Additively Manufactured Digital Microfluidic Platforms for Ion-Selective

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Additively Manufactured Digital Microfluidic Platforms for Ion-selective Sensing Xin Min, Chao Bao, and Woo Soo Kim ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.8b01689 • Publication Date (Web): 11 Mar 2019 Downloaded from http://pubs.acs.org on March 16, 2019

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is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Additively Manufactured Digital Microfluidic Platforms for Ion-selective Sensing

Xin Min, Chao Bao and Woo Soo Kim* Additive Manufacturing Laboratory, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, B.C. Canada V3T 0A3

*To

whom correspondence should be addressed. Phone: +1-778-782-8635, Fax: +1-778-782-7514,

E-mail: [email protected]

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Abstract Digital Microfluidic (DMF) sensors integrated with circuit systems have been applied to a broad range of applications including biology, medicine, and chemistry. Compared with the conventional microfluidic devices that require extra liquid as a carrier and a complex pumping system to operate, DMF is an ideal platform for ion-selective sensing as it enables the droplet operation in a discrete, accurate, and automatic way. However, it is quite rare that DMF platform is utilized for the ion-selective detection. In this paper, we report an integrated DMF system which combines DMF and ion-selective sensing for facile blending of multiple ions, and detection of targeted primary ion. The platform is fabricated through an additive manufacturing method, together with the real-time droplet’s motion monitoring feedback system. Thus, the fabricated system demonstrates controlled droplet manipulation ability including droplet actuation, mixing, and speed control. Targeted primary ion is selectively detected under concentration ranged from 10-6 to 1 M. And the interference study with blended ions has been investigated through on-chip ion selective membranes.

Keywords: Digital microfluidics; 3D printing; Ion-selective sensing; Lab-on-a-Chip; Portable sensing platform


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Electrochemical sensor devices which are accurate, robust, low cost, rapid, and portable are in great demand for various detection technologies including clinical settings1,2. As a subgroup of electrochemical sensors, ion-selective electrode (ISE) is an efficient and convenient way to analyze multiple types of ions3 which can be found in ambient environment4 as well as our human bodies5. ISE has been widely applied in different fields, including agricultural analysis6, food industry7, medicine8, and others9,10. For example, the use of fertilizer increases the amount of nitrate (NO3-) and ammonium (NH4+) in the soil11, which may result in pollution and cause ecological problem in agricultural areas. It is hard for farmers to use liquid chromatography (IC) or flow injection analysis (FIA) to detect NO3- and NH4+ due to the cost and the lack of operation skills12. Alternatively, ISEs’ strength such as portability and easy operation makes ISEs a powerful tool to analyze the ion concentration in soil samples, which is highly needed for the detection of NO3- and NH4+ 13,14. ISEs based on polymetric membranes15 are able to specify a wide varieties of ions16. These membranes contain nanopores and charged carriers17 which make them suitable for cooperating with microfluidic systems18. For example, an ISE junction embeded inside a polydimethylsiloxane (PDMS) based microfluidic chip as a preconcentration tool19, an ISE in a Y-shape microfluidic channel for extracting tetraethylammonium ion20, and polyvinyl chloride (PVC) polymer based ISE21 have been demonstrated. However, previous demnstrations are involved with the conventional continous microfluidic systems, which require pumping tubes, valves, and another liquid phase to carry the sample solution. These configurations increase the complexity of the system results in the difficulty of operation. Digital microfluidic (DMF) devices, which are discrete droplet-based fluid manipulation systems, demonstrrate all the advantages of conventional microfluidic chips, and also own their unique properties like programmability and reconfigurability22–24. Electrowetting on dielectric (EWOD) based DMFs have been developed for decades as their high potential for lab-on-a-chip (LOC) applications25,26. Briefly, EWOD is a phenomenon where the individual droplet subjects to the contact angle change under electric


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field on top of the dielectric layer27, which offers the possibility to manipulate sample solution separately as small droplets with the volume as low as several microliter. Unlike the conventional microfluidic channel, whose discrete droplet operation relies on the continuous flow of another carrying fluid, DMFs are able to transport single droplet without the assistance from another liquid carrier. DMFs are suitable systems to perform sequential drop addition, the interference study with controlled mixing of multiple ion droplets repeatedly. DMFs are reported as a multifunctional, controllable, and efficient platform for electrochemical28, biology29, and medical30 applications. Also, DMFs have unique features such as small sampling amount, fully automatic operation, miniaturized devices size as an ideal platform for ISE. Here, we present DMF based ion-selective sensing systems for the selective detection of specific ions in blended solutions. Additively manufactured DMF electrodes are fabricated for the applications with three dimentionally unique form factors. Droplets are controlled separately from two different paths and demonstrated with quantitative mixing ability. Voltage supplying unit is designed for converting the low voltage source to desired higher voltage to actuate droplets. A commercially available capacitance-todigital converter (CDC) sensor is applied to obtain droplet velocity and position through monitoring the capacitance between adjacent electrodes. An Arduino Due board is used to obtain data from CDC and control the sample drop moving accordingly. Selectivity of the membrane is demonstrated through Fixed Interference Method31 (FIM) on DMF board via blending 10-6 to 1 M of the primary NH4+ with fixed 0.1M of K+ and Ca2+ as interference ions.


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Experimental Section Fabrication of DMF sensors A paste direct writing printer, V-One, from Voltera has been used for the fabrication of DMF patterns in this experiment. Its maximum horizontal resolution is 100 m with constant trace height as 100 m. Silver paste was formulated with 0.4 g of polyurethane, 0.2 g of custom prepared silver nanoparticles31 and 2 g of silver flake (Inframat Advanced Materials, US), mixed with 1 ml of N, N-dimethylformamide (DMF), and 4 ml of tetrahydrofuran (THF). Dielectric material was formulated using urethane tri-acrylate besed oligomer, and Luperox A75 Benzoyl peroxide (5 wt% out of oligomer) as thermal initiator. Isopropyl alcohol was added to dilute the dielectric resin for the optimal spin coating condition. After dielectric layer was coated, devices were cured for 30 min at 120 ℃. Then, a commercial available hydrophobic material from NeverWet was coated on top of dielectric layer via spray coating and dried in room temperature for 1 hour. Working and reference electrodes for ISE have been protected during the coating processes. The ion-selective function was created by a PVC membrane coated on top of working electrode, which is prepared with the mixture of poly(vinyl chloride) (PVC), bis(2-ethylhexyl) sebacate (DOS), nonactin, and sodium tetrakis [3,5-bis(trifluoromethyl) phenyl]borate salt (NaTFPB) with a weight ratio of 32.8%, 64.5%, 1.9% and 0.8% respectively with tetrahydrofuran (THF). PVC solution was drop-casted and dried in ambient environment overnight. All chemicals were used as received from Sigma-Aldrich. System integration and ion-selective sensing operation The fabricated DMF sensors and driving system were connected by two rows of pin connector. Droplets were added through a micro pipette on the starting electrodes in the volume of 10 μL. For the manipulation of blending two different ion solutions, drops were placed at two different starting point, ACS Paragon Plus Environment

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moved toward each other at center point along the route, and then transferred to sensing area. A thin layer of silicon oil was applied to help droplets’ movement. To actuate the droplet, a high voltage supplying unit (HVSU) was designed to provide enough voltage on the electrodes. Also, relays (AQW210EH) worked as switches for controlling electrodes status. Droplets’ speed monitoring function was added with capacitance measurement from a capacitance-to-digital converter (AD7147). All the control and signal processing were completed using an Arduino Due board, which is connected to a laptop. An electrochemical analyzer (CHI1205B) was used to monitor the voltage output from ISE.

Results and Discussion Design of DMF electrode Design of serpentine-shaped ISE electrode is shown in Figure 1A. Each droplet driving electrode contains a capacitive sensing electrode by being buried inside to the center. It is noteworthy that a serpentine shape is selected as the interface shape between neighboring electrodes. Electrowetting force from one electrode toward another is influenced by parameters such as the contact angles, surface tension, and width of actuated droplet boundary. Those curved area enables the droplet to be overlapped with the adjacent electrode, preventing failing movement usually occurred on straight edges32. Design of serpentine electrodes varied with three different radius: 5 4 mm, 2 2 mm, and 10 2 mm. These radii are chosen based on the model from previous study33 regarding our own device configurations: 𝜆/𝑒

(1)

G(𝜆,𝑒,𝛿,𝑛) = (𝛿/𝑒) + [𝜃2/𝜃1](1/𝜋𝑛)

which must larger than 1. Where 𝜃1 and 𝜃2 reprents the contact angle before and after voltage applied, e is the electrode width, n is the number of dents, λ is the size of dent, and δ is the gap size.


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Smaller radius of edge, which gives larger serpentine shape, induces larger overlap of droplet volume between neighboring electrodes. Thus, smaller radius results in moving droplets easier, which is desired in our design. However, with the increasing of sperpentine shape, the concave part of edges becomes too close to the embedded capacitance sensing electrode. Therefore,

2 2 mm is selected for this work. The

DMF channel is formed by an array of eight serpentine electrodes including two droplet-starting locations and one ISE sensing area as shown in Figure 1B. The capacitive sensing on open EWOD devices with a catena on top of the moving path has been reported34. Their electrodes are working both for moving droplets and for measuring capacitance, with a protective capacitor between the electrode and CDC to prevent the damage of sensing chip from high driving voltage. With catena, the moving path is usually designed to be one dimension along single straight line35, which impedes complex operation of the droplets. To our knowledge, this is the first such demonstration of capacitance measurement on opentype DMF without catena. However, the capacitance change is not detectable from single ended electrode connected to both voltage source and CDC without catena. To address this problem, we designed the driving and sensing electrodes as separated parts. The capacitance sensing electrodes are located at the center, which do not hinder the movement of droplet. Ion-selective sensing region is designed to be a whole patch to increase the sensing area due to the fact that larger effective area between electrode and ion-selective membrane have higher voltage output signal36. The fabricated DMF sensor devices is shown in Figure 1C. Unlike widely used lithography method, we use additive manufacturing technology to fabricate the devices in order to open device fabrication potentials for smart 3D form factors. Additive manufacturing allows fast fabrication on a wide variety of substrates, which enables product agility, but reduces the production time and cost. A minor issue here resulted from the spraycoated hydrophobic layer is also investigated by previous studies37–39. Those studies demonstrated that the super-hydrophobicity of the surface with roughened morphologies minimizes the contact area between droplet and substrate. In this application, droplets tend to easily “stick” on the surface while much higher than operating voltage is applied. The contact angle change before and after voltage applied ACS Paragon Plus Environment

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can be found in Supplmentary Fig. S1. And Atomic Froce Microscope (AFM) images of the sprayed surface morphology has also been investigated in Fig. S2. In order to overcome this droplet-merging behavior while DMF is working, a very thin layer of silicon oil is applied to lubricate the hydrophobic surface so that droplets could move between electrodes freely. Driving droplets movement and their speed monitoring The schematics of droplet driving system is shown in Figure 2A, which consists of a microcontroller, relays, a voltage supplying unit, CDC, and a DMF sensor. The voltage supplying unit converts lower source voltage about 5 V to a higher droplet driving DC voltage with the maximum output of 180 V. This converter eliminates the requirement of heavy and giant energy source to provide enough driving voltage to the DMF device, which enables the portability of the platform. Voltage output from voltage supplying unit is connected to relays before being delivered to DMF sensors. Actual device integration is shown in Figure 2B. Droplet’s transporting sequence is programmed with the Arduino. And the Arduino sends the signal to each relay for switching the electrode to be ground or charged. A droplet’s moving sequence toward sensing area is demonstrated in Figure 3A, B, C, and D. This DMF device is capable of driving droplet with a size from 6 μL to 20 μL. 10 μL droplet before mixing has been used for the following experiment to show the device’s maximum driving capability. Additionally, the capacitance change during droplet’s movement is monitored through a CDC chip to monitor positions and moving speed of the droplet in order to control the droplet’s motion accordingly. The capacitance change of each electrode is ploted in Figure 3E. The capacitance change was investigated depending on the parameters, such as thickness of dielectric layer, dielectrics’ relative permittivity, and the distance between droplet and underlying monitoring electrodes. Among these parameters, only the distance changes during the movement of droplet from one electrode to another. Based on this, capacitance increases when droplet is approaching to the monitoring electrode, while it is decreased when droplet is leaving35. This allows us to obtain droplet’s moving speed from peak-to-peak time and the distance ACS Paragon Plus Environment

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between adjacent electrodes. Relation among the spin coating speed, which influence the dielectric layer thickness, driving voltage, and droplet moving speed have been studied based on the data from CDC. For a given open DMF system configuration, the droplet’s moving speed (U) has been calculated with following equation40: 𝜀0𝜀𝑟𝑙 𝑑

U=

∙ 𝑉2 ― 8 ∙ ∆𝑓

(

2𝜋𝐾1𝐾𝑐𝐶𝑉𝜇𝑅 2 +

𝜀0𝜀𝑟𝑙 2𝑑

(2)

)

∙ 𝑉2

Where 𝜀0 and 𝜀𝑟 are the relative permittivity of free space and dielectric, 𝑙 is the length of contact line, 𝑑 represents the thickness of dielectric, V is the driven voltage, ∆𝑓 is a constant representing the hysteresis effect, 𝐾1 and 𝐾𝑐 are factors related to droplet acceleration and deceleration process, and pinning effect of overlapped region respectively, 𝐶𝑉 reprensents viscous damp from area covered by droplet, 𝜇 is the viscosity of the fluid, and 𝑅 is the radius of droplet. Droplet’s moving speed ranged from 1 mm/s to 4 mm/s at 100 V to 180 V, which is adequate for the ion-selective sensing application as shown in Figure 3F. Compared with the droplet’s moving speed in previous report34, whose droplet’s moving speed was about 2.5 mm/s under 380 V, the fabricated device actuates droplets faster at lower voltage. By increasing spin coating speed for thinner dielectic layer, the droplet’s moving speed is increased under same voltage applied, agreeing well with the equation (1). The hysteresis effect is the the main factor that influence the droplet movement at lower driving voltage, hence the speed increase relatively slower in the beginning under 120 V. On the other hand, the droplet’s moving speed tends to be saturated after 160 V. At higher voltage, the hysterisis constant ∆𝑓 is negligible and the equation (2) can be expressed as: 1

U = 2𝜋𝐾𝑐𝐶𝑉𝜇𝑅 ∙

1 1

2𝑑 +

(3)

2 𝜀0𝜀𝑒𝑉2


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2

When driving voltage is high enough, 𝜀 𝜀 𝑉2 is small enough to be neglected. Thus, the droplet speed tends 0 𝑒

to be saturated at higher actuation voltage.

Selective ion detectin from blended interference ions The ion-selective sensor consisted of a working electrode, a reference electrode, and an ion-selective membrane (ISM) is shown in Figure 4A and 4B. It is worth to mention that dielectric and hydrophobic layers are not formed on top of ISM. The droplet has a trend to move toward membrane-covered electrode naturally because of surface property difference, which has been investigated in Fig S1. In addition, the membrane here has similar function as dielectric layer, which drives droplet onto itself when voltage is applied.. The study of ion selectivity is separated into two parts as decribed in experimental part. The concentration of primary ion and measured output should exhibit nerstian response31 as the equation list below:

𝑇

𝐸 = 𝐸0 + 2.303R 𝐿𝑜𝑔𝑎

(4)

ZF

Where E is the measured potential, 𝐸0 represents reference constant, R is the gas constant, T is the temperature, z is the charge on ion, F is the Faraday constant, a is the activity of the ion. First, the primary ion NH4+ in NH4Cl solution is detected. As shown in Figure 4C, it is demonstrated both with and with out silicon oil condition, since a thin layer of silicon oil is used to help the droplet movement as described in previous section. The result shows that the membrane has a linear response in the concentration range of 10-6 to 1 M with a 87 mV/decade slope. After applying silicon oil, the response ACS Paragon Plus Environment

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slope decreases to 55.8 mV/decade, which is still adequate to selectively detect target primary ion. A very thin layer of silicon oil brought by droplet may slow down the combination between target ions and ionophore inside the membrane, and decrease the potential difference near the membrane surface, which results in a lower detected potential. Although silicon oil compromise part of the membrane’s performance, the response remains linear within working range. This proves that this ion selective membrane can be used under our DMF working conditions. The interference study has been investigated through Fixed Interference Method (FIM) to confirm membrane’s selectivity. Mixed droplets which contain primary ions and 0.1M interference ions has been transported to sensing area for testing. The result is shown in Figure 4D, where two different interference ions, K+ and Ca2+, have been included. A comparison between solution with primary ions only and solution containing interference ions is performed. With the interference of Ca2+, the membrane still remains similar linear response as the sample with primary ions only in the range of 10-5 to 1 M. And under the interference of K+, a linear response was obtained only between about 10-3 to 1 M. For solutions with lower primary ion concentration, high concentration interference ion becomes dominant so that the response cannot maintain linear. A distinct selectivity of the fabricated ISE-DMF is shown with interference circumstances.

Conclusion We developed an additively manufacutred DMF platform integrated with ISE to perform detection of primary ion from the mixture with interference ions. The integrated DMF system is fabricated and assembled in a fast and cost-efficient way. In addition, droplet motion monitoring system has been cooperated with the DMF to obtain droplet moving speed for following feedback operations. As a result, the system shows precise control on droplet manipulation including moving, mixing, and sensing. And the ISE demonstrates linear output for ion concentration ranges from 10-6 to 1 M. High selectivity for


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ammounium ions has been proved by interference study over disturbance ions: K+, Ca2+ and environment: silicon oil media. Overall, the results confirm that our system provides a fast, reliable, and easy-operating way to detect target ions. Thus, this study shows the potential of DMF as an ideal controllable, and portable platform for the ion-selective sensing.

Supporting Information Available: The Supporting Information is available free of charge: Supplementary Material: Contact angle measurement, Atomic Force Microscope (AFM) images, one droplet’s moving video, and two droplet’s mixing video.

Acknowledgements This work received financial support from the Discovery Grant and Discovery Accelerator Supplement Grant 493028-2016, funded by the Natural Sciences and Engineering Research Council of Canada (NSERC).


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FIGURE CAPTIONS Figure 1. (A) Dimensions of designed electrode where R was tested with 𝟓 𝟒, 𝟐 𝟐, and 𝟏𝟎 𝟐 (Unit: mm). (B) DMF sensor’s 3D design. (C) As-printed DMF platform.

Figure 2. (A) Circuit design of DMF control system. (B) Actual image of full system setup.

Figure 3. (A) ~ (D) Moving sequence of droplet toward sensing area. (E) Monitored capacitance change of droplets through consecutive electrodes. (F) Droplet’s moving speed under different driving voltage with different dielectric layer thicknesses.

Figure 4: (A) 3D model of ion-selective membrane (ISM), working electrode (WE), and reference electrode (RE). (B) Actual image of installed ISM location on DMF device. (C) Open circuit potential for ISM under different NH4+ concentration with and without silicon oil. (D) Interference study for ISM using fixed interference method.


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Figure 1.


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Figure 2.


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Figure 3.


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Figure 4.


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Additively Manufactured Digital Microfluidic Platforms for Ion-Selective

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