Droplet-based microfluidic device for multiple-droplet clustering

Abstract

We present a multiple-droplet clustering device that can perform sequential droplet trapping and storing. Shape-dependent droplet manipulation in forward and backward flows has been incorporated to achieve high trapping and storing efficiency in a 10 × 12 array of clustering structures (e.g., storing well, storing chamber, trapping well, and guiding track). In the forward flow, flattened droplets are trapped in each trapping well. In the backward flow, the trapped droplets are released from the trapping well and follow the guiding tracks to their corresponding storing wells. The guided droplets float up out of the confining channel to the super stratum of the storing chamber due to interfacial energy and buoyancy effects. This forward/backward flow-based trapping/storing process can be repeated several times to cluster droplets with different contents and samples in the storing chambers. We expect that the proposed platform will be a valuable tool to study complex droplet-based reactions in clustered droplets.

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1. Introduction

Droplet-based microfluidics has proven to be a useful tool to study many biological, chemical, and pharmaceutical reactions in a high-throughput manner.^1,2 The pairing of two droplets containing different reagents and samples is one of the essential unit operations in the droplet-based microfluidics platform. The droplet pairing has been demonstrated in continuous-flow channels^3,4 and static arrays.^5,6 Usually, the flow-through approach is suitable for high-throughput end-point detection, and the static array approach is appropriate for large-scale real-time monitoring. The key requirement for the droplet pairing in the continuous-flow channels is the perfect synchronization of two droplets over long-term periods because uncontrolled synchronization results in unreliable droplet pairing. However, the droplet pairing has been challenged largely due to hydrodynamic resistive coupling effects between droplets in the channels.⁷ The droplet pairing efficiency in the continuous-flow channels could be improved by well-controlled synchronized droplet generation³ or pairwise droplet formation.⁴

Another approach was to use trapping structures to trap and pair droplets in an in-parallel static array⁵ or an in-serial channel array⁶ by means of manipulation of flow directions (e.g., trapping in the forward flow and pairing in the backward flow^8–10). However, their pairing efficiency was poor (e.g., 73% for the in-parallel array⁵ and 40% for the in-serial array⁶) mostly due to the unstable streamline controls or inhomogeneous hydrodynamic nature of the two-phase flow. In addition to the droplet pairing, a more desirable but more challenging unit operation is clustering of multiple droplets containing different reagents and samples with high pairing or clustering efficiency for complex assays.

Here, we introduce a droplet clustering array device performing trapping and storing by forward and backward flows, which can be repeated several times to cluster droplets with different contents and samples. Fig. 1 shows the schematic illustration of the proposed device consisting of two PDMS layers. The lower layer, including a flow-focusing junction and traps, is used for generating and trapping droplets. The upper layer, including guiding tracks and storing chambers, is used for droplet guiding, storing, and clustering. A large-scale droplet manipulation has been maintained in a 10 × 12 array by the forward and backward flows. With the proposed trapping structures and guiding tracks, the trapping and storing efficiencies have been significantly improved (>95%). Also, we have successfully demonstrated multiple-droplet clustering by the repeated trapping and storing with high clustering efficiency (∼95%). If inhomogeneous droplets are used with different reagents and samples, much more complex droplet reaction assays can be performed. We expect that the method presented in this study will facilitate the wide applications in many biological, chemical, and pharmaceutical reactions.

Fig. 1 Schematic illustration of the proposed device that can perform sequential operation of droplet trapping and storing for clustering of multiple droplets. Lower layer includes a flow-focusing junction for droplet generation, microfluidic channels for forward/backward flows, and an array of 10 × 12 traps. Upper layer includes guiding tracks, storing chambers, inlets, and outlets.

2. Methods and materials

2.1 Working mechanism and design

Fig. 2a shows the schematic view of the proposed multiple-droplet clustering array. A unit cell of the array, consisting of a storing well, a storing chamber, a trapping well, and a guiding track, is arranged in a 10 × 12 array (Fig. 2b). The trapping well is designed for single droplet trapping. Multiple-droplet stacking in front of the trapping well is prevented. The spacing (a row spacing of 90 μm and a column spacing of 180 μm) between these trapping structures also plays a critical role in efficient trapping without clogging.⁸ When droplets (∼70 μm in diameter) flow through the trapping array, they are easily captured at each trapping well (Fig. 2c). As soon as a droplet is captured at the trapping well, it blocks the trapping well resulting in the termination of flow within the trap and preventing a second droplet from entering the trapping well.^5,8,11 Subsequent droplets will move through the bypass (Fig. 2d). As a result, single droplets are trapped in the 10 × 12 array by the forward flow.

Fig. 2 Working principle of the proposed device. (a) Top and 3D views of the multiple-droplet clustering array. A unit cell includes a storing well, a storing chamber, a trapping well, and a guiding track placed in the second column between the trapping well (in the first column) and the storing well (in the third column). (b) The unit cell is arranged in a 10 × 12 trapping array for large-scale parallel processing and experimentation. The space between traps is optimized for smoothing passage of droplets. (c) A droplet has a chance to be trapped when the trapping well is empty. (d) A subsequent droplet has to move through the bypass when the trapping well is occupied. (e) Without the guiding tracks, a droplet tends to pass outside the storing well under backward flow. (f) COMSOL simulation results for the magnitude and streamline of the flow velocity in the trapping array. It shows lower velocity through the storing well and higher velocity through the bypass. (g) With the guiding tracks, a confined droplet moves along the track toward its corresponding storing well. (h) Cross-sectional view of A and B in (a). In the backward flow, the flattened droplet follows the guiding track, releases its interfacial energy after entering the storing chamber, and floats up to the super stratum of the chamber. Under the forward flow, the droplet stays in the chamber due to the interfacial energy and buoyancy effects. (i) COMSOL simulation results for velocity distribution in chambers with different thicknesses: 50 μm, 100 μm, and 150 μm.

After all the trapping sites are occupied, the flow direction is reversed. The trapped droplets are supposed to be released from the trapping well and subsequently move toward their corresponding storing well. However, because the flow rate in the bypass is higher than the one through the trapping structure, droplets tend to pass outside the storing well (Fig. 2e). This expectation is proved by COMSOL® simulation as shown in Fig. 2f. This effect reduces the storing efficiency of the device (Fig. 4a).⁵

In order to overcome the problem, the microchannel height (35 μm) in the lower layer is reduced to less than the droplet size (∼60 μm in diameter) and droplet guiding tracks (5 μm in height and 20 μm in width) are implemented in the upper layer (Fig. 2g). A consequence of the vertical confinement on the droplets is that they become sensitive to height modulations of the channel. Any interface between two fluids has an interfacial energy, ε_γ, defined as the product of the interfacial tension γ and the surface area S of the interface: ε_γ = γS. The surface energy is minimal when its shape is spherical, which yields minimum surface area, and it increases as the drop flattens into a pancake shape. Under the guiding track, the flattened droplet releases its interfacial energy by partially entering into the cavity of the track. Therefore, flattened droplets prefer to follow the tracks, which lowers their interfacial energy (Fig. 2h).^12,13

In our design, the track starts at the point where the flow rate is relatively high and ends in the point inside the storing well. The former ensures a smooth releasing of the droplets in the forward flow and the latter guarantees arriving of the droplets in the storing well in the backward flow. To prevent the droplet anchoring, sharp tips are employed at both ends of the track.

Though the storing well has shown its ability to pair droplets,⁵ it cannot be applied to multiple-droplet clustering because the droplets can only be stored temporarily in the storing well. Any employment of forward flow would result in the pushing out of the stored droplets. Therefore, a way to permanently store the droplets needs to be developed for the multiple-droplet clustering. There have been previous attempts for permanent droplet storing, using either interfacial energy¹⁴ or buoyancy effects.¹⁵ In this work, we placed a storing chamber (150 μm thickness) above the storing well in each trap and combined both interfacial energy and buoyancy effects to keep the droplets in the storing chambers (Fig. 2h).

In backward flow, the flattened droplets are released from the trapping wells, follow the guiding tracks to the storing chambers, change their shape into a spherical shape, and float up out of the confining channels to the super stratum of the chambers. In order to study a safety environment for permanent droplet storing, three chambers of different thickness (50 μm, 100 μm, and 150 μm) are simulated by COMSOL® (Fig. 2i). The simulation result illustrates that by increasing the thickness of the chamber the flow velocity within the structure could be greatly reduced. For the chamber with a thickness of 150 μm, we can produce a big dead volume in its super stratum and thus floated droplets could be safely stored.

In forward flow, the stored spherical-shaped droplets will remain in the storing chambers due to the interfacial energy and a big dead volume within the super stratum reducing the flow velocity. Higher forward flow velocity would be required for the spherical droplets to escape from the storing chambers because they have to overcome the hydrodynamic stress to change their shape into the flattened pancake shape. The density of the oil (HFE-7500) that we used is higher than that of water, and buoyancy keeps the water droplets permanently in the storing chamber even with successive forward and backward flows.

2.2 Device fabrication and materials

The device was fabricated using soft lithography to form microfluidic channels in polydimethylsiloxane (PDMS).¹⁶ To prepare the soft mold for the lower layer, a negative photoresist (SU-8 2050) was spin-coated on a silicon wafer with a thickness of 35 μm, and patterned using a conventional UV photolithography method. For the soft mold for the upper layer, a first layer of a 5 μm thick photoresist (SU-8 2005) was exposed to pattern tracks and chambers. A second layer of a 150 μm thick photoresist (SU-8 2050) was then coated on top of the first layer and exposed under a mask containing only chamber patterns. After development, the tracks and the chambers were formed in a single mold. From the molds, PDMS replicas were formed, followed by punching for inlets and outlets. Finally, the upper PDMS layer and the lower PDMS layer were exposed to O₂ plasma and face-to-face sandwiched to bond irreversibly. De-ionized (DI) water and 3M™ Novec™ 7500 Engineered Fluid (HFE-7500) were used as aqueous and oil phases, respectively. Surfactant (2% Krytox 157) was added into the HFE-7500 to prevent droplet coalescence. These fluids were supplied from three different syringe pumps (KD scientific) to the device. Experimental results were captured by a Nikon stereo-type microscope.

3. Results and discussion

3.1 Experimental process and result

In our system, we used a flow-focusing configuration to generate droplets within the size of ∼60 μm.^17,18 The flow rate ratio was set to be 1 : 4 (15 μl h⁻¹ for water and 60 μl h⁻¹ for oil). During the initial stabilization stage in droplet formation, the outlet was closed and the middle outlet was left open, in order to prevent the undesirable droplets from flowing to the trapping array. After a stable train of droplets was established, the outlet was unplugged and the middle outlet was closed. Thus the path of droplets was switched to the trapping array.

Once the droplets (blue) proceeded to the trapping array, they were captured in the trap wells. When we generated enough droplets for trapping, the aqueous phase was stopped and the oil phase was speeded up to 300 μl h⁻¹. Thus the redundant droplets could be flushed and a uniform trapping would be achieved (Fig. 3a). Next, the middle outlet was opened to serve as the exit for the subsequent step of storing. The inlet for the backward oil phase was put into use and the outlet was closed with a plug. Under the backward flow (300 μl h⁻¹), the trapped droplets could be released from the trap wells and could move along the tracks toward their corresponding storing wells and chambers. Thereafter, they were permanently stored in the chambers because the interfacial energy and the buoyancy prevented their escape from the super stratum of the chambers to the confining channels (Fig. 3b and ESI, Movie S1†).

Fig. 3 Photographs of repeated trapping and storing for triple-droplet clustering taken from one set out of three sets of experiments: (a and b) the first trapping (success rate: 94/94) and storing for single-droplet storing (success rate: 90/94) (ESI, Movie S1†), (c and d) the second trapping (success rate: 94/94) and storing for double-droplet pairing (success rate: 94/94) (ESI, Movie S2†), and (e and f) the third trapping (success rate: 94/94) and storing for triple-droplet clustering (success rate: 94/94) (ESI, Movie S3†). In this set of experiments, the total accumulated success rate for the triple-droplet clustering was 90/94 = 95.7%. Two traps (indicated with blue arrows) were not properly working due to fabrication failure (e.g., two trap wells blocked by small particles of dusts), and 94 traps out of 96 traps were counted for the efficiency analysis. Scale bars, 300 μm.

Next, the second set of droplets (yellow) were allowed to enter the trapping array and be paired in the same manner (e.g., repeated trapping and storing by the forward and backward flows) (Fig. 3c and d, and ESI, Movie S2†). The third set of droplets (red) was manipulated in the same trapping and storing procedure (Fig. 3e and f, and ESI, Movie S3†). In these repeated procedures, the previously stored droplets remained in the chambers permanently even in the rapid forward and backward flows. Because the first two columns could not be used to store droplets, the 8 × 12 array of traps (instead of the 10 × 12 array) was used for the clustering. In our device, two traps (indicated with blue arrows in Fig. 3) were not properly working due to fabrication failure (e.g., two trapping wells blocked by small particles of dusts).

3.2 Analysis and discussion

The success rates (efficiency) for trapping, storing, and clustering were tested by repeating the triple-droplet clustering experiment three times using the same device. After about two hours the stored aqueous droplets shrunk noticeably, hence we could flush out the stored tiny droplets (<10 μm) by turning the device upside-down. This may attribute to the slight solubility of water in the HFE-7500 oil.¹⁹ In our device, two traps were not working properly due to blockage by small particles of dusts. Thus, we considered only 94 traps (out of 96) for the efficiency analysis.

We could achieve a success rate of average 99.8% in the droplet trapping (n = 9) (Fig. 4a). Droplet storing in the backward flows also showed a high success rate of average 98.1% with the guiding tracks (n = 9). To prove that the enhanced efficiency comes from the tracking system, a device with no tracks was fabricated and tested. A lower success rate of 78.7% was demonstrated compared to the one with the tracks. During the experiment without the tracks, some of droplets missed their corresponding storing wells due to the higher flow rate in the bypass than the one through the trapping structure. This shows a good agreement with our expectation⁵ and simulation (Fig. 2e and f). Therefore, the cavity tracks ensured excellent guiding of the droplets from the trapping wells to the corresponding storing wells and chambers in the backward flows.

Fig. 4 Experimental results. (a) Success rate in the droplet trapping/storing process and comparison of storing efficiency in devices with and without tracks. Error bars: standard deviation (n = 9). (b) Accumulated efficiency for storing, pairing, and clustering. Error bars: standard deviation (n = 3).

Although the high efficiencies for each trapping and storing process (n = 9) were demonstrated, the accumulated efficiencies, including both trapping and storing processes, were slightly reduced (Fig. 4b). The accumulated efficiencies were 94.7% for the single-droplet storing, 94.3% for the double-droplet pairing, and 93.3% for the triple-droplet clustering (n = 3). Errors will be accumulated due to the failure in the previous processes during the repeated trapping and storing by the forward and backward flows.

The efficiencies for each trapping and storing process can be further improved by using an optimized array structure, a more uniform droplet size, a better surfactant to minimize the droplet shrinkage,¹¹ and careful fabrication and experiment. The failure in the storing process in backward flows occurred mostly near the side walls (see red ovals in Fig. 3b). Due to unstable and asymmetric flow distribution near the side walls, the trapped droplets tend to flow outside the tracks. We can improve upon this failure by optimizing the starting position of the guiding tracks, in order to make sure that all the trapped droplets follow the tracks near the side walls as well, or by modifying the array structure near the side walls, in order to allow more stable and symmetric flow distribution. In our experiment, though the stabilization process for the droplet generation was enhanced with the help of the middle outlet, uniform droplet formation for a short-time period only was still challenging due to the inhomogeneous hydrodynamic nature of the two-phase flow. To resolve the shrinkage problem, the use of a surfactant to provide a superior sealing of the interface between water and oil is critical.^5,20 The defect in fabrication is also an important factor that lowers the efficiency of our device. For example, the presence of small particles of dusts prevented the smooth passage of droplets and caused failure in the repeated droplet trapping and storing.

Nevertheless, the proposed droplet manipulation method using the guiding tracks, the interfacial energy- and buoyancy-based droplet storing, and the forward and backward flows could significantly improve the trapping, storing, and clustering efficiencies compared to the previous reports.^5,6 Furthermore, we can repeat this trapping/storing process several times to store more than three droplets with different contents and samples in properly designed storing chambers with large capacity. If a triangular storing chamber is used, it can allow all three droplets to contact each other. Optionally, any active fusion mechanism (e.g., electrical, optical) can be incorporated in the device for multiple-droplet fusion. Indeed, the proposed multiple-droplet clustering device has strong potential applications to complex droplet-based assays.

4. Conclusion

We presented a droplet-based microfluidic system that can generate, manipulate, trap, guide, store, and finally cluster multiple droplets in a controlled manner. Through structure and dimension optimization, we improved the droplet trapping efficiency. Based on the principle of the interfacial energy, the droplets could be efficiently guided by the tracks and the droplets could be permanently stored in the chambers. Thus we achieved high efficiency in the storing process and demonstrated triple-droplet clustering in a simple passive way. With such an effective and on-demand clustering method, we are able to develop a droplet-based microfluidic system for much more complex droplet reaction assays, such as molecular transfer across the droplets, enzymatic reaction, and high throughput bioassay reaction. The potential use of this multiple-droplet clustering technology is significant.

Acknowledgements

This work was supported by grants from NSF (ECCS-1002255 and ECCS-0736501).

Notes and references

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Footnote

† Electronic supplementary information (ESI) available: Movie S1 for the single-droplet storing (the first droplet trapping and storing), Movie S2 for the double-droplet pairing (the second droplet trapping and storing), and Movie S3 for the triple-droplet clustering (the third droplet trapping and storing). See DOI: 10.1039/c2lc20883k

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