A microfluidic electrostatic separator based on pre-charged droplets

Sensors and Actuators B 210 (2015) 328–335

Contents lists available at ScienceDirect

Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

A microfluidic electrostatic separator based on pre-charged droplets Lang Rao 1 , Bo Cai 1 , Jieli Wang, Qianfang Meng, Chi Ma, Zhaobo He, Junhua Xu, Qinqin Huang, Shasha Li, Yi Cen, Shishang Guo, Wei Liu ∗ , Xing-zhong Zhao Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, PR China

a r t i c l e

i n f o

Article history: Received 17 August 2014 Received in revised form 10 December 2014 Accepted 11 December 2014 Available online 30 December 2014 Keywords: Microfluidic Electric Droplet charging Cell sorting 3D electrodes

a b s t r a c t In this work, a single-layer electric separator based on droplet microfluidics is demonstrated for cell sorting. We introduce a droplet pre-charging stratagem to reduce the voltages needed and increase droplet maneuverability. This stratagem and subsequent sorting process is implemented due to the effect of analogous uniform electric fields, which are generated by the 3D electrodes fabricated through injecting conductive silver paste into chambers in the PDMS layer. The mechanism of this droplet pre-charging process is experimentally verified and the amount of the inductive charges is quantitatively calculated. We also analyze the influence of the interaction between droplet size and channel walls on the manipulations of charge-carried droplets under certain electric fields. After parameter optimization, droplets with single cell encapsulated inside are separated out from other ones using this separator, and cell viability assay indicates that good cell status is maintained through the whole electric cascade. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Cellular heterogeneity within an isogeneic cell population has received more and more attentions in recent years due to its importance in various biological and clinical researches [1–6]. Dissecting these cell–cell variations is vital to understand many cell-fate processes as well as the origin and progression of many diseases [7]. The emergence of single cell analysis can provide insights into studying cellular heterogeneity, and help investigators target those specific cell populations to obtain quantitative and dynamic information about molecular processes that underlie cell-fate decisions or cellular mutations [8–10]. However, the analysis of single cell face technical challenges such as throughput, robustness, easy-to-perform measurements and simultaneous multiple-feature complex data analyses [11]. To address these challenges, various techniques have been developed. Among them, droplet microfluidics has emerged as one of the most promising platforms due to its advantages of high throughput, small compartmentalization, parallel in dependence and quantitative format [12,13]. Benefited from abundant manipulation strategies of acoustic [14], optical [15], thermal [16], magnetic [17], valve-based [18],

∗ Corresponding author at: School of Physics and Technology, Wuhan University, Wuhan 430072, PR China. Tel.: +86 138 8606 6380. E-mail address: [email protected] (W. Liu). 1 Both authors contributed equally to this work. http://dx.doi.org/10.1016/j.snb.2014.12.057 0925-4005/© 2014 Elsevier B.V. All rights reserved.

hydrodynamic [19] and electric [20] methods, droplets can be split, mixed, transported, trapped, sorted etc. And after dispersing cells into nano-liter or pico-liter droplets, combining aforementioned droplet microfluidic techniques can thus fulfill various demands for cell-based research and applications at single cell level in these nano laboratories, including immunoassays [21,22], 3D cell culture and division [23,24], cell sorting [25], cytokine secretion [26], gene detection and sequencing [27,28], drug testing [29], DNA amplification [30] and so on. Although multiple physical manipulations are employed to expand the applications of droplet microfluidics in single cell research, there is still a long way for them to be comprehensively used. For example, optical and valve-based methods need complex apparatus and professionals, while acoustic and hydrodynamic methods are lack of manipulation accuracy. Comparing to these manipulation schemes, the electric methods have certain advantages for droplet manipulations, e.g., short response time, easy setup, label-free, good compatibility with other stratagems and high integration [31]. These merits enable electric methods to be ideal tools for droplet manipulations [32–35], which especially facilitates the cell sorting field. Weitz et al. demonstrated a high-speed microfluidic droplet sorter based on dielectrophoresis (DEP) force [36]. The voltage used for producing sufficient DEP force is usually greater than 1000 V. In order to lower the voltage and improve relative operability, a contact-release droplet pre-charging method has been developed. In this method, neutral droplets flow in the micro-channel and then contact a bare

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

charging-electrode to acquire charges [37]. Link et al. presented a non-contact droplet pre-charging method to avoid possible contamination from the electrodes [38]. When a neutral droplet flows across an electric field in the micro-channel, charges are induced spontaneously around the surface of the droplet, and then the droplet is split into two opposite charged daughter droplets by a T-junction micro-channel. However, the analysis and quantification of this droplet pre-charging procedure remains unclear for subsequent precise manipulations of droplets toward further applications. Herein, we develop a simple single-layer electric charger and separator based on droplet microfluidics. A facile method for threedimensional (3D) electrode fabrication is adopted to replace the traditional complicated deposition and lift-off process for forming planar electrodes on the substrate. The electrodes are made by simply filling conductive silver paste into micro-chambers that are fabricated in the PDMS layer. Due to their equivalent dimensions as the micro-channels, the 3D electrodes can produce analogous uniform electric fields across the whole space of channels. Thus they are more efficient and accurate for droplet charging and sorting, comparing to planar electrodes [39]. Using this simple and effective droplet microfluidic separator, a non-contact droplet pre-charging and sorting procedure is implemented toward possible cell sorting applications. The mechanism of droplet pre-charging process is also carefully analyzed and experimentally verified, and the induced charge is quantitatively calculated. At the same time, the relationship among induced charge, droplet size, sorting/charging voltage and droplet movement is investigated. This pre-charging stratagem notably reduces the sorting voltage as well as the response and recovery time of droplet deflecting compared to non-pre-charging format. Thus it greatly helps to improve the sorting maneuverability and efficiency. After parameter optimization, particular droplets containing single cell inside are selectively sorted out from null ones or those with multiple cells. Corresponding cell viability assays demonstrate the good biocompatibility of our electric droplet-sorting platform for further feasible cellular assays. Considering the better biocompatibility and maneuverability obtained from the lower voltage used and quicker response and recovery time in this droplet pre-charging stratagem, we expect this single-layer, easily-fabricated cell sorting microfluidic platform can provide a potential automation and portability for cellular assays at single cell level after integrating with automated detection systems.

329

sorting channel is another pair of electrodes used to form an electric field to control the droplets deflecting. This microfluidic device (Fig. 1(b)) is fabricated according to the standard soft lithography [40]. First, a mold is fabricated using SU8 2050 negative photoresist (MicroChem Corporation Ltd.) on a silicon wafer by photolithography. Then a PDMS layer (A–B ratio of 10:1) can be casted from the mold, pinhole-punched and irreversibly bonded to a glass slide through oxygen plasma (Harrick Scientific Corporation Ltd.). Subsequently, the charging and sorting electrodes are fabricated through injecting conductive silver paste (Sinopharm Chemical Reagent Corporation Ltd.) into chambers in the PDMS layer. Then stainless steel needles as pins are inserted into holes that are filled by the paste. At last, the microfluidic chip is baked at 120 ◦ C for two days to regain hydrophobicity and solidify the silver paste. The inset of Fig. 1(b) is a scanning electron microscope (SEM, HITACHI S4800) photograph of cross-section of the 3D silver paste electrode embedded in the PDMS layer. The silver paste fills the electrode chamber fully, which guarantees to form an analogous uniform electric field across the whole space of fluid channels. 2.2. Droplet generation, manipulations and quantification As shown in Fig. 1(c), continuous phase (soybean oil, Beiya Medical Oil Corporation Ltd.) and dispersed phase (2% sodium alginate (SA, China National Medicines Corporation Ltd.) or prepared SA-cell suspension) are injected into the chip by syringe pumps (TS260, Longer Precision Pump Corporation Ltd.) through polyethylene tubes. First, the oil phase shears the SA solution into droplets at flow-focusing orifice. During these neutral droplets flow along the charging channel with the charging voltage applied, positive and negative charges can be induced in corresponding hemisphere surfaces of the droplets because of charge induction. Subsequently, due to the effect of the triangle notch, every droplet is split into two daughter droplets that keep the inductive charges within each other and flow into two downstream branches respectively. Then in sorting channels, the movement of these charge-carrying droplets is notably influenced by the sorting electric field. While for those non-pre-charging droplets, their tracks are distinctively different. The processes of droplet generation, charging, split and separation are observed on an inverted fluorescence microscope (IX71, Olympus) and recorded by a digital charge coupled device (CCD, DP 72, Olympus). The images are analyzed by Image-Pro Plus 6.0 software to quantify relative parameters needed for theoretical calculation in Section 3.

2. Materials and methods 2.1. Device design and fabrication

2.3. Cell culture, SA-cell suspension preparation and cell viability assay

A three-dimensional model of this droplet-based microfluidic electrostatic separator is shown in Fig. 1(a). Fluid channels and electrode chambers are in the same polydimethylsiloxane (PDMS, GE Toshiba Silicone Corporation Ltd.) layer. Heights of all the channels are 60 ␮m. Widths of the sodium alginate (SA) and the oil inlet channels are 200 ␮m. Then they taper to 100 and 80 ␮m respectively at the flow-focusing orifice. The charging channel downstream tapers to 50 ␮m and then divides into two branches, each of which is joined by another oil inlet channel used for adjusting the distance between two adjacent droplets along sorting channel. A triangle notch that is 35 ␮m high and 25 ␮m wide is set in the middle of the T-junction channel for the droplet pre-charging stratagem [31]. Near the T-junction, a pair of charging electrodes is symmetrically placed beside the micro-channel. The electrodes are 400 ␮m long along the channel direction and 50 ␮m away from the channel. The subsequent sorting channel that connects to three 100-␮m wide collector channels is 200 ␮m wide. Adjacent to the

Human breast cancer cells (MCF-7 cells, provided by Zhongnan Hospital of Wuhan University) are cultured in Dulbecco’s modified Eagle’s medium (DMEM, high glocuse, Hyclone) supplemented with 10% fetal bovine serum (FBS, Hyclone) and 1% penicillin and streptomycin (10000 U/mL penicillin and 10000 U/mL streptomycin in 0.85% NaCl, Hyclone) at 37 ◦ C and 5% CO2 atmosphere in a cell incubator saturated with water. After harvested and centrifuged to remove supernatant culture medium, cells are suspended in 0.9% (w/w) NaCl solution at needed concentration. The cell suspension is mixed with 4% (w/w) SA solution at volume ratio of 1:1 to obtain SA-cell suspension before on-chip manipulations, in which the cell density of MCF-7 is about 1 × 105 /mL. In order to test the viability, MCF-7 cells, that has undergone all the electric manipulations inside the chip with different charging/sorting voltages applied (0, 200, 400, 600, 800, 1000 V), are collected at outlet of the microfluidic device. After rinsed with phosphate buffer saline (PBS, 1×, 0.0067 M PO4 3+ , Hyclone) and

330

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

Fig. 1. A Microfluidic electrostatic separator based on pre-charged droplets. (a) Three-dimensional model of the droplet-based microfluidic electrostatic separator. (b) A photograph of the 3D-electrode-integrated single-layer PDMS separator. The inset is the SEM photograph of cross-section of the 3D silver paste electrode embedded in the PDMS layer. (c) Schematic of the droplet generation, pre-charging and sorting cascade on the chip.

centrifuged at 1000 rpm for several times, cells are gathered and resuspended in a Petri dish with fresh culture medium. Cell viability study is then implemented based on fluorescein diacetate (FDA, Sigma–Aldrich, USA) and propidium iodide (PI, Sigma–Aldrich, USA) staining. PI is a red fluorescent nuclear dye that cannot enter viable cells with intact plasma membranes, whereas FDA can pass through cell membranes, accumulate inside the living cell and shows green fluorescence when excited. Therefore, after cells are stained by FDA/PI solution (5 ␮g/ml dissolved in PBS respectively) for 5 min, cell viability can be detected and calculated as follows: viability = ((number of green cells/(number of green cells + number of red cells)) × 100%. 2.4. Setup of voltage control system for cell sorting The high-voltage control system (Fig. S1(a)) consists of two highvoltage square pulse generation circuits, a high voltage DC (HVDC) power supply and a matched smartphone trigger. Through Bluetooth communication, an application based on Android operation system has been developed to accurately control the compliance voltage as well as the pulse amplitude and width that are produced by an HVDC power supply. These voltages are directly applied on electrodes in our microfluidic separator. Our voltage control device can supply two square pulses with maximum amplitude of 1500 V, width from 0 to 3000 ms at the same time, as well as a DC voltage from 0 to 1500 V. This high-voltage control system is applied for facile cell sorting. MCF-7 cells are mixed with SA solution and then loaded into the generated droplets. Whenever monitored in the sorting channel, the daughter droplet, which encapsulates single cell, can be sorted to the specified collector from other droplets (empty or containing more than one cell) (Fig. S1(b)). Then single-cell compartment can be gained to beat the Poisson distribution during stochastic cell encapsulations, which will benefit the single cell analysis.

(Fig. 2(a) I–VI). But after applying an appropriate voltage, the neutral droplet has the positive and negative charges induced near its corresponding hemisphere surfaces (Fig. 2(b) I–VI). Subsequently, when the droplet contacts the notch and gradually split to two daughter droplets due to hydrodynamic force, the opposite induced charges respectively stay in each of these two separated daughter droplets (Fig. 2(b) II and III, V and VI). Thus the daughter droplets are positive/negative “pre-charged” [41]. The polarity and amount of the induced charges can be adjusted by changing the charging voltage accordingly. To verify those daughter droplets are truly charged through the pre-charging stratagem, we investigate the movement of these daughter droplets (no pre-charged/pre-charged) under constant electric field (1 V/␮m) in the sorting channels (Fig. 2(a) VII–VIII and Fig. 2(b) VII–VIII). When the charging voltage is off (non-precharging format), the neutral daughter droplets in left and right branch both move toward the cathode in the sorting channel under the sorting electric field. It is because the induced charges in these daughter droplets are homogeneous, and their deflection movement is due to the effect of electric polarization. However, after applying 100 V on the charging electrodes (pre-charging format), the droplets in the left branch move toward the anode (Fig. 2(b) VII), while in the right branch the droplets move toward the cathode (Fig. 2(b) VIII). This fully indicates that these daughter droplets carry opposite charges after pre-charging process, other than keep the neutral state like the non-pre-charging situation.

3. Results and discussion

3.1.2. Movement analysis and charge quantification To fully understand the influence of this droplet pre-charge stratagem on the droplet manipulations, we investigate the movement of non-pre-charged/pre-charged droplets under different electric and fluid conditions. Because there are no direct methods to measure the charges carried on the droplets, a hydrodynamic model of droplet movement in the sorting channel is set up to carry out theoretical calculation for force analysis and charge quantification [20,31]. In the vertical direction of fluid flow, daughter droplets are mainly driven by electric force (FE ) and viscous drag force (FV ):

3.1. Droplet pre-charging

m

3.1.1. Charging mechanism and verification The mechanism of our droplet pre-charging stratagem is illustrated in Fig. 2. When no voltage is applied to the charging electrodes, positive and negative charges keep uniform distribution in the generated droplets, and their daughter droplets are neutral

m is the droplet mass, x is the displacement that the droplet moves across the flow direction, q is the amount of charges carried on the droplet, Ed is the intensity of the electric field,  is the friction factor. According to Eq. (1), we choose the average velocity x/t as an approximate substitution of dx/dt to quantify the movement of

d2 x dx = FE + FV = qEd −  dt dt 2

(1)

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

331

Fig. 2. Mechanism and verification of the droplet pre-charging process. (a) Non-pre-charging format. Positive and negative charges keep uniform distribution in droplets, leaving these droplets and subsequent daughter droplets neutral (I–VI). Both of these two daughter droplets move toward the cathode of the sorting electrodes due to the effect of electric polarization (VII and VIII). (b) Pre-charging format. A neutral droplet that flows along the charger channel has its positive and negative charges induced in corresponding hemisphere surfaces (I and IV). Then the droplet touches the notch and is gradually split to two separated daughter droplets that carry the opposite induced charges respectively (II, III, V and VI). These two charges in compatible droplets move toward the opposite electrodes according to charges they carry (VII and VIII).

different droplets under the effect of the electric field. The displacement of droplets and corresponding time is obtained by analyzing the images recorded by a CCD camera. Fig. 3(a) gives out the influence of droplet size and electric fields on non-pre-charged droplets. Since the droplets are neutral, their deflection is due to the effect of electric polarization under the sorting electric field. It can be seen that to all sizes of droplets, they move faster when raising the voltage. This is because as the sorting voltage rises, the degree of electric polarization becomes greater and thus greater Coulomb force affects the movement of droplets. But the velocity of droplets shows fluctuation for different droplet sizes. At first, the velocity increases as droplets become bigger, and reaches peak when their size is around 60 ␮m. After then, the droplets move slower as their size keeps increasing. For pre-charged droplets, we investigate their velocity across the channel, which are affected by the droplet size and charging voltage while the sorting voltage is fixed at 100 V, as shown in Fig. 3(b). When the charging voltage is set higher, droplets move faster correspondingly no matter what size they are, because more net charges are gained in every daughter droplet if the charging voltage increases during the pre-charging process. When considering the interaction between droplet size and velocity, the curves show similar fluctuation like non-pre-charged situation. We infer that this fluctuation is caused by the deformation of droplets during their size increases. In the experiments, droplet size is precisely controlled through simply adjusting ratio of flow rates of continuous phase (Qc ) and dispersed phase (Qd ), and droplet shape transforms from sphere to cylinder as the fluid velocity changes (Fig. 3(c) and Fig. S2(a)–(b)) [42]. As the height of the micro-channel is 60 ␮m (much smaller than the channel width of 200 ␮m), when the droplet diameter is less than 60 ␮m (i.e., 33, 44 and 53 ␮m), the droplet is spherical due to the surface tension. In this situation, the viscous drag force FV in Eq. (1) comes only from the liquid. Although as droplets becomes bigger the viscous drag force increases as well, the coulomb force also increases and becomes more and more larger than viscous drag force, therefore

the droplets deflect more and more faster as their size increases. However, once the droplet diameter increases bigger than 60 ␮m (i.e., 61, 71, 82 and 90 ␮m), those droplets become cylindrical or disk-like due to the limit of channel height (60 ␮m). Since then the top and bottom surface of the fluid channel interact with those droplets and impede their movement in a way of friction. This interaction, together with the liquid viscous drag force, constitutes the two parts of FV in Eq. (1). As droplets become larger, limitation of the channel on droplets become greater, this makes the droplet to press against the channel walls harder. Thus the interaction between channel walls and droplets increases and causes FV to increase much faster than electric force FE . At this time, when the droplets become bigger, their movement slows down on the contrary. To evaluate the influence of the pre-charging stratagem accurately, we quantify the charges carried by pre-charged and non-pre-charged droplets when their diameters are below the fluid channel height. In this situation, the friction factor in Eq. (1) can be expressed as  = 3R ( is the dynamic viscosity and R is the droplet diameter). Then Eq. (1) can be written as: m

d2 x dx dx = qEd − 3R = qEd −  dt dt dt 2

(2)

So we have: x=

q qR 2 Ed (e18t/R  − 1) E t+ 3R d 542

(3)

 is the density of the droplet. In our experiments, R ≈ 50 ␮m,  ≈ 1 g/cm3 ,  ≈ 50 mPa s, t ≈ 500 ms, we have the approximate condition expressed as: 18t 1 R2 

(4)

Then we can estimate the charges as: q = 3R · Ed ·

x t

(5)

332

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

Fig. 3. Regulation for the droplet movement, droplet size and carried charge. (a) The influence of the droplet size and sorting voltage on the movement of non-pre-charged droplets. (b) Velocity across the channel of pre-charged droplet that is affected by the droplet size and charging voltage with the sorting voltage fixing at 100 V. (c) Droplet size regulation through adjusting ratio of flow rates of continuous phase (Qc ) and dispersed phase (Qd ), two insets show droplet shape transform from sphere to cylinder due to limit of the fluid channel height. (d) The charges induced in 53-␮m-size droplets versus variation of the sorting voltage between non-pre-charged droplets and 400 V pre-charged ones.

Fig. 4. Droplet electric deflection. (a) Relationship between the pre-charging voltage and sorting voltage for droplets of different sizes. (b) Response and recovery time for 400 V pre-charged/non-pre-charged droplets (R = 53 ␮m) deflecting when switching sorting voltage. (c–f) Droplet deflection with different sorting voltages as droplet size and pre-charging voltage kept at 33 ␮m and 1000 V. The scale bars are 200 ␮m.

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

333

Fig. 5. Cell sorting based on pre-charged droplet. (a) Schematic of single cell sorting procedure from target monitoring to droplet manipulations. (b–d) A particular droplet with single cell inside is sorted out to the branch channel for collection. The scale bars are 100 ␮m. (e) Relationship between droplet size and efficiency of target droplet sorting with the charging voltage as 600 V and the sorting electric pulse as 50 ms width and 70 V amplitude. (f) MCF-7 cells viability assay under only charging voltages (VC ), only sorting voltages (VS ), or both of them (VC + VS ) during droplet electric manipulations on chip. The control group is cells without any treatment.

At the same time, as all the electrodes in our chip are fabricated by filling silver conductive paste into cuboid chambers in the PDMS layer, the electrodes are thus three-dimensional to afford uniform electric fields across the whole space of the fluid channels. Taking the influence of the permittivity of PDMS and continuous phase (soybean oil) on the electric field intensity Ed , we have: Ed =

VS 2d1 ε1 + d2 ε2

(6)

where VS is the sorting voltage, d1 is the thickness of PDMS between the 3D electrode and the sorting channel and d2 is the width of the sorting channel. ε1 and ε2 is the relative permittivity of PDMS and soybean oil (see more details in Supporting Information). Thus: q = 3R ·

VS x · 2d1 ε1 + d2 ε2 t

(7)

According to Eq. (7), the induced charge in the droplet can be calculated versus the variation of the sorting voltage between nonpre-charged droplets and 400 V pre-charged ones with the same diameter (R = 53 ␮m) (Fig. 3(d)). It can be clearly seen that precharged droplets carry much more charges than non-pre-charged ones. And as the sorting voltage increases, the charges also increase a little. This is due to the increase of the induced charges as the degree of electric polarization becomes greater when the sorting voltage increases. While, compared to the non-pre-charged droplets, the influence of induced charges by the sorting voltage on droplets processed by the pre-charging stratagem is noteless.

3.2. Droplet electric deflection To facilitate subsequent target cell sorting process, we try to analyze the relationship among droplet pre-charging voltage, sorting

334

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

voltage and droplet size which influence the movement of droplets apparently during electric droplet manipulations. As shown in Fig. 4(a), the sorting voltage decreases as the precharging voltage increases. The reason is that more charges are induced to daughter droplets during the pre-charging process with higher voltages (Fig. 3(b)), thus causes daughter droplets to be driven by stronger electric force FE under the same sorting electric field. It is noteworthy that when the pre-charging voltage VC = 0 V, at least 230 V sorting voltage is needed to direct target droplets to branch channels, while introducing a pre-charging voltage effectively reduces the sorting voltage lowest to about 30 V (corresponding pre-charging voltage is 600 V). With an appropriate pre-charging pre-treatment, the sorting voltage can be effectively reduced. It benefits kinds of biological assays that are sensitive or vulnerable to electricity. When turning on the sorting voltage, the droplets need response time to deflect, while shutting the voltage off the deflected droplets need recovery time to return to the centerline of channels. Fig. 4(b) investigates the response and recovery time for both pre-charged and non-pre-charged droplets with 53 ␮m diameter. It shows that the pre-charging stratagem helps to reduce both response and recovery time, thus improves the maneuverability and accuracy of the droplet sorting. Fig. 4(c)–(f) shows the standard to confirm sorting voltage under different diameters. For instance, the droplet size and pre-charging voltage is kept around 30 ␮m and 1000 V. It can be seen that only when the voltage is at least 30 V, those droplets can be led to left/right branch collector channels. So 30 V is chosen as sorting voltage.

3.3. Droplet-based cell sorting After parameter optimization for electric droplet manipulations, this droplet-based microfluidic separator is applied to facile cell sorting toward possible biological or biomedical cellular assays. Droplets with target cells encapsulated inside can be separated from others by an appropriate electric pulse. For more accurate droplet sorting manipulation, length of the sorting electrode is optimized. The longer electrode can reduce the voltage, as well as the sorting efficiency, however. In our experiment, we set the length of sorting electrodes as 400 ␮m considering both the sorting accuracy and efficiency. The frequency of droplet generation changes with the droplet size (Fig. S2(c)), 3 Hz is a relatively suitable frequency considering both droplets monitoring and sorting efficiency, along with the relationship among the droplet size, droplet pre-charging and droplet sorting (Fig. 4(a)), 53-␮m-size droplets are employed as appropriate cell containers. As shown in Fig. 5(a), when the sorting voltage is off, all droplets are hydrodynamically led to the central channel and collected in the waste reservoir. When a particular droplet with target cell inside flows along and is monitored, a pulse produced by the voltage control system is applied to drive this wanted droplet to a branch channel for collection. Fig. 5(b)–(d) shows a droplet with single cell inside is sorted out from other null ones by a pulse (50 ms width and 70 V amplitude) with the charging voltage as 600 V. In a stochastic cell encapsulation procedure, the cell number encapsulated in each SA droplet fits a Poisson distribution (Fig. S3). Our sorting process helps to beat stochastic Poisson distribution faced by traditional cell encapsulation procedures in a facile way. Fig. 5(e) shows the sorting efficiency of our electric separator under conditions of 600 V charging voltage, and the sorting electric pulse of 50 ms width and 70 V amplitude. The success rate increases when the droplet size increases from 33 to 53 ␮m, because 53 ␮m is a relatively suitable size for droplet electric manipulations as previously discussed. Once droplet diameter is more than 60 ␮m,

the interaction between channel walls and droplets hinders the droplet manipulation, causing the success rate decreases sharply. At last, MCF-7 cell viability assay is implemented to demonstrate the advantages of the decrease of the voltage with the droplet pre-charging process. The assay carries out under different voltage conditions and the droplet diameter is kept at 53 ␮m (Fig. 5(f)). There are no obvious differences in cell viability between the effects of charging voltage and sorting voltage separately or with both of them together, especially at low voltage values. We infer that it is because the chips used are small enough and the charging and sorting process are fast enough to ignore the differences that may be introduced by charging and sorting voltage separately or both of them together. It indicates that if the voltages needed for droplet manipulations are limited to low values, the electric field will have little influence on the metabolism of cells encapsulated inside. This highlights the superiority of reducing the sorting voltage further. Also, when the voltage is less than 600 V, the cell viability is not affected obviously, guaranteeing that cells undergo processes in our electrostatic microfluidic device are at good status enough for further cellular assays.

4. Conclusions In conclusion, we develop a simple single-layer electrostatic microfluidic separator based on pre-charged droplets for facile cell sorting. By simply filling conductive silver paste into cuboid chambers in the PDMS layer, 3D electrodes are integrated into microfluidic chips to afford analogous uniform electric fields across the fluid channels for on-chip electric droplet manipulations. Through a pre-charging stratagem, net charges at 10−14 Coulomb levels can be induced into droplets. The mechanism of the droplet pre-charging process is analyzed and experimentally verified, and the induced charges are quantitatively calculated. Also, the relationship among induced charges, droplet size, sorting/charging voltage and droplet movement is carefully investigated. This precharging stratagem can reduce the sorting voltage as well as the response and recovery time of droplet deflection notably compared to non-pre-charging format, thus help to improve the sorting maneuverability and efficiency greatly. After parameter optimization, suitable droplets containing single cell inside are sorted out from null ones or those with multiple cells. At last, cell viability assay is done to demonstrate the biocompatibility of our electric droplet-sorting platform for further feasible cellular assays. Considering the better biocompatibility and maneuverability obtained from the lower voltage used and quicker response and recovery time in this droplet pre-charging stratagem, we expect our investigation and this single-layer easily-fabricated cell sorting microfluidic platform can provide a potential possible automation and portability for cellular assays at single cell level or personal healthcare after integrated with automated detection systems.

Acknowledgments This work is supported by National Natural Science Foundation of China (Grant No. 81272443 and Grant No. 51272184), the State Key Program of National Natural Science of China (Grant No. 51132001) and National Science Fund for Talent Training in Basic Science (Grant No. J1210061).

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.snb.2014.12.057.

L. Rao et al. / Sensors and Actuators B 210 (2015) 328–335

References [1] J.P. Junker, A. van Oudenaarden, Every cell is special: genome-wide studies add a new dimension to single-cell biology, Cell 157 (2014) 8–11. [2] M. Asano, M. Toda, N. Sakaguchi, S. Sakaguchi, Autoimmune disease as a consequence of developmental abnormality of a T cell subpopulation, J. Exp. Med. 184 (1996) 387–396. [3] K.L. Sugars, D.C. Rubinsztein, Transcriptional abnormalities in Huntington disease, Trends Genet. 19 (2003) 233–238. [4] B. Beck, C. Blanpain, Unravelling cancer stem cell potential, Nat. Rev. Cancer 13 (2013) 727–738. [5] T. Reya, S.J. Morrison, M.F. Clarke, I.L. Weissman, Stem cells, cancer, and cancer stem cells, Nature 414 (2001) 105–111. [6] J.E. Visvader, G.J. Lindeman, Cancer stem cells in solid tumours: accumulating evidence and unresolved questions, Nat. Rev. Cancer 8 (2008) 755–768. [7] D. Wang, S. Bodovitz, Single cell analysis: the new frontier in ‘omics’, Trends Biotechnol. 28 (2010) 281–290. [8] D.G. Spiller, C.D. Wood, D.A. Rand, M.R.H. White, Measurement of single-cell dynamics, Nature 465 (2010) 736–745. [9] C. Schubert, Single-cell analysis: the deepest differences, Nature 480 (2011) 133–137. [10] R. Zenobi, Single-cell metabolomics: analytical and biological perspectives, Science 342 (2013) 533. [11] Y. Zheng, J. Nguyen, Y. Wei, Y. Sun, Recent advances in microfluidic techniques for single-cell biophysical characterization, Lab Chip 13 (2013) 2464–2483. [12] A.B. Theberge, F. Courtois, Y. Schaerli, M. Fischlechner, C. Abell, F. Hollfelder, et al., Microdroplets in microfluidics: an evolving platform for discoveries in chemistry and biology, Angew. Chem. Int. Ed. 49 (2010) 5846–5868. [13] M.T. Guo, A. Rotem, J.A. Heyman, D.A. Weitz, Droplet microfluidics for highthroughput biological assays, Lab Chip 12 (2012) 2146–2155. [14] Z. Wang, J. Zhe, Recent advances in particle and droplet manipulation for lab-on-a-chip devices based on surface acoustic waves, Lab Chip 11 (2011) 1280–1285. [15] J.H. Jung, K.H. Lee, K.S. Lee, B.H. Ha, Y.S. Oh, H.J. Sung, Optical separation of droplets on a microfluidic platform, Microfluid. Nanofluid. 16 (2014) 635–644. [16] T. Say-Hwa, S.M.S. Murshed, N. Nam-Trung, W. Teck Neng, Y. Levent, Thermally controlled droplet formation in flow focusing geometry: formation regimes and effect of nanoparticle suspension, J. Phys. D: Appl. Phys. 41 (2008) 165501. [17] L.B. Zhao, L. Pan, K. Zhang, S.S. Guo, W. Liu, Y. Wang, et al., Generation of Janus alginate hydrogel particles with magnetic anisotropy for cell encapsulation, Lab Chip 9 (2009) 2981–2986. [18] F. Guo, K. Liu, X.-H. Ji, H.-J. Ding, M. Zhang, Q. Zeng, et al., Valve-based microfluidic device for droplet on-demand operation and static assay, Appl. Phys. Lett. 97 (2010) 23370. [19] Y. Shi, X.H. Gao, L.Q. Chen, M. Zhang, J.Y. Ma, X.X. Zhang, et al., High throughput generation and trapping of individual agarose microgel using microfluidic approach, Microfluid. Nanofluid. 15 (2013) 467–474. [20] F. Guo, X.-H. Ji, K. Liu, R.-X. He, L.-B. Zhao, Z.-X. Guo, et al., Droplet electric separator microfluidic device for cell sorting, Appl. Phys. Lett. 96 (2010) 19370. [21] J.-U. Shim, R.T. Ranasinghe, C.A. Smith, S.M. Ibrahim, F. Hollfelder, W.T.S. Huck, et al., Ultrarapid generation of femtoliter microfluidic droplets for singlemolecule-counting immunoassays, ACS Nano 7 (2013) 5955–5964. [22] B. Cai, F. Guo, L. Zhao, R. He, B. Chen, Z. He, et al., Disk-like hydrogel beadbased immunofluorescence staining toward identification and observation of circulating tumor cells, Microfluid. Nanofluid. 16 (2014) 29–37. [23] K. Liu, Y.L. Deng, N.G. Zhang, S.Z. Li, H.J. Ding, F. Guo, et al., Generation of disk-like hydrogel beads for cell encapsulation and manipulation using a droplet-based microfluidic device, Microfluid. Nanofluid. 13 (2012) 761–767. [24] M.C. Good, M.D. Vahey, A. Skandarajah, D.A. Fletcher, R. Heald, Cytoplasmic volume modulates spindle size during embryogenesis, Science 342 (2013) 856–860. [25] L. Mazutis, J. Gilbert, W.L. Ung, D.A. Weitz, A.D. Griffiths, J.A. Heyman, Singlecell analysis and sorting using droplet-based microfluidics, Nat. Protoc. 8 (2013) 870–891. [26] V. Chokkalingam, J. Tel, F. Wimmers, X. Liu, S. Semenov, J. Thiele, et al., Probing cellular heterogeneity in cytokine-secreting immune cells using droplet-based microfluidics, Lab Chip 13 (2013) 4740–4744. [27] R. Novak, Y. Zeng, J. Shuga, G. Venugopalan, D.A. Fletcher, M.T. Smith, et al., Single-cell multiplex gene detection and sequencing with microfluidically generated agarose emulsions, Angew. Chem. Int. Ed. 50 (2011) 390–395. [28] F. Guo, M.I. Lapsley, A.A. Nawaz, Y. Zhao, S.-C.S. Lin, Y. Chen, et al., A dropletbased, optofluidic device for high-throughput, quantitative bioanalysis, Anal. Chem. 84 (2012) 10745–10749. [29] B. Cao, M. Yang, Y. Zhu, X. Qu, C. Mao, Stem cells loaded with nanoparticles as a drug carrier for in vivo breast cancer therapy, Adv. Mater. 26 (2014) 4627–4631. [30] X. Leng, W. Zhang, C. Wang, L. Cui, C.J. Yang, Agarose droplet microfluidics for highly parallel and efficient single molecule emulsion PCR, Lab Chip 10 (2010) 2841–2843. [31] H. Zhou, S. Yao, Electrostatic charging and control of droplets in microfluidic devices, Lab Chip 13 (2013) 962–969. [32] M.G. Simon, R. Lin, J.S. Fisher, A.P. Lee, A Laplace pressure based microfluidic trap for passive droplet trapping and controlled release, Biomicrofluidics 6 (2012) 014110.

335

[33] B. Ahn, K. Lee, R. Louge, K.W. Oh, Concurrent droplet charging and sorting by electrostatic actuation, Biomicrofluidics 3 (2009) 044102. [34] L.M. Fidalgo, G. Whyte, D. Bratton, C.F. Kaminski, C. Abell, W.T.S. Huck, From microdroplets to microfluidics: selective emulsion separation in microfluidic devices, Angew. Chem. Int. Ed. 47 (2008) 2042–2045. [35] R. de Ruiter, A.M. Pit, V.M. de Oliveira, M.H.G. Duits, D. van den Ende, F. Mugele, Electrostatic potential wells for on-demand drop manipulation in microchannels, Lab Chip 14 (2014) 883–891. [36] K. Ahn, C. Kerbage, T.P. Hunt, R.M. Westervelt, D.R. Link, D.A. Weitz, Dielectrophoretic manipulation of drops for high-speed microfluidic sorting devices, Appl. Phys. Lett. 88 (2006) 024104. [37] K. Choi, M. Im, J.M. Choi, Y.K. Choi, Droplet transportation using a pre-charging method for digital microfluidics, Microfluid. Nanofluid. 12 (2012) 821–827. [38] D.R. Link, E. Grasland-Mongrain, A. Duri, F. Sarrazin, Z. Cheng, G. Cristobal, et al., Electric control of droplets in microfluidic devices, Angew. Chem. Int. Ed. 45 (2006) 2556–2560. [39] S. Li, M. Li, Y. Hui, W. Cao, W. Li, W. Wen, A novel method to construct 3D electrodes at the sidewall of microfluidic channel, Microfluid. Nanofluid. 14 (2013) 499–508. [40] Y. Xia, G.M. Whitesides, Soft Lithography, Angew. Chem. Int. Ed. 37 (1998) 550–575. [41] B. Ahn, K. Lee, R. Panchapakesan, K.W. Oh, On-demand electrostatic droplet charging and sorting, Biomicrofluidics 5 (2011) 024113. [42] K. Liu, H.-J. Ding, J. Liu, Y. Chen, X.-Z. Zhao, Shape-controlled production of biodegradable calcium alginate gel microparticles using a novel microfluidic device, Langmuir 22 (2006) 9453–9457.

Biographies Lang Rao received his BS degree in physics at Wuhan University in 2013 and presently is a graduate student for his PhD degree in physics at Wuhan University. His fields of interest are Lab on a Chip and biomaterials. Bo Cai received his BE and ME degrees in electronics at Wuhan University in 2010 and 2013 respectively. Now he is a graduate student for his PhD degree in materials at Wuhan University. His current research interest is microfluidics devices. Jieli Wang received her BE degree in electronics at Wuhan University in 2013 and presently is a graduate student for her Master degree at Wuhan University. Her current research interest is Lab on a Chip. Qianfang Meng received her BE degree in electronics at Wuhan University in 2013 and presently is a graduate student for her Master degree at Wuhan University. Her current research interest is nanomaterial-based electrochemical sensors. Chi Ma received his BE degree in electronics at Wuhan University in 2013 and presently is a graduate student for his Master degree at Wuhan University. His current fields of interest are integrated circuit design and Android application development. Zhaobo He received his BS degree in materials at Wuhan University in 2012. Now he is a graduate student for his PhD degree in physics at Wuhan University. His field of interest is medical nanomaterial acting on cells and enzymes. Junhua Xu received his BS and MS degrees in materials at Wuhan University in 2010 and 2013 respectively. Now he is a graduate student for his PhD degree in physics at Wuhan University. His current research interests include microfluidics and biomaterials. Qinqin Huang received her MS degree in physics at Wuhan University in 2013. Now she is a graduate student for her PhD degree in physics at Wuhan University. Her current research interest is microfluidics devices. Shasha Li received her BE degree in electronics at Wuhan University in 2012 and presently is a graduate student for her Master degree at Wuhan University. Her current research interest is microfluidics devices. Yi Cen received his BE degree in electronics at Wuhan University in 2012. Now he is a graduate student for his Master degree at Wuhan University. His field of interest is microfluidics devices. Shishang Guo received his BS and PhD degrees in physics at Wuhan University in 1999 and 2004. He is presently a professor in School of Physics and Technology of Wuhan University. His current fields of interest are Lab on a Chip and ferroelectrics materials. Wei Liu received his BS and PhD degrees in physics at Wuhan University in 2003 and 2008. He is presently an associate professor in School of Physics and Technology of Wuhan University. His current fields of interest are Lab on a Chip and nanomaterials. Xing-Zhong Zhao received his PhD in physics at University of Science and Technology of Beijing in China (1989) and he is currently working as a professor in School of Physics and Technology of Wuhan University. His current fields of interest are solar cell and Lab on a Chip.