Max
Meissner
*ab,
Jun
Dong
ab,
Jens
Eggers
c,
Annela M.
Seddon
abd and
C. Patrick
Royall
abef
aH.H. Wills Physics Laboratory, University of Bristol, Bristol, BS8 1TL, UK. E-mail: M.Meissner@Bristol.ac.uk
bCentre for Nanoscience and Quantum Information, Tyndall Avenue, Bristol, BS8 1FD, UK
cMathematics Department, University of Bristol, BS8 1TW, Bristol, UK
dBristol Centre for Functional Nanomaterials, University of Bristol, Bristol, BS8 1TL, UK
eChemistry Department, University of Bristol, Bristol, BS8 1TS, UK
fDepartment of Chemical Engineering, Kyoto University, Kyoto 615-8510, Japan
First published on 22nd December 2016
We have developed norland optical adhesive (NOA) flow focusing devices, making use of the excellent solvent compatibility and surface properties of NOA to generate micron scale oil-in-water emulsions with polydispersities as low as 5%. While current work on microfluidic oil-in-water emulsification largely concerns the production of droplets with sizes on the order of 10s of micrometres, large enough that Brownian motion is negligible, our NOA devices can produce droplets with radii ranging from 2 μm to 12 μm. To demonstrate the utility of these emulsions as colloidal model systems we produce fluorescently labelled polydimethylsiloxane droplets suitable for particle resolved studies with confocal microscopy. We analyse the structure of the resulting emulsion in 3D using coordinate tracking and the topological cluster classification and reveal a new mono-disperse thermal system.
Given the considerable amount of interest in emulsions, it should come as no surprise that the formation of emulsions is a well explored field with a huge range of emulsification techniques available. These methods include such techniques as mechanical milling, blending, high pressure homogenization, or shear mixing. While powerful, these techniques tend to produce large emulsion droplets, or emulsions with a broad size distribution. Microemulsions on the other hand, while extremely versatile due to their self assembly behaviour, have sizes in the range of 10–100 nm, and are thereby far too small for real space imaging and coordinate tracking.13 An emulsion that combines the best of both worlds possessing both an average droplet size in the range of a few microns, with a narrow size distribution, would open up a wide range of new possibilities.
An alternative to the aforementioned methods is microchannel emulsification, a versatile technique where two or more distinct fluid phases are flowed through a microscale channel and interfacial stresses are induced to generate droplets with very narrow size distributions.14 Currently microfluidic emulsification techniques remain focussed primarily on the formation of water-in-oil emulsions, usually with the viscosity ratio λ below 1.
In order to develop the desired colloidal model system we must first consider the behaviour of a droplet in solution using the Peclet number Pe = τB/τsed. Here this dimensionless parameter is the ratio between the time it takes for a particle to diffuse its own radius, τB = σ3πη/8kBT, where σ is the particle diameter η is the solution viscosity and T is the temperature, and the time the particle takes to sediment by its diameter, τsed = σ/vsed, where vsed is the sedimentation velocity vsed = δmg/3πησH, where δm is the bouyant mass and σH the hydrodynamic diameter. A Peclet number of around one is generally seen as the dividing line between a colloidal system and an athermal granular system.15 As the Peclet number scales with both particle diameter, and particle-solution density difference, a colloidal emulsion can be achieved either by producing droplets of a sufficiently small diameter or by using liquids with similar densities.16 As such, it is vital that a microfluidic system for the production of colloidal oil-in-water emulsions is capable of both producing droplets which are suitably small and uniform, but also to be solvent-compatible enough to produce emulsions from a range of component materials.
Microfluidic droplet generation can be realised with three types of device: T-junction devices where a slug of the dispersed phase is extruded into a flowing fluid until the dispersed phase fluid breaks up into droplets,17 co-flowing devices where an outer continous phase fluid flows parallel to and surrounding an inner dispersed phase fluid until droplet generation occurs via stretching of the interface between the two fluids,18 and flow-focusing devices, where co-flowing streams are forced through a narrow aperture causing droplet breakup.19 Here we consider flow-focusing devices, as these provide the best system for producing droplets with sizes smaller than those of the channel dimensions.
However, producing suitable oil-in-water emulsions via microfluidic methods remains challenging. The vast majority of microfluidic emulsification systems are manufactured using polydimethylsiloxane (PDMS). While PDMS is an excellent material for water-in-oil microfluidics20 offering good solvent compatibility, good optical transmittivity, high flexibility and great durability, it is also strongly hydrophobic, preventing the stable formation of oil-in-water droplets.21 Although techniques for making PDMS devices hydrophilic and thereby allowing stable droplet generation exist, these are either short lived such as plasma treatment22 or involve sequential surface coatings23 which are impractical for use with devices small enough to easily generate micron scale droplets.
Norland optical adhesives provide a viable alternative to PDMS for oil-in-water microfluidics24,25 allowing rapid templating of complex microchannels.26 Their rapid curing speed, alongside their durability, makes them ideal for pattern transfer from PDMS molds. Additionally, while natively more hydrophilic than PDMS, exposure to an Oxygen plasma forms a long-lasting hydrophilic surface, ideal for the formation of oil-in-water droplets.24 Here we introduce a microfluidic flow focussing system based on the use of NOA microfluidics for the generation of monodisperse oil in water emulsions which can produce droplets on the micron scale with polydispersities of below 5%. To demonstrate the utility of this technique, we use the topological cluster classification to investigate the higher order structure of a polydimethylsiloxane oil emulsion, and compare this to a simulated hard sphere system.
This paper is organised as follows. In Section 2 first we describe the micro-fabrication and polymer casting process of the Norland flow-focusing devices used. In the same section we briefly describe the flow focusing process used to generate micron scale emulsions and the confocal microscopy and coordinate tracking techniques. The topological cluster classification algorithm is used to analyse the structure of the resulting packings.27 In Section 3 we describe the droplets produced and demonstrate the excellent size selectivity of this method by varying flow rates at various viscosity ratios. We then describe the structural insights obtained from using the topological cluster classification algorithm for probing the structure of an emulsion, and our results are compared to a simulated hard sphere system. Finally, we briefly summarise our work and the scientific implications thereof in Section 4.
Oil phase | Aqueous phase | η o/ηi |
---|---|---|
80![]() ![]() |
Deionised water | 0.3 |
80![]() ![]() |
50![]() ![]() |
1.5 |
Dodecane | 50![]() ![]() |
3.8 |
Droplets were subsequently collected by allowing stable droplet collection to proceed long enough to drive the produced emulsion into a 1 ml Eppendorf vial, transferred into a glass capillary and imaged on a Leica brightfield microscope. Droplet sizing was carried out as shown in Fig. 3(a) where the size was taken directly from the image.
For the purpose of analysis using the topological cluster classification (TCC) analysis, droplets were produced as above using a system of 5 cP polydimethylsiloxane oil dyed with Nile red as the oil phase and 32 mmol sodium dodecyl sulfate solution as the aqueous phase. Produced droplets were then collected and diluted with 50% by weight glycerol in order to match refractive indices between the aqueous and non-aqueous phases. The index matched emulsion was filled into a capillary and imaged using confocal laser scanning microscopy on a Leica confocal microscope. A 512 × 512 × 256 pixel image was taken and coordinate tracking was carried out using the Colloids particle tracking package,30 this tracking method identifies particle centres by searching for a Gaussian of the image intensity and produces XYZ coordinates for each detected particle. XYZ coordinates of particle centers were used to calculate a 3D g(r) and the Topological Cluster Classification (TCC) was used to interpret cluster populations.31
Within this range of Qo/Qi the formation of droplets was observed via two distinct mechanisms. Droplet formation in a microfluidic device is governed by three main parameters, the flow rate ratio Qo/Qi, the ratio of the outer and inner fluid viscosities λ = ηo/ηi, and the capillary number Ca = ηoGa0/γ where G is a characteristic deformation rate and ao is the characteristic droplet radius. Of particular importance here is the capillary number, a parameter influenced by the geometry of the device as well as the flow rate of the fluid being considered.36 Depending on the capillary number and thereby the flow rate ratio Qo/Qi, it is possible to select between two separate modes of droplet production. At lower capillary numbers, of order 10−2, geometry controlled droplet formation occurs as shown in Fig. 2(a). In this mode the fluid interface stretches through the aperture and obstructs, leading to a pressure spike followed by droplet breakup. For this mode a weak scaling with flow rate is expected and droplet size is roughly the same as the channel geometry.37 At higher values of the flow rate ratio Qo/Qi, with capillary number of order 10−1 this geometry controlled mode gives way to the dripping mode of droplet formation as shown in Fig. 2(b). The fluid interface in a dripping microfluidic device narrows into a fluid tendril, with the droplet “snap-off” point remaining stationary and within the constricting aperture. This mode of formation yields droplets smaller than the device geometry.38
Once a stable formation regime was established, an emulsion produced at a fixed Qo/Qi value of 40 was collected on the millilitre scale. Droplets produced in this way are shown in Fig. 3 with a polydispersity, here defined as the relative standard deviation, of 5%.
Varying the viscosity ratio of the outer to inner phase, ηo/ηi, lead to some striking differences in droplet production. At a low value ηo/ηi of 0.3, droplet production was stable throughout the largest range of flow rates, with droplet size scaling inversely with flow rate as shown in Fig. 4(a). At a value of ηo/ηi of 1.5, stable droplet formation was found to occur in a much narrower band of Qo/Qi, in particular droplet formation also seemed to proceed via two methods depending on the total net flow rate as shown in Fig. 4(b) this striking difference between two methods of flow seems to suggest a switch between two different modes of droplet behaviour. Finally, at a value of ηo/ηi of 3.8, droplet formation was highly unstable, and droplets produced were twice as large as at lower flow rates, with average radii above 6 μm. Surprisingly we find that droplet formation proceeds in a more stable manner at lower values of Qo/Qi, with only a small trade off in droplet size.
As shown in Fig. 4 and 5 our microfluidic system demonstrates a high degree of versatility in the size of droplets produced. By varying Qo/Qi, a wide range of droplet sizes was produced with excellent size selectivity. Droplets produced ranged in radius from 2 μm to 12 μm and droplet size was observed to be in good agreement with predictions by Garstecki et al.37 as shown by the linear scaling of the log–log plot of droplet diameter, σ and the flow rate ratio Qo/Qi in Fig. 5 suggesting a dripping mode of droplet production.
In the case of higher-order structural measures, beyond the two-point correlations, in a dense assembly of spheres tetrahedra and consequently five membered clusters consisting of two tetrahedra are rapidly formed, with particles arranged as members of these locally favoured structures having lower potential energies and slower dynamics.34,35 The clusters prevalent in our system are shown in Fig. 6(c). In Fig. 6(d) we render droplet coordinates coloured according to the identities of the clusters in which they are found. Organisation of these tetrahedra into larger clusters can be suppressed due to dynamical arrest with the system unable to reach an equilibrated configuration for which the formation of larger clusters is expected. Due to this gels and glasses, as well as athermal granular systems are dominated by tetrahedra, while dense systems which are thermal, and in which reorganisation can occur such as (supercooled liquids) would be dominated by higher membered clusters.39,40 Here the hard spheres have a volume fraction of ϕ = 0.42, which is not sufficiently dense to be supercooled and in fact the most prevalent structures found by the TCC are smaller m = 5, 6 clusters [Fig. 6(e), yellow]. On the other hand, in our emulsion system we see significantly more m = 12 and m = 11 structures, where m is the number of particles in the structure, than m = 5 structures [Fig. 6(e), blue]. Such larger membered clusters suggest that our system is a thermal system analogous to a supercooled liquid.34 This moreover shows that the higher order structure is rather distinct from that of supercooled liquids hard spheres (formed at higher ϕ ≳ 0.56) which are dominated by 10-membered defective icosahedra.31,34,35 This suggests that the emulsion system exhibits an interaction potential very distinct to that of hard spheres. This could arise via two main routes. Firstly, as sodium dodecyl sulphate was used to stabilise the droplets, the emulsion droplets will be charge stabilised. A potential consequence of this charge stabilisation is a higher effective volume fraction, and thereby increased higher order structure in the emulsion. Note in particular that electrostatic effects can lead to slow dynamics at volume fractions that would otherwise be fluid.41,42 Secondly, the increased prevalence of higher order structures could arise through deformation of the droplets allowing rearrangement towards higher order clusters. Due to their small size, the Laplace pressure within the droplets prevents significant deformation, nevertheless, the droplets are intrinsically more deformable than a comparable “hard sphere” system.
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