Synthesizing Pickering Nanoemulsions by Vapor Condensation - ACS

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Synthesizing Pickering nanoemulsions by vapor condensation Dong Jin Kang, Hassan Bararnia, and Sushant Anand ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b06467 • Publication Date (Web): 30 May 2018 Downloaded from http://pubs.acs.org on May 30, 2018

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ACS Applied Materials & Interfaces

Synthesizing Pickering nanoemulsions by vapor condensation Dong Jin Kang,1† Hassan Bararnia,1† Sushant Anand1*

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Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, USA

†

These authors contributed equally to this work

Email: [email protected] (S.A.)

Keyword:

Pickering nanoemulsion, vapor condensation, nanomaterials, particle adsorption,

Nanoparticles

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ACS Paragon Plus Environment

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ABSTRACT Nanoparticle stabilized (Pickering) emulsions are widely used in applications such as cosmetics, drug delivery, membranes and materials synthesis. However, formulating Pickering nanoemulsions remains a significant challenge. Herein, we show that Pickering nanoemulsions can be obtained in a single step even at very low nanoparticle loadings (0.2 wt%) by condensing water vapor on a nanoparticle infused subcooled oil that spreads on water. Droplet nuclei spontaneously submerge within the oil after nucleating at oil-air interface, resulting in suppression of droplet growth by diffusion, and subsequently coalesce to larger sizes until their growth is curtailed by nanoparticle adsorption. The average nanoemulsion size is governed by the competition between nanoparticle adsorption kinetics and droplet growth dynamics that are in turn a function of nanoparticle size, concentration and condensation time. Controlling such factors can lead to formation of highly monodisperse nanoemulsions. Emulsion formation via condensation is a fast, scalable, energy efficient process that can be adapted for wide variety of emulsion-based applications in biology, chemistry and materials science.

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INTRODUCTION Liquid-liquid dispersions or emulsions are the foundation of numerous industrial processes and applications1-2. Stabilizing agents, such as surfactants that adsorb at oil-water (o/w) interfaces and delay droplet coalescence using steric and/or electrostatic forces are used to aid in formation of stable emulsions. However, surfactants can have adverse effects in some applications, and surfactant-based emulsions are prone to surfactant desorption and Ostwald ripening.3 Because of these challenges, there is a growing interest in use of nanoparticles as stabilizing agents for emulsion formation, since they provide superior stabilization against coalescence and can potentially limit Ostwald ripening4. Compared to low molecular weight surfactants, nanoparticles have higher desorption energy barrier and depending upon surface chemistry and shape can irreversibly adsorb at oil-water interfaces5. The attractive capillary forces related to deformation of the oil-water interface around nanoparticles provide enhanced mechanical strength to the interfacial layer, increasing their stability further6. Because of such advantages, nanoparticle stabilized (Pickering) emulsions7-13 are being investigated for a wide range of applications in cosmetics14, food products6, 15, drug delivery systems16-17, water purification18, materials synthesis19-27, and oil recovery28. However, in almost all of these applications the nanoparticle-stabilized droplets were limited to micrometric sizes (e.g. see Table T1 in Supplementary Information for a comprehensive list). Preparing surfactant-based nanoemulsions29-30 on the other hand is straightforward, and numerous studies have shown that reducing the dispersion size to nanometric sizes improves the emulsion stability and rheology1-2, 31. It can thus be expected that synthesizing Pickering nanoemulsions could increase their efficacy, stability and rheological properties. Unfortunately, very few studies have successfully demonstrated preparation of Pickering nanoemulsions with droplet sizes lesser than 500 nm32-34. Pickering emulsions are typically formulated using shear-based methods18, 35 that are energy intensive. While such methods may break the droplets into finer nano-dispersions, the large size of

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particles reduces their adsorption rate on droplets. As a consequence even if very fine nanoparticles are used, stabilizing nanodroplets in nano-scale before they can coalesce is challenging. Pickering emulsions can also be prepared using low energy methods (membrane emulsification or microfluidics)36-37, but such methods are unable to generate nanoemulsions and are also prone to clogging by the nanoparticles38-40. Thus devising a new method to prepare Pickering nanoemulsions could potentially unlock access to a hitherto inaccessible regime of particle stabilized droplets, ushering in new opportunities where such emulsions could be potentially used. Recently, it has been shown that water vapor condensing on a mixture of oil and organic surfactants can lead to formation of nanoemulsions41. Herein we show that the vapor condensation technique can be used to synthesize highly monodisperse Pickering nanoemulsions (100-500 nm in size) in a single step even at relatively low nanoparticle concentrations. Although nanoparticles are orders of magnitude larger than surfactant molecules and diffuse at far slower rates, the kinetics of condensation induced emulsion formation can be finely tuned to allow rapid formation of Pickering water in oil nanoemulsions. The use of an oil that spreads on water leads to suppression of the diffusion mode of droplet growth, and the use of nanoparticles within such oils suppresses droplet coalescence. Nanodroplets (nuclei) first form at oil-air interface, and thereafter grow within the oil to larger sizes until the droplet coalescence is curtailed by nanoparticle adsorption on them. We propose a theoretical framework built upon several competing mechanisms including condensation rate, nanoparticle adsorption kinetics, and finally the droplet coalescence kinetics to predict the typical emulsion size and range during condensation. These predictions are validated by performing parametric studies of the different controlling variables, namely the oil-water spreading coefficient, condensation time, and nanoparticle size and concentration. Finally, we show that our method is scalable and highly energy efficient compared to existing homogenization-based methods.

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EXPERIMENTAL SECTION Synthesis of Si NPs. Si NPs are synthesized by using the method reported previously 42. To prepare NP-1, 91 mg of L-arginine (0.052 mM) is added to 69 mL of water while thoroughly mixing the solution in two neck round flask (t-RB). Then 4.5 mL of cyclohexane is added to the water-arginine solution and the reaction is heated to 60 °C in a water bath under magnetic stirring (300 rpm). Once the solution reached 60 °C, 5.5 mL of TEOS (2.5 mM) is added to mixture. The reaction is then kept at constant stirring and temperature for 20 h. NP-2 is synthesized by regrowth method using NP-1, 10 ml NP-1 mixed with 36 ml DI-water in the t-RB, 5 ml cyclohexane added into mixing solution with stirring. Once the solution is well mixed 3.5 ml TEOS added into mixing solution for 30h at 60 °C. NP-3 is prepared using Stӧber method; 10 ml of NP-2 solution is dispersed in 180 mL of ethanol solution containing water and ammonia with the total concentrations in the final mixture being 11 and 1.2 M, respectively. Upon uniform mixing, 22 mL of TEOS (10.5 mmol) is added slowly and reacted over a 72 h period. Surface modification of Si NPs. We design three different sizes of Si NPs (Fig. 1a, NP-1 (13 ± 2.1 nm), NP-2 (52 ± 4.1 nm), NP3 (92 ± 10.3 nm)), which are silanized by isobutylmethoxysilane for hydrophobiczation. For the visulization of the particle absorption, NP-2 is selected to attach the Rhodamin B (red color). The fluorescent nanoparticle NP-2* is prepared by coupling reaction with amino group moiety43. 10 ml hydrophilic NP-2 mixed with 5 ml of IPA and then Rhodamine B is added into as-synthesized Si NPs to get fluorescent particle for 24 hr under 60 °C. After that 135 µl of isobutylmethoxysilane added in to mixture under mechanical stirring (300 rpm) for 24h at 90 °C. All surface modified Si NPs are purified by centrifugal process with ethanol and water several times. Dried Si NPs are prepared at 80 °C with vacuum in thermal oven.

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Liquids used in the current study. The oils used in the current study were dodecane (ρo=750 kg/m3, no~1.42, γoa~25.4 mN/m, µo~1.485 mPa.s, MP = -10 oC) and kerosene (ρo=810 kg/m3, no~1.44, γoa~30 mN/m, µo~1.64 mPa.s, MP= -20 oC). Here ρo, no, γoa, µo, MP denote density, refractive index, surface tension, dynamic viscosity and melting point of the oil respectively. All chemicals were purchased from Sigma-Aldrich. The dodecane used in the study was anhydrous quality (purity≥99%). The kerosene used in the study was of regent grade with purity≥95%. Preparation of Si NPs dispersed oils. Dried Si NPs are dispersed in dodecane and kerosene using the bath-type ultrasonicator for 10 min at room temperature. Different solutions are prepared for 0.05, 0.2, 0.5 and 1.0 wt% of Si NPs dispersed in 6 ml of dodecane and kerosene. Preparation of water in oil emulsion using condensation process. A composite container comprising of copper base and Teflon walls was fabricated. The container is filled by oil and placed on peltier cooler in a humidity chamber that maintains 78~80% relative humidity throughout all experiments and times. The oil-nanoparticle solution was sonicated for 10 minutes prior to transferring them in the condensation chamber to make sure there were no particle agglomerates in the solution. Note that air convection can have undesirable effects on growth rate, so the experiments were performed in a closed chamber to minimize any convection effects. The peltier cooler temperature is lowered to 2 °C (below the dew point of ~15 °C). A humidity sensor (Sensirion SHT71) was used to monitor the temperature and humidity levels inside the humidity chamber. Condensation on the oil is observed using a Zeiss stereo (Axio Zoom.V16) microscope with (Objective Apo Z 1.5x/0.37 FWD 30mm) and the videos are recorded using a Digital SLR camera (Nikon D810) at 24 fps. The emulsion is collected using a plastic pipette.

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Characterization of Nanoparticles and pickering emulsion. The morphology of Si NPs and the Pickering emulsions (after drying) was analyzed using FESEM (JEOL JSM-6320F) and TEM (JEOL JEM-3010). TEM samples are prepared by dropping kerosene suspensions of Si NPs onto copper grids coated with a holey carbon film, followed by solvent evaporation. A Zeiss LSM 710 confocal microscope was used to visually measure both the colors of individual water droplets and Pickering nanoemulsions. A 10 mW, 488 nm solid-state laser was used to excite sodium green dyed water droplets with fluorescein sodium salt and a 10 mW, 555 nm solid-state laser was used to excite particles dyed with Rhodamine B. Generally, the confocal microscope was operated at a 10× objective lens with a numerical aperture of 0.3. High magnification confocal micrographs were taken using a 63× oil immersion lens with a numerical aperture of 1.3 for observing Pickering nanoemulsions. The size distribution of nanoparticles and emulsions was performed using dynamic light scattering instrument (Malvern, Zetasizer Nano DLS). Each measurement was an average of 16 runs, each run lasting 10 s in duration. Samples are measured after 2 min equilibration at 25 °C and results are reported as the average of 3 measurements. The average emulsion diameter and polydispersity of each sample is obtained from the cumulant analysis of each sample’s correlation function. The interfacial tension between water and oil in presence of nanoparticles was measured using the pendant drop technique in a goniometer (OCA 15 Pro) in room temperature conditions. Based on interfacial tension, the spreading coefficient is defined as Sow(a) = γwa- γow -γoa. From error analysis, the 2 2 error in spreading coefficient is given by δSow(a) = δγ wa . Optical microscope is performed to + δγ oa2 + δγ wo

observe the spreading coefficient such that a drop is put on the oil surface and floating (dodecane) or submerging (kerosene) the drop is monitored from front view by camera (Point Grey Flea®3 USB 3.0) and an attached long-distance lens (Infinity Lens). The photos of the emulsion states and stability are recorded with a digital camera.

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RESULTS Synthesis of nanoparticles that self-assemble at oil-water interface. To investigate formulation of nanoparticle-stabilized water-oil emulsions, we first synthesized silica nanoparticles of three different sizes (Fig. 1a), henceforth designated as NP-1 (dia.= 13 ± 2.1 nm), NP-2 (dia.= 52 ± 4.1 nm), and NP-3 (dia.= 92 ± 10.3 nm). Silica particles were chosen because they are widely used in Pickering emulsion formation due to their low toxicity and high thermal stability. For the oil phase, we chose dodecane and kerosene because they have low vapor pressures and similar properties. The particles can make water-in-oil (w/o) Pickering emulsions provided they are hydrophobic and have low susceptibility to desorb from the o/w interface.8, 44-46 To achieve this, firstly the synthesized particles were treated with silane chemistry. Dynamic light scattering (DLS) measurements of oil-nanoparticle solutions confirmed that the modified nanoparticles (NPs) had high dispersibility and very narrow distribution in oils (Fig. S1 and S2) for 24 hours after which agglomeration and sedimentation effects became noticeable (Fig. S3). The synthesized particles may desorb from the water/oil interface if the particle thermal energy (kbT) becomes larger than the desorption Gibbs free energy given by ∆Gd= πa2γow(1-|cosθ|)2 where a is the particle radius, γow is oil-water interfacial tension and θ is the particle contact angle at the oil/water interface measured across the water surface8, 44-46. However, even for our smallest nanoparticles (NP-1), ∆Gd/(kbT) >103, signifying that adsorption of particles in this study is practically irreversible. To confirm these aspects, a water pendant drop was dispensed in oil-nanoparticle solution followed by its subsequent retraction. During the retraction phase, crumpling of the droplet was observed in either oils (Fig. 1b) indicating strong adsorption of nanoparticles at oil/water interface. In summary, the nanoparticles synthesized in this study demonstrate all the characteristics required for preparing waterin-oil Pickering emulsions.

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Pickering nanoemulsion by vapor condensation. The process of synthesizing Pickering nanoemulsions (Fig. 1c) begins by placing an open-ended container filled with the oil-nanoparticle mixture on a peltier cooler. The setup is placed in a humid environment (at 20 oC and 75-80% relative humidity) and the Peltier temperature (Ts) is then lowered to 2±0.5 °C, far below the dew point (TDP ~15±1 °C) of the air. As the oil-mixture temperature falls below the dew point, water droplets condense on oil surface, eventually dispersing in the oil and forming Pickering emulsion after nanoparticles adsorb on them. To illustrate the formation of Pickering emulsion using this method, we prepared separate solutions of dodecane and kerosene mixed with 0.5 wt% of Rhodamine B doped NP-2 (henceforth referred to as NP-2*, Fig. S4). The time during which the sample was maintained at the set point (2 oC), henceforth referred as “condensation time (tcon)” was maintained at 5 minutes for each case. After 5 minutes of condensation, portions of the solutions were transferred to glass vials and stored for a day. Interestingly, we found that despite identical experimental conditions, condensation of water vapor on the two solutions had different effects. A close inspection of dodecane solution showed existence of a significant population of micrometric water droplets with sizes >10 µm (Fig. 1d) in the bottom of the vial. In comparison, the kerosene solution had a milky appearance throughout in the vial (Fig. 1e). Confocal microscopic imaging of the kerosene solution showed existence of primarily sub-microscopic droplets in the solution (Fig. 1e). DLS measurements of the kerosene solution showed existence of droplets with diameters ranging from 300-1500 nm, with the peak size ~600 nm, thus confirming successful formation of Pickering nanoemulsions in this case. Further analysis of this solution under confocal microscope also showed droplets with diameters ranging from 550-1500 nm (inset image, Fig. 1e), confirming the DLS observations. The significant difference in droplet sizes obtained by condensing water vapor on nanoparticle solutions of dodecane and kerosene indicates that the nature of the oil played a strong role in emulsion formation.

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The mechanism of droplet growth on oils and droplet size control in presence of nanoparticles. On a subcooled oil in a humid environment, water droplets nucleate at the oil-air interface via heterogeneous nucleation47 and grow via vapor diffusion and coalescence48-49. A key factor that controls the growth of the nucleated droplets on an oil is its spreading behavior on water expressed in terms of the spreading coefficient of oil on water in presence of air (Sow(a)), given by Sow(a) = γwa- γow -γoa, where γwa, γow and γoa are the water/air, water/oil, and oil/air interfacial tensions, respectively47, 50. Oils with Sow(a)0 tend to spread on water, as a result of which droplets nucleating on oil/air interface submerge within due to spontaneous oil cloaking and grow primarily by coalescence47, 50. To investigate whether the oil spreading behavior on water played a role in the droplet size differences as observed previously, we calculated the spreading coefficients of dodecane and kerosene on water. Based on the surface tension of dodecane (γoa= 25.4±0.5 mN/m) and its interfacial tension with water (γow= 52.8±1 mN/m), we find that the spreading coefficient of dodecane on water is Sow(a)= 6.4±1.2 mN/m, implying that dodecane does not spread on water. The addition of nanoparticles leads to slight lowering of interfacial tension between dodecane-water (see Fig. S5) from which we find that the Sow(a) = -0.6±1 mN/m, implying that dodecane-nanoparticle solution also does not cloak water. On the other hand, experimental measurements showed that for kerosene γow = 34.7±1 mN/m in absence of nanoparticles and γow = 26.5±1 mN/m in presence of nanoparticles, from which we find that Sow(a) = 12.3±1.2 mN/m and Sow(a) = 20.5±1.2 mN/m in absence and presence of nanoparticles respectively. Thus unlike dodecane, kerosene spreads on water with/without nanoparticles. In order to understand how the spreading behavior of oil solution could influence droplet sizes, we condensed water droplets on dodecane and kerosene in absence and presence of nanoparticles (NP-2,

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1 wt%) and observed the growth behavior of droplets under optical microscope under identical conditions (RH = 75-80%, TDP ~15±1 °C, TS= 2±0.5 °C). As shown in Fig. 2, a dramatic difference in droplet growth behavior is observed for the different cases mentioned above. Droplet growth is found to be highest on pure dodecane (a non-spreading oil) as a consequence of direct diffusional growth from water vapor present in air and coalescence of neighboring droplets (Fig. 2a). The addition of nanoparticles to dodecane drastically suppressed the droplet growth (Fig. 2b) as a result of nanoparticle adsorption at the oil-water interface. The adsorption suppresses the coalescence rate of droplets, however droplet growth still occurs via vapor condensation at the water-air interface of the floating droplets (Fig. 2b schematic). For the case of water droplets condensing on pure kerosene (a spreading oil), the droplets also grew to large micrometric sizes (Fig. 2c), although their growth rate is comparatively less than the growth rate of water droplets on dodecane. The droplets on kerosene are submerged within and their coalescence is limited by the intervening oil film between them47. Since kerosene has low viscosity it can drain quickly between droplets, allowing rapid coalescence of droplets to take place. Finally, the droplet size behavior is found to change dramatically in the case of condensation on kerosene-NP mixture solution (Fig. 2d). The surface of the droplet turned hazy with time, and no discrete droplet was discernible even after 20 minutes of condensation suggesting the droplets were in sub-micron size ranges due to spontaneous nanoparticle adsorption. These experiments suggest that use of nanoparticles with oils can provide as a useful strategy to decouple the growth mode of droplets in condensation. Further, it is clear from these results that the dominant mechanism for droplet growth on oils is coalescence. The key to successfully obtain nanoemulsions via condensation is to suppress both the diffusion growth and coalescence growth of droplets. By choosing oil that spreads on water and adding stabilizing agents such as nanoparticles, Pickering nanoemulsions can be obtained.

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Nanoemulsion size as function of nanoparticle size and concentration. Having established the role of oil properties in determining the size of Pickering emulsions, we next sought to develop an understanding of the effect of nanoparticle size and concentration on emulsion size. We systematically varied the particle size (NP-1, NP-2 and NP-3) and the particle concentration (0.05, 0.2, 0.5 and 1 wt%) in a fixed volume (6 ml) of kerosene and subsequently condensed water on each solution under identical experimental conditions. In each instance, the condensation time (tcon) was fixed as 2 minutes. Subsequent to condensation, a volume of the solution was immediately transferred to a glass vial and analyzed using DLS to obtain a droplet size distribution. The DLS data shows that each solution comprised of emulsions with peak sizes ranging from 300-600 nm (Fig. 3a, and see Fig. S6 for the full droplet distribution). However, there is significant variation in polydispersity of the emulsion droplets as a function of particle concentration and size. Regardless of the particle size, we find that the emulsion size and polydispersity decrease as the particle concentration is increased from 0.05 wt% to 0.5 wt% and thereafter increase marginally as particle concentration is further increased to 1 wt%. Another noticeable aspect of the observations is that the DLS measurements show a complete absence of any measurable peak in the size range below 10 nm – the range within which droplet nuclei (Dnuclei~2-10 nm) due to heterogeneous nucleation are formed at the oil/air interface. Since nuclei sizes are below the size of the nanoparticles themselves, they are likely to coalesce and grow to a minimum size where nanoparticles could successfully encapsulate them and prevent any further coalescence. The maximum surface coverage around a droplet can occur in 3D hexagonally closed packed structure51 wherein the encapsulated droplet and nanoparticle are of similar size. Thus the smallest particle stabilized droplet size (Dmin) that can be detected by DLS is roughly equal to the three times of the particle size, so the smallest emulsion diameter for NP-1, NP-2, NP-3 nm particles are ~45, 150 and 276 nm respectively.

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The increase in particle concentration also brings a visible change in the appearance of each emulsion. An example of this behavior is shown in Fig. 2b where emulsions were prepared using NP-2 nanoparticles. For the lowest concentration case (0.05 wt%), large micrometric droplets settled in the bottom of the vial were observed indicating that in this case, the condensed droplets were insufficiently stabilized by nanoparticles and hence coalesced and precipitated at the bottom, giving the solution a transparent appearance. The solution color was observed to change upon increasing the concentration of Si NPs, especially milky solutions are observed after at concentrations greater than 0.5 wt%. A more detailed picture emerges upon doing SEM analysis of emulsions deposited on a silicon surface after evaporating water and oil medium (Fig. 3b and Fig. S7). For the case of 0.05 wt% the droplets had significant interconnected regions indicating incomplete coverage in line with the macroscopic behavior. The number density of interconnected droplets decreases as the nanoparticle concentration is increased. The images indicate that water droplets are nearly fully covered by NP-2 at 0.5 wt%. Image analysis of these images show that the pore size distribution is in close agreement with the DLS distribution (Fig. S8) for the case of 0.05-0.5 wt%. However for the case of 1 wt%, the structure resembles sub-micron sized / nanoporous membranes with pore sizes (i.e. water droplets) that are significantly lower than the size range obtained through DLS. We hypothesize that the larger droplet distribution obtained through DLS in comparison to SEM can be attributed to combination of two factors: firstly, formation of particle multilayers because of increased hydrophobic interactions between free silanized NPs 52; and secondly, possible formation of multi-layered droplets as has been noted to occur at high particle concentrations53. The significant difference in DLS and SEM size distribution indicates that the second mechanism plays a more decisive role in these observations. It is clear from the images and their analysis that droplet sizes continuously decrease by increasing nanoparticle concentration.

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Factors determining nanoemulsion size in presence of self-assembling nanoparticles. To obtain an idea of the size ranges observed in Fig. 3, we made analytical models to obtain the maximum and average droplet sizes. The upper limit of droplet size on other hand is limited by the total particle concentration available in the medium for which it is important to examine the relation between emulsion droplet diameter (D), nanoparticle radius (a) and number of nanoparticles (np) in oil with volume Vo. The number of nanoparticles np is related to the particle weight fraction (w) in the oil as np = (3wVoρo)/(4πa3ρp) where ρo and ρp are of density of oil and particles respectively. The number of droplets in the oil is given by nw= 6Vw/πD3 where Vw is the volume of water that condensed on the oil in condensation time tcon. For simplicity, we assume all the droplets are of a uniform size and having identical nanoparticle coverage (S) formed by monolayer packing. In such a case, the total area of particles in contact with the droplet equals the total fraction of droplet area covered by particles, i.e. np(πa2sin2θ) = nw(πD2S) where a·sinθ is the radius of the area covered by a particle at the water-oil interface54-55. We can then obtain the upper limit of droplet size in oil, D as

D=

8φ aS ρ p

(1)

wρo sin 2 θ

Here, ϕ is the fraction of dispersed phase in the bulk volume given by ϕ=Vw/Vo= V̇wtcon/Vo where V̇w is volumetric condensation rate and tcon is the condensation time. Eqn. (1) shows that for identical condensation times and condensation rates (i.e. same subcooling), the droplet size decreases by increasing the concentration of nanoparticles – as was observed in experiments (Fig. 3, also see Fig. S7, S8 and S9). Eqn. (1) is valid for steady state conditions and is representative of the upper limit of droplet sizes. However, emulsion formation by condensation is an unsteady process wherein droplet concentration gradually increases within the oil and thus the surface coverage by nanoparticles varies

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spatially and temporally within the solution. Since nanodroplets form at the oil-air interface, there is far greater number density of droplets near the oil-air interface at any time. The nanodroplets are thus likely to coalesce together while also absorbing nanoparticles diffusing inside the oil medium until a droplet is covered to the maximum coverage (S≈0.90 for 2D-HCP), at which point its coalescence with other nanodroplets is finally arrested. Thus the average emulsion droplet size is determined by the competition between nanoparticle adsorption time and coalescence time of droplets. The coalescence process between droplets is driven by forces acting on the droplets that control the rate of oil drainage between them. For simplicity, we consider that two droplets interact via Van der Waals forces only and are represented as hard-spheres, in which case the rate of approach of droplets in oil is given by dh/dt= −AH/(72πrhµo) where r, h, AH, and µo are droplet radius, time-dependent oil thickness between droplets, Hamaker constant of droplets in the medium and oil viscosity respectively56. By integrating the above equation, we can get the coalescence time scale (τc) between two droplets as τ c = 36πµo rh02 AH where ho is the initial distance between droplets (see Supplementary discussion S1). A droplet may undergo a series of coalescences before its size is arrested. Assuming that n coalescence events occurs between an evolving droplet and a minimum possible particle stabilized droplet size (i.e. initial size ri = Dmin/2=a) under influence of Van der Waals forces, the size of the evolving droplet at the end of nth coalescence is given by rn = 3 n + 1ri and the total elapsed coalescence time is given by τc, total= nτc (Fig. S10). As the droplets are interacting with each other, the nanoparticle adsorption may occur simultaneously. Since the hydrophobic nanoparticles in our case are dispersed in low-dielectric oil to begin with, we suggest that it is unlikely for them to develop significant residual charges that could affect droplet adsorption kinetics even if they absorb at oil/water interface (see Supplementary discussion S2) and hence electrostatic interactions were not considered. In order to consider the adsorption aspects, we adopt the Ward and Tordai model57 in spherical co-ordinates58-60:

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∂c 1 ∂  2 ∂c  = Do 2 R ( R > r,t > 0) ∂t R ∂R  ∂R 

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(2)

Here c represents particle concentration [mol/m3], R is the spherical coordinate, t is time and Do is the nanoparticle diffusion coefficient given by the Stokes–Einstein equation (Do = kbT/6πaµo where kb is the Boltzmann constant). Because of irreversible adsorption of nanoparticles, the coverage of nanoparticles on a droplet increases. The time dependent particle adsorption per unit area (mol/m2) - Γ is related to the diffusion of particles by

. The limiting solution for this equation is given by

Γ= c∞Dot/r where c∞ is the initial concentration of particles (mol/m3) respectively (see Supplementary discussion S1 for further details). From this, we can get the critical time of adsorption (t= τa) on a droplet of radius r as given by τa = rΓm/Doc∞ where Γm is the maximum particle absorption per unit area (mol/m2). If the final droplet radius at the nth event is rn, then the adsorption time scale corresponding to such a droplet is given by τa,f = rn Γm/Doc∞. Finally, the droplet coalescence is arrested when adsorption time of nanoparticle to maximum coverage becomes nearly equal to the total droplet coalescence time i.e. τc,total = τa,f from where we can obtain the final droplet size that is completely stabilized by nanoparticles against coalescence as given by

Davg = 2rn + 2a where rn = 3 n + 1ri and n =

2ρ pS

AH a 2 9wρo sin 2 θ k BT h02

(3)

It is clear from the equation that the average droplet size increases with increase in nanoparticle size and reduces with increase in nanoparticle concentration (also see Fig. S11). Taking ri= a, h0= 100 nm, and AH=4e-20 J, we find that for NP-1, NP-2, and NP-3, the average droplet emulsion size (Davg) is ~42, 302 and 842 nm respectively for the concentration of 0.2 wt%. These values correspond reasonably well to the observed emulsion sizes (Fig. 3). Note that the suggested coalescence and adsorption

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mechanism is one possible route for emulsion growth. Obtaining an accurate picture of emulsion growth requires detailed understanding of spatial and temporal variation in droplet distribution within the oil – an aspect that is beyond the scope of the present work. Nanoemulsion size as function of condensation time and their short-term stability. Following Eqn. (1) and Eqn. (3), the emulsion size is directly dependent upon the volume of dispersed phase in the oil that can be controlled by either varying the degree of subcooling or the condensation time (the time period for which the oil is kept subcooled). To investigate these effects, experiments were carried out for tcon=2, 5, 10, 20, and 40 minutes using NP-1, NP-2 and NP-3 nanoparticles. To bring the competition between condensation rate and NP adsorption rate more clearly, a lower concentration of 0.2 wt% was chosen for each solution. Similar to previous experiments, the instantaneous emulsion size was monitored, and additionally the solutions were tracked over one hour to observe their short-term stability. Fig. 4 shows the evolution of droplet sizes for different ‘condensation times’ at approximately 0 minutes, 30 mins and 60 mins after the formation of emulsions (see Fig. S13 for the full DLS spectra of each case). Henceforth, these times will be referred to as observation times (tobs) to distinguish them from ‘condensation times’. We find that for NP-1, nanoemulsions with peaks ranging from 300-400 nm are formed and remain unchanged for condensation times of 2-10 mins. However, for emulsions formed by condensing vapor for 20 and 40 mins, the emulsion comprises of both micrometric and nanometric sized droplets and the micrometric droplets evolve to larger sizes with time. For the case of tcon=40 mins, after an hour the DLS did not detect any distinct peak either because droplets evolved to sizes greater than 10 µm the upper detection limit of DLS and/or because they sedimented at the bottom. These results indicate that while the nanoparticle concentration is sufficient to adsorb on droplets and stabilize them initially, nanoparticle adsorption with time results in depletion of their concentration near the oil-air interface as a

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result of which the droplets condensing at later times may have incomplete NP coverage leading to increase in sizes by coalescence. Emulsions prepared using NP-2 and NP-3 nanoparticles show similar behavior, however the range of stable nanometric droplets is significantly different for them. For NP-2 and NP-3, we find that short-term stability of nanoemulsions is only observed for the cases of tcon up to 10 min and 5 min respectively. For NP-3, we find that the nanometric sized droplets at 5 and 10 minutes are below or nearly the same value as the theoretically minimum predicted droplet size, indicating that this peak represents a mixture of nanoparticle aggregates and particle stabilized droplets. From the Stokes-Einstein equation, it is well known that Do∝1/a, thus smaller nanoparticles diffuse faster compared to larger nanoparticles and hence are more disposed to adsorbing on nanodroplets quickly and preventing further coalescence. We also find that the average droplet size as predicted by considering the adsorption and coalescence kinetics (Eqn. 3) matches reasonably well with the droplet sizes observed experimentally at small condensation times. Note that because of low solubility of water in kerosene, and the fact that nanometric droplet sizes remain practically unchanged during observation period of one hour and more suggests that the droplet size increase is not associated with Ostwald ripening phenomenon, but related to coalescence mechanism as previously suggested. As demonstrated here, unlike previous studies wherein multiple steps and high nanoparticle concentrations were used32-34, Pickering nanoemulsions can be obtained in a single step even using low concentrations. Increasing the nanoparticle concentration can lead to nanoemulsions that last longer (Fig. 1e and Fig. S14). Still, the large density difference between water/silica and kerosene makes the synthesized w/o Pickering nanoemulsions prone to sedimentation in few days. The stability can be increased significantly for example by using janus nanoparticles or using surfactants alongside (e.g. Fig. S14). However long-term stability also depends upon other phenomenon such as particle-particle

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interactions, Ostwald ripening, or development of electrostatic interactions. An investigation on these factors is beyond the scope of this work and requires further studies. DiscussionGeneral aspects of emulsion by condensation method. The vapor condensation process to obtain emulsions also has some unique features. For example, it has the potential to lead to unprecedentedly large number of nanodroplets in very short durations. The nucleation rate of droplets (nnuclei #/s) is given by the relation nnuclei =6V̇w/πD3nuclei and Using Dnuclei= 5 nm and V̇w=0.011 ml/min41, we find that in our experimental conditions ~1015 nuclei are formed every second. Furthermore, because emulsion formation occurs at the oil surface, the amount of emulsion formed scales with the oil surface area. For example, in our study, ϕ varies from 0.37% - 7.33% in oil volume of 6 ml for tcon from 2-40 mins. Because emulsion formation is dependent on available surface area of bulk phase, the process is highly scalable and emulsion can be formed in a millimeter-sized droplet and in large shallow oil baths to yield quantities ranging from microliters to milliliters in the identical times (Fig. S15). Scalable production of highly monodisperse droplet sizes may require controlling factors affecting condensation such as vapor velocity, and minimizing condensation on the side-walls of oil chamber – as demonstrated in this work. Finally, it can be shown that vapor condensation method requires 102-108 times less energy than a process like homogenization to obtain nanoemulsions (Supporting Discussion, S17).

CONCLUSION In summary, we have presented a new approach to formulating Pickering nanoemulsions by condensing water vapor on subcooled oil containing hydrophobic silica nanoparticles that is highly scalable and highly energy efficient. The size of the emulsified droplets is critically dependent upon the spreading behavior of oil on water and the nanoparticle adsorption kinetics. By controlling the diffusion

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growth through use of an oil that spreads on water, and controlling the droplet coalescence through use of nanoparticles that adsorb at the oil-water interface, nanoscale Pickering emulsions can be formulated. Such nanoemulsions could potentially be used to directly prepare sub-micron sized membranes (e.g. as observed in Fig. 3b) and nanoporous membranes. Although the emulsion synthesis process has been demonstrated using pure water-in-oil dispersions stabilized by nanoparticles, different strategies such as co-condensing multiple vapor species or directed aerosolization deposition towards bulk liquid surface could be potentially used to add multiple species in nanodroplets. Exploration of such and other possible pathways to add compounds within condensing droplets poses an interesting challenge, solving which could open doors for new opportunities for example to form complex and drug encapsulated emulsions. We envision that the synthesis of highly monodisperse Pickering nanoemulsions will lead to new applications in biology, chemistry and materials science.

ASSOCIATED CONTENT SUPPORTING INFORMATION. Additional DLS, SEM, confocal microscope and photograph and detail explanation. This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Author * E-mail: [email protected] NOTE The authors declare no competing financial interest.

ACKNOWLEDGEMENTS

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All the DLS measurements were performed at the Nano Core Facility at UIC. The SEM and TEM were obtained at the Electron Microscopy Service (Research Resources Center, UIC). We acknowledge the assistance of Dr Daniel P Bailey in copy-editing of the manuscript. SA thanks the support of Society in Science – Branco Weiss Fellowship and UIC College of Engineering. References (1) Schramm, L. L. Emulsions, Foams, Suspensions, and Aerosols : Microscience and Applications, Wiley-VCH Verlag GmbH & Co. KGaA: 2014; p 23-84. (2) Tadros, T. F. Emulsions: Formation, Stability, Industrial Applications, De Gruyter: 2016. (3) Yang, Y.; Fang, Z.; Chen, X.; Zhang, W.; Xie, Y.; Chen, Y.; Liu, Z.; Yuan, W. An Overview of Pickering Emulsions: Solid-Particle Materials, Classification, Morphology, and Applications. Front. Pharmacol. 2017, 8 (23), 287. (4) Ashby, N. P.; Binks, B. P. Pickering Emulsions Stabilised by Laponite Clay Particles. Phys. Chem. Chem. Phys. 2000, 2 (24), 5640-5646. (5) Sacanna, S.; Kegel, W. K.; Philipse, A. P. Thermodynamically Stable Pickering Emulsions. Phys. Rev. Lett. 2007, 98, 158301. (6) Berton-Carabin, C. C.; Schroën, K. Pickering Emulsions for Food Applications: Background, Trends, and Challenges. Annu. Rev. Food Sci. Technol. 2015, 6, 263-297. (7) Pickering, S. U. CXCVI. - Emulsions. J. Chem. Soc., Trans. 1907, 91, 2001-2021. (8) Binks, B. P. Particles as Surfactants - Similarities and Differences. Curr. Opin. Solid State Mater. Sci. 2002, 7 (1-2), 21-41. (9) Aveyard, R.; Binks, B. P.; Clint, J. H. Emulsions Stabilised Solely by Colloidal Particles. Adv. Colloid Interface Sci. 2003, 100-102, 503-546. (10) Vignati, E.; Piazza, R.; Lockhart, T. P. Pickering Emulsions: Interfacial Tension, Colloidal Layer Morphology, and Trapped-Particle Motion. Langmuir 2003, 19 (17), 6650-6656. (11) Chevalier, Y.; Bolzinger, M. A. Emulsions Stabilized with Solid Nanoparticles: Pickering Emulsions. Colloids Surf. A. 2013, 439, 23-34. (12) Wu, J.; Ma, G. H. Recent Studies of Pickering Emulsions: Particles Make the Difference. Small 2016, 12 (34), 4633-4648. (13) Zanini, M.; Marschelke, C.; Anachkov, S. E.; Marini, E.; Synytska, A.; Isa, L. Universal Emulsion Stabilization from the Arrested Adsorption of Rough Particles at Liquid-Liquid Interfaces. Nat. Commun. 2017, 8, 15701. (14) Patravale, V. B.; Mandawgade, S. D. Novel Cosmetic Delivery Systems: An Application Update. Int. J. Cosmet. Sci. 2008, 30 (1), 19-33. (15) Dickinson, E. Food Emulsions and Foams: Stabilization by Particles. Curr. Opin. Solid State Mater. Sci. 2010, 15 (1-2), 40-49. (16) Frelichowska, J.; Bolzinger, M. A.; Valour, J. P.; Mouaziz, H.; Pelletier, J.; Chevalier, Y. Pickering w/o emulsions: Drug release and topical delivery. Int. J. Pharm. 2009, 368 (1-2), 7-15. (17) Xia, Y.; Wei, J.; Du, Y.; Wan, T.; Ma, X.; An, W.; Guo, A.; Miao, C.; Yue, H.; Li, S.; Cao, X.; Su, Z.; Ma, G. Exploiting the Pliability and Lateral Mobility of Pickering Emulsion for Enhanced Vaccination. Nat. Mater. 2018, 17 (2), 187-194.

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Figure 1| Characteristics of synthesized nanoparticles as stabilizers at oil-water interface and mechanism of Pickering emulsion formation. (a) Transmission electron microscope (TEM) images of silanized silica nanoparticles: NP-1 (dia.=13 ± 2.1 nm), NP-2 (dia.=52 ± 4.1 nm), NP-3 (dia.=92 ± 10.3 nm). (b) Optical images of a water drop retraction in kerosene and dodecane with 2 wt% of NP-2. (c) Schematic illustration of w/o Pickering emulsion using condensation process. (d) Optical and photograph images of water in dodecane (0.5 wt% NP-2*) Pickering emulsion after a day (e) Optical and confocal microscope image of water in kerosene (0.5 wt% NP-2*) Pickering nano emulsions after a day. Scale bars: (a), 100 nm; (d), 200 µm; (e) 10 µm.

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Figure 2| Droplet size evolution and schematic of growth mechanism in absence and presence of NPs, (a) negative spreading coefficient; water in dodecane (w/d) without NPs, (b) negative spreading coefficient; w/d with 1 wt% of NP-2, (c) positive spreading coefficient; water in kerosene (w/k) without NPs, (d) positive spreading coefficient; water in kerosene (w/k) with 1 wt% NP-2. Scale bars (a-d) 10 µm.

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Figure 3| Size variation of Pickering emulsions as function of nanoparticle size and concentration. (a) Evolution of diameter distribution by dynamic light scattering measurement, the size of water droplet with NP-1, NP-2 and NP-3 as function of concentration. Note that the measurements in Figure 3a exclude the particle size peaks and in absence of any particle agglomerates were inferred to give sizes of particle stabilized droplets. The nanoscale region (droplet size

Synthesizing Pickering Nanoemulsions by Vapor Condensation - ACS

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