanical properties. Furthermore, the gel building blocks are deformable in this case, which points to intriguing questions and potentially complex rheological behavior for these systems. The characterization of such properties would be of great interest to the wide host of industries that utilize solid-stabilized emulsions. We therefore investigated the rheology of the emulsion gels presented in Figure 4 using oscillatory measurements. Frequency sweep tests on representative samples showed hallmarks of particulate gels and very stable emulsions with a nearly frequency-independent G0 > G00 (Supporting Information).41
44 Figure 6a presents the results of oscillatory strain sweeps on the mixtures shown in Figure 4b,c. All samples exhibit particulate gel signatures with a zero-shear solidlike storage modulus, G0 0, and an apparent yield stress, τy. These parameters, extracted as described in the Materials and

Methods section, are presented as a function of ϕP in Figure 6b. On the whole, increasing the solids loading produces stronger gels, reflected by power-law scalings of both G0 0 and τy with the particle volume fraction in the form of G0 0 ∼ ϕP3.0 and τy ∼ ϕP1.9. Two important observations can readily be made. First, the power-law dependence of G0 0 on ϕP is consistent with a number of previously characterized particulate gels45
48 but shows a different exponent in this system (G0 0 ∼ ϕP3.7
5.6 in colloidal gels, G0 0 ∼ ϕP3.0 here). Second, we observe a nearly complete overlap between each pair of measurements performed at the same ϕP, despite differences in their values of η or RD. This interesting observation suggests that the primary determinant of rheological behavior in these materials is the extent of particle loading. To examine this notion further, we performed a series of experiments in which identical numbers of particles were used to prepare four samples with increasing η; here RD became progressively larger (Figure 4a). The strain
sweep profiles are nearly indistinguishable across the four samples (Figure 7), highlighting a direct correspondence between the salient rheological characteristics (elastic storage and yielding) and the colloid volume fraction in Pickering emulsion gels. Our results reveal a principal departure from the case of surfactant-stabilized emulsions, for which elasticity stems from the interfacial energy stored upon deforming droplets in a close-packed configuration. In such cases, G0 0 is measurable only at droplet volume fractions above the random-close-packing limit for spheres, and its magnitude is governed by the droplet Laplace pressure and the number density of deformed facets.49 In our system, the mechanism for elasticity is fundamentally different and is not due to excluded volume effects in a homogeneous close-packed structure. This enables the formulation of mechanically stable emulsions and the tuning of their rheology at dispersed-phase volume fractions that are much smaller than the random-close-packing limit. At such low volume fractions of the dispersed phase, a simple surfactant-stabilized emulsion would not be elastic. Stabilization by droplet bridging is also unique in the case of flocculated Pickering droplet bilayers where attractive interparticle interactions through the continuous phase can impart droplet clustering and stability to multiphase mixture.50 In our experiments, we also observed the formation of loose aggregates when the functionalized silica particles were dispersed in the continuous (organic) phase alone. Therefore, some attractive interactions are probably at play between the solid particles 3089

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091

Langmuir through the organic phase. However, we have shown that in our system the majority of particles reside at shared boundaries between droplets. In addition, the magnitude of G0 0 measured for functionalized silica particles dispersed in the continuous phase alone was over 1000 times smaller than in a bridged emulsion prepared at the same ϕP (Supporting Information). Thus, we reason that attractive forces mediated by particle
solvent interactions, even if present, do not contribute appreciably to elastic storage in bridged emulsion gels. Instead, in light of our combined microstructural and rheological findings, we propose that gel-like behavior in these systems is a unique result of the percolating network of droplets that are stitched together via a cohesive web of solid particles. The direct correspondence between gel strength and the solids volume fraction and the scaling of its rheological parameters with ϕP are presumably linked to this unique microstructure. The power-law scaling of G0 0 with ϕP in colloidal gels has been explained on the basis of the gel backbone geometry,48 with the magnitude of G0 0 determined by the interparticle bond strength. Here, the adhesive force between a bridged droplet pair is proportional to the periphery of their shared facet, P, and can be estimated as F = πPγ cos2 (θ/2) = 1 μN.27 Then, the observed scalings of G0 0 ∼ ϕP3.0 and τy ∼ ϕP1.9 are likely related to the spatial distribution of shared boundaries between droplet pairs, and the emulsion microstructure shown in Figure 2a suggests a tenuous arrangement of such threads. Future research in this realm should focus on the detailed characterization of the shared facets and their configuration within the sample volume, which could help us to understand better the origins of gel-like rheology and the scaling of its salient parameters with the particle volume fraction in Pickering emulsion gels. Our findings demonstrate that the rheology of Pickering emulsion gels can be tuned rather independently of their aqueous/organic phase ratio, which may have important implications for the formulation and processing of a variety of multiphase mixtures and their technological applications. Moreover, as mentioned earlier, the gel-like behavior was accessible in our samples only by ultrasonication. This important observation also points to the possibility of dramatic flow-induced rheological transitions in these systems. Finally, the deformability of the faceted building blocks suggests interesting transient shear behavior and large-amplitude rheology in Pickering emulsion gels. Therefore, our findings also offer important questions for future research on these systems.

’ SUMMARY We have studied an interesting class of particle-stabilized emulsions here referred to as Pickering emulsion gels, characterized by a network of faceted aqueous droplets bridged together through a percolating monolayer of colloidal particles at oil
water interfaces. The microstructure of this system bears a striking overall resemblance to a dense colloidal gel. The salient dynamic and rheological signatures are gel-like and are mediated predominately by the extent of particle loading, a unique rheological characteristic presumably caused by the bridging phenomenon. The continuous droplet network found in Pickering gels imparts long-term mechanical stability and resistance to gravitational effects at droplet volume fractions well below the random-close-packing limit, which is integral to improved shelf life. That this system was designed specifically for 3D imaging with single-particle resolution should facilitate the next phase of

ARTICLE

combined microstructure/rheology studies on this stimulating class of soft matter, which is currently underway in our laboratory.

’ ASSOCIATED CONTENT

bS

Supporting Information. Additional images and rheological data. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected].

’ ACKNOWLEDGMENT We thank Iris Fu, Jessica Witt, and Kaela Napolitano for assistance with the experiments and H. Pirouz Kavehpour for providing the interfacial tension measurement. M.N.L. and H.K.C. acknowledge the Department of Education for GAANN fellowships. A.M. thanks UC Irvine for startup funds and a CORCL award. ’ REFERENCES (1) Ramsden, W. Proc. R. Soc. London 1903, 72, 156. (2) Pickering, S. U. J. Chem. Soc. 1907, 91, 2001. (3) Rousseau, D. Food Res. Int. 2000, 33, 3. (4) Frelichowska, J.; Bolzinger, M. A.; Pelletier, J.; Valour, J. P.; Chevalier, Y. Int. J. Pharm. 2009, 371, 56. (5) Sullivan, A. P.; Kilpatrick, P. K. Ind. Eng. Chem. Res. 2002, 41, 3389. (6) Velev, O.; Furusawa, K.; Nagayama, K. Langmuir 1996, 12, 2374. (7) Hong, L.; Jiang, S.; Granick, S. Langmuir 2006, 22, 9495. (8) Yan, N.; Gray, M. R.; Masliyah, J. H. Colloids Surf., A 2001, 193, 97. (9) Binks, B.; Murakami, R. Nat. Mater. 2006, 5, 865. (10) Madivala, B.; Vandebril, S.; Fransaer, J.; Vermant, J. Soft Matter 2009, 5, 1717. (11) Tambe, D. E.; Sharma, M. M. Adv. Colloid Interface Sci. 1994, 52, 1. (12) Tarimala, S.; Dai, L. L. Langmuir 2004, 20, 3492. (13) Clegg, P. S.; Herzig, E. M.; Schofield, A. B.; Egelhaaf, S. U.; Horozov, T. S.; Binks, B. P.; Cates, M. E.; Poon, W. C. K. Langmuir 2007, 23, 5984. (14) Jansen, F.; Harting, J. Phys. Rev. E 2011, 83, 046707. (15) Ghezzi, F.; Earnshaw, J.; Finnis, M.; McCluney, M. J. Colloid Interface Sci. 2001, 238, 433. (16) Horozov, T. S.; Aveyard, R.; Clint, J. H.; Binks, B. P. Langmuir 2003, 19, 2822. (17) Aveyard, R.; Binks, B. P.; Clint, J. H. Adv. Colloid Interface Sci. 2003, 100, 503. (18) Cameron, N. R. Polymer 2005, 46, 1439. (19) Binks, B.; Lumsdon, S. Langmuir 2000, 16, 2539. (20) Thieme, J.; Abend, S.; Lagaly, G. Colloid Polym. Sci. 1999, 277, 257. (21) Gonzenbach, U. T.; Studart, A. R.; Tervoort, E.; Gauckler, L. J. Angew. Chem., Int. Ed. 2006, 45, 3526. (22) Herzig, E. M.; White, K. A.; Schofield, A. B.; Poon, W. C. K.; Clegg, P. S. Nat. Mater. 2007, 6, 966. (23) Tavacoli, J. W.; Thijssen, J. H. J.; Schofield, A. B.; Clegg, P. S. Adv. Funct. Mater. 2011, 21, 1949. (24) Young, T. Trans. R. Soc. 1805, 95, 65. (25) Binks, B. P.; Horozov, T. S. Colloidal Particles at Liquid Interfaces; Cambridge University Press: Cambridge, U.K., 2006. 3090

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091

Langmuir

ARTICLE

(26) Stancik, E. J.; Kouhkan, M.; Fuller, G. G. Langmuir 2004, 20, 90. (27) Stancik, E. J.; Fuller, G. G. Langmuir 2004, 20, 4805. (28) Xu, H.; Lask, M.; Kirkwood, J.; Fuller, G. Langmuir 2007, 23, 4837. (29) Thareja, P.; Velankar, S. Rheol. Acta 2007, 46, 405. (30) Thareja, P.; Velankar, S. Rheol. Acta 2008, 47, 189. (31) Horozov, T. S.; Binks, B. P. Angew. Chem. 2006, 118, 787. (32) Thivilliers, F.; Drelon, N.; Schmitt, V.; Leal-Calderon, F. Europhys. Lett. 2006, 76, 332. (33) Bogush, G.; Tracy, M.; Zukoski, I. J. Non-Cryst. Solids 1988, 104, 95. (34) Van Blaaderen, A.; Vrij, A. Langmuir 1992, 8, 2921. (35) Leunissen, M. E.; Van Blaaderen, A.; Hollingsworth, A. D.; Sullivan, M. T.; Chaikin, P. M. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 2585. (36) Crocker, J. C.; Grier, D. G. J. Colloid Interface Sci. 1996, 179, 298. (37) Dinsmore, A. D.; Weeks, E. R.; Prasad, V.; Levitt, A. C.; Weitz, D. A. Appl. Opt. 2001, 40, 4152. (38) Rycroft, C. Chaos 2009, 19, 041111. (39) Walker, E. M.; Frost, D. S.; Dai, L. L. J. Colloid Interface Sci. 2011, 363, 307. (40) Varadan, P.; Solomon, M. J. Langmuir 2003, 19, 509. (41) Koumakis, N.; Petekidis, G. Soft Matter 2011, 7, 2456. (42) Ueno, K.; Inaba, A.; Ueki, T.; Kondoh, M.; Watanabe, M. Langmuir 2010, 26, 18031. (43) Torres, L.; Iturbe, R.; Snowden, M. J.; Chowdhry, B. Z.; Leharne, S. A. Colloids Surf., A 2007, 302, 439. (44) Binks, B. P.; Clint, J. H.; Whitby, C. P. Langmuir 2005, 21, 5307. (45) Buscall, R.; Mills, P. D. A.; Goodwin, J. W.; Lawson, D. J. Chem. Soc., Faraday Trans. 1 1988, 84, 4249. (46) Rueb, C.; Zukoski, C. J. Rheol. 1997, 41, 197. (47) Gisler, T.; Ball, R. C.; Weitz, D. A. Phys. Rev. Lett. 1999, 82, 1064. (48) Shih, W.-H.; Shih, W. Y.; Kim, S., II; Liu, J; Aksay, I. A. Phys. Rev. A 1990, 42, 4772. (49) Mason, T.; Bibette, J.; Weitz, D. Phys. Rev. Lett. 1995, 75, 2051. (50) Arditty, S.; Schmitt, V.; Giermanska-Kahn, J.; Leal-Calderon, F. J. Colloid Interface Sci. 2004, 275, 659.

3091

dx.doi.org/10.1021/la203384f |Langmuir 2012, 28, 3085–3091